System

Abstract

A system is provided.SOLUTION: The system includes a means for using an artificial intelligence model for verifying the authenticity and bias of information, a means for curating information based on the interest and taste of a user, a means for automatically blocking access to an inaccurate information source or a site having a risk, a means for periodically providing information of various viewpoints, and a means for providing a place for discussing the reliability and diversity of information among users.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] In modern society, the distribution of information via the Internet is rapidly increasing, requiring users to select reliable information from the vast amount of information available, but this is not an easy task. Furthermore, false and biased information can spread quickly, increasing the risk of distorting users' perceptions. Furthermore, the process of personalizing information based on specific preferences and interests can create filter bubbles, reducing opportunities to be exposed to diverse viewpoints. To address these challenges, there is a need to provide users with information from diverse perspectives and a safe internet experience, while reliably verifying the authenticity and bias of information. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides the following means. The system includes a means for using an artificial intelligence model to verify the authenticity and bias of information, a means for curating information based on user interests and preferences, a means for automatically blocking access to inaccurate information sources or risky sites, a means for periodically providing information from diverse perspectives, and a means for providing a forum for users to discuss the reliability and diversity of information. Specifically, the system uses an artificial intelligence model to verify the authenticity and bias of information in real time and provides personalized information based on the user's interests and preferences. Furthermore, the system alleviates the problem of filter bubbles by periodically providing information from diverse perspectives, and provides a safe internet experience by automatically blocking access to dangerous sites. Furthermore, the system provides a discussion space among users to promote discussion about the reliability and diversity of information and improve the quality of information.

[0006] An "artificial intelligence model" is a computational system that uses machine learning algorithms to analyze information and evaluate its veracity and bias.

[0007] "Curation" is the process of selecting, organizing, and providing information based on a user's interests and preferences.

[0008] A "filter bubble" is a phenomenon in which personalization limits users' exposure to information outside their area of ​​interest.

[0009] "Bias" refers to a state in which information is biased toward a particular perspective or opinion.

[0010] "Truth" is an assessment of whether information is accurate and true.

[0011] "Risky sites" are websites that may be harmful to users and contain inaccurate information or malicious content.

[0012] "Personalization" is a technique for individually customizing information and services based on the preferences and behavior of specific users.

[0013] "Discussion Space" is an online platform where users can exchange opinions and debate about the reliability and diversity of information.

[0014] "Diverse perspectives" include information and opinions from different backgrounds and positions, encouraging users to have a broader understanding.

[0015] "Real-time" refers to a situation in which information is processed or reacted to almost as soon as it is generated.

[0016] A "source" refers to the place, person, or organization from which a particular piece of information originates. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram illustrating a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0018] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0019] First, the terms used in the following description will be explained.

[0020] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0021] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0022] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0023] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0024] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0025] [First embodiment]

[0026] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0027] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0028] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0029] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0030] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0031] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0032] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0033] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0034] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0035] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0036] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0037] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0038] This invention describes a system that verifies the authenticity and bias of information accessed by a user and provides only the most appropriate information to the user. This system is especially designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[0039] Verifying the authenticity and bias of information

[0040] Receiving and analyzing information

[0041] The server receives user-provided information (e.g., news articles or blog posts) and uses artificial intelligence models to analyze it for veracity (accuracy) and bias (whether it favors a particular point of view) to generate this information.

[0042] Providing verification results

[0043] The server provides users with a truthfulness score and bias level obtained from the artificial intelligence model, allowing them to determine the reliability of the information.

[0044] Automatically blocks dangerous sites

[0045] Verifying the URL

[0046] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[0047] Access Blocks and Warnings

[0048] If the URL you are trying to access is included in the dangerous site list, the device will automatically block the access and display a warning message to the user, allowing the user to avoid the risk of accessing dangerous sites.

[0049] Personalized information provision

[0050] Obtaining user interests and preferences

[0051] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[0052] Filtering and Serving

[0053] The server filters all content retrieved from the database based on the user's interests and preferences, and then provides the filtered content to the user, allowing the user to efficiently obtain only the information that is most relevant to them.

[0054] Diversity Feed Feature

[0055] Providing information from diverse perspectives

[0056] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology), allowing users to access a wide range of information without being biased towards a particular viewpoint.

[0057] Reducing the filter bubble

[0058] Server-provided diversity feeds allow users to access different perspectives and sources of information, rather than only being informed by their specific interests and preferences, thereby mitigating the filter bubble problem.

[0059] Discussion space between users

[0060] Posting and saving comments

[0061] Users can post comments about the reliability and versatility of the information, which the server stores and makes available for other users to view.

[0062] Facilitating discussion

[0063] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information, allowing users to share various perspectives and opinions about information and promoting the distribution of reliable information.

[0064] Explanation with concrete examples

[0065] For example, when User A checks a specific news article via InfoGuardian, the server receives the URL of that article. The server uses a generative AI model to evaluate the article's veracity and bias and provides the results to User A. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous and blocks access if necessary.

[0066] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, a regular diversity feed will also expose User A to information on politics and culture. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information.

[0067] Through these features, InfoGuardian helps users safely and efficiently access information and gain insights from multiple perspectives.

[0068] The processing flow will be explained below.

[0069] Verifying the authenticity and bias of information

[0070] Program processing

[0071] Step 1:

[0072] The server receives information provided by the user (eg, a URL for a news article).

[0073] Specific operation: When a user submits the URL of a news article, the server receives the URL as data.

[0074] Step 2:

[0075] The server retrieves the content of the news article from the received URL.

[0076] What happens: The server accesses the URL and scrapes the content of the web page to obtain text data.

[0077] Step 3:

[0078] The server loads the generative AI model.

[0079] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[0080] Step 4:

[0081] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[0082] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[0083] Step 5:

[0084] The server returns the analysis results to the user.

[0085] Specific Operation: The server sends the truthfulness score and bias level to the user for display.

[0086] Automatically blocks dangerous sites

[0087] Program processing

[0088] Step 1:

[0089] A user attempts to access a specific URL.

[0090] Specific operation: A user enters a URL in a browser and sends an access request.

[0091] Step 2:

[0092] The device checks the URL that is being accessed.

[0093] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[0094] Step 3:

[0095] The device determines whether the URL is included in the dangerous site list.

[0096] What it does: The device checks the URL and flags it if it's on the list.

[0097] Step 4:

[0098] The device will block access if the URL is dangerous.

[0099] Specific behavior: If the URL is included in the list, the device will block the access request and display a warning to the user.

[0100] Step 5:

[0101] The terminal displays a warning message to the user.

[0102] What it does: Displays a warning that says "Access to dangerous site blocked."

[0103] Personalized information provision

[0104] Program processing

[0105] Step 1:

[0106] The server obtains data about the user's interests and preferences.

[0107] Specific operation: The server refers to the user's profile information and past browsing history.

[0108] Step 2:

[0109] The server retrieves all content from a database.

[0110] What happens: The server queries the database to retrieve news articles and blog posts.

[0111] Step 3:

[0112] The server filters the retrieved content based on the user's interests and preferences.

[0113] Specific operation: The server selects only content related to topics of interest to the user.

[0114] Step 4:

[0115] The server provides the filtered content to the user.

[0116] Specific operation: Send the filtering results to be displayed on the user's screen.

[0117] Diversity Feed Feature

[0118] Program processing

[0119] Step 1:

[0120] The server obtains data about the user's interests and preferences.

[0121] Specific operation: The server refers to the user's profile information and past browsing history.

[0122] Step 2:

[0123] The server retrieves all content from a database.

[0124] What happens: The server queries the database to retrieve news articles and blog posts.

[0125] Step 3:

[0126] The server has a predefined list of topics from various perspectives.

[0127] Specific operation: The server provides topic lists such as politics, economics, culture, and technology.

[0128] Step 4:

[0129] The server filters information from multiple perspectives.

[0130] What it does: The server filters content based on various selected topics.

[0131] Step 5:

[0132] The server provides the user with information from various perspectives.

[0133] Specific behavior: Periodically display filtered diversity content on the user's screen.

[0134] Discussion space between users

[0135] Program processing

[0136] Step 1:

[0137] Users post comments in the discussion space.

[0138] Specific behavior: The user enters a comment in the text box and clicks the post button.

[0139] Step 2:

[0140] The server receives and stores the user's comments.

[0141] Specific operation: The server receives the comment data and stores it in the database.

[0142] Step 3:

[0143] The server retrieves the stored comments.

[0144] Specific behavior: When another user tries to view the discussion space, the server retrieves all comments.

[0145] Step 4:

[0146] The server displays the comments to the user.

[0147] Specific operation: The server displays the retrieved comments in the user's discussion space.

[0148] Step 5:

[0149] Users exchange opinions with other users.

[0150] What it does: Users read other users' comments and add and share their own opinions.

[0151] The above are the specific processing steps for carrying out the present invention, which allow InfoGuardian to provide highly reliable information to users and realize a safe and diverse information access environment.

[0152] Example 1

[0153] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0154] In today's information society, it is difficult for users to determine the authenticity and bias of the information they come into contact with, making it easier for information biased toward a particular viewpoint or inaccurate information to spread. Accessing inaccurate information sources or dangerous websites also poses a significant risk. Furthermore, users are bombarded with information, making it difficult to efficiently obtain important information relevant to them. Therefore, the present invention aims to solve these problems and provide a system that helps users access reliable information.

[0155] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0156] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, and means for automatically blocking access to inaccurate information sources and risky websites, thereby enabling users to efficiently obtain reliable information and avoid access to dangerous websites.

[0157] "Artificial intelligence model for verifying the veracity and bias of information" is an artificial intelligence technology used to analyze and evaluate information provided by users to determine its accuracy and whether it is biased toward a particular viewpoint.

[0158] "Curating information based on user interests and preferences" is the process of selecting, collecting, and providing highly relevant information based on a user's past behavior and preferences.

[0159] "Automatically block access to websites from inaccurate sources or risky websites" is a function that checks the URL of the website the user is trying to access against a predefined list of dangers and prevents access based on the results.

[0160] "Regularly providing information from diverse perspectives" is the process of regularly providing users with information from different perspectives and sources, allowing them to be exposed to a wide range of information that is not biased towards any particular perspective.

[0161] "Providing a forum for users to discuss the reliability and diversity of information" refers to creating a discussion space where users can exchange opinions and evaluations regarding the reliability and diversity of information.

[0162] "Notifying users of the results of analysis using a generative AI model" refers to the process of providing users with the results of information analyzed by artificial intelligence and informing them of the veracity and bias of that information.

[0163] "Compare the URL of the website you are trying to access with a list of dangerous sites" is a function that compares the address of the website you are trying to visit with a pre-defined list of dangerous sites.

[0164] "Filtering and providing content relevant to a user's interests and preferences" refers to the process of selecting and providing appropriate information to a user based on the user's interests and preferences.

[0165] "Save user comments and share with other users" is a function that saves ratings and opinions left by users about information in a database and allows other users to view those comments.

[0166] This invention is a system that verifies the authenticity and bias of the information accessed by the user and provides only the most appropriate information to the user. It is designed especially to support users with low digital literacy, such as young people and the elderly. This system operates based on the following program processing steps:

[0167] The server receives information provided by the user (e.g., news articles or blog posts). To analyze this information, the server uses a generative AI model (e.g., GPT-4). For example, a prompt sentence such as "Please rate the truthfulness and bias of this news article" is generated and input into the model. The generative AI model analyzes the truthfulness score and bias level based on the input information and outputs the results to the server. The server notifies the user of this analysis result. For example, if a news article submitted by a user is evaluated as having a truthfulness score of 80% and a low bias level, the server will notify the user that "This news article has a truthfulness score of 80% and a low bias level."

[0168] When a user attempts to access a website, the device retrieves the URL and compares it with a predefined list of dangerous sites. This list includes websites with inaccurate information sources and risky websites. For example, if a user attempts to access "example.com," the device will compare the URL with the list of dangerous sites and automatically block access if there is a match. The user will see a warning message stating, "This site is dangerous. Access has been blocked."

[0169] The server obtains information based on the user's interests and preferences and curates content based on that information. For example, if a user is interested in "technology" or "health," the server retrieves articles on these topics from the database and provides them after filtering. The filtered content is provided to the user in the form of, "Check out the latest technology news below."

[0170] Furthermore, the server periodically provides information from diverse perspectives. This information is collected from different perspectives and sources, allowing users to access a wide range of information without being biased towards a particular viewpoint. For example, diverse information is provided in the form of "Below are the latest articles on politics, economics, and culture."

[0171] Users can also post comments about the provided information and share them with other users. The server stores these comments and provides a discussion space, promoting discussion about the reliability and diversity of the information. Comments such as "This information is highly reliable and provided from diverse perspectives" can be viewed by other users.

[0172] Through these functions, the system helps users safely and efficiently access information and obtain information from multiple perspectives.

[0173] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0174] Step 1:

[0175] The server receives user-provided information (e.g., news articles or blog posts). The input is the information submitted by the user, and the output is the conversion of the received information into a data format. For example, a user might submit the URL of a particular news article to the server. The server parses the URL to retrieve the article content.

[0176] Step 2:

[0177] The server uses a generative AI model (e.g., GPT-4) to generate a prompt sentence that evaluates the truthfulness and bias of the information. The input is the received information, and the output is a prompt sentence for the AI ​​model. As a specific example, the server generates the prompt sentence, "Please evaluate the truthfulness and bias of this news article."

[0178] Step 3:

[0179] The server sends a prompt to the generative AI model, requesting an analysis of the truthfulness score and bias level. The input is the generated prompt, and the output is the analysis result obtained from the AI ​​model. As a specific example, the AI ​​model returns an analysis result of a truthfulness score of 80% and a low bias level.

[0180] Step 4:

[0181] The server notifies the user of the analysis results obtained from the generative AI model. The input is the generated analysis result, and the output is a message to be notified to the user. For example, the notification may say, "This news article has a truthfulness score of 80% and a low bias level."

[0182] Step 5:

[0183] When a user tries to access a website, the device obtains the URL and compares it with a predefined list of dangerous sites. The input is the URL the user is trying to access, and the output is the result of matching it with the list of dangerous sites. For example, if a user tries to access "example.com", the device will compare the URL with the list of dangerous sites.

[0184] Step 6:

[0185] If the URL matches the dangerous site list, the terminal will automatically block the user's access. The input at this time is the URL matching result, and the output is an access block and a warning message. For example, a warning message saying "This site is dangerous. Access has been blocked" is displayed.

[0186] Step 7:

[0187] The server retrieves information based on the user's interests and preferences. The input is data about the user's interests and preferences, and the output is a filtered list of related content. For example, if the user is interested in "technology" or "health," the server retrieves articles related to these topics.

[0188] Step 8:

[0189] The server filters the information it obtains and provides it to the user. The input is all content before filtering, and the output is the filtered content. For example, it is provided in the form of "Check out the latest news on the following technologies."

[0190] Step 9:

[0191] The server periodically collects information from various perspectives and provides it to the user. The input is data collected from different sources, and the output is a list of information from various perspectives. For example, it is provided in the form of "Below are new articles on politics, economics, and culture."

[0192] Step 10:

[0193] Users post comments about the provided information, and the server stores and shares them. The input is the user's comment, and the output is comment data that can be viewed by other users. For example, a comment such as "This information is highly reliable and provided from a variety of perspectives" is stored.

[0194] Step 11:

[0195] The server provides a discussion space where users can discuss the reliability and diversity of information. The input is information and comments, and the output is a record of the discussion and shared knowledge. For example, the server encourages discussion by saying, "Let's discuss this news article further."

[0196] (Application example 1)

[0197] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0198] Currently, the market is overflowing with information, making it difficult for users to determine its authenticity and bias. Furthermore, particularly in physical stores, there is a lack of ways to quickly assess the authenticity and reliability of product-related information. As a result, users are at a greater risk of making decisions based on incorrect information. Furthermore, there is a lack of effective ways to avoid accessing inaccurate information sources or risky websites. There is a need to solve these problems and provide safe and reliable information.

[0199] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0200] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on user interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for periodically providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, means for verifying the authenticity and bias of information related to products and providing reliable information to users in physical stores, and means for blocking dangerous information in physical stores in real time, thereby enabling users to make decisions based on accurate and reliable information.

[0201] "Truthfulness of information" refers to whether the information is based on facts.

[0202] "Bias" refers to whether information is biased toward a particular perspective or position.

[0203] An "artificial intelligence model" refers to an algorithm that learns from large amounts of data and performs pattern recognition and predictions.

[0204] "User interests and preferences" refers to specific topics or content that interest a user.

[0205] "Curation" refers to the act of selecting, organizing, and providing valuable information from a large amount of information.

[0206] An "inaccurate source" refers to a source that provides unreliable information.

[0207] A "risky site" is a website that may have a harmful effect on users.

[0208] "Diverse perspectives" refers to information from different viewpoints and positions.

[0209] "Reliability" refers to the degree to which information or a system is accurate or safe.

[0210] "Product-related information" refers to information such as reviews, ratings, and descriptions about a particular product.

[0211] "Brick and mortar store" refers to a store that exists in a physical location.

[0212] "Real-time" refers to processing or response occurring immediately, without any time delay.

[0213] "Blocking" refers to restricting or stopping a specific action or access.

[0214] A "discussion" refers to the act of multiple people exchanging opinions on a particular topic or issue.

[0215] To implement this invention, a system is constructed that combines the following elements and their respective functions.

[0216] System configuration

[0217] 1. User Device:

[0218] Using mobile devices such as smartphones and tablets.

[0219] Install a QR code reader application on your device and read product information in physical stores.

[0220] 2. Server:

[0221] The servers are hosted on Amazon Web Services (AWS) EC2.

[0222] The database used is MySQL.

[0223] The artificial intelligence model is built using Google Cloud AI.

[0224] Program and Data Processing

[0225] 1. Receiving and analyzing information:

[0226] The user scans a QR code related to a product with their smartphone while in a physical store.

[0227] The terminal sends the read information to the server.

[0228] The server receives the information and uses an artificial intelligence model to analyze the information's authenticity and bias.

[0229] 2. Providing verification results:

[0230] The server sends the analysis results to the user's device and displays reliable information.

[0231] Users can check the authenticity and reliability of product information.

[0232] 3. Blocking dangerous information:

[0233] When a user attempts to click on a link contained within the information, the server parses the URL.

[0234] If the URL is on the dangerous site list, the server blocks access and displays a warning message to the user.

[0235] 4. Personalized communications:

[0236] The server filters relevant product reviews and promotional information based on the user's interests and preferences.

[0237] To provide filtered information to a user terminal, enabling a user to efficiently obtain information of interest.

[0238] 5. Diversity Feed Feature:

[0239] The server periodically collects reviews and information from different perspectives and provides them to users.

[0240] It will alleviate the filter bubble problem and provide balanced information.

[0241] 6. Discussion Space:

[0242] The server provides a discussion space where users can post comments about product reviews and promotional information.

[0243] It allows users to exchange opinions with other users, encouraging discussion about the reliability and diversity of information.

[0244] Specific examples

[0245] For example, when a user attempts to purchase a product in a physical store, they scan the QR code attached to the product with their smartphone. The information is sent to a server, where an AI model analyzes the authenticity and bias of the information. The server then displays the analysis results to the user, providing a reliable product review.

[0246] Also, when a user tries to click on a link, the server analyzes the URL and, if it is a dangerous site, blocks access and displays a warning message.

[0247] An example prompt might have the following format:

[0248] "Please verify this information to ensure its authenticity. Please rate the following review and return your result: 'This product was amazing!'"

[0249] This allows users to make decisions based on accurate and reliable information.

[0250] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0251] Step 1:

[0252] A user reads a QR code attached to a product in a physical store with their smartphone. The input is the QR code data, and the output is sending the read data to a server. Specifically, the QR code is scanned using a QR code reader application, and the obtained data is transmitted to the server.

[0253] Step 2:

[0254] The server receives the data sent by the user and analyzes the authenticity and bias of the information using an artificial intelligence model (e.g., Google Cloud AI). The input is the data obtained from the QR code, and the output is the authenticity score and bias level of the information. Specifically, the server inputs the received data into the AI ​​model and obtains the analysis results.

[0255] Step 3:

[0256] The server sends the analysis results to the user's device, providing the user with reliable information. The input is the truth score and bias level, and the output is the analysis results displayed on the user's device. Specifically, the server formats the analysis results and communicates them to the user's device.

[0257] Step 4:

[0258] When a user tries to click on a provided link, the server checks the URL against a predefined list of dangerous sites. The input is the URL the user tried to click, and the output is a decision on whether the URL is safe or dangerous. Specifically, the server checks the URL and obtains the result.

[0259] Step 5:

[0260] If the server detects a dangerous URL, it will automatically send a warning message and instructions to block access to the user's device. The input is the result of the dangerous URL judgment, and the output is the display of a warning message. Specifically, the server sends a warning message to the user's device and displays the warning to the user.

[0261] Step 6:

[0262] The server filters relevant product reviews and promotional information based on the user's interest and preference data. The input is the user's interest and preference data, and the output is the filtered product reviews and promotional information. Specifically, the server searches for relevant information from a database and filters it based on the user's interest and preference.

[0263] Step 7:

[0264] The server provides the filtered information to the user terminal, allowing the user to efficiently obtain information of interest. The input is filtered product reviews and promotional information, and the output is the information displayed on the user terminal. Specifically, the server sends the filtered information to the user terminal.

