System

Abstract

A system is provided.SOLUTION: The system includes a means for receiving input data from a user, a data analysis means including a generated AI model for analyzing the received input data, an evaluation means for evaluating an answer generated by the generated AI model to determine an optimal answer, a means for transmitting and displaying the optimal answer to the user, a data collection means for anonymizing and collecting the input data and the generated answer of the user, a visualization means for analyzing the collected data and visualizing a tendency and a problem related to gender identity or gender, and a means for proposing a suitable course based on profile information and analysis data of the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] There are situations in which minors and their guardians who are concerned about gender identity and gender have limited access to appropriate support. This situation can lead to a lack of understanding in education and society, and to high-risk behaviors such as bullying, school refusal, and suicide. There is also the problem of difficulty connecting with appropriate professionals and counselors. This invention aims to provide a reliable means for minors and their guardians to seek advice with peace of mind, and to support individuals who are concerned about gender identity and gender. [Means for solving the problem]

[0005] This invention provides a means for receiving input data from a user. The received input data is analyzed by a generative AI model, and a data analysis means is included for generating an appropriate answer. The generated answers are evaluated and scrutinized by an evaluation means for determining the optimal answer. The optimal answer is then sent to the user and displayed. The user's input data and generated answers are anonymized and collected, and stored by a data collection means. The collected data is analyzed by a visualization means for visualizing trends and issues related to gender identity and gender. The invention also includes a means for suggesting appropriate career paths based on the user's profile information and analysis data. This not only makes it easier for users to receive expert support, but also provides accurate information and career options related to gender identity and gender, promoting mental health management and early intervention.

[0006] Absolutely. Below are definitions of important terms found in the claims.

[0007] "User" refers to individuals who use this system and their guardians.

[0008] "Terminal" refers to a device through which a user accesses the system and inputs questions or concerns in chat format.

[0009] "Server" refers to a central processing unit that receives, analyzes, and evaluates input data, generates and transmits answers, and collects, analyzes, and visualizes data.

[0010] "Input data" refers to text information about questions or concerns entered by a user through a terminal.

[0011] A "generative AI model" refers to an artificial intelligence model that analyzes input data and generates appropriate answers.

[0012] "Data Analysis Means" means a means for analyzing received input data using a generative AI model.

[0013] "Answer" refers to advice or information generated by a generative AI model based on user input data.

[0014] "Evaluation means" refers to a means for evaluating the generated answers and determining the best answer.

[0015] "Transmission means" refers to a means for transmitting and displaying the best answer to the user.

[0016] "Data Collection Means" refers to the means for collecting and anonymizing user input data and generated responses.

[0017] "Visualization tools" refer to the means used to analyze collected data and visualize trends and issues related to sexual identity and gender in the form of graphs and charts.

[0018] "Career suggestion means" refers to a means for suggesting suitable career paths and schools based on the user's profile information and analysis data.

[0019] The above are definitions of important words included in the claims. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6]FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The following describes a "form for carrying out the invention."

[0042] ---

[0043] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0044] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0045] The server then receives the input data and analyzes it using a generative AI model, which uses specialized knowledge about gender identity and gender to generate appropriate answers to the user's questions.

[0046] The server evaluates the generated answers, determines the best answer, and, if necessary, requests review from medical professionals or psychological counselors to improve the accuracy of the answer.

[0047] The server then sends the best answer to the device, which then displays it to the user, allowing the user to quickly receive the information or support they need.

[0048] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0049] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0050] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0051] For example:

[0052] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0053] The device sends this text to the server.

[0054] The server analyzes this text using a generative AI model and generates a response that reads, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0055] The server evaluates this response and sends it to the terminal.

[0056] The terminal displays this response to the user.

[0057] In this way, users can easily obtain support regarding gender identity and gender issues, promoting mental health management and early intervention. This system provides reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0061] Step 2:

[0062] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0063] Step 3:

[0064] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0065] Step 4:

[0066] The server passes the received input data to the generative AI model, which then uses a text analysis algorithm to understand the intent of the input and the gist of the question.

[0067] Step 5:

[0068] The generative AI model generates an answer based on the user's input data, such as "It is natural to feel uncomfortable about your gender identity."

[0069] Step 6:

[0070] The server evaluates the generated answers, automatically filtering and scoring them based on evaluation criteria, and, if necessary, sending them to medical professionals or psychological counselors for review.

[0071] Step 7:

[0072] The server determines the best answer based on the scoring results if review is not required, or expert feedback if required.

[0073] Step 8:

[0074] The server sends the best answer to the device, including contact details for appropriate experts and additional resources if necessary.

[0075] Step 9:

[0076] The device displays the answer received from the server to the user. For example, it displays, "It is natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0077] Step 10:

[0078] The server anonymizes the user's input data and generated answers, stores them in a database, removes personal information, and generates statistics for analysis.

[0079] Step 11:

[0080] The server analyzes the stored data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0081] Step 12:

[0082] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0083] Step 13:

[0084] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0085] The above are the specific processes and actions at each step. This process will enable minors and their guardians to receive prompt and appropriate support regarding issues related to gender identity and gender.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] There is a lack of a system that allows minors and their guardians who are concerned about gender identity and gender issues to receive reliable support quickly and safely. In particular, there are difficulties in providing information in real time, protecting personal information, and connecting with appropriate medical professionals and psychological counselors.

[0089] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0090] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting an appropriate career path based on the user's profile information and analysis data; and means for requesting reviews from optimal medical professionals or psychological counselors based on the user's input data. This allows users to receive reliable support in real time, ensures the protection of their personal information, and enables smooth collaboration with appropriate professionals.

[0091] A "user" is someone who inputs questions or concerns about gender identity or sexual identity through a chat-style UI.

[0092] A "terminal" is a device used by a user that provides a chat-style UI for inputting questions and concerns and transmits the input data to a server.

[0093] The "server" is a system that receives input data sent by the user, analyzes it, uses a generative AI model to generate an appropriate answer, and sends it to the user.

[0094] A "generative AI model" is an artificial intelligence model that analyzes data based on specialized knowledge about sexual identity and gender and generates appropriate answers.

[0095] A "prompt" is a textual instruction used to pass input data to a generative AI model.

