system

Abstract

We provide the system. [Solution] A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal, A means for a user terminal to display the transmitted information and to provide an operation screen for the user to select whether the information is generated by artificial intelligence technology or by human generation, A means of obtaining the user's selection results from the user's terminal, aggregating the obtained selection results, and recording them in a database, A system that includes this.

Description

Technical Field

[0001] The technology of this disclosure relates to a system.

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance that responds to the user utterance.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] With the evolution of generative artificial intelligence technology, it has become difficult to distinguish between information generated by humans and information generated by artificial intelligence. However, means for collecting high-quality datasets for effectively identifying these information at low cost and efficiently are limited. Furthermore, there is a current situation where the opportunity for general users to utilize their spare time to obtain economic benefits is insufficient. Therefore, there is a demand for an efficient system that generates highly accurate identification data and provides users with opportunities for rewards.

Means for Solving the Problems

[0005] This invention provides a system that can collect high-quality datasets by transmitting artificial intelligence-generated information and human-generated information from a content provider to a user terminal and allowing the user to identify them. Specifically, through an operation screen provided by the user terminal, the user selects whether the information is artificial intelligence-generated or human-generated. The collected selection results are recorded in a database, and a means is established to provide economic benefits to the user by determining the accuracy rate and offering rewards. Furthermore, by anonymizing the selection results and providing them to a third-party organization, the system promotes research and development of artificial intelligence generation technology. This makes it possible to dramatically improve user engagement and the efficiency of data collection.

[0006] A "content provision device" is a device that has the function of selecting information generated by artificial intelligence technology and information generated by humans, and transmitting it to the user's terminal.

[0007] "Artificial intelligence technology" refers to technologies that automatically generate or analyze information using algorithms such as machine learning and deep learning.

[0008] A "user terminal" is an electronic device that displays received information and allows users to input or select information related to that information.

[0009] "Information" refers to data expressed in text, images, audio, and other forms, and includes both artificial intelligence-generated information and human-generated information.

[0010] An "operation screen" is a part of the user interface displayed on a user's terminal, a screen that allows the user to perform operations such as selection, input, and confirmation.

[0011] "Selection results" refer to a record of decisions made based on information selected by the user through the operation screen, and include data that determines whether the result was generated by artificial intelligence or by a human.

[0012] A "database" is a storage system designed to efficiently store, manage, and retrieve collected selection results and related information.

[0013] "Anonymization" is the process of removing or transforming information related to a specific individual from data in order to eliminate the possibility of that individual being identified.

[0014] A "third-party organization" is an organization or group that is independent of specific users or providers and can use information for the purpose of technological research or data analysis.

[0015] "Rewards" refer to economic benefits or points provided as compensation when a user successfully identifies information through the system. [Brief explanation of the drawing]

[0016] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] Shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0017] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be described.

[0019] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0020] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0021] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0022] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0024] [First Embodiment]

[0025] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0026] As shown in Figure 1, the 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.

[0027] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0029] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0030] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0032] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0036] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0037] This invention is a system for distinguishing between information generated by artificial intelligence technology and information generated by humans, and is implemented in a form in which a content provider, a user terminal, and a server work in cooperation with each other.

[0038] Overall system configuration

[0039] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. The user's terminal displays the received information and provides an operation screen for the user to identify the information. The user determines whether the information is AI-generated or human-generated and selects the result.

[0040] System operation

[0041] The server receives the user's selection data, aggregates it, and records it in a database. This aggregated result serves as an indicator of how accurately each piece of information was identified. Furthermore, the server calculates a reward based on the accuracy rate and provides it to the user. The reward is added to the user's account as points or credits.

[0042] Specific example

[0043] For example, the server selects both news article texts generated by AI and those written by human journalists and sends them to the user's terminal. The terminal displays the article, and the user selects which author created it. Once the user enters their selection into the terminal, the data is immediately sent to the server. The server aggregates this data and evaluates the accuracy of the identification. If the user's selection is correct, the user is given additional rewards based on their accuracy.

[0044] The purpose of this system is to efficiently collect identification data of artificial intelligence technology and human-generated information, thereby providing economic benefits to users while supplying data to third-party organizations and contributing to the development of better generative models.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server randomly retrieves information from the database, including both AI-generated and human-generated information, and then selects content to send to the user. The information to be sent is determined based on predefined criteria.

[0048] Step 2:

[0049] The server transmits the selected information to the user's terminal and provides an operational interface for displaying and identifying the information.

[0050] Step 3:

[0051] The terminal displays the received content to the user and simultaneously provides an operation screen where the user can select whether the information was generated by an AI or by a human.

[0052] Step 4:

[0053] The user reviews the displayed information, determines its source, and makes a selection. This selection is made through the user interface.

[0054] Step 5:

[0055] The user's selection results are sent to the server by the device. This transmission includes the selected options and related metadata.

[0056] Step 6:

[0057] The server records the received selection results in a database and further calculates the accuracy rate to evaluate the user's identification accuracy.

[0058] Step 7:

[0059] The server calculates rewards based on the user's accuracy rate, according to specified criteria. The calculated rewards are added to the user's account.

[0060] Step 8:

[0061] The server anonymizes the aggregated data as needed and organizes it as data. The organized data is later provided to a third-party organization and used for research and development of generative AI technology.

[0062] (Example 1)

[0063] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0064] In recent years, advancements in artificial intelligence technology have created a problem where it is difficult to distinguish between information generated by AI and information generated by humans. Furthermore, there is a need to improve the accuracy and efficiency of providing rewards to users through this identification process. Additionally, there is a need for a secure method of supplying identification results to third-party organizations.

[0065] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0066] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal; means for acquiring the user's selection results, aggregating the acquired selection results, and recording them on a recording medium; and means for evaluating the identification accuracy based on the aggregated results. This enables effective identification of AI-generated information and human-generated information, provision of rewards based on the results, and secure supply of the identification results.

[0067] A "content provision device" is a device that has the function of collecting information generated by artificial intelligence technology or information generated by humans and transmitting it to the user's terminal.

[0068] "Artificial intelligence technology" refers to technologies that enable computer systems to mimic human intellectual activity and to generate and analyze information.

[0069] A "user terminal" is a device that receives information transmitted from a server and provides an interface that allows the user to manipulate and identify that information.

[0070] "Discrimination accuracy" is a measure used to evaluate how correctly users were able to distinguish whether information was generated by artificial intelligence or by humans.

[0071] A "recording medium" is a technology or device used to hold data and store it in a format that can be accessed later.

[0072] An "external organization" is an organization or group that exists outside the system in order to provide or analyze information.

[0073] This invention is a system that efficiently distinguishes between information generated by artificial intelligence technology and information generated by humans. This system mainly consists of a server, a user terminal, and a content delivery device.

[0074] Server Role

[0075] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. Information is generated using a generation AI model, such as news articles and blog posts. The server also aggregates the identification results submitted by users and calculates the identification accuracy based on these results. This information is used to calculate rewards, which are provided to users as points or credits. The server software used is a solution that supports advanced database management and network communication.

[0076] Terminal role

[0077] The user terminal is responsible for displaying information received from the server. The terminal presents the information in a user-friendly format and provides an interface to help users identify whether the information is AI-generated or human-generated. The terminal's software is designed to facilitate smooth interface display, data input, and transmission.

[0078] User roles

[0079] Users review the displayed information and identify whether it was AI-generated or human-generated. The identification result is sent from the device to the server, after which a reward is provided. This allows users to earn rewards while participating.

[0080] Specific example

[0081] As a concrete example, a server might select both news articles generated by AI and those written by humans, and send them to a terminal. The terminal then presents the displayed articles to the user, who determines and selects which type of article it is. If the user's selection is correct, reward points calculated by the server are added to the user's account.

[0082] Example of a prompt

[0083] An example of input for a generative AI model is: "Classify the following news articles as either AI-generated or human-generated. Read the articles carefully and pay attention to the wording, structure, and logic used."

[0084] This system enables the efficient collection of identification data, contributing to further model improvement, while providing economic benefits to users through the identification of AI-generated and human-generated information.

[0085] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0086] Step 1:

[0087] The server selects information generated by artificial intelligence technology and information generated by humans from the database. During the selection process, it processes the AI-generated information using prompts directed to the AI ​​model. Based on this input, the server formats both types of information and prepares them for transmission to the terminal. This process generates an organized set of information as output.

[0088] Step 2:

[0089] The terminal receives and displays information sent from the server. The display uses an intuitive interface to make it easy for the user to identify the information. Using the information received as input, the terminal presents it clearly on the screen. This process outputs an operation screen for the user to make selections.

[0090] Step 3:

[0091] The user reviews the information displayed on the device and identifies whether it was generated by AI or by a human. The user's judgment is based on the style and content of the information. The user instructs the device to input their selection, and the data is output to the server in an appropriate format.

[0092] Step 4:

[0093] The server receives the user's selection results and aggregates them. The selection results, as input, are stored in a database, and aggregation calculations are performed to evaluate the identification accuracy. These aggregated results are recorded in the database as an indicator of identification accuracy.

[0094] Step 5:

[0095] The server calculates rewards based on the aggregated selection results, according to the user's identification accuracy. It calculates rewards based on the input aggregated data and outputs the results to the user's account. These rewards are added to the user's account as points or credits and provided to the user in a usable format.

[0096] (Application Example 1)

[0097] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0098] In today's society, where systems capable of instantly determining the reliability and source of information are essential, there is a need to efficiently distinguish between information generated by artificial intelligence and information generated by humans, providing users with clear choices. However, current information distribution systems lack sufficient means to easily distinguish between AI-generated and manually generated information, posing a challenge as users may make decisions based on incorrect information.

[0099] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0100] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by a generation method and information generated by a human, from a content provision device to a user device; means for the user device to display the transmitted information and provide an operation screen for the user to select whether the information is generated by a generation method or by a human; and means for obtaining the user's selection results from the user device, aggregating the obtained selection results, and recording them in a storage device. This makes it possible for the user to determine the source of the information and receive rewards based on accurate selections.

[0101] A "content provision device" is a device that generates information and transmits it to a user's terminal.

[0102] A "generative method" refers to a method of creating information using artificial intelligence technology or by humans.

[0103] "Information" refers to data, including text, images, and audio, that is delivered from a content provider to a user's terminal.

[0104] A "user device" is a terminal device operated by a user to receive and display information.

[0105] An "operation screen" is an interface that allows a user to select or identify information.

[0106] "Aggregation" is a procedure for statistically processing acquired data and evaluating the trends and accuracy of the information.

[0107] A "storage device" is a device used to store data and information for the long term.

[0108] "Evaluation" is the process of determining the accuracy and performance of information identification based on the aggregated results.

[0109] "Specific information" refers to data that indicates the user's choices and their accuracy.

[0110] "Rewards" are values ​​given as compensation for users correctly identifying information.

[0111] An "application program" is software created to perform a specific function and provide a specific experience to the user.

[0112] This invention provides a system for identifying information generated by a generation method, which involves implementing a server that interacts with user devices that receive and present information. The server has the function of acquiring information generated by the generation method and information generated manually from a storage device and transmitting it to multiple user devices. This information includes text, images, audio, and the like.

[0113] The user device displays this information and provides a user-friendly interface (operation screen). Through this screen, the user can select whether the information is generated by a data generation method or by human input. The selected data is sent from the user device to the server, which then aggregates the selection results and records them in its storage device.

[0114] To evaluate the accuracy of information identification, the server calculates the accuracy rate based on the aggregated results. This utilizes database processing techniques and algorithms. The recorded data is anonymized and may be provided to third parties.

[0115] This entire process is carried out using cloud servers (such as Amazon Web Services and Google Cloud Platform), hardware such as smartphones and personal computers, database software (such as MySQL and MongoDB), and generative AI models.

[0116] A concrete example is a server that retrieves news articles generated by an AI model and delivers them to the user's device. The user reads the article and identifies the source of the information by choosing whether it was AI-generated or human-generated. The user is rewarded based on the accuracy of the identification result derived from this choice.

[0117] An example of a prompt message is, "Write a news article about a recent rainstorm that caused river flooding. Ensure it is detailed enough to be indistinguishable from a human-written article." In this way, the accuracy of AI-generated content improves, and more reliable information is provided.

[0118] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0119] Step 1:

[0120] The server uses a generative AI model to retrieve information generated from a text database using a generation method, as well as information created by humans. The input is a specified information type, and the output is the retrieved information. AI-generated information is obtained based on a specified prompt statement.

[0121] Step 2:

[0122] The server sends the acquired information to the user terminal. It receives the acquired information as input and sends the information to the user terminal as output. Data processing is performed to format the data so that the terminal can display the information correctly.