[0265] Step 8:

[0266] The server periodically collects reviews and information from different perspectives and provides them to users. The input is reviews and information from diverse perspectives, and the output is a diversity feed displayed on the user's device. Specifically, the server categorizes the collected information and periodically provides it to users.

[0267] Step 9:

[0268] The server provides a discussion space where users can post comments about product reviews and promotional information. The input is the user's comment, and the output is saved as a comment that can be viewed by other users. Specifically, the server receives the comment, saves it in a database, and displays it to other users.

[0269] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0270] This invention describes a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is particularly designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[0271] Verifying the authenticity and bias of information

[0272] Receiving and analyzing information

[0273] The server receives user-provided information (e.g., news articles or blog posts), which it then analyzes for veracity (accuracy) and bias (whether it favors a particular point of view) using a generative AI model.

[0274] Providing verification results

[0275] The server provides users with the truthfulness score and bias level obtained from the AI ​​model. At this time, the emotion engine recognizes the user's emotions and presents the results in a format appropriate to those emotions, making it easier for users to understand the reliability of the information.

[0276] Automatically blocks dangerous sites

[0277] Verifying the URL

[0278] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[0279] Access Blocks and Warnings

[0280] If the URL you are trying to access is on the dangerous site list, the device will automatically block the access and display a warning message to the user. The emotion engine recognizes the user's emotions and adjusts the tone and format of the warning message appropriately to help the user remain calm.

[0281] Personalized information provision

[0282] Obtaining user interests and preferences

[0283] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[0284] Filtering and Serving

[0285] The server filters all content retrieved from the database based on the user's interests and preferences. The filtered content is then provided to the user. The emotion engine provides information at the optimal timing and in the optimal format based on the user's emotional state. This allows users to efficiently receive information that is highly relevant to them.

[0286] Diversity Feed Feature

[0287] Providing information from diverse perspectives

[0288] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology). The emotion engine recognizes the user's emotions and considers how the information provided from various perspectives will be received by the user.

[0289] Reducing the filter bubble

[0290] The server-provided diversity feed allows users to access different perspectives and sources of information, rather than only receiving information based on specific interests or preferences. The emotion engine evaluates the user's emotional state and adjusts the format to provide diverse perspectives while mitigating the filter bubble problem. This makes it easier for users to accept diverse information.

[0291] Discussion space between users

[0292] Posting and saving comments

[0293] Users can post comments about the reliability and diversity of information. The server stores these comments and makes them available for other users to view. The emotion engine also recognizes the poster's emotions and adjusts the display format of the comments accordingly.

[0294] Facilitating discussion

[0295] The server provides a discussion space and encourages users to discuss the reliability and diversity of information. An emotion engine monitors each user's emotional state and guides the discussion to proceed in an appropriate manner. This allows users to share multiple perspectives and opinions about information, promoting the circulation of reliable information.

[0296] Explanation with concrete examples

[0297] For example, when User A checks a specific news article via InfoGuardian, the server receives the article's URL. The server uses a generative AI model to evaluate the article's veracity and bias, and presents the results in a format that matches User A's emotions, as analyzed by an emotion engine. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous, blocks access if necessary, and displays a warning message that matches User A's emotions.

[0298] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, User A can also access information on politics and culture through a regularly provided diversity feed. The emotion engine will also provide this information in an appropriate format, taking into account User A's emotional state. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information. The emotion engine is also involved in these discussions, promoting smooth and constructive communication.

[0299] Through these features, InfoGuardian helps users access information safely and efficiently, gaining information from multiple perspectives, and utilizes an emotion engine to enhance the user experience.

[0300] The processing flow will be explained below.

[0301] Verifying the authenticity and bias of information

[0302] Program processing

[0303] Step 1:

[0304] The server receives information provided by the user (such as a URL for a news article).

[0305] Specific behavior: The user enters the URL of a news article and sends it to the server.

[0306] Step 2:

[0307] The server retrieves the content of the news article from the received URL.

[0308] What it does: The server accesses the URL and scrapes the content of the web page to collect text data.

[0309] Step 3:

[0310] The server loads the generative AI model.

[0311] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[0312] Step 4:

[0313] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[0314] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[0315] Step 5:

[0316] The server activates an emotion engine that recognizes the user's emotions and analyzes the user's emotions.

[0317] How it works: The emotion engine assesses the user's emotional state based on their facial expressions, tone of voice, and input.

[0318] Step 6:

[0319] The server presents the analysis results based on the user's emotions.

[0320] Specific operation: The server allows the user to view the truthfulness score and bias level in a format appropriate to the user's emotional state (e.g., a message in a gentle tone).

[0321] Automatically blocks dangerous sites

[0322] Program processing

[0323] Step 1:

[0324] A user attempts to access a specific URL.

[0325] Specific operation: The user enters a URL in the browser and sends an access request.

[0326] Step 2:

[0327] The device checks the URL that is being accessed.

[0328] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[0329] Step 3:

[0330] The device determines whether the URL is included in the dangerous site list.

[0331] What it does: The device checks the URL and flags it if it's on the list.

[0332] Step 4:

[0333] The device will block access if the URL is dangerous.

[0334] Specific operation: If the URL is included in the list, the terminal will block the access request.

[0335] Step 5:

[0336] The terminal will display a warning message to the user.

[0337] What it does: The emotion engine recognizes the user's emotions and displays the warning "Access to dangerous site blocked" in a tone and format appropriate to that emotional state.

[0338] Personalized information provision

[0339] Program processing

[0340] Step 1:

[0341] The server collects data about the user's interests and preferences.

[0342] Specific operation: The server refers to the user's profile information and past browsing history.

[0343] Step 2:

[0344] The server retrieves all content from a database.

[0345] What happens: The server queries the database to retrieve news articles and blog posts.

[0346] Step 3:

[0347] The server filters the retrieved content based on the user's interests and preferences.

[0348] What it does: The server selects only content related to topics that the user has expressed interest in.

[0349] Step 4:

[0350] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[0351] Specific operation: The emotion engine determines the user's emotional state from their facial expression, tone of voice, and input.

[0352] Step 5:

[0353] The server provides the filtered content to the user.

[0354] What it does: The emotion engine displays filtered content on the user's screen at a time and in a format appropriate to the user's emotional state.

[0355] Diversity Feed Feature

[0356] Program processing

[0357] Step 1:

[0358] The server collects data about the user's interests and preferences.

[0359] Specific operation: The server refers to the user's profile information and past browsing history.

[0360] Step 2:

[0361] The server retrieves all content from a database.

[0362] What happens: The server queries the database to retrieve news articles and blog posts.

[0363] Step 3:

[0364] The server has a list of topics from various predefined perspectives.

[0365] Specific operation: The server provides a variety of topic lists, including politics, economics, culture, and technology.

[0366] Step 4:

[0367] The server filters information from multiple perspectives.

[0368] What it does: The server filters content based on various selected topics.

[0369] Step 5:

[0370] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[0371] What it does: The emotion engine delivers content from multiple perspectives in an appropriate format based on the user's emotional state.

[0372] Step 6:

[0373] The server provides users with information from a variety of perspectives.

[0374] What it does: The sentiment engine periodically provides diversity feeds and adjusts the display format to make it easier for users to access information from different perspectives.

[0375] Discussion space between users

[0376] Program processing

[0377] Step 1:

[0378] Users post comments in the discussion space.

[0379] Specific behavior: The user enters a comment in the text box and clicks the post button.

[0380] Step 2:

[0381] The server receives and stores the user's comments.

[0382] Specific operation: The server receives the comment data and stores it in the database.

[0383] Step 3:

[0384] The server activates an emotion engine that recognizes the user's emotions and evaluates the poster's emotional state.

[0385] Specific operation: The emotion engine analyzes emotions from the poster's expressions and content and saves them in an appropriate format.

[0386] Step 4:

[0387] The server retrieves the stored comments.

[0388] What happens: When another user tries to view the discussion space, the server retrieves all comments.

[0389] Step 5:

[0390] The server displays the comments to the user.

[0391] How it works: The emotion engine adjusts the display format of comments based on the emotional state of the user viewing them.

[0392] Step 6:

[0393] Users exchange opinions with other users.

[0394] How it works: Users read other users' comments, add their own opinions, and share them. The emotion engine performs real-time emotion recognition to facilitate this process.

[0395] The above are the specific processing steps for implementing this invention. As a result, InfoGuardian provides users with highly reliable information and realizes a safe and diverse information access environment. Furthermore, by combining it with an emotion engine, the user experience is further improved, and appropriate information can be provided according to individual needs.

[0396] Example 2

[0397] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0398] In modern society, the amount of information available on the Internet is enormous, and much of it contains false or biased information. Furthermore, users with low digital literacy have difficulty selecting reliable information, increasing the risk of misunderstandings and poor judgment based on misinformation. Furthermore, the risk of users accessing dangerous websites is also increasing. There is a need for a system that can comprehensively resolve these issues and provide users with accurate, unbiased information.

[0399] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0400] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for recognizing user emotions and providing analysis results in an appropriate format, and means for curating information based on the user's interests and preferences. This allows users to receive reliable information in an appropriate format, preventing misunderstandings and incorrect decisions based on false information. Furthermore, by using an emotion engine, optimal information is presented according to the user's emotional state, improving the user experience.

[0401] "Authenticity of information" refers to whether the information provided on the Internet is true and accurate.

[0402] "Bias" refers to information that is overly biased toward a particular perspective or opinion.

[0403] An "artificial intelligence model" refers to a machine learning algorithm that analyzes data, finds patterns in it, and makes predictions and decisions.

[0404] An "emotion engine" is a software component that recognizes emotions from a user's facial expressions and text input, and responds according to that emotional state.

[0405] "Curation" refers to selecting information based on a user's interests and preferences and providing useful information from that selection.

[0406] "Automatic access blocking measures" refers to the ability to automatically detect and block access to dangerous websites or inaccurate information sources.

[0407] "Warning Message" means a message that is displayed to warn a user when they attempt to access a dangerous website.

[0408] "Diverse perspectives" refers to multiple sources of information and opinions provided from different backgrounds and positions.

[0409] "Filter bubble" refers to the phenomenon in which users are only exposed to similar information based on their interests and preferences, making it difficult for them to access different perspectives and information.

[0410] "Discussion forum" refers to a space where users can exchange opinions and debate about the reliability and diversity of information.

[0411] "Comment display format" refers to how a comment posted by a user is visualized and displayed to other users.

[0412] "Means to facilitate smooth discussion" refers to functions that support constructive and smooth discussions between users.

[0413] This invention describes a specific embodiment for implementing a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is especially designed to support users with low digital literacy.

[0414] Hardware and Software Configuration

[0415] Hardware

[0416] Server: Use a high-performance cloud-based computing system, such as an EC2 instance from Amazon Web Services (AWS).

[0417] Device: The device used by the user, such as a PC, tablet, or smartphone.

[0418] software

[0419] Generative AI models: Use open-source machine learning frameworks, such as OpenAI's GPT-4.

[0420] Emotion Engine: Uses Microsoft Azure's Emotion Recognition API to recognize user emotions.

[0421] Database: Use a cloud-based database service, such as Amazon RDS, to store data about the truth, bias, and user interests and preferences.

[0422] Verifying the authenticity and bias of information

[0423] Receiving and analyzing information

[0424] The server receives the URL of the information (news article or blog post) provided by the user.

[0425] The server sends the URL to the generative AI model along with a prompt, such as "Please rate the veracity and bias of this information."

[0426] The generative AI model returns a truthfulness score and bias score for the information.

[0427] Providing verification results

[0428] The server obtains the truthfulness and bias scores returned by the generative AI model.

[0429] The server uses an emotion engine to analyze the user's current emotion.

[0430] The server will present the results to the user in an appropriate format depending on the user's emotional state, for example, if the user is surprised, it will provide a clear and detailed explanation.

[0431] Automatically blocks dangerous sites

[0432] Verifying the URL

[0433] The device receives the URL when the user attempts to access a website.

[0434] The device checks the received URL against a predefined list of dangerous sites (e.g., PhishTank, Safe Browsing API).

[0435] Access Blocks and Warnings

[0436] The device will automatically block access if the URL is included in the dangerous site list.

[0437] The device uses an emotion engine to recognize the user's emotional state and displays a warning message according to that emotion. For example, if the user appears anxious, a reassuring message will be displayed.

[0438] Personalized information provision

[0439] Obtaining user interests and preferences

[0440] The server collects data about the user's interests and preferences, such as past search history and preferences.

[0441] The server identifies specific areas of interest (e.g., "technology" or "health").

[0442] Filtering and Serving

[0443] The server filters all content retrieved from the database using a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[0444] The server uses an emotion engine to provide filtered content in the most appropriate format depending on the user's emotional state: for example, it provides concise information when the user is relaxed, and detailed information when the user is focused.

[0445] Diversity Feed Feature

[0446] Providing information from diverse perspectives

[0447] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[0448] The server uses an emotion engine to analyze the user's emotions and provides information from various perspectives in a format appropriate to the user's emotional state. For example, if the user is curious, detailed information is provided.

[0449] Reducing the filter bubble

[0450] The server provides content from a variety of sources to avoid users being trapped in filter bubbles based on specific interests or preferences.

[0451] The server uses an emotion engine to assess the user's emotional state and adjust the format of information delivery accordingly: for example, if the user is introverted, the server delivers information in a calm and receptive format.

[0452] Discussion space between users

[0453] Posting and saving comments

[0454] Users can post comments about the reliability and diversity of the information.

[0455] The server stores the posted comments and makes them available for other users to view.

[0456] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[0457] Facilitating discussion

[0458] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information.

[0459] The server uses an emotion engine to monitor each user's emotional state and guide the discussion to proceed in an appropriate manner. For example, if the discussion becomes heated, it will display a message urging the user to calm down.

[0460] Through these specific implementations, InfoGuardian helps users safely and efficiently access information and obtain information from various perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[0461] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0462] Program processing flow and specific explanation

[0463] Verifying the authenticity and bias of information

[0464] Step 1: Receiving information

[0465] The server receives a URL for information from the user, for example, a URL for a news article or blog post.

[0466] Input: User-provided URL

[0467] Output: Received URL data

[0468] Step 2: Sending prompts to the generative AI model

[0469] The server sends the received URL along with a prompt ("Please rate the truthfulness and bias of this information") to the generative AI model.

[0470] Input: Received URL

[0471] Data processing: Combining URL and prompt text

[0472] Output: A URL with a prompt sent to the generative AI model

[0473] Step 3: Evaluation by AI model

[0474] The generative AI model generates a truthfulness score and bias score for the provided URL, which it then compares with past data and evaluates using its own algorithm.

[0475] Input: URL with prompt

[0476] Data arithmetic: Calculating truthfulness and bias scores

[0477] Output: Truthfulness score and bias score

[0478] Step 4: User sentiment analysis

[0479] The server uses an emotion engine to analyze the user's emotions before providing the analysis results to the user. It also analyzes the user's webcam and text input.

[0480] Input: User's webcam video or text input

[0481] Data calculation: Analyzing the user's emotional state

[0482] Output: Emotion data (happiness, anger, surprise, etc.)

[0483] Step 5: Presenting the results

[0484] The server presents the truthfulness and bias scores to the user in a format that corresponds to the user's emotional state, for example, providing a clear and detailed explanation to a surprised user.

[0485] Input: Truthfulness score, bias score, sentiment data

[0486] Output: Analysis results presented to the user

[0487] Automatically blocks dangerous sites

[0488] Step 1: Check the URL

[0489] The device receives the URL when the user attempts to access a website.

[0490] Input: The URL the user is trying to access

[0491] Output: Received URL data

[0492] Step 2: Check against the dangerous site list

[0493] The device checks the received URL against a list of dangerous sites.

[0494] Input: Received URL

[0495] Data Computing: Comparison with Dangerous Site List

[0496] Output: Matching result (safe / unsafe)

[0497] Step 3: Blocking access and issuing warnings

[0498] If the verification result indicates a risk, the terminal blocks the access and displays a warning message.

[0499] The device uses an emotion engine to recognize the user's emotional state and displays appropriate warning messages. For example, if the user appears anxious, a reassuring message will be displayed.

[0500] Input: Danger assessment results, user emotion data

[0501] Output: Display of warning message

[0502] Personalized information provision

[0503] Step 1: Obtaining user interests and preferences

[0504] The server collects the user's past search history and preference information to identify the user's interests and preferences.

[0505] Input: User's past search history, preference information

[0506] Data Computing: Interest and Preference Analysis

[0507] Output: User interest and preference data

[0508] Step 2: Filtering content

[0509] The server filters all content retrieved from the database with a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[0510] Input: User interest and preference data

[0511] Data Calculation: Content Filtering

[0512] Output: Filtered content

[0513] Step 3: Provide information

[0514] The server uses an emotion engine to provide the filtered content in the most appropriate format according to the user's emotional state.

[0515] Input: filtered content, user sentiment data

[0516] Output: Information provided to the user

[0517] Diversity Feed Feature

[0518] Step 1: Gather information from diverse perspectives

[0519] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[0520] Input: None (regular execution)

[0521] Output: Collected information from various perspectives

[0522] Step 2: User sentiment analysis

[0523] The server uses an emotion engine to analyze the user's emotions before providing information.

[0524] Input: User emotion data (obtained from webcam or text input)

[0525] Data Computing: Sentiment Analysis

[0526] Output: Parsed emotion data

[0527] Step 3: Mitigating the filter bubble

[0528] The server tailors content from various sources to the user's emotional state, for example, providing it in a calm and receptive format if the user is introverted.

[0529] Input: Information from various perspectives, emotional data

[0530] Data calculations: Adjustments based on user interests, preferences and emotions

[0531] Output: Coordinated and diverse information

[0532] Discussion space between users

[0533] Step 1: Post and save your comment

[0534] Users post comments about the reliability and diversity of the information.

[0535] The server stores the posted comments and makes them available for other users to view.

[0536] Input: User comment

[0537] Output: Saved comment data

[0538] Step 2: Adjust the comment display

[0539] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[0540] Input: Comment data, poster's emotion data

[0541] Data calculation: Adjustment of comment display

[0542] Output: Adjusted comment display

[0543] Step 3: Facilitate discussion

[0544] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information. The emotion engine monitors the emotional state of each user and guides the discussion to proceed in an appropriate manner.

[0545] Input: User emotion data

[0546] Data Computation: A Guide to Analyzing and Discussing Emotional Data

[0547] Output: A well-organized discussion

[0548] This allows InfoGuardian to help users access information safely and efficiently, and gain information from multiple perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[0549] (Application example 2)

[0550] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0551] The modern internet is flooded with information of unknown veracity and bias, making it difficult for users with low digital literacy to access reliable information. There are also issues such as the risk of accessing dangerous websites and filter bubbles. Furthermore, there is a lack of systems that can efficiently collect information from diverse perspectives and provide it appropriately according to the user's emotional state.

[0552] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for regularly providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, and means for recognizing user emotions and providing information tailored to those emotions. This makes it possible to provide reliable information, prevent access to dangerous websites, mitigate filter bubbles, and provide appropriate information that takes user emotions into consideration.

[0553] "Truthfulness of information" refers to assessing whether certain information is true or not, and its accuracy.

[0554] "Bias" refers to an excessive reliance on a particular perspective or opinion.

[0555] An "artificial intelligence model" is one that uses algorithms or models to learn from large amounts of data and perform specific tasks.

[0556] "User interests and preferences" refers to the areas, topics, and preferences of individual users.

[0557] "Information curation" means organizing information collected from a variety of sources and presenting it in a form that is useful to users.

[0558] An "inaccurate source" is a website or other medium that provides information that is not reliable.

[0559] A "risky site" is a website that poses risks such as malware or phishing.

[0560] "Automatically blocking access" means that when a user attempts to access a dangerous site, that access is automatically blocked.

[0561] "Information from diverse perspectives" refers to information from a variety of viewpoints and positions.

[0562] A "filter bubble" is a state in which users receive information only based on their own interests and preferences, thereby excluding different perspectives.

[0563] "Recognizing the user's emotions" means analyzing the user's facial expressions, voice, etc. to understand their emotional state.

[0564] An "appropriate warning message" is one that takes into account the user's emotional state and displays a warning against inaccurate information or dangerous sites.

[0565] An "emotional state" is a set of emotions that a user is feeling.

[0566] An embodiment of the present invention includes the following elements: A server uses an artificial intelligence model to verify the veracity and bias of information. Specifically, the server receives information provided by a user, such as a news article or blog post, and analyzes the information using a generative AI model. This generative AI model is an algorithm that learns from large amounts of data and evaluates the accuracy and bias of the information. The veracity score and bias level obtained as the analysis result are provided to the user.

[0567] The server also curates information based on the user's interests and preferences. User interest and preference data is obtained from the user's behavioral history and profile information. Based on this data, relevant content is filtered and personalized information is provided.

[0568] The device checks the URL the user is trying to access and compares it with a predefined list of dangerous sites. If a dangerous website is detected, the device automatically blocks access and displays a warning message to the user. Here, the emotion engine recognizes the user's emotions and displays the warning message in an appropriate tone and format.

[0569] The server also periodically provides users with information from diverse perspectives, thereby mitigating the filter bubble problem. An emotion engine evaluates the user's emotional state and provides information from different perspectives in a format that is easy for users to accept. It also provides a forum for users to discuss the reliability and diversity of information. The server stores posted comments and opinions and shares them with other users.