[0096] "Data analysis means" means a means for analyzing input data received from a user using a generative AI model.

[0097] "Evaluation means" refers to a means for evaluating the answers generated by a generative AI model, requesting expert review if necessary, and determining the optimal answer.

[0098] The "data collection means" is a means for anonymizing the user's input data and generated responses and collecting them in a database.

[0099] "Visualization tools" are means of analyzing collected data and displaying trends and issues related to sexual identity and gender in the form of graphs and charts.

[0100] The "career suggestion means" is a means for suggesting suitable career paths and schools based on the user's profile information and analysis data.

[0101] The "review request means" is a means for requesting a review from the most suitable medical expert or psychological counselor based on the data input by the user.

[0102] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0103] Users use a chat-style user interface (UI) to input questions and concerns about gender identity and gender. Devices that provide this UI include PCs, smartphones, and tablets. Specifically, users input questions such as, "I feel uncomfortable with my gender. What should I do?"

[0104] The device sends the entered questions to the server in real time, using a secure protocol (e.g., HTTPS) for data transmission.

[0105] The server uses a generative AI model to analyze the received input data. This generative AI model generates an answer based on specialized knowledge about gender identity and gender. The server first generates a prompt. The prompt contains the text entered by the user and may take the form, for example, "The user is asking the following question: I feel uncomfortable with my gender. What should I do?"

[0106] The generative AI model analyzes this prompt and generates an appropriate response, such as, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0107] The server evaluates the generated answers and, if necessary, requests review from medical professionals or psychological counselors. Once the optimal answer is determined, the server sends it to the device. The device displays the answer to the user and quickly provides the necessary information and support.

[0108] The server also anonymizes the user's input data and generated answers and collects them in a database. The anonymized data is stored in a manner that ensures the protection of personal information.

[0109] The collected data is then analyzed by the server, and trends and issues related to gender identity and gender are visualized using graphs and charts, and presented as information to deepen understanding in society as a whole.

[0110] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that is right for them.

[0111] For example, a user enters a question such as, "I feel uncomfortable with my gender. What should I do?" and the device sends this to the server. The server analyzes the text using a generative AI model and generates a response such as, "It's natural to feel uncomfortable with your gender identity. We recommend that you first consult with an expert." The server evaluates this response, and after expert review, sends the optimal response to the device, which then displays it to the user. This series of actions allows the user to receive fast and reliable support.

[0112] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0113] Step 1:

[0114] Users use a chat-style user interface (UI) to input questions or concerns about gender identity and gender identity. The input data is in text format and includes content such as, "I feel uncomfortable with my gender. What should I do?" The input text data is passed to the device, and the device is ready to proceed to the next step.

[0115] Step 2:

[0116] The device sends the text data entered by the user to the server in real time. A secure protocol (e.g., HTTPS) is used to transmit the data, ensuring the integrity and confidentiality of the data during transmission. The input data is passed to the server in the following format: "I'm feeling uncomfortable with my gender. What should I do?"

[0117] Step 3:

[0118] The server receives the input data. Since the received data cannot be used for analysis as is, it first generates a prompt to be passed to the generative AI model. The prompt is processed into a format such as "The user is asking the following question: I feel uncomfortable with my gender. What should I do?" This prompt is then used to proceed to the next step.

[0119] Step 4:

[0120] The server passes the prompt to the generative AI model for analysis. The generative AI model analyzes the prompt based on specialized knowledge about gender identity and gender, and generates an appropriate response. For example, the response output might be, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0121] Step 5:

[0122] The server evaluates the answers generated by the generative AI model, checks whether the generated answers are appropriate, and, if necessary, requests review by medical professionals or psychological counselors. Experts can check and correct the accuracy and appropriateness of the answers, resulting in high-quality answers. For example, experts may add additional information such as, "If you would like a more detailed consultation, you can make an appointment using the link below."

[0123] Step 6:

[0124] The server then sends the best answer after evaluation to the device. This is again done using a secure protocol. The data sent to the device will be in the form of a message saying, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist. If you would like a more detailed consultation, you can make an appointment using the link below."

[0125] Step 7:

[0126] The device then displays the received response data to the user, allowing them to quickly receive the appropriate answer to their question and, if necessary, to view links to further support.

[0127] Step 8:

[0128] The server anonymizes the user's input data and generated answers and collects them in a database. The anonymization process removes any personally identifiable information, and the collected data is stored in a manner that complies with the Personal Information Protection Act. This anonymized data is used for the next analysis step.

[0129] Step 9:

[0130] The server analyzes the collected anonymized data, and the results are used to identify trends and issues related to gender identity and gender, and are visualized in graphs and charts, providing useful information for policymakers and researchers.

[0131] Step 10:

[0132] The server suggests suitable career paths and schools based on the user's profile information (e.g., age, grade, current school, etc.) and analysis results. These career suggestions help users make the best choices for themselves. The results of the career suggestions are also sent to the user's device, allowing the user to view them and make career decisions.

[0133] (Application example 1)

[0134] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0135] In today's information society, security knowledge and countermeasures are becoming increasingly important. However, many users lack adequate security knowledge and are vulnerable to threats such as phishing emails and the leakage of personal information. Furthermore, access to security experts with specialized knowledge is generally difficult, making it difficult for users to solve problems on their own. This creates a need for a system that provides efficient and reliable security support.

[0136] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0137] In this invention, the server includes means for receiving input data from a user, data analysis means including a generative AI model that analyzes the received input data, evaluation means for evaluating answers generated by the generative AI model to determine the optimal answer, data collection means for anonymizing and collecting the user's input data and the generated answers, visualization means for analyzing the collected data and visualizing security trends and issues, and means for proposing appropriate security measures based on the user's profile information and analysis data. This allows users to easily receive professional security support, enabling the protection of personal information and the strengthening of security measures.

[0138] "User" means an individual or entity that uses the System and receives security-related support.

[0139] "Input data" is the textual information of security questions and concerns that users provide to the system.

[0140] A "generative AI model" is an artificial intelligence model that has specialized knowledge about security and analyzes user input data to generate appropriate answers.

[0141] "Data analysis means" is a function that analyzes received input data and generates appropriate answers using a generative AI model.