[0123] Step 3:

[0124] The terminal displays the received information and provides the user with an operation screen with choices. It receives information from the server as input and generates a user-display screen as output. Data is formatted to match the display format.

[0125] Step 4:

[0126] The user chooses whether the presented information is generated by a data generation method or by a human. The user makes a selection based on the terminal's options as input, and the result of that selection is generated as output. The user performs intuitive interface operations.

[0127] Step 5:

[0128] The terminal sends the user's selection results to the server. It receives the user's selection results as input and sends the results to the server as output. The selection data is formatted and appropriately packaged.

[0129] Step 6:

[0130] The server aggregates the received selection results and records them in storage. It receives selection results from terminals as input and records the aggregated results in a database as output. Statistical processing is performed on the database to analyze selection trends.

[0131] Step 7:

[0132] The server calculates the accuracy rate based on the aggregated results and calculates and notifies the user of the reward as needed. It receives the aggregated results as input and notifies the user of the calculated reward as output. Triggers for evaluating the reward data and adding points are set.

[0133] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0134] This invention is a system that improves the accuracy of information identification by applying artificial intelligence technology combined with an emotion engine. Furthermore, by considering the user's emotional state, it provides a form that enhances the user experience while facilitating the information identification process.

[0135] Overall system configuration

[0136] The server, acting as a content provider, transmits information generated using artificial intelligence technology and human-generated information, along with an emotion engine, to the user's terminal. The user's terminal presents this received information and also uses the emotion engine to collect the user's emotional data, which is then used in the identification process.

[0137] System operation

[0138] The device displays information on the provided interface and simultaneously uses its built-in emotion engine to recognize the user's emotional state. This emotional state includes the user's interests, attention span, and stress levels. Based on this emotional data, the device optimizes the order and format of content presentation to enable more efficient user identification.

[0139] Specific example

[0140] For example, the server selects both AI-generated and human-generated news article texts and sends them to the user's terminal. During this process, the terminal utilizes an emotion engine to analyze the user's subtle emotional responses as they review the information. If the user expresses discomfort with certain information, the terminal can change the way the information is presented or present different content to improve their experience. In this way, the entire system dynamically adapts to the user's emotional state during the process, providing an optimal user experience.

[0141] This invention aims to improve user interaction from a scientific and psychological perspective, going beyond mere information identification, by incorporating an emotion engine. This implementation is expected to lead to more effective and efficient data collection and improved user satisfaction.

[0142] The following describes the processing flow.

[0143] Step 1:

[0144] The server randomly selects information generated by artificial intelligence technology and information generated by humans from the database and sends it to the user's terminal. This selection is made considering the diversity of the information and the difficulty of identification.

[0145] Step 2:

[0146] The device displays the received information and simultaneously activates an emotion engine to perform facial recognition and voice analysis of the user. This allows it to acquire emotional data from the process of the user viewing and reacting to the information.

[0147] Step 3:

[0148] The user reviews the displayed information, determines whether it is AI-generated or human-generated, and makes a selection through the user interface. The emotion engine also responds to this selection process, analyzing the user's facial expressions and tone of voice during the selection.

[0149] Step 4:

[0150] The device sends emotional data acquired by the emotion engine to the server simultaneously with the user's selection. This data includes the user's psychological state and stress level at the time of selection.

[0151] Step 5:

[0152] The server calculates the accuracy rate of the selection based on the received selection results and sentiment data, and provides appropriate feedback to the user. If necessary, sentiment information is used as data to adjust the order and format of information presentation in the next session.

[0153] Step 6:

[0154] The server evaluates the user's identification accuracy based on the accuracy rate, determines the reward based on the result, and adds it to the user's account. It also anonymizes sentiment data and processes it for provision to a third-party organization.

[0155] Thus, the present invention realizes a system that optimizes the user experience while refining the information identification process by utilizing the user's emotional state.

[0156] (Example 2)

[0157] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0158] In recent years, the increasing diversity and volume of information has made it difficult for users to quickly and accurately select the information they need. Furthermore, ignoring the impact of information on users' emotional states presents a challenge in providing effective information. Against this backdrop, there is a need to develop information presentation methods that take users' emotions into consideration.

[0159] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0160] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for recognizing the user's emotional state using an emotion analysis device built into the user terminal and dynamically optimizing the presented information; and means for aggregating the selection results and emotion data acquired from the user terminal and storing them in a data recording device. This enables efficient and highly accurate information selection adapted to the user's emotions.

[0161] A "content provision device" is a device that collects information generated using artificial intelligence technology and information generated by humans, and transmits it to the user's terminal.

[0162] A "user terminal" is a device that receives information from a server and presents it to the user, and has the function of recognizing the user's emotional state through a built-in emotion analysis device.

[0163] "Artificial intelligence technology" refers to technologies that analyze data, recognize patterns, and improve the accuracy of information generation and processing.

[0164] An "emotion analysis device" is a technological device for recognizing and evaluating a user's emotional state, and it has the function of determining emotions using the user's facial expressions and physiological data.

[0165] "Selection result" refers to the content that the user selected from the information presented on their device.

[0166] "Emotional data" refers to information about the user's emotional state and is collected by an emotion analysis device.

[0167] A "data recording device" is a device for collecting and storing selection results and emotional data.

[0168] "Anonymization" is the process of removing elements that identify individuals from collected data and making it available to third parties.

[0169] This invention is a system for improving information identification accuracy and user experience by taking into account the emotional state of the user. Specifically, it consists of a server which is a content provider, a user terminal which receives and displays information, and a device which performs emotion analysis.

[0170] The server collects news and various content from sources such as the internet and databases. This collected information is then restructured or summarized using generative AI models. Natural language processing techniques are utilized in this process. The generated information is integrated with human-generated information and optimized to suit the user's interests.

[0171] The terminal displays information transmitted from the server to the user. The terminal also has a built-in emotion analyzer that uses cameras and sensors to determine the user's emotions in real time. This emotion data includes, for example, facial expressions, eye movements, and voice tone. The terminal analyzes this data to evaluate how the user feels about the information. Based on this evaluation, it improves the user experience by changing or adjusting the way the information is presented.

[0172] Users can select information on the device and provide feedback. This feedback is stored in a data recording device and used to improve future information provision. For example, if a user shows interest in a particular news topic, the device can display more information related to it.

[0173] As a concrete example, by providing the server with the prompt message, "Present the latest technology news tailored to the user's interests," appropriate information is selected and delivered to the user via the terminal. In this way, the system can achieve more effective information selection and presentation that is in line with the user's interests and emotions.

[0174] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0175] Step 1:

[0176] The server collects news articles and related content from the internet and databases. It is given URLs of content sources and database queries as input, and the output is the collected raw information data. This step specifically involves web scraping and API access.

[0177] Step 2:

[0178] The server processes the collected information using a generative AI model to generate new information. Raw data is provided as input, and summaries or newly generated information are obtained as output. This process specifically includes summarization and article generation using natural language processing algorithms.

[0179] Step 3:

[0180] The server integrates the generated information with the human-generated information and sends it to the user's terminal. The input consists of generated information and human-generated information, and the output is a composite information ready for transmission. This step includes tagging the information, evaluating its importance, and formatting the data in a format suitable for the target user.

[0181] Step 4:

[0182] The terminal receives information sent from the server and displays it to the user. The input is the transmitted composite information, and the output is information visually presented to the user. Specific operations include information rendering using a GUI and the application of responsive design.

[0183] Step 5:

[0184] The device uses a built-in emotion analyzer to recognize the user's emotional state in real time while they are viewing information. The user's biometric data and facial expressions are provided as input, and quantified emotion data is obtained as output. Specific operations include data collection using cameras, microphones, and sensors, and emotion analysis using machine learning.

[0185] Step 6:

[0186] The device dynamically optimizes how information is presented based on emotional data to improve the user experience. Emotional data is provided as input, and optimized information presentation is obtained as output. Specific actions include changing the presentation order, highlighting content, and adjusting the visual design.

[0187] Step 7:

[0188] Users select information based on their interests and reactions, and provide feedback via their device. The input is user selection data, and the output is improvement suggestions based on that data. Specific actions include selection via clicks and taps on the user interface, and the use of feedback buttons.

[0189] Step 8:

[0190] The terminal collects user selection results and sentiment data and sends it to the server. The input is selection and sentiment data, and the output is a data packet ready for transmission. Secure data transfer using a communication protocol is a concrete operation.

[0191] Step 9:

[0192] The server stores the received data in a data recording device and uses it for aggregation and analysis. The input is the transmitted data packets, and the output is the accumulated database. Specific operations include writing to the database and aggregation using statistical analysis tools.

[0193] (Application Example 2)

[0194] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0195] In modern information delivery, it is crucial to improve user satisfaction with the information they receive. Especially in an increasingly diverse information landscape, there is a need to dynamically adjust the order and format of information delivery to best suit the user. Furthermore, distributing information uniformly without considering user emotions can fail to capture user interest or even cause stress. The challenge lies in resolving these issues and providing a better user experience.

[0196] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0197] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for displaying the transmitted information on the user terminal and providing an operation screen for the user to select whether the information is generated by artificial intelligence technology or by humans; means for obtaining the user's selection results from the user terminal, aggregating the obtained selection results, and recording them in a database; and means for the user terminal to analyze the user's emotional state using emotion recognition technology and dynamically optimizing the order in which the information is presented based on that data. This makes it possible to provide information optimally according to the user's emotional state.

[0198] A "content provider" is a device that transmits information to a user's terminal and plays the role of providing multiple pieces of content, including information generated by artificial intelligence technology and by humans.

[0199] "Artificial intelligence technology" refers to technologies that use computational techniques, including machine learning and natural language processing, to mimic human intellectual work and perform information generation and analysis.

[0200] A "user terminal" refers to a device used to receive and display information transmitted from a content provider, and includes electronic devices such as smartphones and computers.

[0201] An "operation screen" is an interface that allows users to select, input, or confirm information through their device.

[0202] "Emotion recognition technology" is a technology that identifies a user's inner emotional state by analyzing their facial expressions and behavior.

[0203] "Presentation order" refers to the sequence and arrangement of information displayed to the user, and is an element that is dynamically adjusted based on the user's emotions and preferences.

[0204] A "database" is a system for efficiently storing, managing, and retrieving collected user selection results and sentiment data.

[0205] In order to implement this invention, the entire content delivery system must operate in a coordinated manner. The details are described below.

[0206] First, the server, acting as a content provider, scans information generated by artificial intelligence technology and information generated by humans, and transmits it to the user's terminal. The server transmits this information using standard data protocols, but it is preferable to use a cloud service with superior processing capabilities (e.g., Amazon Web Services or Google Cloud Platform).

[0207] The terminal is a user device such as a smartphone or tablet that displays received information on its screen. Furthermore, the terminal incorporates emotion recognition technology that analyzes the user's facial expressions and actions to identify the user's emotional state. The emotion recognition process uses a high-precision camera and emotion recognition software such as Microsoft® Emotion API or Google Cloud Vision.

[0208] User emotional state data is dynamically processed on the device to determine the optimal content presentation order for each individual user. For example, if a user is determined to be relaxed, detailed articles will be prioritized, while shorter content can be selected if the user is experiencing high stress levels.

[0209] Furthermore, a real-time data processing framework (e.g., Apache® Kafka) is used to collect and record user selections in a database. Based on this data, a reward feedback system can be implemented to evaluate the accuracy of selections and improve user satisfaction.

[0210] As a concrete example, let's consider a scenario where a user is using a news app. If the app detects a happy expression on the user's face while they are reading a news article, it will then present articles in a similar category. Furthermore, if the user is struggling to choose an article for an extended period, it will offer simpler options to improve the user experience.

[0211] An example of a prompt message might be: "The user is currently viewing a news article. Use real-time sentiment data to prioritize the articles viewed and optimize the news experience. Consider the user's interests, attention span, and stress level."

[0212] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0213] Step 1:

[0214] The server collects multiple pieces of information, including artificial intelligence and human-generated data, and transmits this information to the user's terminal. The input is the information database maintained by the server. The output is the list of information sent to the user's terminal. This forms the basis for the user to access the latest information.

[0215] Step 2:

[0216] The terminal displays the received information and provides a screen that allows the user to select whether the information is generated by artificial intelligence or by a human. The input is the information sent from the server in step 1. The output is the user's selection result. Based on this selection result, the terminal understands the user's information preferences.

[0217] Step 3:

[0218] The device uses built-in emotion recognition technology to analyze the user's emotional state in real time. Inputs include the user's facial expressions and operation patterns. Outputs include the user's emotional data, such as interest levels and stress levels. The device uses this data to prepare for the next processing step.