[0570] The hardware used is a smartphone camera to recognize user emotions and an internet connection to acquire information. The software uses the requests library to acquire information from the internet and the face_recognition library to recognize emotions from the user's facial image. The generative AI model is used to analyze the truth and bias of the information.

[0571] For example, if a user attempts to access the URL "http: / / example.com / news," the URL is sent to the server and analyzed by the generative AI model. The truthfulness score and bias level are provided to the user in a format that is tailored to the user's emotions. If the user attempts to access the dangerous site "http: / / malware.com," the device automatically blocks access and displays an emotionally sensitive warning message. Furthermore, if the user is interested in health or technology, content related to these topics will be filtered and provided.

[0572] Examples of prompts to be input to the generative AI model include "Please rate the truthfulness and bias of this news article," "Please check if this URL is included in the dangerous site list," and "Please filter content relevant to the user's interests." This allows users to receive safe and reliable information.

[0573] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0574] Step 1:

[0575] A user provides information such as a news article or blog post. The user enters the URL of the information into the application, which then sends it to the server. The server retrieves the data based on the input URL and uses a generative AI model to analyze the information for truth and bias. The result of this analysis is a truthfulness score and bias level.

[0576] Step 2:

[0577] The server provides the user with a truthfulness score and bias level based on the results of the generative AI model analysis. At this time, the emotion engine detects the user's emotional state and understands what emotional state the user is in. The user's facial image is captured using the smartphone camera, and emotions are recognized using the face_recognition library. This recognition result becomes input data, and the results are displayed in a format appropriate for the user.

[0578] Step 3:

[0579] When a user attempts to browse a website, the device checks the URL the user is attempting to access. It checks the server to see if the URL is included in a list of dangerous sites. The results of this check are used as input, and if there is a risk, the device automatically blocks access and displays a warning message to the user to prevent access to inaccurate information sources or risky sites. This warning message is also displayed in a tone that matches the user's emotions using an emotion engine.

[0580] Step 4:

[0581] The server curates relevant information based on the user's interests and preferences, and filters the information to be provided based on the user's profile information and behavioral history. This filtering process is performed, and personalized information is output.

[0582] Step 5:

[0583] The server periodically collects information from diverse perspectives and provides it to users, thereby mitigating filter bubbles and creating an environment where users can be exposed to diverse information. The collected information from diverse perspectives serves as input data, and the emotion engine evaluates the user's emotional state and displays the information in a relevant format.

[0584] Step 6:

[0585] The server provides a forum for users to discuss the reliability and diversity of information. Users can post comments that can be seen by other users. The emotion engine monitors each user's emotional state and helps ensure smooth discussions.

[0586] Specific actions include providing information, checking URLs, analysis using a generative AI model, emotion recognition using an emotion engine, filtering, displaying warning messages, providing information from diverse perspectives, and maintaining a forum environment. Examples of prompts for the generative AI model include "Please rate the truthfulness and bias of this news article," "Check if this URL is included in a dangerous site list," and "Filter content relevant to the user's interests."

[0587] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0588] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0589] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0590] [Second embodiment]

[0591] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0592] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0593] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0594] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0595] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0596] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0597] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0598] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0599] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0600] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0601] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0602] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0603] This invention describes a system that verifies the authenticity and bias of information accessed by a user and provides only the most appropriate information to the user. This system is especially designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[0604] Verifying the authenticity and bias of information

[0605] Receiving and analyzing information

[0606] The server receives user-provided information (e.g., news articles or blog posts) and uses artificial intelligence models to analyze it for veracity (accuracy) and bias (whether it favors a particular point of view) to generate this information.

[0607] Providing verification results

[0608] The server provides users with a truthfulness score and bias level obtained from the artificial intelligence model, allowing them to determine the reliability of the information.

[0609] Automatically blocks dangerous sites

[0610] Verifying the URL

[0611] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[0612] Access Blocks and Warnings

[0613] If the URL you are trying to access is included in the dangerous site list, the device will automatically block the access and display a warning message to the user, allowing the user to avoid the risk of accessing dangerous sites.

[0614] Personalized information provision

[0615] Obtaining user interests and preferences

[0616] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[0617] Filtering and Serving

[0618] The server filters all content retrieved from the database based on the user's interests and preferences, and then provides the filtered content to the user, allowing the user to efficiently obtain only the information that is most relevant to them.

[0619] Diversity Feed Feature

[0620] Providing information from diverse perspectives

[0621] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology), allowing users to access a wide range of information without being biased towards a particular viewpoint.

[0622] Reducing the filter bubble

[0623] Server-provided diversity feeds allow users to access different perspectives and sources of information, rather than only being informed by their specific interests and preferences, thereby mitigating the filter bubble problem.

[0624] Discussion space between users

[0625] Posting and saving comments

[0626] Users can post comments about the reliability and versatility of the information, which the server stores and makes available for other users to view.

[0627] Facilitating discussion

[0628] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information, allowing users to share various perspectives and opinions about information and promoting the distribution of reliable information.

[0629] Explanation with concrete examples

[0630] For example, when User A checks a specific news article via InfoGuardian, the server receives the URL of that article. The server uses a generative AI model to evaluate the article's veracity and bias and provides the results to User A. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous and blocks access if necessary.

[0631] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, a regular diversity feed will also expose User A to information on politics and culture. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information.

[0632] Through these features, InfoGuardian helps users safely and efficiently access information and gain insights from multiple perspectives.

[0633] The processing flow will be explained below.

[0634] Verifying the authenticity and bias of information

[0635] Program processing

[0636] Step 1:

[0637] The server receives information provided by the user (eg, a URL for a news article).

[0638] Specific operation: When a user submits the URL of a news article, the server receives the URL as data.

[0639] Step 2:

[0640] The server retrieves the content of the news article from the received URL.

[0641] What happens: The server accesses the URL and scrapes the content of the web page to obtain text data.

[0642] Step 3:

[0643] The server loads the generative AI model.

[0644] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[0645] Step 4:

[0646] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[0647] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[0648] Step 5:

[0649] The server returns the analysis results to the user.

[0650] Specific Operation: The server sends the truthfulness score and bias level to the user for display.

[0651] Automatically blocks dangerous sites

[0652] Program processing

[0653] Step 1:

[0654] A user attempts to access a specific URL.

[0655] Specific operation: A user enters a URL in a browser and sends an access request.

[0656] Step 2:

[0657] The device checks the URL that is being accessed.

[0658] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[0659] Step 3:

[0660] The device determines whether the URL is included in the dangerous site list.

[0661] What it does: The device checks the URL and flags it if it's on the list.

[0662] Step 4:

[0663] The device will block access if the URL is dangerous.

[0664] Specific behavior: If the URL is included in the list, the device will block the access request and display a warning to the user.

[0665] Step 5:

[0666] The terminal displays a warning message to the user.

[0667] What it does: Displays a warning that says "Access to dangerous site blocked."

[0668] Personalized information provision

[0669] Program processing

[0670] Step 1:

[0671] The server obtains data about the user's interests and preferences.

[0672] Specific operation: The server refers to the user's profile information and past browsing history.

[0673] Step 2:

[0674] The server retrieves all content from a database.

[0675] What happens: The server queries the database to retrieve news articles and blog posts.

[0676] Step 3:

[0677] The server filters the retrieved content based on the user's interests and preferences.

[0678] Specific operation: The server selects only content related to topics of interest to the user.

[0679] Step 4:

[0680] The server provides the filtered content to the user.

[0681] Specific operation: Send the filtering results to be displayed on the user's screen.

[0682] Diversity Feed Feature

[0683] Program processing

[0684] Step 1:

[0685] The server obtains data about the user's interests and preferences.

[0686] Specific operation: The server refers to the user's profile information and past browsing history.

[0687] Step 2:

[0688] The server retrieves all content from a database.

[0689] What happens: The server queries the database to retrieve news articles and blog posts.

[0690] Step 3:

[0691] The server has a predefined list of topics from various perspectives.

[0692] Specific operation: The server provides topic lists such as politics, economics, culture, and technology.

[0693] Step 4:

[0694] The server filters information from multiple perspectives.

[0695] What it does: The server filters content based on various selected topics.

[0696] Step 5:

[0697] The server provides the user with information from various perspectives.

[0698] Specific behavior: Periodically display filtered diversity content on the user's screen.

[0699] Discussion space between users

[0700] Program processing

[0701] Step 1:

[0702] Users post comments in the discussion space.

[0703] Specific behavior: The user enters a comment in the text box and clicks the post button.

[0704] Step 2:

[0705] The server receives and stores the user's comments.

[0706] Specific operation: The server receives the comment data and stores it in the database.

[0707] Step 3:

[0708] The server retrieves the stored comments.

[0709] Specific behavior: When another user tries to view the discussion space, the server retrieves all comments.

[0710] Step 4:

[0711] The server displays the comments to the user.

[0712] Specific operation: The server displays the retrieved comments in the user's discussion space.

[0713] Step 5:

[0714] Users exchange opinions with other users.

[0715] What it does: Users read other users' comments and add and share their own opinions.

[0716] The above are the specific processing steps for carrying out the present invention, which allow InfoGuardian to provide highly reliable information to users and realize a safe and diverse information access environment.

[0717] Example 1

[0718] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0719] In today's information society, it is difficult for users to determine the authenticity and bias of the information they come into contact with, making it easier for information biased toward a particular viewpoint or inaccurate information to spread. Accessing inaccurate information sources or dangerous websites also poses a significant risk. Furthermore, users are bombarded with information, making it difficult to efficiently obtain important information relevant to them. Therefore, the present invention aims to solve these problems and provide a system that helps users access reliable information.

[0720] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0721] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, and means for automatically blocking access to inaccurate information sources and risky websites, thereby enabling users to efficiently obtain reliable information and avoid access to dangerous websites.

[0722] "Artificial intelligence model for verifying the veracity and bias of information" is an artificial intelligence technology used to analyze and evaluate information provided by users to determine its accuracy and whether it is biased toward a particular viewpoint.

[0723] "Curating information based on user interests and preferences" is the process of selecting, collecting, and providing highly relevant information based on a user's past behavior and preferences.

[0724] "Automatically block access to websites from inaccurate sources or risky websites" is a function that checks the URL of the website the user is trying to access against a predefined list of dangers and prevents access based on the results.

[0725] "Regularly providing information from diverse perspectives" is the process of regularly providing users with information from different perspectives and sources, allowing them to be exposed to a wide range of information that is not biased towards any particular perspective.

[0726] "Providing a forum for users to discuss the reliability and diversity of information" refers to creating a discussion space where users can exchange opinions and evaluations regarding the reliability and diversity of information.

[0727] "Notifying users of the results of analysis using a generative AI model" refers to the process of providing users with the results of information analyzed by artificial intelligence and informing them of the veracity and bias of that information.

[0728] "Compare the URL of the website you are trying to access with a list of dangerous sites" is a function that compares the address of the website you are trying to visit with a pre-defined list of dangerous sites.

[0729] "Filtering and providing content relevant to a user's interests and preferences" refers to the process of selecting and providing appropriate information to a user based on the user's interests and preferences.

[0730] "Save user comments and share with other users" is a function that saves ratings and opinions left by users about information in a database and allows other users to view those comments.

[0731] This invention is a system that verifies the authenticity and bias of the information accessed by the user and provides only the most appropriate information to the user. It is designed especially to support users with low digital literacy, such as young people and the elderly. This system operates based on the following program processing steps:

[0732] The server receives information provided by the user (e.g., news articles or blog posts). To analyze this information, the server uses a generative AI model (e.g., GPT-4). For example, a prompt sentence such as "Please rate the truthfulness and bias of this news article" is generated and input into the model. The generative AI model analyzes the truthfulness score and bias level based on the input information and outputs the results to the server. The server notifies the user of this analysis result. For example, if a news article submitted by a user is evaluated as having a truthfulness score of 80% and a low bias level, the server will notify the user that "This news article has a truthfulness score of 80% and a low bias level."

[0733] When a user attempts to access a website, the device retrieves the URL and compares it with a predefined list of dangerous sites. This list includes websites with inaccurate information sources and risky websites. For example, if a user attempts to access "example.com," the device will compare the URL with the list of dangerous sites and automatically block access if there is a match. The user will see a warning message stating, "This site is dangerous. Access has been blocked."

[0734] The server obtains information based on the user's interests and preferences and curates content based on that information. For example, if a user is interested in "technology" or "health," the server retrieves articles on these topics from the database and provides them after filtering. The filtered content is provided to the user in the form of, "Check out the latest technology news below."

[0735] Furthermore, the server periodically provides information from diverse perspectives. This information is collected from different perspectives and sources, allowing users to access a wide range of information without being biased towards a particular viewpoint. For example, diverse information is provided in the form of "Below are the latest articles on politics, economics, and culture."

[0736] Users can also post comments about the provided information and share them with other users. The server stores these comments and provides a discussion space, promoting discussion about the reliability and diversity of the information. Comments such as "This information is highly reliable and provided from diverse perspectives" can be viewed by other users.

[0737] Through these functions, the system helps users safely and efficiently access information and obtain information from multiple perspectives.

[0738] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0739] Step 1:

[0740] The server receives user-provided information (e.g., news articles or blog posts). The input is the information submitted by the user, and the output is the conversion of the received information into a data format. For example, a user might submit the URL of a particular news article to the server. The server parses the URL to retrieve the article content.

[0741] Step 2:

[0742] The server uses a generative AI model (e.g., GPT-4) to generate a prompt sentence that evaluates the truthfulness and bias of the information. The input is the received information, and the output is a prompt sentence for the AI ​​model. As a specific example, the server generates the prompt sentence, "Please evaluate the truthfulness and bias of this news article."

[0743] Step 3:

[0744] The server sends a prompt to the generative AI model, requesting an analysis of the truthfulness score and bias level. The input is the generated prompt, and the output is the analysis result obtained from the AI ​​model. As a specific example, the AI ​​model returns an analysis result of a truthfulness score of 80% and a low bias level.

[0745] Step 4:

[0746] The server notifies the user of the analysis results obtained from the generative AI model. The input is the generated analysis result, and the output is a message to be notified to the user. For example, the notification may say, "This news article has a truthfulness score of 80% and a low bias level."

[0747] Step 5:

[0748] When a user tries to access a website, the device obtains the URL and compares it with a predefined list of dangerous sites. The input is the URL the user is trying to access, and the output is the result of matching it with the list of dangerous sites. For example, if a user tries to access "example.com", the device will compare the URL with the list of dangerous sites.

[0749] Step 6:

[0750] If the URL matches the dangerous site list, the terminal will automatically block the user's access. The input at this time is the URL matching result, and the output is an access block and a warning message. For example, a warning message saying "This site is dangerous. Access has been blocked" is displayed.

[0751] Step 7:

[0752] The server retrieves information based on the user's interests and preferences. The input is data about the user's interests and preferences, and the output is a filtered list of related content. For example, if the user is interested in "technology" or "health," the server retrieves articles related to these topics.

[0753] Step 8:

[0754] The server filters the information it obtains and provides it to the user. The input is all content before filtering, and the output is the filtered content. For example, it is provided in the form of "Check out the latest news on the following technologies."

[0755] Step 9:

[0756] The server periodically collects information from various perspectives and provides it to the user. The input is data collected from different sources, and the output is a list of information from various perspectives. For example, it is provided in the form of "Below are new articles on politics, economics, and culture."

[0757] Step 10:

[0758] Users post comments about the provided information, and the server stores and shares them. The input is the user's comment, and the output is comment data that can be viewed by other users. For example, a comment such as "This information is highly reliable and provided from a variety of perspectives" is stored.

[0759] Step 11:

[0760] The server provides a discussion space where users can discuss the reliability and diversity of information. The input is information and comments, and the output is a record of the discussion and shared knowledge. For example, the server encourages discussion by saying, "Let's discuss this news article further."

[0761] (Application example 1)

[0762] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0763] Currently, the market is overflowing with information, making it difficult for users to determine its authenticity and bias. Furthermore, particularly in physical stores, there is a lack of ways to quickly assess the authenticity and reliability of product-related information. As a result, users are at a greater risk of making decisions based on incorrect information. Furthermore, there is a lack of effective ways to avoid accessing inaccurate information sources or risky websites. There is a need to solve these problems and provide safe and reliable information.

[0764] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0765] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on user interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for periodically providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, means for verifying the authenticity and bias of information related to products and providing reliable information to users in physical stores, and means for blocking dangerous information in physical stores in real time, thereby enabling users to make decisions based on accurate and reliable information.

[0766] "Truthfulness of information" refers to whether the information is based on facts.

[0767] "Bias" refers to whether information is biased toward a particular perspective or position.

[0768] An "artificial intelligence model" refers to an algorithm that learns from large amounts of data and performs pattern recognition and predictions.

[0769] "User interests and preferences" refers to specific topics or content that interest a user.

[0770] "Curation" refers to the act of selecting, organizing, and providing valuable information from a large amount of information.

[0771] An "inaccurate source" refers to a source that provides unreliable information.

[0772] A "risky site" is a website that may have a harmful effect on users.

[0773] "Diverse perspectives" refers to information from different viewpoints and positions.

[0774] "Reliability" refers to the degree to which information or a system is accurate or safe.

[0775] "Product-related information" refers to information such as reviews, ratings, and descriptions about a particular product.

[0776] "Brick and mortar store" refers to a store that exists in a physical location.

[0777] "Real-time" refers to processing or response occurring immediately, without any time delay.

[0778] "Blocking" refers to restricting or stopping a specific action or access.

[0779] A "discussion" refers to the act of multiple people exchanging opinions on a particular topic or issue.

[0780] To implement this invention, a system is constructed that combines the following elements and their respective functions.

[0781] System configuration

[0782] 1. User Device:

[0783] Using mobile devices such as smartphones and tablets.

[0784] Install a QR code reader application on your device and read product information in physical stores.

[0785] 2. Server:

[0786] The servers are hosted on Amazon Web Services (AWS) EC2.

[0787] The database used is MySQL.

[0788] The artificial intelligence model is built using Google Cloud AI.

[0789] Program and Data Processing

[0790] 1. Receiving and analyzing information:

[0791] The user scans a QR code related to a product with their smartphone while in a physical store.

[0792] The terminal sends the read information to the server.

[0793] The server receives the information and uses an artificial intelligence model to analyze the information's authenticity and bias.

[0794] 2. Providing verification results:

[0795] The server sends the analysis results to the user's device and displays reliable information.

[0796] Users can check the authenticity and reliability of product information.

[0797] 3. Blocking dangerous information:

[0798] When a user attempts to click on a link contained within the information, the server parses the URL.

[0799] If the URL is on the dangerous site list, the server blocks access and displays a warning message to the user.

[0800] 4. Personalized communications:

[0801] The server filters relevant product reviews and promotional information based on the user's interests and preferences.

[0802] To provide filtered information to a user terminal, enabling a user to efficiently obtain information of interest.

[0803] 5. Diversity Feed Feature:

[0804] The server periodically collects reviews and information from different perspectives and provides them to users.

[0805] It will alleviate the filter bubble problem and provide balanced information.

[0806] 6. Discussion Space:

[0807] The server provides a discussion space where users can post comments about product reviews and promotional information.

[0808] It allows users to exchange opinions with other users, encouraging discussion about the reliability and diversity of information.

[0809] Specific examples

[0810] For example, when a user attempts to purchase a product in a physical store, they scan the QR code attached to the product with their smartphone. The information is sent to a server, where an AI model analyzes the authenticity and bias of the information. The server then displays the analysis results to the user, providing a reliable product review.

[0811] Also, when a user tries to click on a link, the server analyzes the URL and, if it is a dangerous site, blocks access and displays a warning message.

[0812] An example prompt might have the following format:

[0813] "Please verify this information to ensure its authenticity. Please rate the following review and return your result: 'This product was amazing!'"

[0814] This allows users to make decisions based on accurate and reliable information.

[0815] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0816] Step 1:

[0817] A user reads a QR code attached to a product in a physical store with their smartphone. The input is the QR code data, and the output is sending the read data to a server. Specifically, the QR code is scanned using a QR code reader application, and the obtained data is transmitted to the server.

[0818] Step 2:

[0819] The server receives the data sent by the user and analyzes the authenticity and bias of the information using an artificial intelligence model (e.g., Google Cloud AI). The input is the data obtained from the QR code, and the output is the authenticity score and bias level of the information. Specifically, the server inputs the received data into the AI ​​model and obtains the analysis results.

[0820] Step 3:

[0821] The server sends the analysis results to the user's device, providing the user with reliable information. The input is the truth score and bias level, and the output is the analysis results displayed on the user's device. Specifically, the server formats the analysis results and communicates them to the user's device.

[0822] Step 4:

[0823] When a user tries to click on a provided link, the server checks the URL against a predefined list of dangerous sites. The input is the URL the user tried to click, and the output is a decision on whether the URL is safe or dangerous. Specifically, the server checks the URL and obtains the result.

[0824] Step 5:

[0825] If the server detects a dangerous URL, it will automatically send a warning message and instructions to block access to the user's device. The input is the result of the dangerous URL judgment, and the output is the display of a warning message. Specifically, the server sends a warning message to the user's device and displays the warning to the user.

[0826] Step 6:

[0827] The server filters relevant product reviews and promotional information based on the user's interest and preference data. The input is the user's interest and preference data, and the output is the filtered product reviews and promotional information. Specifically, the server searches for relevant information from a database and filters it based on the user's interest and preference.