[0142] The "evaluation means" is a function that evaluates the answers generated by the generative AI model and determines the best answer for the user.

[0143] The "transmission means" is a function for transmitting the optimal answer to the user and displaying it on the terminal.

[0144] The "data collection means" is a function for anonymizing and collecting user input data and generated responses.

[0145] "Visualization means" is a function that analyzes collected data and displays security trends and issues in graphs and charts.

[0146] "Profile Information" refers to personal information about a user, such as their age, occupation, and the device they use.

[0147] "Security measures" are specific actions and settings that users take to protect themselves from cyber attacks and information leaks.

[0148] The system for implementing this invention allows users to input security-related questions or concerns, and generates and provides information to resolve those questions. The major components required to implement this system and their functions are described below.

[0149] 1. A means of receiving input data from the user

[0150] The device (smartphone app) provides a chat-style UI that allows users to enter security questions. For example, the user might enter a question like, "How can I spot a phishing email?"

[0151] 2. A data analysis method that includes a generative AI model that analyzes the received input data.

[0152] The device sends the input question in real time to the server, which uses a generative AI model (e.g., OpenAI® GPT-3®) to analyze the received question and generate an appropriate answer.

[0153] 3. An evaluation tool to evaluate the generated answers and determine the best answer.

[0154] The server evaluates the answers generated by the generative AI model, and if necessary, requests a security expert for review to determine the best answer. This evaluation method improves the accuracy and reliability of the answers.

[0155] 4. A means to send and display the best answer to the user

[0156] The server generates the optimal answer, which is then sent to the user's device and displayed to them, allowing the user to quickly receive practical advice on security measures.

[0157] 5. Data collection method to anonymize and collect user input data and generated responses

[0158] The server anonymizes the user's input data and generated answers and collects them in a database, thereby protecting personal information.

[0159] 6. A visualization tool to analyze collected data and visualize security trends and issues.

[0160] The server analyzes the collected data and visualizes security trends and issues. The visualized data is displayed in graphs and charts, making it easier to understand the overall security situation and issues.

[0161] 7. A method for suggesting appropriate security measures based on user profile information and analytical data

[0162] The server proposes appropriate security measures based on the user's profile information (e.g., age, occupation, device used, etc.) and analysis data, allowing users to implement specific measures tailored to their individual circumstances.

[0163] Examples of concrete examples and prompts

[0164] For example, if a user types the question "How can I spot a phishing email?", the system will process it as follows:

[0165] The user's terminal sends this question to the server.

[0166] The server analyzes this question using a generative AI model and generates the answer, "Phishing emails typically encourage you to click on a link. Be careful of links in suspicious emails."

[0167] The server evaluates the answers and sends the best answer to the terminal.

[0168] The terminal displays this response to the user.

[0169] Example prompt sentence:

[0170] "User Question: How do I spot a phishing email?

[0171] Generate the best security answers:

[0172] In this way, the system of the present invention allows users to instantly acquire security expertise and contributes to strengthening security measures. Furthermore, by analyzing and visualizing the collected data, it is possible to grasp the overall security situation and provide valuable information for taking further measures.

[0173] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0174] Step 1:

[0175] A user inputs a question into a smartphone device. For example, the user inputs a question such as "How can I identify a phishing email?" into a chat-style UI. This input data is sent from the device to the server.

[0176] Step 2:

[0177] The terminal transmits the user's input data in real time to the server, which receives the data and passes it to the data analysis means.

[0178] Step 3:

[0179] The server sends the received input data to the generative AI model, which analyzes the input data based on its pre-trained security expertise and generates an appropriate answer. In this process, the AI ​​model extracts key keywords and context from the input data and generates an answer based on that.

[0180] Step 4:

[0181] The server passes the answers generated by the generative AI model to an evaluation method, which may then be verified by security experts to assess the reliability and appropriateness of the generated answers. Once the evaluation is complete, the best answer is determined.

[0182] Step 5:

[0183] After the server determines the optimal answer, it sends it back to the device, where it is displayed to the user, allowing the user to receive specific security advice.

[0184] Step 6:

[0185] The server anonymizes the user's input data and generated responses and stores them in a data collection tool, processing the data in a way that ensures appropriate protection of personal information.

[0186] Step 7:

[0187] The server uses the collected data to analyze security trends and issues, and displays them in the form of graphs and charts using visualization tools. This visualization data is used to understand the overall security situation and issues.

[0188] Step 8:

[0189] The server then proposes appropriate security measures to the user based on the user's profile information and analytical data, providing personalized advice based on the user's age, occupation, device used, etc.

[0190] The above is a specific flow of the processing steps of the system that realizes the application example.

[0191] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0192] ---

[0193] This invention is a system that enables minors and their guardians with concerns about gender identity and gender identity to receive reliable support. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, more appropriate support can be provided. This system receives input data from the user, analyzes it, recognizes emotions, generates answers, evaluates and transmits them, collects and analyzes data, visualizes it, and makes career suggestions.

[0194] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0195] The server then receives the input data and recognizes the user's emotions using an emotion engine, which analyzes emotions from the user's text input to detect emotional states such as "anxiety" or "excitement."

[0196] The server passes the recognized emotion data to a generative AI model, which then begins analyzing the data. The generative AI model generates appropriate answers to the user's questions based on specialized knowledge of sexual identity and gender. Based on the emotion data, the answer is revised, adding phrases that take emotion into consideration, such as "Don't worry," to provide more appropriate support to the user.

[0197] The server evaluates the generated answers and determines the most appropriate one. If necessary, it requests reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes anxiety, it makes decisions based on the level of urgency, such as increasing the priority of connecting to a specialist.

[0198] The server then sends the best possible answer to the device, which displays it to the user, sometimes including reassuring words and specific guidelines for action, taking into consideration the user's feelings.

[0199] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0200] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0201] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0202] For example:

[0203] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0204] The device sends this text to the server.

[0205] The server analyzes the text using an emotion engine to detect emotions such as "anxiety."

[0206] The server analyzes this text using a generative AI model and generates a response: "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0207] The server evaluates this response and sends it to the terminal.

[0208] The terminal displays this response to the user.

[0209] In this way, users can quickly and accurately obtain the information and support they need, promoting mental health management and early intervention. The system provides emotionally sensitive and reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0210] The processing flow will be explained below.