[0219] Step 4:

[0220] The device dynamically optimizes the information presentation order by combining emotional data and the user's selection results. The input is the selection result from step 2 and the emotional data from step 3. The output is the optimized information presentation order. In this step, a generative AI model is used to formulate a presentation order that is adapted to various scenarios.

[0221] Step 5:

[0222] Based on the presented information, users view information that matches their preferences. The input is the information presentation order optimized in step 4. The output is user behavior data, recording how the user reacted to the information. The data obtained in this step contributes to further improving the user experience.

[0223] Step 6:

[0224] The terminal aggregates all selection results and sentiment data, anonymizes them, and records them in a database. The input is the result data from steps 2, 3, and 5. The output is the anonymized data stored in the database. This data is used for subsequent analysis and system improvement.

[0225] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0226] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0227] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0228] [Second Embodiment]

[0229] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0230] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0231] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0232] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0233] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0234] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0235] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0236] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0237] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0238] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0239] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0240] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0241] This invention is a system for distinguishing between information generated by artificial intelligence technology and information generated by humans, and is implemented in a form in which a content provider, a user terminal, and a server work in cooperation with each other.

[0242] Overall system configuration

[0243] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. The user's terminal displays the received information and provides an operation screen for the user to identify the information. The user determines whether the information is AI-generated or human-generated and selects the result.

[0244] System operation

[0245] The server receives the user's selection data, aggregates it, and records it in a database. This aggregated result serves as an indicator of how accurately each piece of information was identified. Furthermore, the server calculates a reward based on the accuracy rate and provides it to the user. The reward is added to the user's account as points or credits.

[0246] Specific example

[0247] For example, the server selects both news article texts generated by AI and those written by human journalists and sends them to the user's terminal. The terminal displays the article, and the user selects which author created it. Once the user enters their selection into the terminal, the data is immediately sent to the server. The server aggregates this data and evaluates the accuracy of the identification. If the user's selection is correct, the user is given additional rewards based on their accuracy.

[0248] The purpose of this system is to efficiently collect identification data of artificial intelligence technology and human-generated information, thereby providing economic benefits to users while supplying data to third-party organizations and contributing to the development of better generative models.

[0249] The following describes the processing flow.

[0250] Step 1:

[0251] The server randomly retrieves information from the database, including both AI-generated and human-generated information, and then selects content to send to the user. The information to be sent is determined based on predefined criteria.

[0252] Step 2:

[0253] The server transmits the selected information to the user's terminal and provides an operational interface for displaying and identifying the information.

[0254] Step 3:

[0255] The terminal displays the received content to the user and simultaneously provides an operation screen where the user can select whether the information was generated by an AI or by a human.

[0256] Step 4:

[0257] The user reviews the displayed information, determines its source, and makes a selection. This selection is made through the user interface.

[0258] Step 5:

[0259] The user's selection results are sent to the server by the device. This transmission includes the selected options and related metadata.

[0260] Step 6:

[0261] The server records the received selection results in a database and further calculates the accuracy rate to evaluate the user's identification accuracy.

[0262] Step 7:

[0263] The server calculates rewards based on the user's accuracy rate, according to specified criteria. The calculated rewards are added to the user's account.

[0264] Step 8:

[0265] The server anonymizes the aggregated data as needed and organizes it as data. The organized data is later provided to a third-party organization and used for research and development of generative AI technology.

[0266] (Example 1)

[0267] Next, we will describe Example 1. 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."

[0268] In recent years, advancements in artificial intelligence technology have created a problem where it is difficult to distinguish between information generated by AI and information generated by humans. Furthermore, there is a need to improve the accuracy and efficiency of providing rewards to users through this identification process. Additionally, there is a need for a secure method of supplying identification results to third-party organizations.

[0269] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0270] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal; means for acquiring the user's selection results, aggregating the acquired selection results, and recording them on a recording medium; and means for evaluating the identification accuracy based on the aggregated results. This enables effective identification of AI-generated information and human-generated information, provision of rewards based on the results, and secure supply of the identification results.

[0271] A "content provision device" is a device that has the function of collecting information generated by artificial intelligence technology or information generated by humans and transmitting it to the user's terminal.

[0272] "Artificial intelligence technology" refers to technologies that enable computer systems to mimic human intellectual activity and to generate and analyze information.

[0273] A "user terminal" is a device that receives information transmitted from a server and provides an interface that allows the user to manipulate and identify that information.

[0274] "Discrimination accuracy" is a measure used to evaluate how correctly users were able to distinguish whether information was generated by artificial intelligence or by humans.

[0275] A "recording medium" is a technology or device used to hold data and store it in a format that can be accessed later.

[0276] An "external organization" is an organization or group that exists outside the system in order to provide or analyze information.

[0277] This invention is a system that efficiently distinguishes between information generated by artificial intelligence technology and information generated by humans. This system mainly consists of a server, a user terminal, and a content delivery device.

[0278] Server Role

[0279] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. Information is generated using a generation AI model, such as news articles and blog posts. The server also aggregates the identification results submitted by users and calculates the identification accuracy based on these results. This information is used to calculate rewards, which are provided to users as points or credits. The server software used is a solution that supports advanced database management and network communication.

[0280] Terminal role

[0281] The user terminal is responsible for displaying the information received from the server. The terminal presents the information in a form that is easy for the user to judge and provides an operation screen for identifying whether the information is generated by AI or by a human. The software of the terminal is configured to smoothly perform interface display, data input, and transmission.

[0282] The role of the user

[0283] The user checks the displayed information and identifies whether it is AI-generated or human-generated. The identification result is sent from the terminal to the server, and then a reward is provided. In this way, the user can obtain a reward while participating.

[0284] Specific example

[0285] As a specific example, there is a case where the server selects both news articles generated by AI and those created by humans and sends them to the terminal. The terminal presents the displayed article to the user, and the user judges and selects which one it is. If the user's selection is correct, the reward points calculated by the server are added to the user's account.

[0286] Example of a prompt sentence

[0287] An example of the input to the generation AI model is "Please classify the following news article as generated by AI and as generated by a human. Read the article carefully and pay attention to the word usage, structure, logic, etc. used."

[0288] Through this system, it is possible to provide economic benefits to users while efficiently collecting identification data through the identification of AI-generated information and human-generated information, and contributing to the further improvement of the model.

[0289] The flow of the specific process in Example 1 will be described using FIG. 11.

[0290] Step 1:

[0291] The server selects information generated by artificial intelligence technology and information generated by humans from the database. During the selection process, it processes the AI-generated information using prompts directed to the AI ​​model. Based on this input, the server formats both types of information and prepares them for transmission to the terminal. This process generates an organized set of information as output.

[0292] Step 2:

[0293] The terminal receives and displays information sent from the server. The display uses an intuitive interface to make it easy for the user to identify the information. Using the information received as input, the terminal presents it clearly on the screen. This process outputs an operation screen for the user to make selections.

[0294] Step 3:

[0295] The user reviews the information displayed on the device and identifies whether it was generated by AI or by a human. The user's judgment is based on the style and content of the information. The user instructs the device to input their selection, and the data is output to the server in an appropriate format.

[0296] Step 4:

[0297] The server receives the user's selection results and aggregates them. The selection results, as input, are stored in a database, and aggregation calculations are performed to evaluate the identification accuracy. These aggregated results are recorded in the database as an indicator of identification accuracy.

[0298] Step 5:

[0299] The server calculates rewards based on the aggregated selection results, according to the user's identification accuracy. It calculates rewards based on the input aggregated data and outputs the results to the user's account. These rewards are added to the user's account as points or credits and provided to the user in a usable format.

[0300] (Application Example 1)

[0301] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0302] In today's society, where systems capable of instantly determining the reliability and source of information are essential, there is a need to efficiently distinguish between information generated by artificial intelligence and information generated by humans, providing users with clear choices. However, current information distribution systems lack sufficient means to easily distinguish between AI-generated and manually generated information, posing a challenge as users may make decisions based on incorrect information.

[0303] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0304] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by a generation method and information generated by a human, from a content provision device to a user device; means for the user device to display the transmitted information and provide an operation screen for the user to select whether the information is generated by a generation method or by a human; and means for obtaining the user's selection results from the user device, aggregating the obtained selection results, and recording them in a storage device. This makes it possible for the user to determine the source of the information and receive rewards based on accurate selections.

[0305] A "content provision device" is a device that generates information and transmits it to a user's terminal.

[0306] "Generation method" refers to a method of creating information by artificial intelligence technology or by humans.

[0307] "Information" refers to data including text, images, voices, etc., and is distributed from a content providing device to a user terminal.

[0308] "Usage device" refers to terminal equipment that a user operates to receive and display information.

[0309] "Operation screen" refers to an interface for a user to select or identify information.

[0310] "Aggregation" refers to a procedure for statistically processing acquired data to evaluate the trends and accuracy of information.

[0311] "Storage device" refers to a device for storing data and information in the long term.

[0312] "Evaluation" refers to a process of determining the accuracy and performance of information identification based on the aggregated results.

[0313] "Specific information" refers to data indicating a user's selection result and accuracy.

[0314] "Reward" refers to something of value given as a return for a user's correct information identification.

[0315] "Application program" refers to software created to realize a specific function and provides a specific experience to a user.

[0316] This invention provides a system that implements a server that cooperates with a usage device that receives and presents information, and identifies information generated by a generation method. The server has a function of acquiring information generated by a generation method and information generated by human hands from a storage device, and transmitting this to a plurality of usage devices. This information includes text, images, voices, etc.

[0317] The user device displays this information and provides a user-friendly interface (operation screen). Through this screen, the user can select whether the information is generated by a data generation method or by human input. The selected data is sent from the user device to the server, which then aggregates the selection results and records them in its storage device.

[0318] To evaluate the accuracy of information identification, the server calculates the accuracy rate based on the aggregated results. This utilizes database processing techniques and algorithms. The recorded data is anonymized and may be provided to third parties.

[0319] This entire process is carried out using cloud servers (such as Amazon Web Services and Google Cloud Platform), hardware such as smartphones and personal computers, database software (such as MySQL and MongoDB), and generative AI models.

[0320] A concrete example is a server that retrieves news articles generated by an AI model and delivers them to the user's device. The user reads the article and identifies the source of the information by choosing whether it was AI-generated or human-generated. The user is rewarded based on the accuracy of the identification result derived from this choice.

[0321] An example of a prompt message is, "Write a news article about a recent rainstorm that caused river flooding. Ensure it is detailed enough to be indistinguishable from a human-written article." In this way, the accuracy of AI-generated content improves, and more reliable information is provided.

[0322] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0323] Step 1:

[0324] The server uses a generative AI model to retrieve information generated from a text database using a generation method, as well as information created by humans. The input is a specified information type, and the output is the retrieved information. AI-generated information is obtained based on a specified prompt statement.

[0325] Step 2:

[0326] The server sends the acquired information to the user terminal. It receives the acquired information as input and sends the information to the user terminal as output. Data processing is performed to format the data so that the terminal can display the information correctly.

[0327] Step 3:

[0328] The terminal displays the received information and provides the user with an operation screen with choices. It receives information from the server as input and generates a user-display screen as output. Data is formatted to match the display format.

[0329] Step 4:

[0330] The user chooses whether the presented information is generated by a data generation method or by a human. The user makes a selection based on the terminal's options as input, and the result of that selection is generated as output. The user performs intuitive interface operations.

[0331] Step 5:

[0332] The terminal sends the user's selection results to the server. It receives the user's selection results as input and sends the results to the server as output. The selection data is formatted and appropriately packaged.

[0333] Step 6:

[0334] The server aggregates the received selection results and records them in storage. It receives selection results from terminals as input and records the aggregated results in a database as output. Statistical processing is performed on the database to analyze selection trends.

[0335] Step 7:

[0336] The server calculates the accuracy rate based on the aggregated results and calculates and notifies the user of the reward as needed. It receives the aggregated results as input and notifies the user of the calculated reward as output. Triggers for evaluating the reward data and adding points are set.

[0337] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0338] This invention is a system that improves the accuracy of information identification by applying artificial intelligence technology combined with an emotion engine. Furthermore, by considering the user's emotional state, it provides a form that enhances the user experience while facilitating the information identification process.

[0339] Overall system configuration

[0340] The server, acting as a content provider, transmits information generated using artificial intelligence technology and human-generated information, along with an emotion engine, to the user's terminal. The user's terminal presents this received information and also uses the emotion engine to collect the user's emotional data, which is then used in the identification process.

[0341] System operation

[0342] The device displays information on the provided interface and simultaneously uses its built-in emotion engine to recognize the user's emotional state. This emotional state includes the user's interests, attention span, and stress levels. Based on this emotional data, the device optimizes the order and format of content presentation to enable more efficient user identification.