[0828] Step 7:

[0829] The server provides the filtered information to the user terminal, allowing the user to efficiently obtain information of interest. The input is filtered product reviews and promotional information, and the output is the information displayed on the user terminal. Specifically, the server sends the filtered information to the user terminal.

[0830] Step 8:

[0831] The server periodically collects reviews and information from different perspectives and provides them to users. The input is reviews and information from diverse perspectives, and the output is a diversity feed displayed on the user's device. Specifically, the server categorizes the collected information and periodically provides it to users.

[0832] Step 9:

[0833] The server provides a discussion space where users can post comments about product reviews and promotional information. The input is the user's comment, and the output is saved as a comment that can be viewed by other users. Specifically, the server receives the comment, saves it in a database, and displays it to other users.

[0834] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0835] This invention describes a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is particularly designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[0836] Verifying the authenticity and bias of information

[0837] Receiving and analyzing information

[0838] The server receives user-provided information (e.g., news articles or blog posts), which it then analyzes for veracity (accuracy) and bias (whether it favors a particular point of view) using a generative AI model.

[0839] Providing verification results

[0840] The server provides users with the truthfulness score and bias level obtained from the AI ​​model. At this time, the emotion engine recognizes the user's emotions and presents the results in a format appropriate to those emotions, making it easier for users to understand the reliability of the information.

[0841] Automatically blocks dangerous sites

[0842] Verifying the URL

[0843] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[0844] Access Blocks and Warnings

[0845] If the URL you are trying to access is on the dangerous site list, the device will automatically block the access and display a warning message to the user. The emotion engine recognizes the user's emotions and adjusts the tone and format of the warning message appropriately to help the user remain calm.

[0846] Personalized information provision

[0847] Obtaining user interests and preferences

[0848] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[0849] Filtering and Serving

[0850] The server filters all content retrieved from the database based on the user's interests and preferences. The filtered content is then provided to the user. The emotion engine provides information at the optimal timing and in the optimal format based on the user's emotional state. This allows users to efficiently receive information that is highly relevant to them.

[0851] Diversity Feed Feature

[0852] Providing information from diverse perspectives

[0853] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology). The emotion engine recognizes the user's emotions and considers how the information provided from various perspectives will be received by the user.

[0854] Reducing the filter bubble

[0855] The server-provided diversity feed allows users to access different perspectives and sources of information, rather than only receiving information based on specific interests or preferences. The emotion engine evaluates the user's emotional state and adjusts the format to provide diverse perspectives while mitigating the filter bubble problem. This makes it easier for users to accept diverse information.

[0856] Discussion space between users

[0857] Posting and saving comments

[0858] Users can post comments about the reliability and diversity of information. The server stores these comments and makes them available for other users to view. The emotion engine also recognizes the poster's emotions and adjusts the display format of the comments accordingly.

[0859] Facilitating discussion

[0860] The server provides a discussion space and encourages users to discuss the reliability and diversity of information. An emotion engine monitors each user's emotional state and guides the discussion to proceed in an appropriate manner. This allows users to share multiple perspectives and opinions about information, promoting the circulation of reliable information.

[0861] Explanation with concrete examples

[0862] For example, when User A checks a specific news article via InfoGuardian, the server receives the article's URL. The server uses a generative AI model to evaluate the article's veracity and bias, and presents the results in a format that matches User A's emotions, as analyzed by an emotion engine. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous, blocks access if necessary, and displays a warning message that matches User A's emotions.

[0863] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, User A can also access information on politics and culture through a regularly provided diversity feed. The emotion engine will also provide this information in an appropriate format, taking into account User A's emotional state. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information. The emotion engine is also involved in these discussions, promoting smooth and constructive communication.

[0864] Through these features, InfoGuardian helps users access information safely and efficiently, gaining information from multiple perspectives, and utilizes an emotion engine to enhance the user experience.

[0865] The processing flow will be explained below.

[0866] Verifying the authenticity and bias of information

[0867] Program processing

[0868] Step 1:

[0869] The server receives information provided by the user (such as a URL for a news article).

[0870] Specific behavior: The user enters the URL of a news article and sends it to the server.

[0871] Step 2:

[0872] The server retrieves the content of the news article from the received URL.

[0873] What it does: The server accesses the URL and scrapes the content of the web page to collect text data.

[0874] Step 3:

[0875] The server loads the generative AI model.

[0876] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[0877] Step 4:

[0878] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[0879] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[0880] Step 5:

[0881] The server activates an emotion engine that recognizes the user's emotions and analyzes the user's emotions.

[0882] How it works: The emotion engine assesses the user's emotional state based on their facial expressions, tone of voice, and input.

[0883] Step 6:

[0884] The server presents the analysis results based on the user's emotions.

[0885] Specific operation: The server allows the user to view the truthfulness score and bias level in a format appropriate to the user's emotional state (e.g., a message in a gentle tone).

[0886] Automatically blocks dangerous sites

[0887] Program processing

[0888] Step 1:

[0889] A user attempts to access a specific URL.

[0890] Specific operation: The user enters a URL in the browser and sends an access request.

[0891] Step 2:

[0892] The device checks the URL that is being accessed.

[0893] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[0894] Step 3:

[0895] The device determines whether the URL is included in the dangerous site list.

[0896] What it does: The device checks the URL and flags it if it's on the list.

[0897] Step 4:

[0898] The device will block access if the URL is dangerous.

[0899] Specific operation: If the URL is included in the list, the terminal will block the access request.

[0900] Step 5:

[0901] The terminal will display a warning message to the user.

[0902] What it does: The emotion engine recognizes the user's emotions and displays the warning "Access to dangerous site blocked" in a tone and format appropriate to that emotional state.

[0903] Personalized information provision

[0904] Program processing

[0905] Step 1:

[0906] The server collects data about the user's interests and preferences.

[0907] Specific operation: The server refers to the user's profile information and past browsing history.

[0908] Step 2:

[0909] The server retrieves all content from a database.

[0910] What happens: The server queries the database to retrieve news articles and blog posts.

[0911] Step 3:

[0912] The server filters the retrieved content based on the user's interests and preferences.

[0913] What it does: The server selects only content related to topics that the user has expressed interest in.

[0914] Step 4:

[0915] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[0916] Specific operation: The emotion engine determines the user's emotional state from their facial expression, tone of voice, and input.

[0917] Step 5:

[0918] The server provides the filtered content to the user.

[0919] What it does: The emotion engine displays filtered content on the user's screen at a time and in a format appropriate to the user's emotional state.

[0920] Diversity Feed Feature

[0921] Program processing

[0922] Step 1:

[0923] The server collects data about the user's interests and preferences.

[0924] Specific operation: The server refers to the user's profile information and past browsing history.

[0925] Step 2:

[0926] The server retrieves all content from a database.

[0927] What happens: The server queries the database to retrieve news articles and blog posts.

[0928] Step 3:

[0929] The server has a list of topics from various predefined perspectives.

[0930] Specific operation: The server provides a variety of topic lists, including politics, economics, culture, and technology.

[0931] Step 4:

[0932] The server filters information from multiple perspectives.

[0933] What it does: The server filters content based on various selected topics.

[0934] Step 5:

[0935] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[0936] What it does: The emotion engine delivers content from multiple perspectives in an appropriate format based on the user's emotional state.

[0937] Step 6:

[0938] The server provides users with information from a variety of perspectives.

[0939] What it does: The sentiment engine periodically provides diversity feeds and adjusts the display format to make it easier for users to access information from different perspectives.

[0940] Discussion space between users

[0941] Program processing

[0942] Step 1:

[0943] Users post comments in the discussion space.

[0944] Specific behavior: The user enters a comment in the text box and clicks the post button.

[0945] Step 2:

[0946] The server receives and stores the user's comments.

[0947] Specific operation: The server receives the comment data and stores it in the database.

[0948] Step 3:

[0949] The server activates an emotion engine that recognizes the user's emotions and evaluates the poster's emotional state.

[0950] Specific operation: The emotion engine analyzes emotions from the poster's expressions and content and saves them in an appropriate format.

[0951] Step 4:

[0952] The server retrieves the stored comments.

[0953] What happens: When another user tries to view the discussion space, the server retrieves all comments.

[0954] Step 5:

[0955] The server displays the comments to the user.

[0956] How it works: The emotion engine adjusts the display format of comments based on the emotional state of the user viewing them.

[0957] Step 6:

[0958] Users exchange opinions with other users.

[0959] How it works: Users read other users' comments, add their own opinions, and share them. The emotion engine performs real-time emotion recognition to facilitate this process.

[0960] The above are the specific processing steps for implementing this invention. As a result, InfoGuardian provides users with highly reliable information and realizes a safe and diverse information access environment. Furthermore, by combining it with an emotion engine, the user experience is further improved, and appropriate information can be provided according to individual needs.

[0961] Example 2

[0962] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0963] In modern society, the amount of information available on the Internet is enormous, and much of it contains false or biased information. Furthermore, users with low digital literacy have difficulty selecting reliable information, increasing the risk of misunderstandings and poor judgment based on misinformation. Furthermore, the risk of users accessing dangerous websites is also increasing. There is a need for a system that can comprehensively resolve these issues and provide users with accurate, unbiased information.

[0964] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0965] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for recognizing user emotions and providing analysis results in an appropriate format, and means for curating information based on the user's interests and preferences. This allows users to receive reliable information in an appropriate format, preventing misunderstandings and incorrect decisions based on false information. Furthermore, by using an emotion engine, optimal information is presented according to the user's emotional state, improving the user experience.

[0966] "Authenticity of information" refers to whether the information provided on the Internet is true and accurate.

[0967] "Bias" refers to information that is overly biased toward a particular perspective or opinion.

[0968] An "artificial intelligence model" refers to a machine learning algorithm that analyzes data, finds patterns in it, and makes predictions and decisions.

[0969] An "emotion engine" is a software component that recognizes emotions from a user's facial expressions and text input, and responds according to that emotional state.

[0970] "Curation" refers to selecting information based on a user's interests and preferences and providing useful information from that selection.

[0971] "Automatic access blocking measures" refers to the ability to automatically detect and block access to dangerous websites or inaccurate information sources.

[0972] "Warning Message" means a message that is displayed to warn a user when they attempt to access a dangerous website.

[0973] "Diverse perspectives" refers to multiple sources of information and opinions provided from different backgrounds and positions.

[0974] "Filter bubble" refers to the phenomenon in which users are only exposed to similar information based on their interests and preferences, making it difficult for them to access different perspectives and information.

[0975] "Discussion forum" refers to a space where users can exchange opinions and debate about the reliability and diversity of information.

[0976] "Comment display format" refers to how a comment posted by a user is visualized and displayed to other users.

[0977] "Means to facilitate smooth discussion" refers to functions that support constructive and smooth discussions between users.

[0978] This invention describes a specific embodiment for implementing a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is especially designed to support users with low digital literacy.

[0979] Hardware and Software Configuration

[0980] Hardware

[0981] Server: Use a high-performance cloud-based computing system, such as an EC2 instance from Amazon Web Services (AWS).

[0982] Device: The device used by the user, such as a PC, tablet, or smartphone.

[0983] software

[0984] Generative AI models: Use open-source machine learning frameworks, such as OpenAI's GPT-4.

[0985] Emotion Engine: Uses Microsoft Azure's Emotion Recognition API to recognize user emotions.

[0986] Database: Use a cloud-based database service, such as Amazon RDS, to store data about the truth, bias, and user interests and preferences.

[0987] Verifying the authenticity and bias of information

[0988] Receiving and analyzing information

[0989] The server receives the URL of the information (news article or blog post) provided by the user.

[0990] The server sends the URL to the generative AI model along with a prompt, such as "Please rate the veracity and bias of this information."

[0991] The generative AI model returns a truthfulness score and bias score for the information.

[0992] Providing verification results

[0993] The server obtains the truthfulness and bias scores returned by the generative AI model.

[0994] The server uses an emotion engine to analyze the user's current emotion.

[0995] The server will present the results to the user in an appropriate format depending on the user's emotional state, for example, if the user is surprised, it will provide a clear and detailed explanation.

[0996] Automatically blocks dangerous sites

[0997] Verifying the URL

[0998] The device receives the URL when the user attempts to access a website.

[0999] The device checks the received URL against a predefined list of dangerous sites (e.g., PhishTank, Safe Browsing API).

[1000] Access Blocks and Warnings

[1001] The device will automatically block access if the URL is included in the dangerous site list.

[1002] The device uses an emotion engine to recognize the user's emotional state and displays a warning message according to that emotion. For example, if the user appears anxious, a reassuring message will be displayed.

[1003] Personalized information provision

[1004] Obtaining user interests and preferences

[1005] The server collects data about the user's interests and preferences, such as past search history and preferences.

[1006] The server identifies specific areas of interest (e.g., "technology" or "health").

[1007] Filtering and Serving

[1008] The server filters all content retrieved from the database using a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[1009] The server uses an emotion engine to provide filtered content in the most appropriate format depending on the user's emotional state: for example, it provides concise information when the user is relaxed, and detailed information when the user is focused.

[1010] Diversity Feed Feature

[1011] Providing information from diverse perspectives

[1012] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[1013] The server uses an emotion engine to analyze the user's emotions and provides information from various perspectives in a format appropriate to the user's emotional state. For example, if the user is curious, detailed information is provided.

[1014] Reducing the filter bubble

[1015] The server provides content from a variety of sources to avoid users being trapped in filter bubbles based on specific interests or preferences.

[1016] The server uses an emotion engine to assess the user's emotional state and adjust the format of information delivery accordingly: for example, if the user is introverted, the server delivers information in a calm and receptive format.

[1017] Discussion space between users

[1018] Posting and saving comments

[1019] Users can post comments about the reliability and diversity of the information.

[1020] The server stores the posted comments and makes them available for other users to view.

[1021] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[1022] Facilitating discussion

[1023] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information.

[1024] The server uses an emotion engine to monitor each user's emotional state and guide the discussion to proceed in an appropriate manner. For example, if the discussion becomes heated, it will display a message urging the user to calm down.

[1025] Through these specific implementations, InfoGuardian helps users safely and efficiently access information and obtain information from various perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[1026] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1027] Program processing flow and specific explanation

[1028] Verifying the authenticity and bias of information

[1029] Step 1: Receiving information

[1030] The server receives a URL for information from the user, for example, a URL for a news article or blog post.

[1031] Input: User-provided URL

[1032] Output: Received URL data

[1033] Step 2: Sending prompts to the generative AI model

[1034] The server sends the received URL along with a prompt ("Please rate the truthfulness and bias of this information") to the generative AI model.

[1035] Input: Received URL

[1036] Data processing: Combining URL and prompt text

[1037] Output: A URL with a prompt sent to the generative AI model

[1038] Step 3: Evaluation by AI model

[1039] The generative AI model generates a truthfulness score and bias score for the provided URL, which it then compares with past data and evaluates using its own algorithm.

[1040] Input: URL with prompt

[1041] Data arithmetic: Calculating truthfulness and bias scores

[1042] Output: Truthfulness score and bias score

[1043] Step 4: User sentiment analysis

[1044] The server uses an emotion engine to analyze the user's emotions before providing the analysis results to the user. It also analyzes the user's webcam and text input.

[1045] Input: User's webcam video or text input

[1046] Data calculation: Analyzing the user's emotional state

[1047] Output: Emotion data (happiness, anger, surprise, etc.)

[1048] Step 5: Presenting the results

[1049] The server presents the truthfulness and bias scores to the user in a format that corresponds to the user's emotional state, for example, providing a clear and detailed explanation to a surprised user.

[1050] Input: Truthfulness score, bias score, sentiment data

[1051] Output: Analysis results presented to the user

[1052] Automatically blocks dangerous sites

[1053] Step 1: Check the URL

[1054] The device receives the URL when the user attempts to access a website.

[1055] Input: The URL the user is trying to access

[1056] Output: Received URL data

[1057] Step 2: Check against the dangerous site list

[1058] The device checks the received URL against a list of dangerous sites.

[1059] Input: Received URL

[1060] Data Computing: Comparison with Dangerous Site List

[1061] Output: Matching result (safe / unsafe)

[1062] Step 3: Blocking access and issuing warnings

[1063] If the verification result indicates a risk, the terminal blocks the access and displays a warning message.

[1064] The device uses an emotion engine to recognize the user's emotional state and displays appropriate warning messages. For example, if the user appears anxious, a reassuring message will be displayed.

[1065] Input: Danger assessment results, user emotion data

[1066] Output: Display of warning message

[1067] Personalized information provision

[1068] Step 1: Obtaining user interests and preferences

[1069] The server collects the user's past search history and preference information to identify the user's interests and preferences.

[1070] Input: User's past search history, preference information

[1071] Data Computing: Interest and Preference Analysis

[1072] Output: User interest and preference data

[1073] Step 2: Filtering content

[1074] The server filters all content retrieved from the database with a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[1075] Input: User interest and preference data

[1076] Data Calculation: Content Filtering

[1077] Output: Filtered content

[1078] Step 3: Provide information

[1079] The server uses an emotion engine to provide the filtered content in the most appropriate format according to the user's emotional state.

[1080] Input: filtered content, user sentiment data

[1081] Output: Information provided to the user

[1082] Diversity Feed Feature

[1083] Step 1: Gather information from diverse perspectives

[1084] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[1085] Input: None (regular execution)

[1086] Output: Collected information from various perspectives

[1087] Step 2: User sentiment analysis

[1088] The server uses an emotion engine to analyze the user's emotions before providing information.

[1089] Input: User emotion data (obtained from webcam or text input)

[1090] Data Computing: Sentiment Analysis

[1091] Output: Parsed emotion data

[1092] Step 3: Mitigating the filter bubble

[1093] The server tailors content from various sources to the user's emotional state, for example, providing it in a calm and receptive format if the user is introverted.

[1094] Input: Information from various perspectives, emotional data

[1095] Data calculations: Adjustments based on user interests, preferences and emotions

[1096] Output: Coordinated and diverse information

[1097] Discussion space between users

[1098] Step 1: Post and save your comment

[1099] Users post comments about the reliability and diversity of the information.

[1100] The server stores the posted comments and makes them available for other users to view.

[1101] Input: User comment

[1102] Output: Saved comment data

[1103] Step 2: Adjust the comment display

[1104] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[1105] Input: Comment data, poster's emotion data

[1106] Data calculation: Adjustment of comment display

[1107] Output: Adjusted comment display

[1108] Step 3: Facilitate discussion

[1109] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information. The emotion engine monitors the emotional state of each user and guides the discussion to proceed in an appropriate manner.

[1110] Input: User emotion data

[1111] Data Computation: A Guide to Analyzing and Discussing Emotional Data

[1112] Output: A well-organized discussion

[1113] This allows InfoGuardian to help users access information safely and efficiently, and gain information from multiple perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[1114] (Application example 2)

[1115] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[1116] The modern internet is flooded with information of unknown veracity and bias, making it difficult for users with low digital literacy to access reliable information. There are also issues such as the risk of accessing dangerous websites and filter bubbles. Furthermore, there is a lack of systems that can efficiently collect information from diverse perspectives and provide it appropriately according to the user's emotional state.

[1117] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for regularly providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, and means for recognizing user emotions and providing information tailored to those emotions. This makes it possible to provide reliable information, prevent access to dangerous websites, mitigate filter bubbles, and provide appropriate information that takes user emotions into consideration.

[1118] "Truthfulness of information" refers to assessing whether certain information is true or not, and its accuracy.

[1119] "Bias" refers to an excessive reliance on a particular perspective or opinion.

[1120] An "artificial intelligence model" is one that uses algorithms or models to learn from large amounts of data and perform specific tasks.

[1121] "User interests and preferences" refers to the areas, topics, and preferences of individual users.

[1122] "Information curation" means organizing information collected from a variety of sources and presenting it in a form that is useful to users.

[1123] An "inaccurate source" is a website or other medium that provides information that is not reliable.

[1124] A "risky site" is a website that poses risks such as malware or phishing.

[1125] "Automatically blocking access" means that when a user attempts to access a dangerous site, that access is automatically blocked.

[1126] "Information from diverse perspectives" refers to information from a variety of viewpoints and positions.

[1127] A "filter bubble" is a state in which users receive information only based on their own interests and preferences, thereby excluding different perspectives.

[1128] "Recognizing the user's emotions" means analyzing the user's facial expressions, voice, etc. to understand their emotional state.

[1129] An "appropriate warning message" is one that takes into account the user's emotional state and displays a warning against inaccurate information or dangerous sites.

[1130] An "emotional state" is a set of emotions that a user is feeling.

[1131] An embodiment of the present invention includes the following elements: A server uses an artificial intelligence model to verify the veracity and bias of information. Specifically, the server receives information provided by a user, such as a news article or blog post, and analyzes the information using a generative AI model. This generative AI model is an algorithm that learns from large amounts of data and evaluates the accuracy and bias of the information. The veracity score and bias level obtained as the analysis result are provided to the user.

[1132] The server also curates information based on the user's interests and preferences. User interest and preference data is obtained from the user's behavioral history and profile information. Based on this data, relevant content is filtered and personalized information is provided.

[1133] The device checks the URL the user is trying to access and compares it with a predefined list of dangerous sites. If a dangerous website is detected, the device automatically blocks access and displays a warning message to the user. Here, the emotion engine recognizes the user's emotions and displays the warning message in an appropriate tone and format.