[0211] Step 1:

[0212] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0213] Step 2:

[0214] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0215] Step 3:

[0216] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0217] Step 4:

[0218] The server passes the received input data to the emotion engine, which then uses natural language processing technology to analyze the user's text data and detect emotions such as "anxiety" or "sadness."

[0219] Step 5:

[0220] The server then passes the recognized emotion data to the generative AI model, which then uses a text analysis algorithm to understand the intent and gist of the questions about gender identity and gender identity.

[0221] Step 6:

[0222] The generative AI model generates answers based on the user's input data and emotional data, such as "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0223] Step 7:

[0224] The server evaluates the generated answers and determines the best answer, automatically filtering and scoring them based on evaluation criteria, and, if necessary, requests review by medical professionals or psychological counselors.

[0225] Step 8:

[0226] The server sends the optimal answer to the device, which then displays it to the user, for example, "Don't worry. It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0227] Step 9:

[0228] The server anonymizes the user's input data and generated responses, collects them in a database, removes personal information, and generates statistics for analysis.

[0229] Step 10:

[0230] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0231] Step 11:

[0232] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0233] Step 12:

[0234] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0235] These are the specific processing steps of the system that combines the emotion engine. This process allows users to quickly and accurately obtain the information and support they need, promoting mental health management and early response.

[0236] Example 2

[0237] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0238] There is a problem that minors and their guardians who are concerned about gender identity and gender identity have difficulty receiving appropriate and reliable support. Furthermore, answers generated without consideration for the user's feelings may further aggravate the user's feelings. Therefore, there is a need for a system that provides fast and accurate support in a way that takes the user's feelings into consideration.

[0239] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0240] In this invention, the server includes: means for receiving input data from a user; emotion recognition means for analyzing the received input data and recognizing the user's emotions; data analysis means including a generative AI model for generating appropriate answers based on the analysis data and emotion data; evaluation means for evaluating the generated answers and determining an optimal answer; means for submitting the answers for expert review and, if necessary, making a decision to correspond to the level of urgency; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; and means for suggesting appropriate career paths based on the user's profile information and analysis data. This makes it possible to provide prompt and appropriate support while taking the user's emotions into consideration.

[0241] A "user" is someone who uses this system to input questions or concerns about gender identity and gender.

[0242] A "terminal" is a device used by a user to communicate with the system, such as a smartphone, tablet, or PC.

[0243] The "server" is a computer system that receives data sent by users and performs analysis, emotion recognition, answer generation, evaluation, transmission, data collection and analysis, visualization, and career suggestions.

[0244] "Emotion recognition means" refers to a technical means for detecting and analyzing emotions from user input data, and includes an emotion engine.

[0245] A "generative AI model" is an artificial intelligence model used for data analysis that generates answers to users' questions and concerns based on specialized knowledge.

[0246] "Data analysis means" refers to technical means, including generative AI models, that generate appropriate answers based on user input data and emotional data.

[0247] The "evaluation means" is a technical means for evaluating the generated answers and determining the optimal answer.

[0248] "Means for sending answers for expert review and, if necessary, making a determination as to the level of urgency" refers to means for sending the generated answers to medical professionals or psychological counselors and for improving the accuracy of the answers as necessary.

[0249] "Data Collection Measures" are technical measures that anonymize and securely collect user input data and generated responses.

[0250] "Visualization tools" are technical means for analyzing collected data and displaying trends and issues related to gender identity and gender in the form of graphs and charts.

[0251] The "career suggestion means" is a technical means for suggesting suitable career paths and educational institutions based on the user's profile information and analysis data.

[0252] This invention is a system designed to provide reliable support to minors and their guardians who are concerned about gender identity and gender identity. The system provides more appropriate support by incorporating an emotion engine that recognizes the user's emotions.

[0253] First, a user uses a device such as a smartphone, tablet, or PC to input questions or concerns about gender identity and gender through a chat-style interface. This interface is designed to be intuitive and easy to use. Consider the example of a user typing, "Recently, I've been feeling uncomfortable with my gender. What should I do?"

[0254] The device then transmits the input data to the server in real time via an API, for example by converting the input text to JSON format and sending an HTTP POST request to the server.

[0255] The server analyzes the received data and uses an emotion engine to recognize the user's emotion. Specifically, the server parses the received JSON data and extracts the text portion. This is then sent to an emotion engine (e.g., Google® Cloud Natural Language API, IBM Watson® Tone Analyzer) to analyze the user's emotional state, such as "anxiety."

[0256] The server passes the emotion data to a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an appropriate answer based on the user's question. The generated answer adds emotion-sensitive phrases such as "Don't worry," based on the emotion data. For example, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0257] The server then evaluates the generated answers to determine the best fit. In some cases, it may request reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes "anxiety," it prioritizes connecting with experts.

[0258] The server then sends the best evaluated answer to the device, which then displays it to the user, including reassuring words and specific guidelines for action that take the user's feelings into consideration.

[0259] The server then anonymizes the user's input data and generated responses and securely stores them in a database. This anonymization process ensures the protection of personal information. The server then analyzes the collected data and visualizes trends and issues related to gender identity and gender in the form of graphs and charts.

[0260] Finally, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0261] An example prompt is:

[0262] "I've been feeling uncomfortable with my gender lately. What should I do?"

[0263] "My child is struggling with gender identity, how should I address this?"

[0264] In this way, users can quickly and accurately obtain the information and support they need. The system not only takes into consideration users' feelings and provides a sense of security, but also contributes to improving understanding in society as a whole by analyzing the data.

[0265] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0266] Step 1:

[0267] Users input questions and concerns about gender identity and gender identity through a chat-style interface. The input is text data such as, "Recently, I've been feeling uncomfortable with my gender. What should I do?" The input text data is sent to the device as output.

[0268] Step 2:

[0269] The terminal receives text data entered by the user and sends it to the server in real time. As input, the text data entered in step 1 is provided to the terminal. Specifically, the input text is converted into JSON format and sent to the server using an HTTP POST request. As output, the text data is sent to the server in JSON format.