[0343] Specific example

[0344] For example, the server selects both AI-generated and human-generated news article texts and sends them to the user's terminal. During this process, the terminal utilizes an emotion engine to analyze the user's subtle emotional responses as they review the information. If the user expresses discomfort with certain information, the terminal can change the way the information is presented or present different content to improve their experience. In this way, the entire system dynamically adapts to the user's emotional state during the process, providing an optimal user experience.

[0345] This invention aims to improve user interaction from a scientific and psychological perspective, going beyond mere information identification, by incorporating an emotion engine. This implementation is expected to lead to more effective and efficient data collection and improved user satisfaction.

[0346] The following describes the processing flow.

[0347] Step 1:

[0348] The server randomly selects information generated by artificial intelligence technology and information generated by humans from the database and sends it to the user's terminal. This selection is made considering the diversity of the information and the difficulty of identification.

[0349] Step 2:

[0350] The device displays the received information and simultaneously activates an emotion engine to perform facial recognition and voice analysis of the user. This allows it to acquire emotional data from the process of the user viewing and reacting to the information.

[0351] Step 3:

[0352] The user reviews the displayed information, determines whether it is AI-generated or human-generated, and makes a selection through the user interface. The emotion engine also responds to this selection process, analyzing the user's facial expressions and tone of voice during the selection.

[0353] Step 4:

[0354] The device sends emotional data acquired by the emotion engine to the server simultaneously with the user's selection. This data includes the user's psychological state and stress level at the time of selection.

[0355] Step 5:

[0356] The server calculates the accuracy rate of the selection based on the received selection results and sentiment data, and provides appropriate feedback to the user. If necessary, sentiment information is used as data to adjust the order and format of information presentation in the next session.

[0357] Step 6:

[0358] The server evaluates the user's identification accuracy based on the accuracy rate, determines the reward based on the result, and adds it to the user's account. It also anonymizes sentiment data and processes it for provision to a third-party organization.

[0359] Thus, the present invention realizes a system that optimizes the user experience while refining the information identification process by utilizing the user's emotional state.

[0360] (Example 2)

[0361] Next, we will describe Example 2. 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".

[0362] In recent years, the increasing diversity and volume of information has made it difficult for users to quickly and accurately select the information they need. Furthermore, ignoring the impact of information on users' emotional states presents a challenge in providing effective information. Against this backdrop, there is a need to develop information presentation methods that take users' emotions into consideration.

[0363] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0364] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for recognizing the user's emotional state using an emotion analysis device built into the user terminal and dynamically optimizing the presented information; and means for aggregating the selection results and emotion data acquired from the user terminal and storing them in a data recording device. This enables efficient and highly accurate information selection adapted to the user's emotions.

[0365] A "content provision device" is a device that collects information generated using artificial intelligence technology and information generated by humans, and transmits it to the user's terminal.

[0366] A "user terminal" is a device that receives information from a server and presents it to the user, and has the function of recognizing the user's emotional state through a built-in emotion analysis device.

[0367] "Artificial intelligence technology" refers to technologies that analyze data, recognize patterns, and improve the accuracy of information generation and processing.

[0368] An "emotion analysis device" is a technological device for recognizing and evaluating a user's emotional state, and it has the function of determining emotions using the user's facial expressions and physiological data.

[0369] "Selection result" refers to the content that the user selected from the information presented on their device.

[0370] "Emotional data" refers to information about the user's emotional state and is collected by an emotion analysis device.

[0371] A "data recording device" is a device for collecting and storing selection results and emotional data.

[0372] "Anonymization" is the process of removing elements that identify individuals from collected data and making it available to third parties.

[0373] This invention is a system for improving information identification accuracy and user experience by taking into account the emotional state of the user. Specifically, it consists of a server which is a content provider, a user terminal which receives and displays information, and a device which performs emotion analysis.

[0374] The server collects news and various content from sources such as the internet and databases. This collected information is then restructured or summarized using generative AI models. Natural language processing techniques are utilized in this process. The generated information is integrated with human-generated information and optimized to suit the user's interests.

[0375] The terminal displays information transmitted from the server to the user. The terminal also has a built-in emotion analyzer that uses cameras and sensors to determine the user's emotions in real time. This emotion data includes, for example, facial expressions, eye movements, and voice tone. The terminal analyzes this data to evaluate how the user feels about the information. Based on this evaluation, it improves the user experience by changing or adjusting the way the information is presented.

[0376] Users can select information on the device and provide feedback. This feedback is stored in a data recording device and used to improve future information provision. For example, if a user shows interest in a particular news topic, the device can display more information related to it.

[0377] As a concrete example, by providing the server with the prompt message, "Present the latest technology news tailored to the user's interests," appropriate information is selected and delivered to the user via the terminal. In this way, the system can achieve more effective information selection and presentation that is in line with the user's interests and emotions.

[0378] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0379] Step 1:

[0380] The server collects news articles and related content from the internet and databases. It is given URLs of content sources and database queries as input, and the output is the collected raw information data. This step specifically involves web scraping and API access.

[0381] Step 2:

[0382] The server processes the collected information using a generative AI model to generate new information. Raw data is provided as input, and summaries or newly generated information are obtained as output. This process specifically includes summarization and article generation using natural language processing algorithms.

[0383] Step 3:

[0384] The server integrates the generated information with the human-generated information and sends it to the user's terminal. The input consists of generated information and human-generated information, and the output is a composite information ready for transmission. This step includes tagging the information, evaluating its importance, and formatting the data in a format suitable for the target user.

[0385] Step 4:

[0386] The terminal receives information sent from the server and displays it to the user. The input is the transmitted composite information, and the output is information visually presented to the user. Specific operations include information rendering using a GUI and the application of responsive design.

[0387] Step 5:

[0388] The device uses a built-in emotion analyzer to recognize the user's emotional state in real time while they are viewing information. The user's biometric data and facial expressions are provided as input, and quantified emotion data is obtained as output. Specific operations include data collection using cameras, microphones, and sensors, and emotion analysis using machine learning.

[0389] Step 6:

[0390] The device dynamically optimizes how information is presented based on emotional data to improve the user experience. Emotional data is provided as input, and optimized information presentation is obtained as output. Specific actions include changing the presentation order, highlighting content, and adjusting the visual design.

[0391] Step 7:

[0392] Users select information based on their interests and reactions, and provide feedback via their device. The input is user selection data, and the output is improvement suggestions based on that data. Specific actions include selection via clicks and taps on the user interface, and the use of feedback buttons.

[0393] Step 8:

[0394] The terminal collects user selection results and sentiment data and sends it to the server. The input is selection and sentiment data, and the output is a data packet ready for transmission. Secure data transfer using a communication protocol is a concrete operation.

[0395] Step 9:

[0396] The server stores the received data in a data recording device and uses it for aggregation and analysis. The input is the transmitted data packets, and the output is the accumulated database. Specific operations include writing to the database and aggregation using statistical analysis tools.

[0397] (Application Example 2)

[0398] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0399] In modern information delivery, it is crucial to improve user satisfaction with the information they receive. Especially in an increasingly diverse information landscape, there is a need to dynamically adjust the order and format of information delivery to best suit the user. Furthermore, distributing information uniformly without considering user emotions can fail to capture user interest or even cause stress. The challenge lies in resolving these issues and providing a better user experience.

[0400] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0401] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for displaying the transmitted information on the user terminal and providing an operation screen for the user to select whether the information is generated by artificial intelligence technology or by humans; means for obtaining the user's selection results from the user terminal, aggregating the obtained selection results, and recording them in a database; and means for the user terminal to analyze the user's emotional state using emotion recognition technology and dynamically optimizing the order in which the information is presented based on that data. This makes it possible to provide information optimally according to the user's emotional state.

[0402] A "content provider" is a device that transmits information to a user's terminal and plays the role of providing multiple pieces of content, including information generated by artificial intelligence technology and by humans.

[0403] "Artificial intelligence technology" refers to technologies that use computational techniques, including machine learning and natural language processing, to mimic human intellectual work and perform information generation and analysis.

[0404] A "user terminal" refers to a device used to receive and display information transmitted from a content provider, and includes electronic devices such as smartphones and computers.

[0405] An "operation screen" is an interface that allows users to select, input, or confirm information through their device.

[0406] "Emotion recognition technology" is a technology that identifies a user's inner emotional state by analyzing their facial expressions and behavior.

[0407] "Presentation order" refers to the sequence and arrangement of information displayed to the user, and is an element that is dynamically adjusted based on the user's emotions and preferences.

[0408] A "database" is a system for efficiently storing, managing, and retrieving collected user selection results and sentiment data.

[0409] In order to implement this invention, the entire content delivery system must operate in a coordinated manner. The details are described below.

[0410] First, the server, acting as a content provider, scans information generated by artificial intelligence technology and information generated by humans, and transmits it to the user's terminal. The server transmits this information using standard data protocols, but it is preferable to use a cloud service with superior processing capabilities (e.g., Amazon Web Services or Google Cloud Platform).

[0411] The terminal is a user device such as a smartphone or tablet that displays received information on its screen. Furthermore, the terminal incorporates emotion recognition technology that analyzes the user's facial expressions and actions to identify the user's emotional state. High-precision cameras and emotion recognition software such as Microsoft Emotion API and Google Cloud Vision are used for emotion recognition processing.

[0412] User emotional state data is dynamically processed on the device to determine the optimal content presentation order for each individual user. For example, if a user is determined to be relaxed, detailed articles will be prioritized, while shorter content can be selected if the user is experiencing high stress levels.

[0413] Furthermore, a real-time data processing framework (e.g., Apache Kafka) is used to collect and record user selections in a database. Based on this data, a reward feedback system can be implemented to evaluate the accuracy of selections and improve user satisfaction.

[0414] As a concrete example, let's consider a scenario where a user is using a news app. If the app detects a happy expression on the user's face while they are reading a news article, it will then present articles in a similar category. Furthermore, if the user is struggling to choose an article for an extended period, it will offer simpler options to improve the user experience.

[0415] An example of a prompt message might be: "The user is currently viewing a news article. Use real-time sentiment data to prioritize the articles viewed and optimize the news experience. Consider the user's interests, attention span, and stress level."

[0416] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0417] Step 1:

[0418] The server collects multiple pieces of information, including artificial intelligence and human-generated data, and transmits this information to the user's terminal. The input is the information database maintained by the server. The output is the list of information sent to the user's terminal. This forms the basis for the user to access the latest information.

[0419] Step 2:

[0420] The terminal displays the received information and provides a screen that allows the user to select whether the information is generated by artificial intelligence or by a human. The input is the information sent from the server in step 1. The output is the user's selection result. Based on this selection result, the terminal understands the user's information preferences.

[0421] Step 3:

[0422] The device uses built-in emotion recognition technology to analyze the user's emotional state in real time. Inputs include the user's facial expressions and operation patterns. Outputs include the user's emotional data, such as interest levels and stress levels. The device uses this data to prepare for the next processing step.

[0423] Step 4:

[0424] The device dynamically optimizes the information presentation order by combining emotional data and the user's selection results. The input is the selection result from step 2 and the emotional data from step 3. The output is the optimized information presentation order. In this step, a generative AI model is used to formulate a presentation order that is adapted to various scenarios.

[0425] Step 5:

[0426] Based on the presented information, users view information that matches their preferences. The input is the information presentation order optimized in step 4. The output is user behavior data, recording how the user reacted to the information. The data obtained in this step contributes to further improving the user experience.

[0427] Step 6:

[0428] The terminal aggregates all selection results and sentiment data, anonymizes them, and records them in a database. The input is the result data from steps 2, 3, and 5. The output is the anonymized data stored in the database. This data is used for subsequent analysis and system improvement.

[0429] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0430] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0431] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0432] [Third Embodiment]

[0433] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0434] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0435] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0436] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0437] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0438] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0439] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0440] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0441] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0442] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0443] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0444] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0445] This invention is a system for distinguishing between information generated by artificial intelligence technology and information generated by humans, and is implemented in a form in which a content provider, a user terminal, and a server work in cooperation with each other.

[0446] Overall system configuration

[0447] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. The user's terminal displays the received information and provides an operation screen for the user to identify the information. The user determines whether the information is AI-generated or human-generated and selects the result.

[0448] System operation

[0449] The server receives the user's selection data, aggregates it, and records it in a database. This aggregated result serves as an indicator of how accurately each piece of information was identified. Furthermore, the server calculates a reward based on the accuracy rate and provides it to the user. The reward is added to the user's account as points or credits.

[0450] Specific example

[0451] For example, the server selects both news article texts generated by AI and those written by human journalists and sends them to the user's terminal. The terminal displays the article, and the user selects which author created it. Once the user enters their selection into the terminal, the data is immediately sent to the server. The server aggregates this data and evaluates the accuracy of the identification. If the user's selection is correct, the user is given additional rewards based on their accuracy.