[1134] The server also periodically provides users with information from diverse perspectives, thereby mitigating the filter bubble problem. An emotion engine evaluates the user's emotional state and provides information from different perspectives in a format that is easy for users to accept. It also provides a forum for users to discuss the reliability and diversity of information. The server stores posted comments and opinions and shares them with other users.

[1135] The hardware used is a smartphone camera to recognize user emotions and an internet connection to acquire information. The software uses the requests library to acquire information from the internet and the face_recognition library to recognize emotions from the user's facial image. The generative AI model is used to analyze the truth and bias of the information.

[1136] For example, if a user attempts to access the URL "http: / / example.com / news," the URL is sent to the server and analyzed by the generative AI model. The truthfulness score and bias level are provided to the user in a format that is tailored to the user's emotions. If the user attempts to access the dangerous site "http: / / malware.com," the device automatically blocks access and displays an emotionally sensitive warning message. Furthermore, if the user is interested in health or technology, content related to these topics will be filtered and provided.

[1137] Examples of prompts to be input to the generative AI model include "Please rate the truthfulness and bias of this news article," "Please check if this URL is included in the dangerous site list," and "Please filter content relevant to the user's interests." This allows users to receive safe and reliable information.

[1138] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1139] Step 1:

[1140] A user provides information such as a news article or blog post. The user enters the URL of the information into the application, which then sends it to the server. The server retrieves the data based on the input URL and uses a generative AI model to analyze the information for truth and bias. The result of this analysis is a truthfulness score and bias level.

[1141] Step 2:

[1142] The server provides the user with a truthfulness score and bias level based on the results of the generative AI model analysis. At this time, the emotion engine detects the user's emotional state and understands what emotional state the user is in. The user's facial image is captured using the smartphone camera, and emotions are recognized using the face_recognition library. This recognition result becomes input data, and the results are displayed in a format appropriate for the user.

[1143] Step 3:

[1144] When a user attempts to browse a website, the device checks the URL the user is attempting to access. It checks the server to see if the URL is included in a list of dangerous sites. The results of this check are used as input, and if there is a risk, the device automatically blocks access and displays a warning message to the user to prevent access to inaccurate information sources or risky sites. This warning message is also displayed in a tone that matches the user's emotions using an emotion engine.

[1145] Step 4:

[1146] The server curates relevant information based on the user's interests and preferences, and filters the information to be provided based on the user's profile information and behavioral history. This filtering process is performed, and personalized information is output.

[1147] Step 5:

[1148] The server periodically collects information from diverse perspectives and provides it to users, thereby mitigating filter bubbles and creating an environment where users can be exposed to diverse information. The collected information from diverse perspectives serves as input data, and the emotion engine evaluates the user's emotional state and displays the information in a relevant format.

[1149] Step 6:

[1150] The server provides a forum for users to discuss the reliability and diversity of information. Users can post comments that can be seen by other users. The emotion engine monitors each user's emotional state and helps ensure smooth discussions.

[1151] Specific actions include providing information, checking URLs, analysis using a generative AI model, emotion recognition using an emotion engine, filtering, displaying warning messages, providing information from diverse perspectives, and maintaining a forum environment. Examples of prompts for the generative AI model include "Please rate the truthfulness and bias of this news article," "Check if this URL is included in a dangerous site list," and "Filter content relevant to the user's interests."

[1152] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1153] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1154] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[1155] [Third embodiment]

[1156] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1157] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1158] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1159] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[1160] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1161] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1162] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1163] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1164] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1165] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1166] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1167] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1168] This invention describes a system that verifies the authenticity and bias of information accessed by a user and provides only the most appropriate information to the user. This system is especially designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[1169] Verifying the authenticity and bias of information

[1170] Receiving and analyzing information

[1171] The server receives user-provided information (e.g., news articles or blog posts) and uses artificial intelligence models to analyze it for veracity (accuracy) and bias (whether it favors a particular point of view) to generate this information.

[1172] Providing verification results

[1173] The server provides users with a truthfulness score and bias level obtained from the artificial intelligence model, allowing them to determine the reliability of the information.

[1174] Automatically blocks dangerous sites

[1175] Verifying the URL

[1176] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[1177] Access Blocks and Warnings

[1178] If the URL you are trying to access is included in the dangerous site list, the device will automatically block the access and display a warning message to the user, allowing the user to avoid the risk of accessing dangerous sites.

[1179] Personalized information provision

[1180] Obtaining user interests and preferences

[1181] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[1182] Filtering and Serving

[1183] The server filters all content retrieved from the database based on the user's interests and preferences, and then provides the filtered content to the user, allowing the user to efficiently obtain only the information that is most relevant to them.

[1184] Diversity Feed Feature

[1185] Providing information from diverse perspectives

[1186] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology), allowing users to access a wide range of information without being biased towards a particular viewpoint.

[1187] Reducing the filter bubble

[1188] Server-provided diversity feeds allow users to access different perspectives and sources of information, rather than only being informed by their specific interests and preferences, thereby mitigating the filter bubble problem.

[1189] Discussion space between users

[1190] Posting and saving comments

[1191] Users can post comments about the reliability and versatility of the information, which the server stores and makes available for other users to view.

[1192] Facilitating discussion

[1193] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information, allowing users to share various perspectives and opinions about information and promoting the distribution of reliable information.

[1194] Explanation with concrete examples

[1195] For example, when User A checks a specific news article via InfoGuardian, the server receives the URL of that article. The server uses a generative AI model to evaluate the article's veracity and bias and provides the results to User A. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous and blocks access if necessary.

[1196] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, a regular diversity feed will also expose User A to information on politics and culture. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information.

[1197] Through these features, InfoGuardian helps users safely and efficiently access information and gain insights from multiple perspectives.

[1198] The processing flow will be explained below.

[1199] Verifying the authenticity and bias of information

[1200] Program processing

[1201] Step 1:

[1202] The server receives information provided by the user (eg, a URL for a news article).

[1203] Specific operation: When a user submits the URL of a news article, the server receives the URL as data.

[1204] Step 2:

[1205] The server retrieves the content of the news article from the received URL.

[1206] What happens: The server accesses the URL and scrapes the content of the web page to obtain text data.

[1207] Step 3:

[1208] The server loads the generative AI model.

[1209] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[1210] Step 4:

[1211] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[1212] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[1213] Step 5:

[1214] The server returns the analysis results to the user.

[1215] Specific Operation: The server sends the truthfulness score and bias level to the user for display.

[1216] Automatically blocks dangerous sites

[1217] Program processing

[1218] Step 1:

[1219] A user attempts to access a specific URL.

[1220] Specific operation: A user enters a URL in a browser and sends an access request.

[1221] Step 2:

[1222] The device checks the URL that is being accessed.

[1223] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[1224] Step 3:

[1225] The device determines whether the URL is included in the dangerous site list.

[1226] What it does: The device checks the URL and flags it if it's on the list.

[1227] Step 4:

[1228] The device will block access if the URL is dangerous.

[1229] Specific behavior: If the URL is included in the list, the device will block the access request and display a warning to the user.

[1230] Step 5:

[1231] The terminal displays a warning message to the user.

[1232] What it does: Displays a warning that says "Access to dangerous site blocked."

[1233] Personalized information provision

[1234] Program processing

[1235] Step 1:

[1236] The server obtains data about the user's interests and preferences.

[1237] Specific operation: The server refers to the user's profile information and past browsing history.

[1238] Step 2:

[1239] The server retrieves all content from a database.

[1240] What happens: The server queries the database to retrieve news articles and blog posts.

[1241] Step 3:

[1242] The server filters the retrieved content based on the user's interests and preferences.

[1243] Specific operation: The server selects only content related to topics of interest to the user.

[1244] Step 4:

[1245] The server provides the filtered content to the user.

[1246] Specific operation: Send the filtering results to be displayed on the user's screen.

[1247] Diversity Feed Feature

[1248] Program processing

[1249] Step 1:

[1250] The server obtains data about the user's interests and preferences.

[1251] Specific operation: The server refers to the user's profile information and past browsing history.

[1252] Step 2:

[1253] The server retrieves all content from a database.

[1254] What happens: The server queries the database to retrieve news articles and blog posts.

[1255] Step 3:

[1256] The server has a predefined list of topics from various perspectives.

[1257] Specific operation: The server provides topic lists such as politics, economics, culture, and technology.

[1258] Step 4:

[1259] The server filters information from multiple perspectives.

[1260] What it does: The server filters content based on various selected topics.

[1261] Step 5:

[1262] The server provides the user with information from various perspectives.

[1263] Specific behavior: Periodically display filtered diversity content on the user's screen.

[1264] Discussion space between users

[1265] Program processing

[1266] Step 1:

[1267] Users post comments in the discussion space.

[1268] Specific behavior: The user enters a comment in the text box and clicks the post button.

[1269] Step 2:

[1270] The server receives and stores the user's comments.

[1271] Specific operation: The server receives the comment data and stores it in the database.

[1272] Step 3:

[1273] The server retrieves the stored comments.

[1274] Specific behavior: When another user tries to view the discussion space, the server retrieves all comments.

[1275] Step 4:

[1276] The server displays the comments to the user.

[1277] Specific operation: The server displays the retrieved comments in the user's discussion space.

[1278] Step 5:

[1279] Users exchange opinions with other users.

[1280] What it does: Users read other users' comments and add and share their own opinions.

[1281] The above are the specific processing steps for carrying out the present invention, which allow InfoGuardian to provide highly reliable information to users and realize a safe and diverse information access environment.

[1282] Example 1

[1283] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1284] In today's information society, it is difficult for users to determine the authenticity and bias of the information they come into contact with, making it easier for information biased toward a particular viewpoint or inaccurate information to spread. Accessing inaccurate information sources or dangerous websites also poses a significant risk. Furthermore, users are bombarded with information, making it difficult to efficiently obtain important information relevant to them. Therefore, the present invention aims to solve these problems and provide a system that helps users access reliable information.

[1285] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1286] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, and means for automatically blocking access to inaccurate information sources and risky websites, thereby enabling users to efficiently obtain reliable information and avoid access to dangerous websites.

[1287] "Artificial intelligence model for verifying the veracity and bias of information" is an artificial intelligence technology used to analyze and evaluate information provided by users to determine its accuracy and whether it is biased toward a particular viewpoint.

[1288] "Curating information based on user interests and preferences" is the process of selecting, collecting, and providing highly relevant information based on a user's past behavior and preferences.

[1289] "Automatically block access to websites from inaccurate sources or risky websites" is a function that checks the URL of the website the user is trying to access against a predefined list of dangers and prevents access based on the results.

[1290] "Regularly providing information from diverse perspectives" is the process of regularly providing users with information from different perspectives and sources, allowing them to be exposed to a wide range of information that is not biased towards any particular perspective.

[1291] "Providing a forum for users to discuss the reliability and diversity of information" refers to creating a discussion space where users can exchange opinions and evaluations regarding the reliability and diversity of information.

[1292] "Notifying users of the results of analysis using a generative AI model" refers to the process of providing users with the results of information analyzed by artificial intelligence and informing them of the veracity and bias of that information.

[1293] "Compare the URL of the website you are trying to access with a list of dangerous sites" is a function that compares the address of the website you are trying to visit with a pre-defined list of dangerous sites.

[1294] "Filtering and providing content relevant to a user's interests and preferences" refers to the process of selecting and providing appropriate information to a user based on the user's interests and preferences.

[1295] "Save user comments and share with other users" is a function that saves ratings and opinions left by users about information in a database and allows other users to view those comments.

[1296] This invention is a system that verifies the authenticity and bias of the information accessed by the user and provides only the most appropriate information to the user. It is designed especially to support users with low digital literacy, such as young people and the elderly. This system operates based on the following program processing steps:

[1297] The server receives information provided by the user (e.g., news articles or blog posts). To analyze this information, the server uses a generative AI model (e.g., GPT-4). For example, a prompt sentence such as "Please rate the truthfulness and bias of this news article" is generated and input into the model. The generative AI model analyzes the truthfulness score and bias level based on the input information and outputs the results to the server. The server notifies the user of this analysis result. For example, if a news article submitted by a user is evaluated as having a truthfulness score of 80% and a low bias level, the server will notify the user that "This news article has a truthfulness score of 80% and a low bias level."

[1298] When a user attempts to access a website, the device retrieves the URL and compares it with a predefined list of dangerous sites. This list includes websites with inaccurate information sources and risky websites. For example, if a user attempts to access "example.com," the device will compare the URL with the list of dangerous sites and automatically block access if there is a match. The user will see a warning message stating, "This site is dangerous. Access has been blocked."

[1299] The server obtains information based on the user's interests and preferences and curates content based on that information. For example, if a user is interested in "technology" or "health," the server retrieves articles on these topics from the database and provides them after filtering. The filtered content is provided to the user in the form of, "Check out the latest technology news below."

[1300] Furthermore, the server periodically provides information from diverse perspectives. This information is collected from different perspectives and sources, allowing users to access a wide range of information without being biased towards a particular viewpoint. For example, diverse information is provided in the form of "Below are the latest articles on politics, economics, and culture."

[1301] Users can also post comments about the provided information and share them with other users. The server stores these comments and provides a discussion space, promoting discussion about the reliability and diversity of the information. Comments such as "This information is highly reliable and provided from diverse perspectives" can be viewed by other users.

[1302] Through these functions, the system helps users safely and efficiently access information and obtain information from multiple perspectives.

[1303] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1304] Step 1:

[1305] The server receives user-provided information (e.g., news articles or blog posts). The input is the information submitted by the user, and the output is the conversion of the received information into a data format. For example, a user might submit the URL of a particular news article to the server. The server parses the URL to retrieve the article content.

[1306] Step 2:

[1307] The server uses a generative AI model (e.g., GPT-4) to generate a prompt sentence that evaluates the truthfulness and bias of the information. The input is the received information, and the output is a prompt sentence for the AI ​​model. As a specific example, the server generates the prompt sentence, "Please evaluate the truthfulness and bias of this news article."

[1308] Step 3:

[1309] The server sends a prompt to the generative AI model, requesting an analysis of the truthfulness score and bias level. The input is the generated prompt, and the output is the analysis result obtained from the AI ​​model. As a specific example, the AI ​​model returns an analysis result of a truthfulness score of 80% and a low bias level.

[1310] Step 4:

[1311] The server notifies the user of the analysis results obtained from the generative AI model. The input is the generated analysis result, and the output is a message to be notified to the user. For example, the notification may say, "This news article has a truthfulness score of 80% and a low bias level."

[1312] Step 5:

[1313] When a user tries to access a website, the device obtains the URL and compares it with a predefined list of dangerous sites. The input is the URL the user is trying to access, and the output is the result of matching it with the list of dangerous sites. For example, if a user tries to access "example.com", the device will compare the URL with the list of dangerous sites.

[1314] Step 6:

[1315] If the URL matches the dangerous site list, the terminal will automatically block the user's access. The input at this time is the URL matching result, and the output is an access block and a warning message. For example, a warning message saying "This site is dangerous. Access has been blocked" is displayed.

[1316] Step 7:

[1317] The server retrieves information based on the user's interests and preferences. The input is data about the user's interests and preferences, and the output is a filtered list of related content. For example, if the user is interested in "technology" or "health," the server retrieves articles related to these topics.

[1318] Step 8:

[1319] The server filters the information it obtains and provides it to the user. The input is all content before filtering, and the output is the filtered content. For example, it is provided in the form of "Check out the latest news on the following technologies."

[1320] Step 9:

[1321] The server periodically collects information from various perspectives and provides it to the user. The input is data collected from different sources, and the output is a list of information from various perspectives. For example, it is provided in the form of "Below are new articles on politics, economics, and culture."

[1322] Step 10:

[1323] Users post comments about the provided information, and the server stores and shares them. The input is the user's comment, and the output is comment data that can be viewed by other users. For example, a comment such as "This information is highly reliable and provided from a variety of perspectives" is stored.

[1324] Step 11:

[1325] The server provides a discussion space where users can discuss the reliability and diversity of information. The input is information and comments, and the output is a record of the discussion and shared knowledge. For example, the server encourages discussion by saying, "Let's discuss this news article further."

[1326] (Application example 1)

[1327] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1328] Currently, the market is overflowing with information, making it difficult for users to determine its authenticity and bias. Furthermore, particularly in physical stores, there is a lack of ways to quickly assess the authenticity and reliability of product-related information. As a result, users are at a greater risk of making decisions based on incorrect information. Furthermore, there is a lack of effective ways to avoid accessing inaccurate information sources or risky websites. There is a need to solve these problems and provide safe and reliable information.

[1329] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1330] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on user interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for periodically providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, means for verifying the authenticity and bias of information related to products and providing reliable information to users in physical stores, and means for blocking dangerous information in physical stores in real time, thereby enabling users to make decisions based on accurate and reliable information.

[1331] "Truthfulness of information" refers to whether the information is based on facts.

[1332] "Bias" refers to whether information is biased toward a particular perspective or position.

[1333] An "artificial intelligence model" refers to an algorithm that learns from large amounts of data and performs pattern recognition and predictions.

[1334] "User interests and preferences" refers to specific topics or content that interest a user.

[1335] "Curation" refers to the act of selecting, organizing, and providing valuable information from a large amount of information.

[1336] An "inaccurate source" refers to a source that provides unreliable information.

[1337] A "risky site" is a website that may have a harmful effect on users.

[1338] "Diverse perspectives" refers to information from different viewpoints and positions.

[1339] "Reliability" refers to the degree to which information or a system is accurate or safe.

[1340] "Product-related information" refers to information such as reviews, ratings, and descriptions about a particular product.

[1341] "Brick and mortar store" refers to a store that exists in a physical location.

[1342] "Real-time" refers to processing or response occurring immediately, without any time delay.

[1343] "Blocking" refers to restricting or stopping a specific action or access.

[1344] A "discussion" refers to the act of multiple people exchanging opinions on a particular topic or issue.

[1345] To implement this invention, a system is constructed that combines the following elements and their respective functions.

[1346] System configuration

[1347] 1. User Device:

[1348] Using mobile devices such as smartphones and tablets.

[1349] Install a QR code reader application on your device and read product information in physical stores.

[1350] 2. Server:

[1351] The servers are hosted on Amazon Web Services (AWS) EC2.

[1352] The database used is MySQL.

[1353] The artificial intelligence model is built using Google Cloud AI.

[1354] Program and Data Processing

[1355] 1. Receiving and analyzing information:

[1356] The user scans a QR code related to a product with their smartphone while in a physical store.

[1357] The terminal sends the read information to the server.

[1358] The server receives the information and uses an artificial intelligence model to analyze the information's authenticity and bias.

[1359] 2. Providing verification results:

[1360] The server sends the analysis results to the user's device and displays reliable information.

[1361] Users can check the authenticity and reliability of product information.

[1362] 3. Blocking dangerous information:

[1363] When a user attempts to click on a link contained within the information, the server parses the URL.

[1364] If the URL is on the dangerous site list, the server blocks access and displays a warning message to the user.

[1365] 4. Personalized communications:

[1366] The server filters relevant product reviews and promotional information based on the user's interests and preferences.

[1367] To provide filtered information to a user terminal, enabling a user to efficiently obtain information of interest.

[1368] 5. Diversity Feed Feature:

[1369] The server periodically collects reviews and information from different perspectives and provides them to users.

[1370] It will alleviate the filter bubble problem and provide balanced information.

[1371] 6. Discussion Space:

[1372] The server provides a discussion space where users can post comments about product reviews and promotional information.

[1373] It allows users to exchange opinions with other users, encouraging discussion about the reliability and diversity of information.

[1374] Specific examples

[1375] For example, when a user attempts to purchase a product in a physical store, they scan the QR code attached to the product with their smartphone. The information is sent to a server, where an AI model analyzes the authenticity and bias of the information. The server then displays the analysis results to the user, providing a reliable product review.

[1376] Also, when a user tries to click on a link, the server analyzes the URL and, if it is a dangerous site, blocks access and displays a warning message.

[1377] An example prompt might have the following format:

[1378] "Please verify this information to ensure its authenticity. Please rate the following review and return your result: 'This product was amazing!'"

[1379] This allows users to make decisions based on accurate and reliable information.

[1380] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1381] Step 1:

[1382] A user reads a QR code attached to a product in a physical store with their smartphone. The input is the QR code data, and the output is sending the read data to a server. Specifically, the QR code is scanned using a QR code reader application, and the obtained data is transmitted to the server.

[1383] Step 2:

[1384] The server receives the data sent by the user and analyzes the authenticity and bias of the information using an artificial intelligence model (e.g., Google Cloud AI). The input is the data obtained from the QR code, and the output is the authenticity score and bias level of the information. Specifically, the server inputs the received data into the AI ​​model and obtains the analysis results.

[1385] Step 3:

[1386] The server sends the analysis results to the user's device, providing the user with reliable information. The input is the truth score and bias level, and the output is the analysis results displayed on the user's device. Specifically, the server formats the analysis results and communicates them to the user's device.

[1387] Step 4:

[1388] When a user tries to click on a provided link, the server checks the URL against a predefined list of dangerous sites. The input is the URL the user tried to click, and the output is a decision on whether the URL is safe or dangerous. Specifically, the server checks the URL and obtains the result.

[1389] Step 5:

[1390] If the server detects a dangerous URL, it will automatically send a warning message and instructions to block access to the user's device. The input is the result of the dangerous URL judgment, and the output is the display of a warning message. Specifically, the server sends a warning message to the user's device and displays the warning to the user.