[0270] Step 3:

[0271] The server receives the received text data and uses an emotion engine to recognize the user's emotions. JSON-formatted text data is provided to the server as input. Specifically, the received data is parsed and the text portion is extracted. An emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) is used to analyze emotions and detect emotional states such as "anxiety" or "excitement." Emotion data is generated as output.

[0272] Step 4:

[0273] The server passes the generated emotion data and text data to a generative AI model, which generates an appropriate answer based on the user's question. The emotion data and text data are provided as input. Specifically, the data is input into a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an answer based on the question. Based on the emotion data, a phrase such as "Don't worry" is added. The generated answer text is obtained as output.

[0274] Step 5:

[0275] The server evaluates the generated answers and determines the best answer. As input, the generated answer text is provided. Specifically, it uses an internal evaluation algorithm to evaluate the quality of the answer and, in some cases, requests an expert for review. In particular, if the emotion engine recognizes the answer as "anxious," it increases the priority of connecting to an expert. As output, the evaluated best answer is determined.

[0276] Step 6:

[0277] The server sends the evaluated best answer to the terminal. The best answer text is provided as input. Specifically, the best answer is sent to the terminal as an HTTP response. The best answer data is sent to the terminal in JSON format as output.

[0278] Step 7:

[0279] The terminal displays the received answer to the user. The answer data sent from the server is provided as input. Specifically, the received data is analyzed and displayed to the user in a chat format. The answer text is displayed to the user as output.

[0280] Step 8:

[0281] The server anonymizes the user's input data and generated answers and securely collects them in a database. As input, the user's input data and generated answer data are provided. Specifically, personal identifying information is removed and the data is anonymized. As output, the anonymized data is stored in a database.

[0282] Step 9:

[0283] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Anonymized data is provided as input. Specifically, the server analyzes the data using data analysis algorithms and generates graphs and charts using visualization tools (e.g., Google Charts, D3.js). The analysis results are displayed as graphs and charts as output.

[0284] Step 10:

[0285] The server proposes suitable career paths and schools based on the user's profile information and analytical data. The user's profile information and analytical data are provided as input. Specifically, the server evaluates information such as the user's age, grade, and school, and generates a list of optimal career paths and educational institutions by referring to the collected data. The server provides information on the proposed career paths and schools as output.

[0286] (Application example 2)

[0287] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0288] Conventional systems have had difficulty providing appropriate support that takes into account emotions to minors and their guardians who have concerns about gender identity or gender. Furthermore, when customer service staff in brick-and-mortar stores deal with customers who have concerns about gender identity or gender, it is difficult to respond appropriately and with consideration for emotions in real time, resulting in a decline in customer satisfaction and trust. Furthermore, real-time emotion recognition and feedback-based responses have been difficult due to the lack of appropriate technology.

[0289] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0290] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting appropriate career paths based on the user's profile information and analysis data; emotion recognition means for recognizing the customer's emotional state; means for generating appropriate answers using the generative AI model based on the emotional state; and display means for providing feedback to staff in real time. This enables real-time, emotion-sensitive support to customers with concerns about gender identity and gender, even in physical stores.

[0291] The "means for receiving input data from a user" refers to an interface and communication device for transmitting text data input by a user through a terminal to a server.

[0292] "Data analysis means" refers to software and hardware that analyzes received input data and generates appropriate answers using a generative AI model.

[0293] An "evaluation means" is a software algorithm that compares and evaluates multiple answer candidates generated by a generative AI model to determine the optimal answer.

[0294] The "means for transmitting and displaying to the user" refers to a device and software that transmits the determined optimal answer to the user's terminal in real time and displays it.

[0295] "Data collection means" refers to technology for anonymizing user input data and generated responses, and collecting data while protecting personal information.

[0296] "Visualization tools" are software that analyzes collected data and displays trends and issues related to gender identity and gender as graphs and charts.

[0297] The "means for suggesting suitable career paths" refers to algorithms and systems that suggest the most suitable career paths and schools for users based on the user's profile information and analysis data.

[0298] "Emotion Recognition Means" means software and AI engines for recognizing the emotional state of a user or customer from input text or voice data.

[0299] The "means for generating appropriate responses" is an algorithm for generating emotion-sensitive responses using a generative AI model based on the perceived emotional state.

[0300] The "display means for providing feedback to staff in real time" refers to a device and software for providing and displaying the generated appropriate response to the wait staff in real time.

[0301] This invention is a system for providing appropriate support to minors and their guardians who are concerned about gender identity and gender identity. This system has functions for receiving input data from users, analyzing it, recognizing emotions, generating answers, evaluating, transmitting, collecting and analyzing data, visualizing it, and making career suggestions. Furthermore, by applying this system to customer service in brick-and-mortar stores, it can realize real-time, emotion-sensitive responses.

[0302] System configuration

[0303] The system is configured as follows:

[0304] 1. A means for receiving input data from the user: Text data entered by the user through a device (such as a smartphone or PC) is sent to the server in real time. The hardware used at this stage includes smartphones, tablets, and PCs.

[0305] 2. Data analysis: The data received from the user is analyzed on the server, and a generative AI model is used to generate an appropriate answer based on the user's input. The software used includes OpenAI's generative models (e.g., GPT-3) and TextBlob.

[0306] 3. Evaluation methods: Comparing multiple candidate answers generated by the generative AI model to determine the best answer. This evaluation can include automated evaluation using algorithms and expert review.

[0307] 4. Means of sending and displaying to the user: The determined optimal answer is sent to the user's terminal in real time and displayed appropriately.

[0308] 5. Data collection method: The data entered by the user and the responses generated are anonymized and collected while protecting personal information. This data is stored for future analysis.

[0309] 6. Visualization methods: Based on the collected data, trends and issues related to gender identity and gender will be visualized using graphs and charts.

[0310] 7. Career Recommendation: Based on the user's profile information and analytical data, the system will suggest suitable career paths for the user, including career counseling and school introductions.

[0311] 8. Emotion Recognition: Analyze the emotional state from the user or customer's input text and use an emotion engine to recognize emotions such as "anxiety" or "relief."

[0312] 9. Means of generating appropriate answers: Based on the perceived emotional state, generative AI models are used to generate emotion-sensitive answers.

[0313] 10. Display means for providing feedback to staff in real time: Smart glasses or head-mounted displays can be used to display the generated appropriate answers to the waiting staff in real time.