[0452] The purpose of this system is to efficiently collect identification data of artificial intelligence technology and human-generated information, thereby providing economic benefits to users while supplying data to third-party organizations and contributing to the development of better generative models.

[0453] The following describes the processing flow.

[0454] Step 1:

[0455] The server randomly retrieves information from the database, including both AI-generated and human-generated information, and then selects content to send to the user. The information to be sent is determined based on predefined criteria.

[0456] Step 2:

[0457] The server transmits the selected information to the user's terminal and provides an operational interface for displaying and identifying the information.

[0458] Step 3:

[0459] The terminal displays the received content to the user and simultaneously provides an operation screen where the user can select whether the information was generated by an AI or by a human.

[0460] Step 4:

[0461] The user reviews the displayed information, determines its source, and makes a selection. This selection is made through the user interface.

[0462] Step 5:

[0463] The user's selection results are sent to the server by the device. This transmission includes the selected options and related metadata.

[0464] Step 6:

[0465] The server records the received selection results in a database and further calculates the accuracy rate to evaluate the user's identification accuracy.

[0466] Step 7:

[0467] The server calculates rewards based on the user's accuracy rate, according to specified criteria. The calculated rewards are added to the user's account.

[0468] Step 8:

[0469] The server anonymizes the aggregated data as needed and organizes it as data. The organized data is later provided to a third-party organization and used for research and development of generative AI technology.

[0470] (Example 1)

[0471] Next, we will describe Example 1. 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."

[0472] In recent years, advancements in artificial intelligence technology have created a problem where it is difficult to distinguish between information generated by AI and information generated by humans. Furthermore, there is a need to improve the accuracy and efficiency of providing rewards to users through this identification process. Additionally, there is a need for a secure method of supplying identification results to third-party organizations.

[0473] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0474] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal; means for acquiring the user's selection results, aggregating the acquired selection results, and recording them on a recording medium; and means for evaluating the identification accuracy based on the aggregated results. This enables effective identification of AI-generated information and human-generated information, provision of rewards based on the results, and secure supply of the identification results.

[0475] A "content provision device" is a device that has the function of collecting information generated by artificial intelligence technology or information generated by humans and transmitting it to the user's terminal.

[0476] "Artificial intelligence technology" refers to technologies that enable computer systems to mimic human intellectual activity and to generate and analyze information.

[0477] A "user terminal" is a device that receives information transmitted from a server and provides an interface that allows the user to manipulate and identify that information.

[0478] "Discrimination accuracy" is a measure used to evaluate how correctly users were able to distinguish whether information was generated by artificial intelligence or by humans.

[0479] A "recording medium" is a technology or device used to hold data and store it in a format that can be accessed later.

[0480] An "external organization" is an organization or group that exists outside the system in order to provide or analyze information.

[0481] This invention is a system that efficiently distinguishes between information generated by artificial intelligence technology and information generated by humans. This system mainly consists of a server, a user terminal, and a content delivery device.

[0482] Server Role

[0483] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. Information is generated using a generation AI model, such as news articles and blog posts. The server also aggregates the identification results submitted by users and calculates the identification accuracy based on these results. This information is used to calculate rewards, which are provided to users as points or credits. The server software used is a solution that supports advanced database management and network communication.

[0484] Terminal role

[0485] The user terminal is responsible for displaying information received from the server. The terminal presents the information in a user-friendly format and provides an interface to help users identify whether the information is AI-generated or human-generated. The terminal's software is designed to facilitate smooth interface display, data input, and transmission.

[0486] User roles

[0487] Users review the displayed information and identify whether it was AI-generated or human-generated. The identification result is sent from the device to the server, after which a reward is provided. This allows users to earn rewards while participating.

[0488] Specific example

[0489] As a concrete example, a server might select both news articles generated by AI and those written by humans, and send them to a terminal. The terminal then presents the displayed articles to the user, who determines and selects which type of article it is. If the user's selection is correct, reward points calculated by the server are added to the user's account.

[0490] Example of a prompt

[0491] An example of input for a generative AI model is: "Classify the following news articles as either AI-generated or human-generated. Read the articles carefully and pay attention to the wording, structure, and logic used."

[0492] This system enables the efficient collection of identification data, contributing to further model improvement, while providing economic benefits to users through the identification of AI-generated and human-generated information.

[0493] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0494] Step 1:

[0495] The server selects information generated by artificial intelligence technology and information generated by humans from the database. During the selection process, it processes the AI-generated information using prompts directed to the AI ​​model. Based on this input, the server formats both types of information and prepares them for transmission to the terminal. This process generates an organized set of information as output.

[0496] Step 2:

[0497] The terminal receives and displays information sent from the server. The display uses an intuitive interface to make it easy for the user to identify the information. Using the information received as input, the terminal presents it clearly on the screen. This process outputs an operation screen for the user to make selections.

[0498] Step 3:

[0499] The user reviews the information displayed on the device and identifies whether it was generated by AI or by a human. The user's judgment is based on the style and content of the information. The user instructs the device to input their selection, and the data is output to the server in an appropriate format.

[0500] Step 4:

[0501] The server receives the user's selection results and aggregates them. The selection results, as input, are stored in a database, and aggregation calculations are performed to evaluate the identification accuracy. These aggregated results are recorded in the database as an indicator of identification accuracy.

[0502] Step 5:

[0503] The server calculates rewards based on the aggregated selection results, according to the user's identification accuracy. It calculates rewards based on the input aggregated data and outputs the results to the user's account. These rewards are added to the user's account as points or credits and provided to the user in a usable format.

[0504] (Application Example 1)

[0505] Next, we will explain Application Example 1. In the following explanation, 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."

[0506] In today's society, where systems capable of instantly determining the reliability and source of information are essential, there is a need to efficiently distinguish between information generated by artificial intelligence and information generated by humans, providing users with clear choices. However, current information distribution systems lack sufficient means to easily distinguish between AI-generated and manually generated information, posing a challenge as users may make decisions based on incorrect information.

[0507] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0508] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by a generation method and information generated by a human, from a content provision device to a user device; means for the user device to display the transmitted information and provide an operation screen for the user to select whether the information is generated by a generation method or by a human; and means for obtaining the user's selection results from the user device, aggregating the obtained selection results, and recording them in a storage device. This makes it possible for the user to determine the source of the information and receive rewards based on accurate selections.

[0509] A "content provision device" is a device that generates information and transmits it to a user's terminal.

[0510] A "generative method" refers to a method of creating information using artificial intelligence technology or by humans.

[0511] "Information" refers to data, including text, images, and audio, that is delivered from a content provider to a user's terminal.

[0512] A "user device" is a terminal device operated by a user to receive and display information.

[0513] An "operation screen" is an interface that allows a user to select or identify information.

[0514] "Aggregation" is a procedure for statistically processing acquired data and evaluating the trends and accuracy of the information.

[0515] A "storage device" is a device used to store data and information for the long term.

[0516] "Evaluation" is the process of determining the accuracy and performance of information identification based on the aggregated results.

[0517] "Specific information" refers to data that indicates the user's choices and their accuracy.

[0518] "Rewards" are values ​​given as compensation for users correctly identifying information.

[0519] An "application program" is software created to perform a specific function and provide a specific experience to the user.

[0520] This invention provides a system for identifying information generated by a generation method, which involves implementing a server that interacts with user devices that receive and present information. The server has the function of acquiring information generated by the generation method and information generated manually from a storage device and transmitting it to multiple user devices. This information includes text, images, audio, and the like.

[0521] The user device displays this information and provides a user-friendly interface (operation screen). Through this screen, the user can select whether the information is generated by a data generation method or by human input. The selected data is sent from the user device to the server, which then aggregates the selection results and records them in its storage device.

[0522] To evaluate the accuracy of information identification, the server calculates the accuracy rate based on the aggregated results. This utilizes database processing techniques and algorithms. The recorded data is anonymized and may be provided to third parties.

[0523] This entire process is carried out using cloud servers (such as Amazon Web Services and Google Cloud Platform), hardware such as smartphones and personal computers, database software (such as MySQL and MongoDB), and generative AI models.

[0524] A concrete example is a server that retrieves news articles generated by an AI model and delivers them to the user's device. The user reads the article and identifies the source of the information by choosing whether it was AI-generated or human-generated. The user is rewarded based on the accuracy of the identification result derived from this choice.

[0525] An example of a prompt message is, "Write a news article about a recent rainstorm that caused river flooding. Ensure it is detailed enough to be indistinguishable from a human-written article." In this way, the accuracy of AI-generated content improves, and more reliable information is provided.

[0526] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0527] Step 1:

[0528] The server uses a generative AI model to retrieve information generated from a text database using a generation method, as well as information created by humans. The input is a specified information type, and the output is the retrieved information. AI-generated information is obtained based on a specified prompt statement.

[0529] Step 2:

[0530] The server sends the acquired information to the user terminal. It receives the acquired information as input and sends the information to the user terminal as output. Data processing is performed to format the data so that the terminal can display the information correctly.

[0531] Step 3:

[0532] The terminal displays the received information and provides the user with an operation screen with choices. It receives information from the server as input and generates a user-display screen as output. Data is formatted to match the display format.

[0533] Step 4:

[0534] The user chooses whether the presented information is generated by a data generation method or by a human. The user makes a selection based on the terminal's options as input, and the result of that selection is generated as output. The user performs intuitive interface operations.

[0535] Step 5:

[0536] The terminal sends the user's selection results to the server. It receives the user's selection results as input and sends the results to the server as output. The selection data is formatted and appropriately packaged.

[0537] Step 6:

[0538] The server aggregates the received selection results and records them in storage. It receives selection results from terminals as input and records the aggregated results in a database as output. Statistical processing is performed on the database to analyze selection trends.

[0539] Step 7:

[0540] The server calculates the accuracy rate based on the aggregated results and calculates and notifies the user of the reward as needed. It receives the aggregated results as input and notifies the user of the calculated reward as output. Triggers for evaluating the reward data and adding points are set.

[0541] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0542] This invention is a system that improves the accuracy of information identification by applying artificial intelligence technology combined with an emotion engine. Furthermore, by considering the user's emotional state, it provides a form that enhances the user experience while facilitating the information identification process.

[0543] Overall system configuration

[0544] The server, acting as a content provider, transmits information generated using artificial intelligence technology and human-generated information, along with an emotion engine, to the user's terminal. The user's terminal presents this received information and also uses the emotion engine to collect the user's emotional data, which is then used in the identification process.

[0545] System operation

[0546] The device displays information on the provided interface and simultaneously uses its built-in emotion engine to recognize the user's emotional state. This emotional state includes the user's interests, attention span, and stress levels. Based on this emotional data, the device optimizes the order and format of content presentation to enable more efficient user identification.

[0547] Specific example

[0548] For example, the server selects both AI-generated and human-generated news article texts and sends them to the user's terminal. During this process, the terminal utilizes an emotion engine to analyze the user's subtle emotional responses as they review the information. If the user expresses discomfort with certain information, the terminal can change the way the information is presented or present different content to improve their experience. In this way, the entire system dynamically adapts to the user's emotional state during the process, providing an optimal user experience.

[0549] This invention aims to improve user interaction from a scientific and psychological perspective, going beyond mere information identification, by incorporating an emotion engine. This implementation is expected to lead to more effective and efficient data collection and improved user satisfaction.

[0550] The following describes the processing flow.

[0551] Step 1:

[0552] The server randomly selects information generated by artificial intelligence technology and information generated by humans from the database and sends it to the user's terminal. This selection is made considering the diversity of the information and the difficulty of identification.

[0553] Step 2:

[0554] The device displays the received information and simultaneously activates an emotion engine to perform facial recognition and voice analysis of the user. This allows it to acquire emotional data from the process of the user viewing and reacting to the information.

[0555] Step 3:

[0556] The user reviews the displayed information, determines whether it is AI-generated or human-generated, and makes a selection through the user interface. The emotion engine also responds to this selection process, analyzing the user's facial expressions and tone of voice during the selection.

[0557] Step 4:

[0558] The device sends emotional data acquired by the emotion engine to the server simultaneously with the user's selection. This data includes the user's psychological state and stress level at the time of selection.

[0559] Step 5:

[0560] The server calculates the accuracy rate of the selection based on the received selection results and sentiment data, and provides appropriate feedback to the user. If necessary, sentiment information is used as data to adjust the order and format of information presentation in the next session.

[0561] Step 6:

[0562] The server evaluates the user's identification accuracy based on the accuracy rate, determines the reward based on the result, and adds it to the user's account. It also anonymizes sentiment data and processes it for provision to a third-party organization.