[1391] Step 6:

[1392] The server filters relevant product reviews and promotional information based on the user's interest and preference data. The input is the user's interest and preference data, and the output is the filtered product reviews and promotional information. Specifically, the server searches for relevant information from a database and filters it based on the user's interest and preference.

[1393] Step 7:

[1394] The server provides the filtered information to the user terminal, allowing the user to efficiently obtain information of interest. The input is filtered product reviews and promotional information, and the output is the information displayed on the user terminal. Specifically, the server sends the filtered information to the user terminal.

[1395] Step 8:

[1396] The server periodically collects reviews and information from different perspectives and provides them to users. The input is reviews and information from diverse perspectives, and the output is a diversity feed displayed on the user's device. Specifically, the server categorizes the collected information and periodically provides it to users.

[1397] Step 9:

[1398] The server provides a discussion space where users can post comments about product reviews and promotional information. The input is the user's comment, and the output is saved as a comment that can be viewed by other users. Specifically, the server receives the comment, saves it in a database, and displays it to other users.

[1399] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1400] This invention describes a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is particularly designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[1401] Verifying the authenticity and bias of information

[1402] Receiving and analyzing information

[1403] The server receives user-provided information (e.g., news articles or blog posts), which it then analyzes for veracity (accuracy) and bias (whether it favors a particular point of view) using a generative AI model.

[1404] Providing verification results

[1405] The server provides users with the truthfulness score and bias level obtained from the AI ​​model. At this time, the emotion engine recognizes the user's emotions and presents the results in a format appropriate to those emotions, making it easier for users to understand the reliability of the information.

[1406] Automatically blocks dangerous sites

[1407] Verifying the URL

[1408] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[1409] Access Blocks and Warnings

[1410] If the URL you are trying to access is on the dangerous site list, the device will automatically block the access and display a warning message to the user. The emotion engine recognizes the user's emotions and adjusts the tone and format of the warning message appropriately to help the user remain calm.

[1411] Personalized information provision

[1412] Obtaining user interests and preferences

[1413] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[1414] Filtering and Serving

[1415] The server filters all content retrieved from the database based on the user's interests and preferences. The filtered content is then provided to the user. The emotion engine provides information at the optimal timing and in the optimal format based on the user's emotional state. This allows users to efficiently receive information that is highly relevant to them.

[1416] Diversity Feed Feature

[1417] Providing information from diverse perspectives

[1418] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology). The emotion engine recognizes the user's emotions and considers how the information provided from various perspectives will be received by the user.

[1419] Reducing the filter bubble

[1420] The server-provided diversity feed allows users to access different perspectives and sources of information, rather than only receiving information based on specific interests or preferences. The emotion engine evaluates the user's emotional state and adjusts the format to provide diverse perspectives while mitigating the filter bubble problem. This makes it easier for users to accept diverse information.

[1421] Discussion space between users

[1422] Posting and saving comments

[1423] Users can post comments about the reliability and diversity of information. The server stores these comments and makes them available for other users to view. The emotion engine also recognizes the poster's emotions and adjusts the display format of the comments accordingly.

[1424] Facilitating discussion

[1425] The server provides a discussion space and encourages users to discuss the reliability and diversity of information. An emotion engine monitors each user's emotional state and guides the discussion to proceed in an appropriate manner. This allows users to share multiple perspectives and opinions about information, promoting the circulation of reliable information.

[1426] Explanation with concrete examples

[1427] For example, when User A checks a specific news article via InfoGuardian, the server receives the article's URL. The server uses a generative AI model to evaluate the article's veracity and bias, and presents the results in a format that matches User A's emotions, as analyzed by an emotion engine. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous, blocks access if necessary, and displays a warning message that matches User A's emotions.

[1428] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, User A can also access information on politics and culture through a regularly provided diversity feed. The emotion engine will also provide this information in an appropriate format, taking into account User A's emotional state. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information. The emotion engine is also involved in these discussions, promoting smooth and constructive communication.

[1429] Through these features, InfoGuardian helps users access information safely and efficiently, gaining information from multiple perspectives, and utilizes an emotion engine to enhance the user experience.

[1430] The processing flow will be explained below.

[1431] Verifying the authenticity and bias of information

[1432] Program processing

[1433] Step 1:

[1434] The server receives information provided by the user (such as a URL for a news article).

[1435] Specific behavior: The user enters the URL of a news article and sends it to the server.

[1436] Step 2:

[1437] The server retrieves the content of the news article from the received URL.

[1438] What it does: The server accesses the URL and scrapes the content of the web page to collect text data.

[1439] Step 3:

[1440] The server loads the generative AI model.

[1441] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[1442] Step 4:

[1443] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[1444] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[1445] Step 5:

[1446] The server activates an emotion engine that recognizes the user's emotions and analyzes the user's emotions.

[1447] How it works: The emotion engine assesses the user's emotional state based on their facial expressions, tone of voice, and input.

[1448] Step 6:

[1449] The server presents the analysis results based on the user's emotions.

[1450] Specific operation: The server allows the user to view the truthfulness score and bias level in a format appropriate to the user's emotional state (e.g., a message in a gentle tone).

[1451] Automatically blocks dangerous sites

[1452] Program processing

[1453] Step 1:

[1454] A user attempts to access a specific URL.

[1455] Specific operation: The user enters a URL in the browser and sends an access request.

[1456] Step 2:

[1457] The device checks the URL that is being accessed.

[1458] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[1459] Step 3:

[1460] The device determines whether the URL is included in the dangerous site list.

[1461] What it does: The device checks the URL and flags it if it's on the list.

[1462] Step 4:

[1463] The device will block access if the URL is dangerous.

[1464] Specific operation: If the URL is included in the list, the terminal will block the access request.

[1465] Step 5:

[1466] The terminal will display a warning message to the user.

[1467] What it does: The emotion engine recognizes the user's emotions and displays the warning "Access to dangerous site blocked" in a tone and format appropriate to that emotional state.

[1468] Personalized information provision

[1469] Program processing

[1470] Step 1:

[1471] The server collects data about the user's interests and preferences.

[1472] Specific operation: The server refers to the user's profile information and past browsing history.

[1473] Step 2:

[1474] The server retrieves all content from a database.

[1475] What happens: The server queries the database to retrieve news articles and blog posts.

[1476] Step 3:

[1477] The server filters the retrieved content based on the user's interests and preferences.

[1478] What it does: The server selects only content related to topics that the user has expressed interest in.

[1479] Step 4:

[1480] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[1481] Specific operation: The emotion engine determines the user's emotional state from their facial expression, tone of voice, and input.

[1482] Step 5:

[1483] The server provides the filtered content to the user.

[1484] What it does: The emotion engine displays filtered content on the user's screen at a time and in a format appropriate to the user's emotional state.

[1485] Diversity Feed Feature

[1486] Program processing

[1487] Step 1:

[1488] The server collects data about the user's interests and preferences.

[1489] Specific operation: The server refers to the user's profile information and past browsing history.

[1490] Step 2:

[1491] The server retrieves all content from a database.

[1492] What happens: The server queries the database to retrieve news articles and blog posts.

[1493] Step 3:

[1494] The server has a list of topics from various predefined perspectives.

[1495] Specific operation: The server provides a variety of topic lists, including politics, economics, culture, and technology.

[1496] Step 4:

[1497] The server filters information from multiple perspectives.

[1498] What it does: The server filters content based on various selected topics.

[1499] Step 5:

[1500] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[1501] What it does: The emotion engine delivers content from multiple perspectives in an appropriate format based on the user's emotional state.

[1502] Step 6:

[1503] The server provides users with information from a variety of perspectives.

[1504] What it does: The sentiment engine periodically provides diversity feeds and adjusts the display format to make it easier for users to access information from different perspectives.

[1505] Discussion space between users

[1506] Program processing

[1507] Step 1:

[1508] Users post comments in the discussion space.

[1509] Specific behavior: The user enters a comment in the text box and clicks the post button.

[1510] Step 2:

[1511] The server receives and stores the user's comments.

[1512] Specific operation: The server receives the comment data and stores it in the database.

[1513] Step 3:

[1514] The server activates an emotion engine that recognizes the user's emotions and evaluates the poster's emotional state.

[1515] Specific operation: The emotion engine analyzes emotions from the poster's expressions and content and saves them in an appropriate format.

[1516] Step 4:

[1517] The server retrieves the stored comments.

[1518] What happens: When another user tries to view the discussion space, the server retrieves all comments.

[1519] Step 5:

[1520] The server displays the comments to the user.

[1521] How it works: The emotion engine adjusts the display format of comments based on the emotional state of the user viewing them.

[1522] Step 6:

[1523] Users exchange opinions with other users.

[1524] How it works: Users read other users' comments, add their own opinions, and share them. The emotion engine performs real-time emotion recognition to facilitate this process.

[1525] The above are the specific processing steps for implementing this invention. As a result, InfoGuardian provides users with highly reliable information and realizes a safe and diverse information access environment. Furthermore, by combining it with an emotion engine, the user experience is further improved, and appropriate information can be provided according to individual needs.

[1526] Example 2

[1527] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1528] In modern society, the amount of information available on the Internet is enormous, and much of it contains false or biased information. Furthermore, users with low digital literacy have difficulty selecting reliable information, increasing the risk of misunderstandings and poor judgment based on misinformation. Furthermore, the risk of users accessing dangerous websites is also increasing. There is a need for a system that can comprehensively resolve these issues and provide users with accurate, unbiased information.

[1529] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1530] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for recognizing user emotions and providing analysis results in an appropriate format, and means for curating information based on the user's interests and preferences. This allows users to receive reliable information in an appropriate format, preventing misunderstandings and incorrect decisions based on false information. Furthermore, by using an emotion engine, optimal information is presented according to the user's emotional state, improving the user experience.

[1531] "Authenticity of information" refers to whether the information provided on the Internet is true and accurate.

[1532] "Bias" refers to information that is overly biased toward a particular perspective or opinion.

[1533] An "artificial intelligence model" refers to a machine learning algorithm that analyzes data, finds patterns in it, and makes predictions and decisions.

[1534] An "emotion engine" is a software component that recognizes emotions from a user's facial expressions and text input, and responds according to that emotional state.

[1535] "Curation" refers to selecting information based on a user's interests and preferences and providing useful information from that selection.

[1536] "Automatic access blocking measures" refers to the ability to automatically detect and block access to dangerous websites or inaccurate information sources.

[1537] "Warning Message" means a message that is displayed to warn a user when they attempt to access a dangerous website.

[1538] "Diverse perspectives" refers to multiple sources of information and opinions provided from different backgrounds and positions.

[1539] "Filter bubble" refers to the phenomenon in which users are only exposed to similar information based on their interests and preferences, making it difficult for them to access different perspectives and information.

[1540] "Discussion forum" refers to a space where users can exchange opinions and debate about the reliability and diversity of information.

[1541] "Comment display format" refers to how a comment posted by a user is visualized and displayed to other users.

[1542] "Means to facilitate smooth discussion" refers to functions that support constructive and smooth discussions between users.

[1543] This invention describes a specific embodiment for implementing a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is especially designed to support users with low digital literacy.

[1544] Hardware and Software Configuration

[1545] Hardware

[1546] Server: Use a high-performance cloud-based computing system, such as an EC2 instance from Amazon Web Services (AWS).

[1547] Device: The device used by the user, such as a PC, tablet, or smartphone.

[1548] software

[1549] Generative AI models: Use open-source machine learning frameworks, such as OpenAI's GPT-4.

[1550] Emotion Engine: Uses Microsoft Azure's Emotion Recognition API to recognize user emotions.

[1551] Database: Use a cloud-based database service, such as Amazon RDS, to store data about the truth, bias, and user interests and preferences.

[1552] Verifying the authenticity and bias of information

[1553] Receiving and analyzing information

[1554] The server receives the URL of the information (news article or blog post) provided by the user.

[1555] The server sends the URL to the generative AI model along with a prompt, such as "Please rate the veracity and bias of this information."

[1556] The generative AI model returns a truthfulness score and bias score for the information.

[1557] Providing verification results

[1558] The server obtains the truthfulness and bias scores returned by the generative AI model.

[1559] The server uses an emotion engine to analyze the user's current emotion.

[1560] The server will present the results to the user in an appropriate format depending on the user's emotional state, for example, if the user is surprised, it will provide a clear and detailed explanation.

[1561] Automatically blocks dangerous sites

[1562] Verifying the URL

[1563] The device receives the URL when the user attempts to access a website.

[1564] The device checks the received URL against a predefined list of dangerous sites (e.g., PhishTank, Safe Browsing API).

[1565] Access Blocks and Warnings

[1566] The device will automatically block access if the URL is included in the dangerous site list.

[1567] The device uses an emotion engine to recognize the user's emotional state and displays a warning message according to that emotion. For example, if the user appears anxious, a reassuring message will be displayed.

[1568] Personalized information provision

[1569] Obtaining user interests and preferences

[1570] The server collects data about the user's interests and preferences, such as past search history and preferences.

[1571] The server identifies specific areas of interest (e.g., "technology" or "health").

[1572] Filtering and Serving

[1573] The server filters all content retrieved from the database using a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[1574] The server uses an emotion engine to provide filtered content in the most appropriate format depending on the user's emotional state: for example, it provides concise information when the user is relaxed, and detailed information when the user is focused.

[1575] Diversity Feed Feature

[1576] Providing information from diverse perspectives

[1577] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[1578] The server uses an emotion engine to analyze the user's emotions and provides information from various perspectives in a format appropriate to the user's emotional state. For example, if the user is curious, detailed information is provided.

[1579] Reducing the filter bubble

[1580] The server provides content from a variety of sources to avoid users being trapped in filter bubbles based on specific interests or preferences.

[1581] The server uses an emotion engine to assess the user's emotional state and adjust the format of information delivery accordingly: for example, if the user is introverted, the server delivers information in a calm and receptive format.

[1582] Discussion space between users

[1583] Posting and saving comments

[1584] Users can post comments about the reliability and diversity of the information.

[1585] The server stores the posted comments and makes them available for other users to view.

[1586] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[1587] Facilitating discussion

[1588] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information.

[1589] The server uses an emotion engine to monitor each user's emotional state and guide the discussion to proceed in an appropriate manner. For example, if the discussion becomes heated, it will display a message urging the user to calm down.

[1590] Through these specific implementations, InfoGuardian helps users safely and efficiently access information and obtain information from various perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[1591] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1592] Program processing flow and specific explanation

[1593] Verifying the authenticity and bias of information

[1594] Step 1: Receiving information

[1595] The server receives a URL for information from the user, for example, a URL for a news article or blog post.

[1596] Input: User-provided URL

[1597] Output: Received URL data

[1598] Step 2: Sending prompts to the generative AI model

[1599] The server sends the received URL along with a prompt ("Please rate the truthfulness and bias of this information") to the generative AI model.

[1600] Input: Received URL

[1601] Data processing: Combining URL and prompt text

[1602] Output: A URL with a prompt sent to the generative AI model

[1603] Step 3: Evaluation by AI model

[1604] The generative AI model generates a truthfulness score and bias score for the provided URL, which it then compares with past data and evaluates using its own algorithm.

[1605] Input: URL with prompt

[1606] Data arithmetic: Calculating truthfulness and bias scores

[1607] Output: Truthfulness score and bias score

[1608] Step 4: User sentiment analysis

[1609] The server uses an emotion engine to analyze the user's emotions before providing the analysis results to the user. It also analyzes the user's webcam and text input.

[1610] Input: User's webcam video or text input

[1611] Data calculation: Analyzing the user's emotional state

[1612] Output: Emotion data (happiness, anger, surprise, etc.)

[1613] Step 5: Presenting the results

[1614] The server presents the truthfulness and bias scores to the user in a format that corresponds to the user's emotional state, for example, providing a clear and detailed explanation to a surprised user.

[1615] Input: Truthfulness score, bias score, sentiment data

[1616] Output: Analysis results presented to the user

[1617] Automatically blocks dangerous sites

[1618] Step 1: Check the URL

[1619] The device receives the URL when the user attempts to access a website.

[1620] Input: The URL the user is trying to access

[1621] Output: Received URL data

[1622] Step 2: Check against the dangerous site list

[1623] The device checks the received URL against a list of dangerous sites.

[1624] Input: Received URL

[1625] Data Computing: Comparison with Dangerous Site List

[1626] Output: Matching result (safe / unsafe)

[1627] Step 3: Blocking access and issuing warnings

[1628] If the verification result indicates a risk, the terminal blocks the access and displays a warning message.

[1629] The device uses an emotion engine to recognize the user's emotional state and displays appropriate warning messages. For example, if the user appears anxious, a reassuring message will be displayed.

[1630] Input: Danger assessment results, user emotion data

[1631] Output: Display of warning message

[1632] Personalized information provision

[1633] Step 1: Obtaining user interests and preferences

[1634] The server collects the user's past search history and preference information to identify the user's interests and preferences.

[1635] Input: User's past search history, preference information

[1636] Data Computing: Interest and Preference Analysis

[1637] Output: User interest and preference data

[1638] Step 2: Filtering content

[1639] The server filters all content retrieved from the database with a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[1640] Input: User interest and preference data

[1641] Data Calculation: Content Filtering

[1642] Output: Filtered content

[1643] Step 3: Provide information

[1644] The server uses an emotion engine to provide the filtered content in the most appropriate format according to the user's emotional state.

[1645] Input: filtered content, user sentiment data

[1646] Output: Information provided to the user

[1647] Diversity Feed Feature

[1648] Step 1: Gather information from diverse perspectives

[1649] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[1650] Input: None (regular execution)

[1651] Output: Collected information from various perspectives

[1652] Step 2: User sentiment analysis

[1653] The server uses an emotion engine to analyze the user's emotions before providing information.

[1654] Input: User emotion data (obtained from webcam or text input)

[1655] Data Computing: Sentiment Analysis

[1656] Output: Parsed emotion data

[1657] Step 3: Mitigating the filter bubble

[1658] The server tailors content from various sources to the user's emotional state, for example, providing it in a calm and receptive format if the user is introverted.

[1659] Input: Information from various perspectives, emotional data

[1660] Data calculations: Adjustments based on user interests, preferences and emotions

[1661] Output: Coordinated and diverse information

[1662] Discussion space between users

[1663] Step 1: Post and save your comment

[1664] Users post comments about the reliability and diversity of the information.

[1665] The server stores the posted comments and makes them available for other users to view.

[1666] Input: User comment

[1667] Output: Saved comment data

[1668] Step 2: Adjust the comment display

[1669] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[1670] Input: Comment data, poster's emotion data

[1671] Data calculation: Adjustment of comment display

[1672] Output: Adjusted comment display

[1673] Step 3: Facilitate discussion

[1674] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information. The emotion engine monitors the emotional state of each user and guides the discussion to proceed in an appropriate manner.

[1675] Input: User emotion data

[1676] Data Computation: A Guide to Analyzing and Discussing Emotional Data

[1677] Output: A well-organized discussion

[1678] This allows InfoGuardian to help users access information safely and efficiently, and gain information from multiple perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[1679] (Application example 2)

[1680] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1681] The modern internet is flooded with information of unknown veracity and bias, making it difficult for users with low digital literacy to access reliable information. There are also issues such as the risk of accessing dangerous websites and filter bubbles. Furthermore, there is a lack of systems that can efficiently collect information from diverse perspectives and provide it appropriately according to the user's emotional state.

[1682] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for regularly providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, and means for recognizing user emotions and providing information tailored to those emotions. This makes it possible to provide reliable information, prevent access to dangerous websites, mitigate filter bubbles, and provide appropriate information that takes user emotions into consideration.

[1683] "Truthfulness of information" refers to assessing whether certain information is true or not, and its accuracy.

[1684] "Bias" refers to an excessive reliance on a particular perspective or opinion.

[1685] An "artificial intelligence model" is one that uses algorithms or models to learn from large amounts of data and perform specific tasks.

[1686] "User interests and preferences" refers to the areas, topics, and preferences of individual users.

[1687] "Information curation" means organizing information collected from a variety of sources and presenting it in a form that is useful to users.

[1688] An "inaccurate source" is a website or other medium that provides information that is not reliable.

[1689] A "risky site" is a website that poses risks such as malware or phishing.

[1690] "Automatically blocking access" means that when a user attempts to access a dangerous site, that access is automatically blocked.

[1691] "Information from diverse perspectives" refers to information from a variety of viewpoints and positions.

[1692] A "filter bubble" is a state in which users receive information only based on their own interests and preferences, thereby excluding different perspectives.

[1693] "Recognizing the user's emotions" means analyzing the user's facial expressions, voice, etc. to understand their emotional state.

[1694] An "appropriate warning message" is one that takes into account the user's emotional state and displays a warning against inaccurate information or dangerous sites.

[1695] An "emotional state" is a set of emotions that a user is feeling.

[1696] An embodiment of the present invention includes the following elements: A server uses an artificial intelligence model to verify the veracity and bias of information. Specifically, the server receives information provided by a user, such as a news article or blog post, and analyzes the information using a generative AI model. This generative AI model is an algorithm that learns from large amounts of data and evaluates the accuracy and bias of the information. The veracity score and bias level obtained as the analysis result are provided to the user.

[1697] The server also curates information based on the user's interests and preferences. User interest and preference data is obtained from the user's behavioral history and profile information. Based on this data, relevant content is filtered and personalized information is provided.