[0314] Example of operation

[0315] As an example of a brick-and-mortar application, it works as follows:

[0316] The user inputs a question such as, "I feel uncomfortable with my gender. What should I do?" This question is sent to the server via the device.

[0317] The server receives this input data and recognizes the emotion of "anxiety" through an emotion engine.

[0318] The server uses a generative AI model to generate the answer, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0319] The server evaluates this answer to determine if it is the best answer.

[0320] The generated answers are provided to the wait staff in real time through smart glasses.

[0321] Customer service staff will refer to the answers displayed on the smart glasses and respond appropriately to the customer.

[0322] Prompt Sentence Examples

[0323] "Answer the following question to emotionally anxious users: I feel uncomfortable with my gender. What should I do? Answer:"

[0324] In this way, users can receive fast and reliable support for their mental health care, and brick-and-mortar stores can provide emotionally sensitive customer service.

[0325] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0326] Step 1:

[0327] The user inputs a question, and the terminal receives the input data and sends it to the server.

[0328] Input: The text entered by the user.

[0329] Output: The text data received by the server.

[0330] Specific operation: The user types "I feel uncomfortable with my gender. What should I do?" into the chat-style UI on their smartphone or PC and presses the send button. The device then sends this text data to the server.

[0331] Step 2:

[0332] To analyze the input data received by the server, an emotion engine is used to recognize the user's emotional state.

[0333] Input: Received text data.

[0334] Output: Emotional state (e.g., "anxious," "relieved," etc.).

[0335] What it does: The server analyzes the input text using an emotion recognition algorithm such as TextBlob and detects the emotional state as "anxiety."

[0336] Step 3:

[0337] The server uses a generative AI model based on the perceived emotional state to generate an appropriate response.

[0338] Input: Text data, emotional state.

[0339] Output: The generated answer text.

[0340] Specific operation: The server uses OpenAI's generative model (e.g., GPT-3) and inputs the prompt "For a user who is emotionally anxious, please answer the following question: I feel uncomfortable with my gender. What should I do? Answer:" into the model, generating the answer "Don't worry. It's natural to feel uncomfortable with your gender identity."

[0341] Step 4:

[0342] The server evaluates the generated answers and determines the best answer.

[0343] Input: Multiple generated answer candidates.

[0344] Output: The best answer.

[0345] What it does: The server runs the generated answers through a rating algorithm to select the most appropriate answer, adding expert review if necessary.

[0346] Step 5:

[0347] The server sends the best answer to the user's device and displays it.

[0348] Input: Best answer.

[0349] Output: The answer displayed on the user's terminal.

[0350] Specific operation: The server sends the best answer to the user's device, and the device displays the answer on the screen.

[0351] Step 6:

[0352] The server anonymizes the user's input data and generated answers and collects them in a database.

[0353] Input: User input data, generated answers.

[0354] Output: Anonymized data.

[0355] What it does: The server uses a data anonymization algorithm to remove personally identifiable information such as your name and address, generating anonymized data that is then stored in a database.

[0356] Step 7:

[0357] The server analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[0358] Input: Anonymized data.

[0359] Output: Visualized graphs and charts.

[0360] What it does: The server uses data analysis software to analyze the collected data to find trends and issues, and displays the results in graphs and charts.

[0361] Step 8:

[0362] The server suggests suitable paths based on the user's profile information and analytical data.

[0363] Input: User profile information, analytics data.

[0364] Output:Career suggestions.

[0365] Specific operation: The server uses a career suggestion algorithm to suggest suitable career paths and schools to the user based on profile information such as the user's age, grade, and current school, as well as the results of data analysis.

[0366] Step 9:

[0367] The server uses the emotion recognition means to recognize the emotional state of the customer in the physical store.

[0368] Input: Customer statements and behavior data in physical stores.

[0369] Output: Emotional state.

[0370] Specific operation: The server applies an emotion recognition algorithm to data input from microphones and cameras installed in physical stores to recognize the customer's emotional state.

[0371] Step 10:

[0372] The server uses generative AI models to generate appropriate responses based on emotional state and provide feedback to staff in real time.

[0373] Input: Emotional state, customer question.

[0374] Output: Feedback display to staff.

[0375] How it works: The server inputs prompts into the generative AI model based on the customer's emotional state and question, and displays the generated answers in real time on smart glasses or a head-mounted display.

[0376] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0377] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0378] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0379] [Second embodiment]

[0380] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0381] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0382] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0383] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0384] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0385] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0386] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0387] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0388] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0389] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0390] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0391] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0392] The following describes a "form for carrying out the invention."

[0393] ---

[0394] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0395] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0396] The server then receives the input data and analyzes it using a generative AI model, which uses specialized knowledge about gender identity and gender to generate appropriate answers to the user's questions.

[0397] The server evaluates the generated answers, determines the best answer, and, if necessary, requests review from medical professionals or psychological counselors to improve the accuracy of the answer.

[0398] The server then sends the best answer to the device, which then displays it to the user, allowing the user to quickly receive the information or support they need.

[0399] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0400] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0401] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0402] For example:

[0403] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0404] The device sends this text to the server.

[0405] The server analyzes this text using a generative AI model and generates a response that reads, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0406] The server evaluates this response and sends it to the terminal.

[0407] The terminal displays this response to the user.

[0408] In this way, users can easily obtain support regarding gender identity and gender issues, promoting mental health management and early intervention. This system provides reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0409] The processing flow will be explained below.

[0410] Step 1:

[0411] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0412] Step 2:

[0413] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0414] Step 3:

[0415] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0416] Step 4:

[0417] The server passes the received input data to the generative AI model, which then uses a text analysis algorithm to understand the intent of the input and the gist of the question.

[0418] Step 5:

[0419] The generative AI model generates an answer based on the user's input data, such as "It is natural to feel uncomfortable about your gender identity."

[0420] Step 6:

[0421] The server evaluates the generated answers, automatically filtering and scoring them based on evaluation criteria, and, if necessary, sending them to medical professionals or psychological counselors for review.

[0422] Step 7:

[0423] The server determines the best answer based on the scoring results if review is not required, or expert feedback if required.

[0424] Step 8:

[0425] The server sends the best answer to the device, including contact details for appropriate experts and additional resources if necessary.