[0563] Thus, the present invention realizes a system that optimizes the user experience while refining the information identification process by utilizing the user's emotional state.

[0564] (Example 2)

[0565] Next, we will describe Example 2. 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."

[0566] In recent years, the increasing diversity and volume of information has made it difficult for users to quickly and accurately select the information they need. Furthermore, ignoring the impact of information on users' emotional states presents a challenge in providing effective information. Against this backdrop, there is a need to develop information presentation methods that take users' emotions into consideration.

[0567] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0568] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for recognizing the user's emotional state using an emotion analysis device built into the user terminal and dynamically optimizing the presented information; and means for aggregating the selection results and emotion data acquired from the user terminal and storing them in a data recording device. This enables efficient and highly accurate information selection adapted to the user's emotions.

[0569] A "content provision device" is a device that collects information generated using artificial intelligence technology and information generated by humans, and transmits it to the user's terminal.

[0570] A "user terminal" is a device that receives information from a server and presents it to the user, and has the function of recognizing the user's emotional state through a built-in emotion analysis device.

[0571] "Artificial intelligence technology" refers to technologies that analyze data, recognize patterns, and improve the accuracy of information generation and processing.

[0572] An "emotion analysis device" is a technological device for recognizing and evaluating a user's emotional state, and it has the function of determining emotions using the user's facial expressions and physiological data.

[0573] "Selection result" refers to the content that the user selected from the information presented on their device.

[0574] "Emotional data" refers to information about the user's emotional state and is collected by an emotion analysis device.

[0575] A "data recording device" is a device for collecting and storing selection results and emotional data.

[0576] "Anonymization" is the process of removing elements that identify individuals from collected data and making it available to third parties.

[0577] This invention is a system for improving information identification accuracy and user experience by taking into account the emotional state of the user. Specifically, it consists of a server which is a content provider, a user terminal which receives and displays information, and a device which performs emotion analysis.

[0578] The server collects news and various content from sources such as the internet and databases. This collected information is then restructured or summarized using generative AI models. Natural language processing techniques are utilized in this process. The generated information is integrated with human-generated information and optimized to suit the user's interests.

[0579] The terminal displays information transmitted from the server to the user. The terminal also has a built-in emotion analyzer that uses cameras and sensors to determine the user's emotions in real time. This emotion data includes, for example, facial expressions, eye movements, and voice tone. The terminal analyzes this data to evaluate how the user feels about the information. Based on this evaluation, it improves the user experience by changing or adjusting the way the information is presented.

[0580] Users can select information on the device and provide feedback. This feedback is stored in a data recording device and used to improve future information provision. For example, if a user shows interest in a particular news topic, the device can display more information related to it.

[0581] As a concrete example, by providing the server with the prompt message, "Present the latest technology news tailored to the user's interests," appropriate information is selected and delivered to the user via the terminal. In this way, the system can achieve more effective information selection and presentation that is in line with the user's interests and emotions.

[0582] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0583] Step 1:

[0584] The server collects news articles and related content from the internet and databases. It is given URLs of content sources and database queries as input, and the output is the collected raw information data. This step specifically involves web scraping and API access.

[0585] Step 2:

[0586] The server processes the collected information using a generative AI model to generate new information. Raw data is provided as input, and summaries or newly generated information are obtained as output. This process specifically includes summarization and article generation using natural language processing algorithms.

[0587] Step 3:

[0588] The server integrates the generated information with the human-generated information and sends it to the user's terminal. The input consists of generated information and human-generated information, and the output is a composite information ready for transmission. This step includes tagging the information, evaluating its importance, and formatting the data in a format suitable for the target user.

[0589] Step 4:

[0590] The terminal receives information sent from the server and displays it to the user. The input is the transmitted composite information, and the output is information visually presented to the user. Specific operations include information rendering using a GUI and the application of responsive design.

[0591] Step 5:

[0592] The device uses a built-in emotion analyzer to recognize the user's emotional state in real time while they are viewing information. The user's biometric data and facial expressions are provided as input, and quantified emotion data is obtained as output. Specific operations include data collection using cameras, microphones, and sensors, and emotion analysis using machine learning.

[0593] Step 6:

[0594] The device dynamically optimizes how information is presented based on emotional data to improve the user experience. Emotional data is provided as input, and optimized information presentation is obtained as output. Specific actions include changing the presentation order, highlighting content, and adjusting the visual design.

[0595] Step 7:

[0596] Users select information based on their interests and reactions, and provide feedback via their device. The input is user selection data, and the output is improvement suggestions based on that data. Specific actions include selection via clicks and taps on the user interface, and the use of feedback buttons.

[0597] Step 8:

[0598] The terminal collects user selection results and sentiment data and sends it to the server. The input is selection and sentiment data, and the output is a data packet ready for transmission. Secure data transfer using a communication protocol is a concrete operation.

[0599] Step 9:

[0600] The server stores the received data in a data recording device and uses it for aggregation and analysis. The input is the transmitted data packets, and the output is the accumulated database. Specific operations include writing to the database and aggregation using statistical analysis tools.

[0601] (Application Example 2)

[0602] Next, we will explain application example 2. In the following explanation, 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."

[0603] In modern information delivery, it is crucial to improve user satisfaction with the information they receive. Especially in an increasingly diverse information landscape, there is a need to dynamically adjust the order and format of information delivery to best suit the user. Furthermore, distributing information uniformly without considering user emotions can fail to capture user interest or even cause stress. The challenge lies in resolving these issues and providing a better user experience.

[0604] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0605] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for displaying the transmitted information on the user terminal and providing an operation screen for the user to select whether the information is generated by artificial intelligence technology or by humans; means for obtaining the user's selection results from the user terminal, aggregating the obtained selection results, and recording them in a database; and means for the user terminal to analyze the user's emotional state using emotion recognition technology and dynamically optimizing the order in which the information is presented based on that data. This makes it possible to provide information optimally according to the user's emotional state.

[0606] A "content provider" is a device that transmits information to a user's terminal and plays the role of providing multiple pieces of content, including information generated by artificial intelligence technology and by humans.

[0607] "Artificial intelligence technology" refers to technologies that use computational techniques, including machine learning and natural language processing, to mimic human intellectual work and perform information generation and analysis.

[0608] A "user terminal" refers to a device used to receive and display information transmitted from a content provider, and includes electronic devices such as smartphones and computers.

[0609] An "operation screen" is an interface that allows users to select, input, or confirm information through their device.

[0610] "Emotion recognition technology" is a technology that identifies a user's inner emotional state by analyzing their facial expressions and behavior.

[0611] "Presentation order" refers to the sequence and arrangement of information displayed to the user, and is an element that is dynamically adjusted based on the user's emotions and preferences.

[0612] A "database" is a system for efficiently storing, managing, and retrieving collected user selection results and sentiment data.

[0613] In order to implement this invention, the entire content delivery system must operate in a coordinated manner. The details are described below.

[0614] First, the server, acting as a content provider, scans information generated by artificial intelligence technology and information generated by humans, and transmits it to the user's terminal. The server transmits this information using standard data protocols, but it is preferable to use a cloud service with superior processing capabilities (e.g., Amazon Web Services or Google Cloud Platform).

[0615] The terminal is a user device such as a smartphone or tablet that displays received information on its screen. Furthermore, the terminal incorporates emotion recognition technology that analyzes the user's facial expressions and actions to identify the user's emotional state. High-precision cameras and emotion recognition software such as Microsoft Emotion API and Google Cloud Vision are used for emotion recognition processing.

[0616] User emotional state data is dynamically processed on the device to determine the optimal content presentation order for each individual user. For example, if a user is determined to be relaxed, detailed articles will be prioritized, while shorter content can be selected if the user is experiencing high stress levels.

[0617] Furthermore, a real-time data processing framework (e.g., Apache Kafka) is used to collect and record user selections in a database. Based on this data, a reward feedback system can be implemented to evaluate the accuracy of selections and improve user satisfaction.

[0618] As a concrete example, let's consider a scenario where a user is using a news app. If the app detects a happy expression on the user's face while they are reading a news article, it will then present articles in a similar category. Furthermore, if the user is struggling to choose an article for an extended period, it will offer simpler options to improve the user experience.

[0619] An example of a prompt message might be: "The user is currently viewing a news article. Use real-time sentiment data to prioritize the articles viewed and optimize the news experience. Consider the user's interests, attention span, and stress level."

[0620] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0621] Step 1:

[0622] The server collects multiple pieces of information, including artificial intelligence and human-generated data, and transmits this information to the user's terminal. The input is the information database maintained by the server. The output is the list of information sent to the user's terminal. This forms the basis for the user to access the latest information.

[0623] Step 2:

[0624] The terminal displays the received information and provides a screen that allows the user to select whether the information is generated by artificial intelligence or by a human. The input is the information sent from the server in step 1. The output is the user's selection result. Based on this selection result, the terminal understands the user's information preferences.

[0625] Step 3:

[0626] The device uses built-in emotion recognition technology to analyze the user's emotional state in real time. Inputs include the user's facial expressions and operation patterns. Outputs include the user's emotional data, such as interest levels and stress levels. The device uses this data to prepare for the next processing step.

[0627] Step 4:

[0628] The device dynamically optimizes the information presentation order by combining emotional data and the user's selection results. The input is the selection result from step 2 and the emotional data from step 3. The output is the optimized information presentation order. In this step, a generative AI model is used to formulate a presentation order that is adapted to various scenarios.

[0629] Step 5:

[0630] Based on the presented information, users view information that matches their preferences. The input is the information presentation order optimized in step 4. The output is user behavior data, recording how the user reacted to the information. The data obtained in this step contributes to further improving the user experience.

[0631] Step 6:

[0632] The terminal aggregates all selection results and sentiment data, anonymizes them, and records them in a database. The input is the result data from steps 2, 3, and 5. The output is the anonymized data stored in the database. This data is used for subsequent analysis and system improvement.

[0633] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0634] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0635] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0636] [Fourth Embodiment]

[0637] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0638] As shown in Figure 7, the 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.

[0639] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0640] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0641] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0642] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0643] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0644] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0645] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0646] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0647] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0648] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0649] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0650] This invention is a system for distinguishing between information generated by artificial intelligence technology and information generated by humans, and is implemented in a form in which a content provider, a user terminal, and a server work in cooperation with each other.

[0651] Overall system configuration

[0652] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. The user's terminal displays the received information and provides an operation screen for the user to identify the information. The user determines whether the information is AI-generated or human-generated and selects the result.

[0653] System operation

[0654] The server receives the user's selection data, aggregates it, and records it in a database. This aggregated result serves as an indicator of how accurately each piece of information was identified. Furthermore, the server calculates a reward based on the accuracy rate and provides it to the user. The reward is added to the user's account as points or credits.

[0655] Specific example

[0656] For example, the server selects both news article texts generated by AI and those written by human journalists and sends them to the user's terminal. The terminal displays the article, and the user selects which author created it. Once the user enters their selection into the terminal, the data is immediately sent to the server. The server aggregates this data and evaluates the accuracy of the identification. If the user's selection is correct, the user is given additional rewards based on their accuracy.

[0657] The purpose of this system is to efficiently collect identification data of artificial intelligence technology and human-generated information, thereby providing economic benefits to users while supplying data to third-party organizations and contributing to the development of better generative models.

[0658] The following describes the processing flow.

[0659] Step 1:

[0660] The server randomly retrieves information from the database, including both AI-generated and human-generated information, and then selects content to send to the user. The information to be sent is determined based on predefined criteria.

[0661] Step 2:

[0662] The server transmits the selected information to the user's terminal and provides an operational interface for displaying and identifying the information.

[0663] Step 3:

[0664] The terminal displays the received content to the user and simultaneously provides an operation screen where the user can select whether the information was generated by an AI or by a human.

[0665] Step 4:

[0666] The user reviews the displayed information, determines its source, and makes a selection. This selection is made through the user interface.

[0667] Step 5:

[0668] The user's selection results are sent to the server by the device. This transmission includes the selected options and related metadata.

[0669] Step 6:

[0670] The server records the received selection results in a database and further calculates the accuracy rate to evaluate the user's identification accuracy.

[0671] Step 7:

[0672] The server calculates rewards based on the user's accuracy rate, according to specified criteria. The calculated rewards are added to the user's account.

[0673] Step 8:

[0674] The server anonymizes the aggregated data as needed and organizes it as data. The organized data is later provided to a third-party organization and used for research and development of generative AI technology.

[0675] (Example 1)

[0676] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0677] In recent years, advancements in artificial intelligence technology have created a problem where it is difficult to distinguish between information generated by AI and information generated by humans. Furthermore, there is a need to improve the accuracy and efficiency of providing rewards to users through this identification process. Additionally, there is a need for a secure method of supplying identification results to third-party organizations.