[1698] The device checks the URL the user is trying to access and compares it with a predefined list of dangerous sites. If a dangerous website is detected, the device automatically blocks access and displays a warning message to the user. Here, the emotion engine recognizes the user's emotions and displays the warning message in an appropriate tone and format.

[1699] The server also periodically provides users with information from diverse perspectives, thereby mitigating the filter bubble problem. An emotion engine evaluates the user's emotional state and provides information from different perspectives in a format that is easy for users to accept. It also provides a forum for users to discuss the reliability and diversity of information. The server stores posted comments and opinions and shares them with other users.

[1700] The hardware used is a smartphone camera to recognize user emotions and an internet connection to acquire information. The software uses the requests library to acquire information from the internet and the face_recognition library to recognize emotions from the user's facial image. The generative AI model is used to analyze the truth and bias of the information.

[1701] For example, if a user attempts to access the URL "http: / / example.com / news," the URL is sent to the server and analyzed by the generative AI model. The truthfulness score and bias level are provided to the user in a format that is tailored to the user's emotions. If the user attempts to access the dangerous site "http: / / malware.com," the device automatically blocks access and displays an emotionally sensitive warning message. Furthermore, if the user is interested in health or technology, content related to these topics will be filtered and provided.

[1702] Examples of prompts to be input to the generative AI model include "Please rate the truthfulness and bias of this news article," "Please check if this URL is included in the dangerous site list," and "Please filter content relevant to the user's interests." This allows users to receive safe and reliable information.

[1703] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1704] Step 1:

[1705] A user provides information such as a news article or blog post. The user enters the URL of the information into the application, which then sends it to the server. The server retrieves the data based on the input URL and uses a generative AI model to analyze the information for truth and bias. The result of this analysis is a truthfulness score and bias level.

[1706] Step 2:

[1707] The server provides the user with a truthfulness score and bias level based on the results of the generative AI model analysis. At this time, the emotion engine detects the user's emotional state and understands what emotional state the user is in. The user's facial image is captured using the smartphone camera, and emotions are recognized using the face_recognition library. This recognition result becomes input data, and the results are displayed in a format appropriate for the user.

[1708] Step 3:

[1709] When a user attempts to browse a website, the device checks the URL the user is attempting to access. It checks the server to see if the URL is included in a list of dangerous sites. The results of this check are used as input, and if there is a risk, the device automatically blocks access and displays a warning message to the user to prevent access to inaccurate information sources or risky sites. This warning message is also displayed in a tone that matches the user's emotions using an emotion engine.

[1710] Step 4:

[1711] The server curates relevant information based on the user's interests and preferences, and filters the information to be provided based on the user's profile information and behavioral history. This filtering process is performed, and personalized information is output.

[1712] Step 5:

[1713] The server periodically collects information from diverse perspectives and provides it to users, thereby mitigating filter bubbles and creating an environment where users can be exposed to diverse information. The collected information from diverse perspectives serves as input data, and the emotion engine evaluates the user's emotional state and displays the information in a relevant format.

[1714] Step 6:

[1715] The server provides a forum for users to discuss the reliability and diversity of information. Users can post comments that can be seen by other users. The emotion engine monitors each user's emotional state and helps ensure smooth discussions.

[1716] Specific actions include providing information, checking URLs, analysis using a generative AI model, emotion recognition using an emotion engine, filtering, displaying warning messages, providing information from diverse perspectives, and maintaining a forum environment. Examples of prompts for the generative AI model include "Please rate the truthfulness and bias of this news article," "Check if this URL is included in a dangerous site list," and "Filter content relevant to the user's interests."

[1717] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1718] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1719] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1720] [Fourth embodiment]

[1721] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1722] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1723] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1724] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1725] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1726] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1727] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1728] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1729] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1730] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1731] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1732] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1733] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1734] This invention describes a system that verifies the authenticity and bias of information accessed by a user and provides only the most appropriate information to the user. This system is especially designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[1735] Verifying the authenticity and bias of information

[1736] Receiving and analyzing information

[1737] The server receives user-provided information (e.g., news articles or blog posts) and uses artificial intelligence models to analyze it for veracity (accuracy) and bias (whether it favors a particular point of view) to generate this information.

[1738] Providing verification results

[1739] The server provides users with a truthfulness score and bias level obtained from the artificial intelligence model, allowing them to determine the reliability of the information.

[1740] Automatically blocks dangerous sites

[1741] Verifying the URL

[1742] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[1743] Access Blocks and Warnings

[1744] If the URL you are trying to access is included in the dangerous site list, the device will automatically block the access and display a warning message to the user, allowing the user to avoid the risk of accessing dangerous sites.

[1745] Personalized information provision

[1746] Obtaining user interests and preferences

[1747] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[1748] Filtering and Serving

[1749] The server filters all content retrieved from the database based on the user's interests and preferences, and then provides the filtered content to the user, allowing the user to efficiently obtain only the information that is most relevant to them.

[1750] Diversity Feed Feature

[1751] Providing information from diverse perspectives

[1752] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology), allowing users to access a wide range of information without being biased towards a particular viewpoint.

[1753] Reducing the filter bubble

[1754] Server-provided diversity feeds allow users to access different perspectives and sources of information, rather than only being informed by their specific interests and preferences, thereby mitigating the filter bubble problem.

[1755] Discussion space between users

[1756] Posting and saving comments

[1757] Users can post comments about the reliability and versatility of the information, which the server stores and makes available for other users to view.

[1758] Facilitating discussion

[1759] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information, allowing users to share various perspectives and opinions about information and promoting the distribution of reliable information.

[1760] Explanation with concrete examples

[1761] For example, when User A checks a specific news article via InfoGuardian, the server receives the URL of that article. The server uses a generative AI model to evaluate the article's veracity and bias and provides the results to User A. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous and blocks access if necessary.

[1762] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, a regular diversity feed will also expose User A to information on politics and culture. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information.

[1763] Through these features, InfoGuardian helps users safely and efficiently access information and gain insights from multiple perspectives.

[1764] The processing flow will be explained below.

[1765] Verifying the authenticity and bias of information

[1766] Program processing

[1767] Step 1:

[1768] The server receives information provided by the user (eg, a URL for a news article).

[1769] Specific operation: When a user submits the URL of a news article, the server receives the URL as data.

[1770] Step 2:

[1771] The server retrieves the content of the news article from the received URL.

[1772] What happens: The server accesses the URL and scrapes the content of the web page to obtain text data.

[1773] Step 3:

[1774] The server loads the generative AI model.

[1775] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[1776] Step 4:

[1777] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[1778] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[1779] Step 5:

[1780] The server returns the analysis results to the user.

[1781] Specific Operation: The server sends the truthfulness score and bias level to the user for display.

[1782] Automatically blocks dangerous sites

[1783] Program processing

[1784] Step 1:

[1785] A user attempts to access a specific URL.

[1786] Specific operation: A user enters a URL in a browser and sends an access request.

[1787] Step 2:

[1788] The device checks the URL that is being accessed.

[1789] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[1790] Step 3:

[1791] The device determines whether the URL is included in the dangerous site list.

[1792] What it does: The device checks the URL and flags it if it's on the list.

[1793] Step 4:

[1794] The device will block access if the URL is dangerous.

[1795] Specific behavior: If the URL is included in the list, the device will block the access request and display a warning to the user.

[1796] Step 5:

[1797] The terminal displays a warning message to the user.

[1798] What it does: Displays a warning that says "Access to dangerous site blocked."

[1799] Personalized information provision

[1800] Program processing

[1801] Step 1:

[1802] The server obtains data about the user's interests and preferences.

[1803] Specific operation: The server refers to the user's profile information and past browsing history.

[1804] Step 2:

[1805] The server retrieves all content from a database.

[1806] What happens: The server queries the database to retrieve news articles and blog posts.

[1807] Step 3:

[1808] The server filters the retrieved content based on the user's interests and preferences.

[1809] Specific operation: The server selects only content related to topics of interest to the user.

[1810] Step 4:

[1811] The server provides the filtered content to the user.

[1812] Specific operation: Send the filtering results to be displayed on the user's screen.

[1813] Diversity Feed Feature

[1814] Program processing

[1815] Step 1:

[1816] The server obtains data about the user's interests and preferences.

[1817] Specific operation: The server refers to the user's profile information and past browsing history.

[1818] Step 2:

[1819] The server retrieves all content from a database.

[1820] What happens: The server queries the database to retrieve news articles and blog posts.

[1821] Step 3:

[1822] The server has a predefined list of topics from various perspectives.

[1823] Specific operation: The server provides topic lists such as politics, economics, culture, and technology.

[1824] Step 4:

[1825] The server filters information from multiple perspectives.

[1826] What it does: The server filters content based on various selected topics.

[1827] Step 5:

[1828] The server provides the user with information from various perspectives.

[1829] Specific behavior: Periodically display filtered diversity content on the user's screen.

[1830] Discussion space between users

[1831] Program processing

[1832] Step 1:

[1833] Users post comments in the discussion space.

[1834] Specific behavior: The user enters a comment in the text box and clicks the post button.

[1835] Step 2:

[1836] The server receives and stores the user's comments.

[1837] Specific operation: The server receives the comment data and stores it in the database.

[1838] Step 3:

[1839] The server retrieves the stored comments.

[1840] Specific behavior: When another user tries to view the discussion space, the server retrieves all comments.

[1841] Step 4:

[1842] The server displays the comments to the user.

[1843] Specific operation: The server displays the retrieved comments in the user's discussion space.

[1844] Step 5:

[1845] Users exchange opinions with other users.

[1846] What it does: Users read other users' comments and add and share their own opinions.

[1847] The above are the specific processing steps for carrying out the present invention, which allow InfoGuardian to provide highly reliable information to users and realize a safe and diverse information access environment.

[1848] Example 1

[1849] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1850] In today's information society, it is difficult for users to determine the authenticity and bias of the information they come into contact with, making it easier for information biased toward a particular viewpoint or inaccurate information to spread. Accessing inaccurate information sources or dangerous websites also poses a significant risk. Furthermore, users are bombarded with information, making it difficult to efficiently obtain important information relevant to them. Therefore, the present invention aims to solve these problems and provide a system that helps users access reliable information.

[1851] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1852] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on the user's interests and preferences, and means for automatically blocking access to inaccurate information sources and risky websites, thereby enabling users to efficiently obtain reliable information and avoid access to dangerous websites.

[1853] "Artificial intelligence model for verifying the veracity and bias of information" is an artificial intelligence technology used to analyze and evaluate information provided by users to determine its accuracy and whether it is biased toward a particular viewpoint.

[1854] "Curating information based on user interests and preferences" is the process of selecting, collecting, and providing highly relevant information based on a user's past behavior and preferences.

[1855] "Automatically block access to websites from inaccurate sources or risky websites" is a function that checks the URL of the website the user is trying to access against a predefined list of dangers and prevents access based on the results.

[1856] "Regularly providing information from diverse perspectives" is the process of regularly providing users with information from different perspectives and sources, allowing them to be exposed to a wide range of information that is not biased towards any particular perspective.

[1857] "Providing a forum for users to discuss the reliability and diversity of information" refers to creating a discussion space where users can exchange opinions and evaluations regarding the reliability and diversity of information.

[1858] "Notifying users of the results of analysis using a generative AI model" refers to the process of providing users with the results of information analyzed by artificial intelligence and informing them of the veracity and bias of that information.

[1859] "Compare the URL of the website you are trying to access with a list of dangerous sites" is a function that compares the address of the website you are trying to visit with a pre-defined list of dangerous sites.

[1860] "Filtering and providing content relevant to a user's interests and preferences" refers to the process of selecting and providing appropriate information to a user based on the user's interests and preferences.

[1861] "Save user comments and share with other users" is a function that saves ratings and opinions left by users about information in a database and allows other users to view those comments.

[1862] This invention is a system that verifies the authenticity and bias of the information accessed by the user and provides only the most appropriate information to the user. It is designed especially to support users with low digital literacy, such as young people and the elderly. This system operates based on the following program processing steps:

[1863] The server receives information provided by the user (e.g., news articles or blog posts). To analyze this information, the server uses a generative AI model (e.g., GPT-4). For example, a prompt sentence such as "Please rate the truthfulness and bias of this news article" is generated and input into the model. The generative AI model analyzes the truthfulness score and bias level based on the input information and outputs the results to the server. The server notifies the user of this analysis result. For example, if a news article submitted by a user is evaluated as having a truthfulness score of 80% and a low bias level, the server will notify the user that "This news article has a truthfulness score of 80% and a low bias level."

[1864] When a user attempts to access a website, the device retrieves the URL and compares it with a predefined list of dangerous sites. This list includes websites with inaccurate information sources and risky websites. For example, if a user attempts to access "example.com," the device will compare the URL with the list of dangerous sites and automatically block access if there is a match. The user will see a warning message stating, "This site is dangerous. Access has been blocked."

[1865] The server obtains information based on the user's interests and preferences and curates content based on that information. For example, if a user is interested in "technology" or "health," the server retrieves articles on these topics from the database and provides them after filtering. The filtered content is provided to the user in the form of, "Check out the latest technology news below."

[1866] Furthermore, the server periodically provides information from diverse perspectives. This information is collected from different perspectives and sources, allowing users to access a wide range of information without being biased towards a particular viewpoint. For example, diverse information is provided in the form of "Below are the latest articles on politics, economics, and culture."

[1867] Users can also post comments about the provided information and share them with other users. The server stores these comments and provides a discussion space, promoting discussion about the reliability and diversity of the information. Comments such as "This information is highly reliable and provided from diverse perspectives" can be viewed by other users.

[1868] Through these functions, the system helps users safely and efficiently access information and obtain information from multiple perspectives.

[1869] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1870] Step 1:

[1871] The server receives user-provided information (e.g., news articles or blog posts). The input is the information submitted by the user, and the output is the conversion of the received information into a data format. For example, a user might submit the URL of a particular news article to the server. The server parses the URL to retrieve the article content.

[1872] Step 2:

[1873] The server uses a generative AI model (e.g., GPT-4) to generate a prompt sentence that evaluates the truthfulness and bias of the information. The input is the received information, and the output is a prompt sentence for the AI ​​model. As a specific example, the server generates the prompt sentence, "Please evaluate the truthfulness and bias of this news article."

[1874] Step 3:

[1875] The server sends a prompt to the generative AI model, requesting an analysis of the truthfulness score and bias level. The input is the generated prompt, and the output is the analysis result obtained from the AI ​​model. As a specific example, the AI ​​model returns an analysis result of a truthfulness score of 80% and a low bias level.

[1876] Step 4:

[1877] The server notifies the user of the analysis results obtained from the generative AI model. The input is the generated analysis result, and the output is a message to be notified to the user. For example, the notification may say, "This news article has a truthfulness score of 80% and a low bias level."

[1878] Step 5:

[1879] When a user tries to access a website, the device obtains the URL and compares it with a predefined list of dangerous sites. The input is the URL the user is trying to access, and the output is the result of matching it with the list of dangerous sites. For example, if a user tries to access "example.com", the device will compare the URL with the list of dangerous sites.

[1880] Step 6:

[1881] If the URL matches the dangerous site list, the terminal will automatically block the user's access. The input at this time is the URL matching result, and the output is an access block and a warning message. For example, a warning message saying "This site is dangerous. Access has been blocked" is displayed.

[1882] Step 7:

[1883] The server retrieves information based on the user's interests and preferences. The input is data about the user's interests and preferences, and the output is a filtered list of related content. For example, if the user is interested in "technology" or "health," the server retrieves articles related to these topics.

[1884] Step 8:

[1885] The server filters the information it obtains and provides it to the user. The input is all content before filtering, and the output is the filtered content. For example, it is provided in the form of "Check out the latest news on the following technologies."

[1886] Step 9:

[1887] The server periodically collects information from various perspectives and provides it to the user. The input is data collected from different sources, and the output is a list of information from various perspectives. For example, it is provided in the form of "Below are new articles on politics, economics, and culture."

[1888] Step 10:

[1889] Users post comments about the provided information, and the server stores and shares them. The input is the user's comment, and the output is comment data that can be viewed by other users. For example, a comment such as "This information is highly reliable and provided from a variety of perspectives" is stored.

[1890] Step 11:

[1891] The server provides a discussion space where users can discuss the reliability and diversity of information. The input is information and comments, and the output is a record of the discussion and shared knowledge. For example, the server encourages discussion by saying, "Let's discuss this news article further."

[1892] (Application example 1)

[1893] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1894] Currently, the market is overflowing with information, making it difficult for users to determine its authenticity and bias. Furthermore, particularly in physical stores, there is a lack of ways to quickly assess the authenticity and reliability of product-related information. As a result, users are at a greater risk of making decisions based on incorrect information. Furthermore, there is a lack of effective ways to avoid accessing inaccurate information sources or risky websites. There is a need to solve these problems and provide safe and reliable information.

[1895] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1896] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for curating information based on user interests and preferences, means for automatically blocking access to inaccurate information sources or risky sites, means for periodically providing information from diverse perspectives, means for providing a forum for users to discuss the reliability and diversity of information, means for verifying the authenticity and bias of information related to products and providing reliable information to users in physical stores, and means for blocking dangerous information in physical stores in real time, thereby enabling users to make decisions based on accurate and reliable information.

[1897] "Truthfulness of information" refers to whether the information is based on facts.

[1898] "Bias" refers to whether information is biased toward a particular perspective or position.

[1899] An "artificial intelligence model" refers to an algorithm that learns from large amounts of data and performs pattern recognition and predictions.

[1900] "User interests and preferences" refers to specific topics or content that interest a user.

[1901] "Curation" refers to the act of selecting, organizing, and providing valuable information from a large amount of information.

[1902] An "inaccurate source" refers to a source that provides unreliable information.

[1903] A "risky site" is a website that may have a harmful effect on users.

[1904] "Diverse perspectives" refers to information from different viewpoints and positions.

[1905] "Reliability" refers to the degree to which information or a system is accurate or safe.

[1906] "Product-related information" refers to information such as reviews, ratings, and descriptions about a particular product.

[1907] "Brick and mortar store" refers to a store that exists in a physical location.

[1908] "Real-time" refers to processing or response occurring immediately, without any time delay.

[1909] "Blocking" refers to restricting or stopping a specific action or access.

[1910] A "discussion" refers to the act of multiple people exchanging opinions on a particular topic or issue.

[1911] To implement this invention, a system is constructed that combines the following elements and their respective functions.

[1912] System configuration

[1913] 1. User Device:

[1914] Using mobile devices such as smartphones and tablets.

[1915] Install a QR code reader application on your device and read product information in physical stores.

[1916] 2. Server:

[1917] The servers are hosted on Amazon Web Services (AWS) EC2.

[1918] The database used is MySQL.

[1919] The artificial intelligence model is built using Google Cloud AI.

[1920] Program and Data Processing

[1921] 1. Receiving and analyzing information:

[1922] The user scans a QR code related to a product with their smartphone while in a physical store.

[1923] The terminal sends the read information to the server.

[1924] The server receives the information and uses an artificial intelligence model to analyze the information's authenticity and bias.

[1925] 2. Providing verification results:

[1926] The server sends the analysis results to the user's device and displays reliable information.

[1927] Users can check the authenticity and reliability of product information.

[1928] 3. Blocking dangerous information:

[1929] When a user attempts to click on a link contained within the information, the server parses the URL.

[1930] If the URL is on the dangerous site list, the server blocks access and displays a warning message to the user.

[1931] 4. Personalized communications:

[1932] The server filters relevant product reviews and promotional information based on the user's interests and preferences.

[1933] To provide filtered information to a user terminal, enabling a user to efficiently obtain information of interest.

[1934] 5. Diversity Feed Feature:

[1935] The server periodically collects reviews and information from different perspectives and provides them to users.

[1936] It will alleviate the filter bubble problem and provide balanced information.

[1937] 6. Discussion Space:

[1938] The server provides a discussion space where users can post comments about product reviews and promotional information.

[1939] It allows users to exchange opinions with other users, encouraging discussion about the reliability and diversity of information.

[1940] Specific examples

[1941] For example, when a user attempts to purchase a product in a physical store, they scan the QR code attached to the product with their smartphone. The information is sent to a server, where an AI model analyzes the authenticity and bias of the information. The server then displays the analysis results to the user, providing a reliable product review.

[1942] Also, when a user tries to click on a link, the server analyzes the URL and, if it is a dangerous site, blocks access and displays a warning message.

[1943] An example prompt might have the following format:

[1944] "Please verify this information to ensure its authenticity. Please rate the following review and return your result: 'This product was amazing!'"

[1945] This allows users to make decisions based on accurate and reliable information.

[1946] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1947] Step 1:

[1948] A user reads a QR code attached to a product in a physical store with their smartphone. The input is the QR code data, and the output is sending the read data to a server. Specifically, the QR code is scanned using a QR code reader application, and the obtained data is transmitted to the server.

[1949] Step 2:

[1950] The server receives the data sent by the user and analyzes the authenticity and bias of the information using an artificial intelligence model (e.g., Google Cloud AI). The input is the data obtained from the QR code, and the output is the authenticity score and bias level of the information. Specifically, the server inputs the received data into the AI ​​model and obtains the analysis results.

[1951] Step 3:

[1952] The server sends the analysis results to the user's device, providing the user with reliable information. The input is the truth score and bias level, and the output is the analysis results displayed on the user's device. Specifically, the server formats the analysis results and communicates them to the user's device.