[0426] Step 9:

[0427] The device displays the answer received from the server to the user. For example, it displays, "It is natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0428] Step 10:

[0429] The server anonymizes the user's input data and generated answers, stores them in a database, removes personal information, and generates statistics for analysis.

[0430] Step 11:

[0431] The server analyzes the stored data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0432] Step 12:

[0433] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0434] Step 13:

[0435] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0436] The above are the specific processes and actions at each step. This process will enable minors and their guardians to receive prompt and appropriate support regarding issues related to gender identity and gender.

[0437] Example 1

[0438] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0439] There is a lack of a system that allows minors and their guardians who are concerned about gender identity and gender issues to receive reliable support quickly and safely. In particular, there are difficulties in providing information in real time, protecting personal information, and connecting with appropriate medical professionals and psychological counselors.

[0440] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0441] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting an appropriate career path based on the user's profile information and analysis data; and means for requesting reviews from optimal medical professionals or psychological counselors based on the user's input data. This allows users to receive reliable support in real time, ensures the protection of their personal information, and enables smooth collaboration with appropriate professionals.

[0442] A "user" is someone who inputs questions or concerns about gender identity or sexual identity through a chat-style UI.

[0443] A "terminal" is a device used by a user that provides a chat-style UI for inputting questions and concerns and transmits the input data to a server.

[0444] The "server" is a system that receives input data sent by the user, analyzes it, uses a generative AI model to generate an appropriate answer, and sends it to the user.

[0445] A "generative AI model" is an artificial intelligence model that analyzes data based on specialized knowledge about sexual identity and gender and generates appropriate answers.

[0446] A "prompt" is a textual instruction used to pass input data to a generative AI model.

[0447] "Data analysis means" means a means for analyzing input data received from a user using a generative AI model.

[0448] "Evaluation means" refers to a means for evaluating the answers generated by a generative AI model, requesting expert review if necessary, and determining the optimal answer.

[0449] The "data collection means" is a means for anonymizing the user's input data and generated responses and collecting them in a database.

[0450] "Visualization tools" are means of analyzing collected data and displaying trends and issues related to sexual identity and gender in the form of graphs and charts.

[0451] The "career suggestion means" is a means for suggesting suitable career paths and schools based on the user's profile information and analysis data.

[0452] The "review request means" is a means for requesting a review from the most suitable medical expert or psychological counselor based on the data input by the user.

[0453] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0454] Users use a chat-style user interface (UI) to input questions and concerns about gender identity and gender. Devices that provide this UI include PCs, smartphones, and tablets. Specifically, users input questions such as, "I feel uncomfortable with my gender. What should I do?"

[0455] The device sends the entered questions to the server in real time, using a secure protocol (e.g., HTTPS) for data transmission.

[0456] The server uses a generative AI model to analyze the received input data. This generative AI model generates an answer based on specialized knowledge about gender identity and gender. The server first generates a prompt. The prompt contains the text entered by the user and may take the form, for example, "The user is asking the following question: I feel uncomfortable with my gender. What should I do?"

[0457] The generative AI model analyzes this prompt and generates an appropriate response, such as, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0458] The server evaluates the generated answers and, if necessary, requests review from medical professionals or psychological counselors. Once the optimal answer is determined, the server sends it to the device. The device displays the answer to the user and quickly provides the necessary information and support.

[0459] The server also anonymizes the user's input data and generated answers and collects them in a database. The anonymized data is stored in a manner that ensures the protection of personal information.

[0460] The collected data is then analyzed by the server, and trends and issues related to gender identity and gender are visualized using graphs and charts, and presented as information to deepen understanding in society as a whole.

[0461] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that is right for them.

[0462] For example, a user enters a question such as, "I feel uncomfortable with my gender. What should I do?" and the device sends this to the server. The server analyzes the text using a generative AI model and generates a response such as, "It's natural to feel uncomfortable with your gender identity. We recommend that you first consult with an expert." The server evaluates this response, and after expert review, sends the optimal response to the device, which then displays it to the user. This series of actions allows the user to receive fast and reliable support.

[0463] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0464] Step 1:

[0465] Users use a chat-style user interface (UI) to input questions or concerns about gender identity and gender identity. The input data is in text format and includes content such as, "I feel uncomfortable with my gender. What should I do?" The input text data is passed to the device, and the device is ready to proceed to the next step.

[0466] Step 2:

[0467] The device sends the text data entered by the user to the server in real time. A secure protocol (e.g., HTTPS) is used to transmit the data, ensuring the integrity and confidentiality of the data during transmission. The input data is passed to the server in the following format: "I'm feeling uncomfortable with my gender. What should I do?"

[0468] Step 3:

[0469] The server receives the input data. Since the received data cannot be used for analysis as is, it first generates a prompt to be passed to the generative AI model. The prompt is processed into a format such as "The user is asking the following question: I feel uncomfortable with my gender. What should I do?" This prompt is then used to proceed to the next step.

[0470] Step 4:

[0471] The server passes the prompt to the generative AI model for analysis. The generative AI model analyzes the prompt based on specialized knowledge about gender identity and gender, and generates an appropriate response. For example, the response output might be, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0472] Step 5:

[0473] The server evaluates the answers generated by the generative AI model, checks whether the generated answers are appropriate, and, if necessary, requests review by medical professionals or psychological counselors. Experts can check and correct the accuracy and appropriateness of the answers, resulting in high-quality answers. For example, experts may add additional information such as, "If you would like a more detailed consultation, you can make an appointment using the link below."

[0474] Step 6:

[0475] The server then sends the best answer after evaluation to the device. This is again done using a secure protocol. The data sent to the device will be in the form of a message saying, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist. If you would like a more detailed consultation, you can make an appointment using the link below."

[0476] Step 7:

[0477] The device then displays the received response data to the user, allowing them to quickly receive the appropriate answer to their question and, if necessary, to view links to further support.

[0478] Step 8:

[0479] The server anonymizes the user's input data and generated answers and collects them in a database. The anonymization process removes any personally identifiable information, and the collected data is stored in a manner that complies with the Personal Information Protection Act. This anonymized data is used for the next analysis step.