[0678] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0679] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal; means for acquiring the user's selection results, aggregating the acquired selection results, and recording them on a recording medium; and means for evaluating the identification accuracy based on the aggregated results. This enables effective identification of AI-generated information and human-generated information, provision of rewards based on the results, and secure supply of the identification results.

[0680] A "content provision device" is a device that has the function of collecting information generated by artificial intelligence technology or information generated by humans and transmitting it to the user's terminal.

[0681] "Artificial intelligence technology" refers to technologies that enable computer systems to mimic human intellectual activity and to generate and analyze information.

[0682] A "user terminal" is a device that receives information transmitted from a server and provides an interface that allows the user to manipulate and identify that information.

[0683] "Discrimination accuracy" is a measure used to evaluate how correctly users were able to distinguish whether information was generated by artificial intelligence or by humans.

[0684] A "recording medium" is a technology or device used to hold data and store it in a format that can be accessed later.

[0685] An "external organization" is an organization or group that exists outside the system in order to provide or analyze information.

[0686] This invention is a system that efficiently distinguishes between information generated by artificial intelligence technology and information generated by humans. This system mainly consists of a server, a user terminal, and a content delivery device.

[0687] Server Role

[0688] The server functions as a content provider, selecting information generated by artificial intelligence technology and human-generated information from a database and sending it to the user's terminal. Information is generated using a generation AI model, such as news articles and blog posts. The server also aggregates the identification results submitted by users and calculates the identification accuracy based on these results. This information is used to calculate rewards, which are provided to users as points or credits. The server software used is a solution that supports advanced database management and network communication.

[0689] Terminal role

[0690] The user terminal is responsible for displaying information received from the server. The terminal presents the information in a user-friendly format and provides an interface to help users identify whether the information is AI-generated or human-generated. The terminal's software is designed to facilitate smooth interface display, data input, and transmission.

[0691] User roles

[0692] Users review the displayed information and identify whether it was AI-generated or human-generated. The identification result is sent from the device to the server, after which a reward is provided. This allows users to earn rewards while participating.

[0693] Specific example

[0694] As a concrete example, a server might select both news articles generated by AI and those written by humans, and send them to a terminal. The terminal then presents the displayed articles to the user, who determines and selects which type of article it is. If the user's selection is correct, reward points calculated by the server are added to the user's account.

[0695] Example of a prompt

[0696] An example of input for a generative AI model is: "Classify the following news articles as either AI-generated or human-generated. Read the articles carefully and pay attention to the wording, structure, and logic used."

[0697] This system enables the efficient collection of identification data, contributing to further model improvement, while providing economic benefits to users through the identification of AI-generated and human-generated information.

[0698] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0699] Step 1:

[0700] The server selects information generated by artificial intelligence technology and information generated by humans from the database. During the selection process, it processes the AI-generated information using prompts directed to the AI ​​model. Based on this input, the server formats both types of information and prepares them for transmission to the terminal. This process generates an organized set of information as output.

[0701] Step 2:

[0702] The terminal receives and displays information sent from the server. The display uses an intuitive interface to make it easy for the user to identify the information. Using the information received as input, the terminal presents it clearly on the screen. This process outputs an operation screen for the user to make selections.

[0703] Step 3:

[0704] The user reviews the information displayed on the device and identifies whether it was generated by AI or by a human. The user's judgment is based on the style and content of the information. The user instructs the device to input their selection, and the data is output to the server in an appropriate format.

[0705] Step 4:

[0706] The server receives the user's selection results and aggregates them. The selection results, as input, are stored in a database, and aggregation calculations are performed to evaluate the identification accuracy. These aggregated results are recorded in the database as an indicator of identification accuracy.

[0707] Step 5:

[0708] The server calculates rewards based on the aggregated selection results, according to the user's identification accuracy. It calculates rewards based on the input aggregated data and outputs the results to the user's account. These rewards are added to the user's account as points or credits and provided to the user in a usable format.

[0709] (Application Example 1)

[0710] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0711] In today's society, where systems capable of instantly determining the reliability and source of information are essential, there is a need to efficiently distinguish between information generated by artificial intelligence and information generated by humans, providing users with clear choices. However, current information distribution systems lack sufficient means to easily distinguish between AI-generated and manually generated information, posing a challenge as users may make decisions based on incorrect information.

[0712] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0713] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by a generation method and information generated by a human, from a content provision device to a user device; means for the user device to display the transmitted information and provide an operation screen for the user to select whether the information is generated by a generation method or by a human; and means for obtaining the user's selection results from the user device, aggregating the obtained selection results, and recording them in a storage device. This makes it possible for the user to determine the source of the information and receive rewards based on accurate selections.

[0714] A "content provision device" is a device that generates information and transmits it to a user's terminal.

[0715] A "generative method" refers to a method of creating information using artificial intelligence technology or by humans.

[0716] "Information" refers to data, including text, images, and audio, that is delivered from a content provider to a user's terminal.

[0717] A "user device" is a terminal device operated by a user to receive and display information.

[0718] An "operation screen" is an interface that allows a user to select or identify information.

[0719] "Aggregation" is a procedure for statistically processing acquired data and evaluating the trends and accuracy of the information.

[0720] A "storage device" is a device used to store data and information for the long term.

[0721] "Evaluation" is the process of determining the accuracy and performance of information identification based on the aggregated results.

[0722] "Specific information" refers to data that indicates the user's choices and their accuracy.

[0723] "Rewards" are values ​​given as compensation for users correctly identifying information.

[0724] An "application program" is software created to perform a specific function and provide a specific experience to the user.

[0725] This invention provides a system for identifying information generated by a generation method, which involves implementing a server that interacts with user devices that receive and present information. The server has the function of acquiring information generated by the generation method and information generated manually from a storage device and transmitting it to multiple user devices. This information includes text, images, audio, and the like.

[0726] The user device displays this information and provides a user-friendly interface (operation screen). Through this screen, the user can select whether the information is generated by a data generation method or by human input. The selected data is sent from the user device to the server, which then aggregates the selection results and records them in its storage device.

[0727] To evaluate the accuracy of information identification, the server calculates the accuracy rate based on the aggregated results. This utilizes database processing techniques and algorithms. The recorded data is anonymized and may be provided to third parties.

[0728] This entire process is carried out using cloud servers (such as Amazon Web Services and Google Cloud Platform), hardware such as smartphones and personal computers, database software (such as MySQL and MongoDB), and generative AI models.

[0729] A concrete example is a server that retrieves news articles generated by an AI model and delivers them to the user's device. The user reads the article and identifies the source of the information by choosing whether it was AI-generated or human-generated. The user is rewarded based on the accuracy of the identification result derived from this choice.

[0730] An example of a prompt message is, "Write a news article about a recent rainstorm that caused river flooding. Ensure it is detailed enough to be indistinguishable from a human-written article." In this way, the accuracy of AI-generated content improves, and more reliable information is provided.

[0731] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0732] Step 1:

[0733] The server uses a generative AI model to retrieve information generated from a text database using a generation method, as well as information created by humans. The input is a specified information type, and the output is the retrieved information. AI-generated information is obtained based on a specified prompt statement.

[0734] Step 2:

[0735] The server sends the acquired information to the user terminal. It receives the acquired information as input and sends the information to the user terminal as output. Data processing is performed to format the data so that the terminal can display the information correctly.

[0736] Step 3:

[0737] The terminal displays the received information and provides the user with an operation screen with choices. It receives information from the server as input and generates a user-display screen as output. Data is formatted to match the display format.

[0738] Step 4:

[0739] The user chooses whether the presented information is generated by a data generation method or by a human. The user makes a selection based on the terminal's options as input, and the result of that selection is generated as output. The user performs intuitive interface operations.

[0740] Step 5:

[0741] The terminal sends the user's selection results to the server. It receives the user's selection results as input and sends the results to the server as output. The selection data is formatted and appropriately packaged.

[0742] Step 6:

[0743] The server aggregates the received selection results and records them in storage. It receives selection results from terminals as input and records the aggregated results in a database as output. Statistical processing is performed on the database to analyze selection trends.

[0744] Step 7:

[0745] The server calculates the accuracy rate based on the aggregated results and calculates and notifies the user of the reward as needed. It receives the aggregated results as input and notifies the user of the calculated reward as output. Triggers for evaluating the reward data and adding points are set.

[0746] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0747] This invention is a system that improves the accuracy of information identification by applying artificial intelligence technology combined with an emotion engine. Furthermore, by considering the user's emotional state, it provides a form that enhances the user experience while facilitating the information identification process.

[0748] Overall system configuration

[0749] The server, acting as a content provider, transmits information generated using artificial intelligence technology and human-generated information, along with an emotion engine, to the user's terminal. The user's terminal presents this received information and also uses the emotion engine to collect the user's emotional data, which is then used in the identification process.

[0750] System operation

[0751] The device displays information on the provided interface and simultaneously uses its built-in emotion engine to recognize the user's emotional state. This emotional state includes the user's interests, attention span, and stress levels. Based on this emotional data, the device optimizes the order and format of content presentation to enable more efficient user identification.

[0752] Specific example

[0753] For example, the server selects both AI-generated and human-generated news article texts and sends them to the user's terminal. During this process, the terminal utilizes an emotion engine to analyze the user's subtle emotional responses as they review the information. If the user expresses discomfort with certain information, the terminal can change the way the information is presented or present different content to improve their experience. In this way, the entire system dynamically adapts to the user's emotional state during the process, providing an optimal user experience.

[0754] This invention aims to improve user interaction from a scientific and psychological perspective, going beyond mere information identification, by incorporating an emotion engine. This implementation is expected to lead to more effective and efficient data collection and improved user satisfaction.

[0755] The following describes the processing flow.

[0756] Step 1:

[0757] The server randomly selects information generated by artificial intelligence technology and information generated by humans from the database and sends it to the user's terminal. This selection is made considering the diversity of the information and the difficulty of identification.

[0758] Step 2:

[0759] The device displays the received information and simultaneously activates an emotion engine to perform facial recognition and voice analysis of the user. This allows it to acquire emotional data from the process of the user viewing and reacting to the information.

[0760] Step 3:

[0761] The user reviews the displayed information, determines whether it is AI-generated or human-generated, and makes a selection through the user interface. The emotion engine also responds to this selection process, analyzing the user's facial expressions and tone of voice during the selection.

[0762] Step 4:

[0763] The device sends emotional data acquired by the emotion engine to the server simultaneously with the user's selection. This data includes the user's psychological state and stress level at the time of selection.

[0764] Step 5:

[0765] The server calculates the accuracy rate of the selection based on the received selection results and sentiment data, and provides appropriate feedback to the user. If necessary, sentiment information is used as data to adjust the order and format of information presentation in the next session.

[0766] Step 6:

[0767] The server evaluates the user's identification accuracy based on the accuracy rate, determines the reward based on the result, and adds it to the user's account. It also anonymizes sentiment data and processes it for provision to a third-party organization.

[0768] Thus, the present invention realizes a system that optimizes the user experience while refining the information identification process by utilizing the user's emotional state.

[0769] (Example 2)

[0770] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0771] In recent years, the increasing diversity and volume of information has made it difficult for users to quickly and accurately select the information they need. Furthermore, ignoring the impact of information on users' emotional states presents a challenge in providing effective information. Against this backdrop, there is a need to develop information presentation methods that take users' emotions into consideration.

[0772] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0773] In this invention, the server includes means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for recognizing the user's emotional state using an emotion analysis device built into the user terminal and dynamically optimizing the presented information; and means for aggregating the selection results and emotion data acquired from the user terminal and storing them in a data recording device. This enables efficient and highly accurate information selection adapted to the user's emotions.

[0774] A "content provision device" is a device that collects information generated using artificial intelligence technology and information generated by humans, and transmits it to the user's terminal.

[0775] A "user terminal" is a device that receives information from a server and presents it to the user, and has the function of recognizing the user's emotional state through a built-in emotion analysis device.

[0776] "Artificial intelligence technology" refers to technologies that analyze data, recognize patterns, and improve the accuracy of information generation and processing.

[0777] An "emotion analysis device" is a technological device for recognizing and evaluating a user's emotional state, and it has the function of determining emotions using the user's facial expressions and physiological data.

[0778] "Selection result" refers to the content that the user selected from the information presented on their device.

[0779] "Emotional data" refers to information about the user's emotional state and is collected by an emotion analysis device.

[0780] A "data recording device" is a device for collecting and storing selection results and emotional data.

[0781] "Anonymization" is the process of removing elements that identify individuals from collected data and making it available to third parties.

[0782] This invention is a system for improving information identification accuracy and user experience by taking into account the emotional state of the user. Specifically, it consists of a server which is a content provider, a user terminal which receives and displays information, and a device which performs emotion analysis.