[1953] Step 4:

[1954] When a user tries to click on a provided link, the server checks the URL against a predefined list of dangerous sites. The input is the URL the user tried to click, and the output is a decision on whether the URL is safe or dangerous. Specifically, the server checks the URL and obtains the result.

[1955] Step 5:

[1956] If the server detects a dangerous URL, it will automatically send a warning message and instructions to block access to the user's device. The input is the result of the dangerous URL judgment, and the output is the display of a warning message. Specifically, the server sends a warning message to the user's device and displays the warning to the user.

[1957] Step 6:

[1958] The server filters relevant product reviews and promotional information based on the user's interest and preference data. The input is the user's interest and preference data, and the output is the filtered product reviews and promotional information. Specifically, the server searches for relevant information from a database and filters it based on the user's interest and preference.

[1959] Step 7:

[1960] The server provides the filtered information to the user terminal, allowing the user to efficiently obtain information of interest. The input is filtered product reviews and promotional information, and the output is the information displayed on the user terminal. Specifically, the server sends the filtered information to the user terminal.

[1961] Step 8:

[1962] The server periodically collects reviews and information from different perspectives and provides them to users. The input is reviews and information from diverse perspectives, and the output is a diversity feed displayed on the user's device. Specifically, the server categorizes the collected information and periodically provides it to users.

[1963] Step 9:

[1964] The server provides a discussion space where users can post comments about product reviews and promotional information. The input is the user's comment, and the output is saved as a comment that can be viewed by other users. Specifically, the server receives the comment, saves it in a database, and displays it to other users.

[1965] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1966] This invention describes a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is particularly designed to support users with low digital literacy, such as young people and the elderly. As an example of this system, a detailed description based on each processing step is provided below.

[1967] Verifying the authenticity and bias of information

[1968] Receiving and analyzing information

[1969] The server receives user-provided information (e.g., news articles or blog posts), which it then analyzes for veracity (accuracy) and bias (whether it favors a particular point of view) using a generative AI model.

[1970] Providing verification results

[1971] The server provides users with the truthfulness score and bias level obtained from the AI ​​model. At this time, the emotion engine recognizes the user's emotions and presents the results in a format appropriate to those emotions, making it easier for users to understand the reliability of the information.

[1972] Automatically blocks dangerous sites

[1973] Verifying the URL

[1974] When a user attempts to access a website, the device checks the URL by checking it against a predefined list of dangerous sites.

[1975] Access Blocks and Warnings

[1976] If the URL you are trying to access is on the dangerous site list, the device will automatically block the access and display a warning message to the user. The emotion engine recognizes the user's emotions and adjusts the tone and format of the warning message appropriately to help the user remain calm.

[1977] Personalized information provision

[1978] Obtaining user interests and preferences

[1979] The server collects data about the user's interests and preferences, for example, if the user is interested in "technology" or "health," it can filter content accordingly.

[1980] Filtering and Serving

[1981] The server filters all content retrieved from the database based on the user's interests and preferences. The filtered content is then provided to the user. The emotion engine provides information at the optimal timing and in the optimal format based on the user's emotional state. This allows users to efficiently receive information that is highly relevant to them.

[1982] Diversity Feed Feature

[1983] Providing information from diverse perspectives

[1984] The server periodically provides users with information from various perspectives (e.g., politics, economy, culture, technology). The emotion engine recognizes the user's emotions and considers how the information provided from various perspectives will be received by the user.

[1985] Reducing the filter bubble

[1986] The server-provided diversity feed allows users to access different perspectives and sources of information, rather than only receiving information based on specific interests or preferences. The emotion engine evaluates the user's emotional state and adjusts the format to provide diverse perspectives while mitigating the filter bubble problem. This makes it easier for users to accept diverse information.

[1987] Discussion space between users

[1988] Posting and saving comments

[1989] Users can post comments about the reliability and diversity of information. The server stores these comments and makes them available for other users to view. The emotion engine also recognizes the poster's emotions and adjusts the display format of the comments accordingly.

[1990] Facilitating discussion

[1991] The server provides a discussion space and encourages users to discuss the reliability and diversity of information. An emotion engine monitors each user's emotional state and guides the discussion to proceed in an appropriate manner. This allows users to share multiple perspectives and opinions about information, promoting the circulation of reliable information.

[1992] Explanation with concrete examples

[1993] For example, when User A checks a specific news article via InfoGuardian, the server receives the article's URL. The server uses a generative AI model to evaluate the article's veracity and bias, and presents the results in a format that matches User A's emotions, as analyzed by an emotion engine. At the same time, when User A attempts to access another site, the device checks whether the site is dangerous, blocks access if necessary, and displays a warning message that matches User A's emotions.

[1994] Furthermore, if User A is interested in technology or health, the server will filter and provide content related to these topics. Meanwhile, User A can also access information on politics and culture through a regularly provided diversity feed. The emotion engine will also provide this information in an appropriate format, taking into account User A's emotional state. User A can also use the discussion space to exchange opinions with other users and debate the reliability of the information. The emotion engine is also involved in these discussions, promoting smooth and constructive communication.

[1995] Through these features, InfoGuardian helps users access information safely and efficiently, gaining information from multiple perspectives, and utilizes an emotion engine to enhance the user experience.

[1996] The processing flow will be explained below.

[1997] Verifying the authenticity and bias of information

[1998] Program processing

[1999] Step 1:

[2000] The server receives information provided by the user (such as a URL for a news article).

[2001] Specific behavior: The user enters the URL of a news article and sends it to the server.

[2002] Step 2:

[2003] The server retrieves the content of the news article from the received URL.

[2004] What it does: The server accesses the URL and scrapes the content of the web page to collect text data.

[2005] Step 3:

[2006] The server loads the generative AI model.

[2007] Specific operation: The server loads a pre-trained artificial intelligence model into memory.

[2008] Step 4:

[2009] The server inputs the text data into a generative AI model and analyzes the information for veracity and bias.

[2010] How it works: The generative AI model analyzes text data and calculates a truthfulness score and bias level.

[2011] Step 5:

[2012] The server activates an emotion engine that recognizes the user's emotions and analyzes the user's emotions.

[2013] How it works: The emotion engine assesses the user's emotional state based on their facial expressions, tone of voice, and input.

[2014] Step 6:

[2015] The server presents the analysis results based on the user's emotions.

[2016] Specific operation: The server allows the user to view the truthfulness score and bias level in a format appropriate to the user's emotional state (e.g., a message in a gentle tone).

[2017] Automatically blocks dangerous sites

[2018] Program processing

[2019] Step 1:

[2020] A user attempts to access a specific URL.

[2021] Specific operation: The user enters a URL in the browser and sends an access request.

[2022] Step 2:

[2023] The device checks the URL that is being accessed.

[2024] Specific operation: The device retrieves the URL and checks it against a predefined list of dangerous sites.

[2025] Step 3:

[2026] The device determines whether the URL is included in the dangerous site list.

[2027] What it does: The device checks the URL and flags it if it's on the list.

[2028] Step 4:

[2029] The device will block access if the URL is dangerous.

[2030] Specific operation: If the URL is included in the list, the terminal will block the access request.

[2031] Step 5:

[2032] The terminal will display a warning message to the user.

[2033] What it does: The emotion engine recognizes the user's emotions and displays the warning "Access to dangerous site blocked" in a tone and format appropriate to that emotional state.

[2034] Personalized information provision

[2035] Program processing

[2036] Step 1:

[2037] The server collects data about the user's interests and preferences.

[2038] Specific operation: The server refers to the user's profile information and past browsing history.

[2039] Step 2:

[2040] The server retrieves all content from a database.

[2041] What happens: The server queries the database to retrieve news articles and blog posts.

[2042] Step 3:

[2043] The server filters the retrieved content based on the user's interests and preferences.

[2044] What it does: The server selects only content related to topics that the user has expressed interest in.

[2045] Step 4:

[2046] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[2047] Specific operation: The emotion engine determines the user's emotional state from their facial expression, tone of voice, and input.

[2048] Step 5:

[2049] The server provides the filtered content to the user.

[2050] What it does: The emotion engine displays filtered content on the user's screen at a time and in a format appropriate to the user's emotional state.

[2051] Diversity Feed Feature

[2052] Program processing

[2053] Step 1:

[2054] The server collects data about the user's interests and preferences.

[2055] Specific operation: The server refers to the user's profile information and past browsing history.

[2056] Step 2:

[2057] The server retrieves all content from a database.

[2058] What happens: The server queries the database to retrieve news articles and blog posts.

[2059] Step 3:

[2060] The server has a list of topics from various predefined perspectives.

[2061] Specific operation: The server provides a variety of topic lists, including politics, economics, culture, and technology.

[2062] Step 4:

[2063] The server filters information from multiple perspectives.

[2064] What it does: The server filters content based on various selected topics.

[2065] Step 5:

[2066] The server activates an emotion engine that recognizes the user's emotions and evaluates the user's emotional state.

[2067] What it does: The emotion engine delivers content from multiple perspectives in an appropriate format based on the user's emotional state.

[2068] Step 6:

[2069] The server provides users with information from a variety of perspectives.

[2070] What it does: The sentiment engine periodically provides diversity feeds and adjusts the display format to make it easier for users to access information from different perspectives.

[2071] Discussion space between users

[2072] Program processing

[2073] Step 1:

[2074] Users post comments in the discussion space.

[2075] Specific behavior: The user enters a comment in the text box and clicks the post button.

[2076] Step 2:

[2077] The server receives and stores the user's comments.

[2078] Specific operation: The server receives the comment data and stores it in the database.

[2079] Step 3:

[2080] The server activates an emotion engine that recognizes the user's emotions and evaluates the poster's emotional state.

[2081] Specific operation: The emotion engine analyzes emotions from the poster's expressions and content and saves them in an appropriate format.

[2082] Step 4:

[2083] The server retrieves the stored comments.

[2084] What happens: When another user tries to view the discussion space, the server retrieves all comments.

[2085] Step 5:

[2086] The server displays the comments to the user.

[2087] How it works: The emotion engine adjusts the display format of comments based on the emotional state of the user viewing them.

[2088] Step 6:

[2089] Users exchange opinions with other users.

[2090] How it works: Users read other users' comments, add their own opinions, and share them. The emotion engine performs real-time emotion recognition to facilitate this process.

[2091] The above are the specific processing steps for implementing this invention. As a result, InfoGuardian provides users with highly reliable information and realizes a safe and diverse information access environment. Furthermore, by combining it with an emotion engine, the user experience is further improved, and appropriate information can be provided according to individual needs.

[2092] Example 2

[2093] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[2094] In modern society, the amount of information available on the Internet is enormous, and much of it contains false or biased information. Furthermore, users with low digital literacy have difficulty selecting reliable information, increasing the risk of misunderstandings and poor judgment based on misinformation. Furthermore, the risk of users accessing dangerous websites is also increasing. There is a need for a system that can comprehensively resolve these issues and provide users with accurate, unbiased information.

[2095] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[2096] In this invention, the server includes means for using an artificial intelligence model to verify the authenticity and bias of information, means for recognizing user emotions and providing analysis results in an appropriate format, and means for curating information based on the user's interests and preferences. This allows users to receive reliable information in an appropriate format, preventing misunderstandings and incorrect decisions based on false information. Furthermore, by using an emotion engine, optimal information is presented according to the user's emotional state, improving the user experience.

[2097] "Authenticity of information" refers to whether the information provided on the Internet is true and accurate.

[2098] "Bias" refers to information that is overly biased toward a particular perspective or opinion.

[2099] An "artificial intelligence model" refers to a machine learning algorithm that analyzes data, finds patterns in it, and makes predictions and decisions.

[2100] An "emotion engine" is a software component that recognizes emotions from a user's facial expressions and text input, and responds according to that emotional state.

[2101] "Curation" refers to selecting information based on a user's interests and preferences and providing useful information from that selection.

[2102] "Automatic access blocking measures" refers to the ability to automatically detect and block access to dangerous websites or inaccurate information sources.

[2103] "Warning Message" means a message that is displayed to warn a user when they attempt to access a dangerous website.

[2104] "Diverse perspectives" refers to multiple sources of information and opinions provided from different backgrounds and positions.

[2105] "Filter bubble" refers to the phenomenon in which users are only exposed to similar information based on their interests and preferences, making it difficult for them to access different perspectives and information.

[2106] "Discussion forum" refers to a space where users can exchange opinions and debate about the reliability and diversity of information.

[2107] "Comment display format" refers to how a comment posted by a user is visualized and displayed to other users.

[2108] "Means to facilitate smooth discussion" refers to functions that support constructive and smooth discussions between users.

[2109] This invention describes a specific embodiment for implementing a system that verifies the authenticity and bias of information accessed by a user and combines it with an emotion engine that recognizes the user's emotions to provide only the most appropriate information to the user. This system is especially designed to support users with low digital literacy.

[2110] Hardware and Software Configuration

[2111] Hardware

[2112] Server: Use a high-performance cloud-based computing system, such as an EC2 instance from Amazon Web Services (AWS).

[2113] Device: The device used by the user, such as a PC, tablet, or smartphone.

[2114] software

[2115] Generative AI models: Use open-source machine learning frameworks, such as OpenAI's GPT-4.

[2116] Emotion Engine: Uses Microsoft Azure's Emotion Recognition API to recognize user emotions.

[2117] Database: Use a cloud-based database service, such as Amazon RDS, to store data about the truth, bias, and user interests and preferences.

[2118] Verifying the authenticity and bias of information

[2119] Receiving and analyzing information

[2120] The server receives the URL of the information (news article or blog post) provided by the user.

[2121] The server sends the URL to the generative AI model along with a prompt, such as "Please rate the veracity and bias of this information."

[2122] The generative AI model returns a truthfulness score and bias score for the information.

[2123] Providing verification results

[2124] The server obtains the truthfulness and bias scores returned by the generative AI model.

[2125] The server uses an emotion engine to analyze the user's current emotion.

[2126] The server will present the results to the user in an appropriate format depending on the user's emotional state, for example, if the user is surprised, it will provide a clear and detailed explanation.

[2127] Automatically blocks dangerous sites

[2128] Verifying the URL

[2129] The device receives the URL when the user attempts to access a website.

[2130] The device checks the received URL against a predefined list of dangerous sites (e.g., PhishTank, Safe Browsing API).

[2131] Access Blocks and Warnings

[2132] The device will automatically block access if the URL is included in the dangerous site list.

[2133] The device uses an emotion engine to recognize the user's emotional state and displays a warning message according to that emotion. For example, if the user appears anxious, a reassuring message will be displayed.

[2134] Personalized information provision

[2135] Obtaining user interests and preferences

[2136] The server collects data about the user's interests and preferences, such as past search history and preferences.

[2137] The server identifies specific areas of interest (e.g., "technology" or "health").

[2138] Filtering and Serving

[2139] The server filters all content retrieved from the database using a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[2140] The server uses an emotion engine to provide filtered content in the most appropriate format depending on the user's emotional state: for example, it provides concise information when the user is relaxed, and detailed information when the user is focused.

[2141] Diversity Feed Feature

[2142] Providing information from diverse perspectives

[2143] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[2144] The server uses an emotion engine to analyze the user's emotions and provides information from various perspectives in a format appropriate to the user's emotional state. For example, if the user is curious, detailed information is provided.

[2145] Reducing the filter bubble

[2146] The server provides content from a variety of sources to avoid users being trapped in filter bubbles based on specific interests or preferences.

[2147] The server uses an emotion engine to assess the user's emotional state and adjust the format of information delivery accordingly: for example, if the user is introverted, the server delivers information in a calm and receptive format.

[2148] Discussion space between users

[2149] Posting and saving comments

[2150] Users can post comments about the reliability and diversity of the information.

[2151] The server stores the posted comments and makes them available for other users to view.

[2152] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[2153] Facilitating discussion

[2154] The server provides a discussion space and encourages discussion among users about the reliability and diversity of information.

[2155] The server uses an emotion engine to monitor each user's emotional state and guide the discussion to proceed in an appropriate manner. For example, if the discussion becomes heated, it will display a message urging the user to calm down.

[2156] Through these specific implementations, InfoGuardian helps users safely and efficiently access information and obtain information from various perspectives. By utilizing the emotion engine, it is possible to improve the user experience and provide reliable information.

[2157] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2158] Program processing flow and specific explanation

[2159] Verifying the authenticity and bias of information

[2160] Step 1: Receiving information

[2161] The server receives a URL for information from the user, for example, a URL for a news article or blog post.

[2162] Input: User-provided URL

[2163] Output: Received URL data

[2164] Step 2: Sending prompts to the generative AI model

[2165] The server sends the received URL along with a prompt ("Please rate the truthfulness and bias of this information") to the generative AI model.

[2166] Input: Received URL

[2167] Data processing: Combining URL and prompt text

[2168] Output: A URL with a prompt sent to the generative AI model

[2169] Step 3: Evaluation by AI model

[2170] The generative AI model generates a truthfulness score and bias score for the provided URL, which it then compares with past data and evaluates using its own algorithm.

[2171] Input: URL with prompt

[2172] Data arithmetic: Calculating truthfulness and bias scores

[2173] Output: Truthfulness score and bias score

[2174] Step 4: User sentiment analysis

[2175] The server uses an emotion engine to analyze the user's emotions before providing the analysis results to the user. It also analyzes the user's webcam and text input.

[2176] Input: User's webcam video or text input

[2177] Data calculation: Analyzing the user's emotional state

[2178] Output: Emotion data (happiness, anger, surprise, etc.)

[2179] Step 5: Presenting the results

[2180] The server presents the truthfulness and bias scores to the user in a format that corresponds to the user's emotional state, for example, providing a clear and detailed explanation to a surprised user.

[2181] Input: Truthfulness score, bias score, sentiment data

[2182] Output: Analysis results presented to the user

[2183] Automatically blocks dangerous sites

[2184] Step 1: Check the URL

[2185] The device receives the URL when the user attempts to access a website.

[2186] Input: The URL the user is trying to access

[2187] Output: Received URL data

[2188] Step 2: Check against the dangerous site list

[2189] The device checks the received URL against a list of dangerous sites.

[2190] Input: Received URL

[2191] Data Computing: Comparison with Dangerous Site List

[2192] Output: Matching result (safe / unsafe)

[2193] Step 3: Blocking access and issuing warnings

[2194] If the verification result indicates a risk, the terminal blocks the access and displays a warning message.

[2195] The device uses an emotion engine to recognize the user's emotional state and displays appropriate warning messages. For example, if the user appears anxious, a reassuring message will be displayed.

[2196] Input: Danger assessment results, user emotion data

[2197] Output: Display of warning message

[2198] Personalized information provision

[2199] Step 1: Obtaining user interests and preferences

[2200] The server collects the user's past search history and preference information to identify the user's interests and preferences.

[2201] Input: User's past search history, preference information

[2202] Data Computing: Interest and Preference Analysis

[2203] Output: User interest and preference data

[2204] Step 2: Filtering content

[2205] The server filters all content retrieved from the database with a prompt, such as "Please provide up-to-date, reliable information in your technical field."

[2206] Input: User interest and preference data

[2207] Data Calculation: Content Filtering

[2208] Output: Filtered content

[2209] Step 3: Provide information

[2210] The server uses an emotion engine to provide the filtered content in the most appropriate format according to the user's emotional state.

[2211] Input: filtered content, user sentiment data

[2212] Output: Information provided to the user

[2213] Diversity Feed Feature

[2214] Step 1: Gather information from diverse perspectives

[2215] The server periodically collects information from different perspectives (e.g., politics, economy, culture, technology).

[2216] Input: None (regular execution)

[2217] Output: Collected information from various perspectives

[2218] Step 2: User sentiment analysis

[2219] The server uses an emotion engine to analyze the user's emotions before providing information.

[2220] Input: User emotion data (obtained from webcam or text input)

[2221] Data Computing: Sentiment Analysis

[2222] Output: Parsed emotion data

[2223] Step 3: Mitigating the filter bubble

[2224] The server tailors content from various sources to the user's emotional state, for example, providing it in a calm and receptive format if the user is introverted.

[2225] Input: Information from various perspectives, emotional data

[2226] Data calculations: Adjustments based on user interests, preferences and emotions

[2227] Output: Coordinated and diverse information

[2228] Discussion space between users

[2229] Step 1: Post and save your comment

[2230] Users post comments about the reliability and diversity of the information.

[2231] The server stores the posted comments and makes them available for other users to view.

[2232] Input: User comment

[2233] Output: Saved comment data

[2234] Step 2: Adjust the comment display

[2235] The server uses an emotion engine to recognize the poster's emotions and displays comments in a format that reflects their emotions. For example, it adjusts the opinions of angry commenters to appear calmer.

[2236] Input: Comment data, poster's emotion data

[2237] Data calculation: Adjustment of comment display

[2238] Output: Adjusted comment display

[2239] Step 3: Facilitate discussion ...

Claims

1. A means of using artificial intelligence models to verify the authenticity and bias of information; A means of curating information based on users' interests and preferences; Automatically blocking access to inaccurate sources and risky sites; A means of providing information from diverse perspectives on a regular basis; A means to provide a forum for users to discuss the reliability and diversity of information, and A system including:

2. 10. The system of claim 1, further comprising means for using a generative AI model to verify the authenticity and bias of information in real time.

3. 10. The system of claim 1, further comprising means for protecting a user from information overload by providing personalized information based on the user's interests and preferences.

Images