[0783] The server collects news and various content from sources such as the internet and databases. This collected information is then restructured or summarized using generative AI models. Natural language processing techniques are utilized in this process. The generated information is integrated with human-generated information and optimized to suit the user's interests.

[0784] The terminal displays information transmitted from the server to the user. The terminal also has a built-in emotion analyzer that uses cameras and sensors to determine the user's emotions in real time. This emotion data includes, for example, facial expressions, eye movements, and voice tone. The terminal analyzes this data to evaluate how the user feels about the information. Based on this evaluation, it improves the user experience by changing or adjusting the way the information is presented.

[0785] Users can select information on the device and provide feedback. This feedback is stored in a data recording device and used to improve future information provision. For example, if a user shows interest in a particular news topic, the device can display more information related to it.

[0786] As a concrete example, by providing the server with the prompt message, "Present the latest technology news tailored to the user's interests," appropriate information is selected and delivered to the user via the terminal. In this way, the system can achieve more effective information selection and presentation that is in line with the user's interests and emotions.

[0787] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0788] Step 1:

[0789] The server collects news articles and related content from the internet and databases. It is given URLs of content sources and database queries as input, and the output is the collected raw information data. This step specifically involves web scraping and API access.

[0790] Step 2:

[0791] The server processes the collected information using a generative AI model to generate new information. Raw data is provided as input, and summaries or newly generated information are obtained as output. This process specifically includes summarization and article generation using natural language processing algorithms.

[0792] Step 3:

[0793] The server integrates the generated information with the human-generated information and sends it to the user's terminal. The input consists of generated information and human-generated information, and the output is a composite information ready for transmission. This step includes tagging the information, evaluating its importance, and formatting the data in a format suitable for the target user.

[0794] Step 4:

[0795] The terminal receives information sent from the server and displays it to the user. The input is the transmitted composite information, and the output is information visually presented to the user. Specific operations include information rendering using a GUI and the application of responsive design.

[0796] Step 5:

[0797] The device uses a built-in emotion analyzer to recognize the user's emotional state in real time while they are viewing information. The user's biometric data and facial expressions are provided as input, and quantified emotion data is obtained as output. Specific operations include data collection using cameras, microphones, and sensors, and emotion analysis using machine learning.

[0798] Step 6:

[0799] The device dynamically optimizes how information is presented based on emotional data to improve the user experience. Emotional data is provided as input, and optimized information presentation is obtained as output. Specific actions include changing the presentation order, highlighting content, and adjusting the visual design.

[0800] Step 7:

[0801] Users select information based on their interests and reactions, and provide feedback via their device. The input is user selection data, and the output is improvement suggestions based on that data. Specific actions include selection via clicks and taps on the user interface, and the use of feedback buttons.

[0802] Step 8:

[0803] The terminal collects user selection results and sentiment data and sends it to the server. The input is selection and sentiment data, and the output is a data packet ready for transmission. Secure data transfer using a communication protocol is a concrete operation.

[0804] Step 9:

[0805] The server stores the received data in a data recording device and uses it for aggregation and analysis. The input is the transmitted data packets, and the output is the accumulated database. Specific operations include writing to the database and aggregation using statistical analysis tools.

[0806] (Application Example 2)

[0807] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0808] In modern information delivery, it is crucial to improve user satisfaction with the information they receive. Especially in an increasingly diverse information landscape, there is a need to dynamically adjust the order and format of information delivery to best suit the user. Furthermore, distributing information uniformly without considering user emotions can fail to capture user interest or even cause stress. The challenge lies in resolving these issues and providing a better user experience.

[0809] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0810] In this invention, the server includes means for transmitting a plurality of pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provisioning device to a user terminal; means for displaying the transmitted information on the user terminal and providing an operation screen for the user to select whether the information is generated by artificial intelligence technology or by humans; means for obtaining the user's selection results from the user terminal, aggregating the obtained selection results, and recording them in a database; and means for the user terminal to analyze the user's emotional state using emotion recognition technology and dynamically optimizing the order in which the information is presented based on that data. This makes it possible to provide information optimally according to the user's emotional state.

[0811] A "content provider" is a device that transmits information to a user's terminal and plays the role of providing multiple pieces of content, including information generated by artificial intelligence technology and by humans.

[0812] "Artificial intelligence technology" refers to technologies that use computational techniques, including machine learning and natural language processing, to mimic human intellectual work and perform information generation and analysis.

[0813] A "user terminal" refers to a device used to receive and display information transmitted from a content provider, and includes electronic devices such as smartphones and computers.

[0814] An "operation screen" is an interface that allows users to select, input, or confirm information through their device.

[0815] "Emotion recognition technology" is a technology that identifies a user's inner emotional state by analyzing their facial expressions and behavior.

[0816] "Presentation order" refers to the sequence and arrangement of information displayed to the user, and is an element that is dynamically adjusted based on the user's emotions and preferences.

[0817] A "database" is a system for efficiently storing, managing, and retrieving collected user selection results and sentiment data.

[0818] In order to implement this invention, the entire content delivery system must operate in a coordinated manner. The details are described below.

[0819] First, the server, acting as a content provider, scans information generated by artificial intelligence technology and information generated by humans, and transmits it to the user's terminal. The server transmits this information using standard data protocols, but it is preferable to use a cloud service with superior processing capabilities (e.g., Amazon Web Services or Google Cloud Platform).

[0820] The terminal is a user device such as a smartphone or tablet that displays received information on its screen. Furthermore, the terminal incorporates emotion recognition technology that analyzes the user's facial expressions and actions to identify the user's emotional state. High-precision cameras and emotion recognition software such as Microsoft Emotion API and Google Cloud Vision are used for emotion recognition processing.

[0821] User emotional state data is dynamically processed on the device to determine the optimal content presentation order for each individual user. For example, if a user is determined to be relaxed, detailed articles will be prioritized, while shorter content can be selected if the user is experiencing high stress levels.

[0822] Furthermore, a real-time data processing framework (e.g., Apache Kafka) is used to collect and record user selections in a database. Based on this data, a reward feedback system can be implemented to evaluate the accuracy of selections and improve user satisfaction.

[0823] As a concrete example, let's consider a scenario where a user is using a news app. If the app detects a happy expression on the user's face while they are reading a news article, it will then present articles in a similar category. Furthermore, if the user is struggling to choose an article for an extended period, it will offer simpler options to improve the user experience.

[0824] An example of a prompt message might be: "The user is currently viewing a news article. Use real-time sentiment data to prioritize the articles viewed and optimize the news experience. Consider the user's interests, attention span, and stress level."

[0825] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0826] Step 1:

[0827] The server collects multiple pieces of information, including artificial intelligence and human-generated data, and transmits this information to the user's terminal. The input is the information database maintained by the server. The output is the list of information sent to the user's terminal. This forms the basis for the user to access the latest information.

[0828] Step 2:

[0829] The terminal displays the received information and provides a screen that allows the user to select whether the information is generated by artificial intelligence or by a human. The input is the information sent from the server in step 1. The output is the user's selection result. Based on this selection result, the terminal understands the user's information preferences.

[0830] Step 3:

[0831] The device uses built-in emotion recognition technology to analyze the user's emotional state in real time. Inputs include the user's facial expressions and operation patterns. Outputs include the user's emotional data, such as interest levels and stress levels. The device uses this data to prepare for the next processing step.

[0832] Step 4:

[0833] The device dynamically optimizes the information presentation order by combining emotional data and the user's selection results. The input is the selection result from step 2 and the emotional data from step 3. The output is the optimized information presentation order. In this step, a generative AI model is used to formulate a presentation order that is adapted to various scenarios.

[0834] Step 5:

[0835] Based on the presented information, users view information that matches their preferences. The input is the information presentation order optimized in step 4. The output is user behavior data, recording how the user reacted to the information. The data obtained in this step contributes to further improving the user experience.

[0836] Step 6:

[0837] The terminal aggregates all selection results and sentiment data, anonymizes them, and records them in a database. The input is the result data from steps 2, 3, and 5. The output is the anonymized data stored in the database. This data is used for subsequent analysis and system improvement.

[0838] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0839] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet Search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0840] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0841] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0842] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0843] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0844] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0845] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0846] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0847] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0848] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0849] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0850] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0851] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0852] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0853] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0854] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0855] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0856] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0857] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0858] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0859] The following is further disclosed regarding the embodiments described above.

[0860] (Claim 1)

[0861] A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal,

[0862] A means for a user terminal to display the transmitted information and to provide an operation screen for the user to select whether the information is generated by artificial intelligence technology or by human generation,

[0863] A means of obtaining the user's selection results from the user's terminal, aggregating the obtained selection results, and recording them in a database,

[0864] A system that includes this.

[0865] (Claim 2)

[0866] The system according to claim 1, comprising means for determining the accuracy rate based on the aggregated selection results and providing a reward to the user.

[0867] (Claim 3)

[0868] The system according to claim 1, comprising means for anonymizing recorded selection results and providing them to a third-party organization.

[0869] "Example 1"

[0870] (Claim 1)

[0871] A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal,

[0872] A means for a user terminal to display the transmitted information and to provide an operation screen for the user to select whether the information is generated by artificial intelligence technology or by human generation,

[0873] A means for obtaining the user's selection results, aggregating the obtained selection results, and recording them on a recording medium,

[0874] A means for evaluating the identification accuracy based on the aggregated results,

[0875] A system that includes this.

[0876] (Claim 2)

[0877] The system according to claim 1, comprising means for determining the identification accuracy based on the aggregated selection results and providing a reward to the user.

[0878] (Claim 3)

[0879] The system according to claim 1, comprising means for anonymizing recorded selection results and supplying them to an external organization.

[0880] "Application Example 1"

[0881] (Claim 1)

[0882] A means for transmitting multiple pieces of information, including information generated by a generation method and information generated by a human, from a content provision device to a user device,

[0883] The device provides means for displaying the transmitted information and for the user to select whether the information was generated by a generation method or by human generation,

[0884] A means for obtaining the user's selection results from the device being used, aggregating the obtained selection results, and recording them in a storage device,

[0885] A means of evaluating recorded selection results and rewarding users based on specific information,

[0886] A means including an application program that enables a user to have a specific experience in identifying information,

[0887] A system that includes this.

[0888] (Claim 2)

[0889] The system according to claim 1, comprising means for determining the accuracy rate based on the aggregated selection results and providing compensation.

[0890] (Claim 3)

[0891] The system according to claim 1, comprising means for providing the recorded selection results to a third party in an inidentifiable manner.

[0892] "Example 2 of combining an emotion engine"

[0893] (Claim 1)

[0894] A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal,

[0895] The user terminal displays the transmitted information and uses a built-in emotion analysis device to recognize the user's emotional state and dynamically optimize the presented information.

[0896] A means for obtaining the user's selection results from the user's terminal, aggregating the obtained selection results and sentiment data, and storing them in a data recording device,

[0897] A system that includes this.

[0898] (Claim 2)

[0899] The system according to claim 1, comprising means for performing an evaluation based on aggregated selection results and sentiment data, and providing a reward to the user.

[0900] (Claim 3)

[0901] The system according to claim 1, comprising means for anonymizing stored selection results and sentiment data and providing them to a third-party organization.

[0902] "Application example 2 when combining with an emotional engine"

[0903] (Claim 1)

[0904] A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal,

[0905] A means for a user terminal to display the transmitted information and to provide an operation screen for the user to select whether the information is generated by artificial intelligence technology or by human generation,

[0906] A means of obtaining the user's selection results from the user's terminal, aggregating the obtained selection results, and recording them in a database,

[0907] A means for a user terminal to analyze the user's emotional state using emotion recognition technology and dynamically optimize the order in which information is presented based on that data,

[0908] A system that includes this.

[0909] (Claim 2)

[0910] The system according to claim 1, comprising means for determining the accuracy rate based on aggregated selection results and sentiment data, and providing a reward to the user.

[0911] (Claim 3)

[0912] The system according to claim 1, comprising means for anonymizing recorded selection results and sentiment data and providing them to a third-party organization. [Explanation of symbols]

[0913] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for transmitting multiple pieces of information, including information generated by artificial intelligence technology and information generated by humans, from a content provision device to a user terminal, A means for a user terminal to display the transmitted information and to provide an operation screen for the user to select whether the information is generated by artificial intelligence technology or by human generation, A means of obtaining the user's selection results from the user's terminal, aggregating the obtained selection results, and recording them in a database, A system that includes this.

2. The system according to claim 1, comprising means for determining the accuracy rate based on the aggregated selection results and providing a reward to the user.

3. The system according to claim 1, comprising means for anonymizing the recorded selection results and providing them to a third-party organization.

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