[0480] Step 9:

[0481] The server analyzes the collected anonymized data, and the results are used to identify trends and issues related to gender identity and gender, and are visualized in graphs and charts, providing useful information for policymakers and researchers.

[0482] Step 10:

[0483] The server suggests suitable career paths and schools based on the user's profile information (e.g., age, grade, current school, etc.) and analysis results. These career suggestions help users make the best choices for themselves. The results of the career suggestions are also sent to the user's device, allowing the user to view them and make career decisions.

[0484] (Application example 1)

[0485] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0486] In today's information society, security knowledge and countermeasures are becoming increasingly important. However, many users lack adequate security knowledge and are vulnerable to threats such as phishing emails and the leakage of personal information. Furthermore, access to security experts with specialized knowledge is generally difficult, making it difficult for users to solve problems on their own. This creates a need for a system that provides efficient and reliable security support.

[0487] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0488] In this invention, the server includes means for receiving input data from a user, data analysis means including a generative AI model that analyzes the received input data, evaluation means for evaluating answers generated by the generative AI model to determine the optimal answer, data collection means for anonymizing and collecting the user's input data and the generated answers, visualization means for analyzing the collected data and visualizing security trends and issues, and means for proposing appropriate security measures based on the user's profile information and analysis data. This allows users to easily receive professional security support, enabling the protection of personal information and the strengthening of security measures.

[0489] "User" means an individual or entity that uses the System and receives security-related support.

[0490] "Input data" is the textual information of security questions and concerns that users provide to the system.

[0491] A "generative AI model" is an artificial intelligence model that has specialized knowledge about security and analyzes user input data to generate appropriate answers.

[0492] "Data analysis means" is a function that analyzes received input data and generates appropriate answers using a generative AI model.

[0493] The "evaluation means" is a function that evaluates the answers generated by the generative AI model and determines the best answer for the user.

[0494] The "transmission means" is a function for transmitting the optimal answer to the user and displaying it on the terminal.

[0495] The "data collection means" is a function for anonymizing and collecting user input data and generated responses.

[0496] "Visualization means" is a function that analyzes collected data and displays security trends and issues in graphs and charts.

[0497] "Profile Information" refers to personal information about a user, such as their age, occupation, and the device they use.

[0498] "Security measures" are specific actions and settings that users take to protect themselves from cyber attacks and information leaks.

[0499] The system for implementing this invention allows users to input security-related questions or concerns, and generates and provides information to resolve those questions. The major components required to implement this system and their functions are described below.

[0500] 1. A means of receiving input data from the user

[0501] The device (smartphone app) provides a chat-style UI that allows users to enter security questions. For example, the user might enter a question like, "How can I spot a phishing email?"

[0502] 2. A data analysis method that includes a generative AI model that analyzes the received input data.

[0503] The device sends the input question in real time to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the received question and generate an appropriate answer.

[0504] 3. An evaluation tool to evaluate the generated answers and determine the best answer.

[0505] The server evaluates the answers generated by the generative AI model, and if necessary, requests a security expert for review to determine the best answer. This evaluation method improves the accuracy and reliability of the answers.

[0506] 4. A means to send and display the best answer to the user

[0507] The server generates the optimal answer, which is then sent to the user's device and displayed to them, allowing the user to quickly receive practical advice on security measures.

[0508] 5. Data collection method to anonymize and collect user input data and generated responses

[0509] The server anonymizes the user's input data and generated answers and collects them in a database, thereby protecting personal information.

[0510] 6. A visualization tool to analyze collected data and visualize security trends and issues.

[0511] The server analyzes the collected data and visualizes security trends and issues. The visualized data is displayed in graphs and charts, making it easier to understand the overall security situation and issues.

[0512] 7. A method for suggesting appropriate security measures based on user profile information and analytical data

[0513] The server proposes appropriate security measures based on the user's profile information (e.g., age, occupation, device used, etc.) and analysis data, allowing users to implement specific measures tailored to their individual circumstances.

[0514] Examples of concrete examples and prompts

[0515] For example, if a user types the question "How can I spot a phishing email?", the system will process it as follows:

[0516] The user's terminal sends this question to the server.

[0517] The server analyzes this question using a generative AI model and generates the answer, "Phishing emails typically encourage you to click on a link. Be careful of links in suspicious emails."

[0518] The server evaluates the answers and sends the best answer to the terminal.

[0519] The terminal displays this response to the user.

[0520] Example prompt sentence:

[0521] "User Question: How do I spot a phishing email?

[0522] Generate the best security answers:

[0523] In this way, the system of the present invention allows users to instantly acquire security expertise and contributes to strengthening security measures. Furthermore, by analyzing and visualizing the collected data, it is possible to grasp the overall security situation and provide valuable information for taking further measures.

[0524] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0525] Step 1:

[0526] A user inputs a question into a smartphone device. For example, the user inputs a question such as "How can I identify a phishing email?" into a chat-style UI. This input data is sent from the device to the server.

[0527] Step 2:

[0528] The terminal transmits the user's input data in real time to the server, which receives the data and passes it to the data analysis means.

[0529] Step 3:

[0530] The server sends the received input data to the generative AI model, which analyzes the input data based on its pre-trained security expertise and generates an appropriate answer. In this process, the AI ​​model extracts key keywords and context from the input data and generates an answer based on that.

[0531] Step 4:

[0532] The server passes the answers generated by the generative AI model to an evaluation method, which may then be verified by security experts to assess the reliability and appropriateness of the generated answers. Once the evaluation is complete, the best answer is determined.

[0533] Step 5:

[0534] After the server determines the optimal answer, it sends it back to the device, where it is displayed to the user, allowing the user to receive specific security advice.

[0535] Step 6:

[0536] The server anonymizes the user's input data and generated responses and stores them in a data collection tool, processing the data in a way that ensures appropriate protection of personal information.

[0537] Step 7:

[0538] The server uses the collected data to analyze security trends and issues, and displays them in the form of graphs and charts using visualization tools. This visualization data is used to understand the overall security situation and issues.

[0539] Step 8:

[0540] The server then proposes appropriate security measures to the user based on the user's profile information and analytical data, providing personalized advice based on the user's age, occupation, device used, etc.

[0541] The above is a specific flow of the processing steps of the system that realizes the application example.

[0542] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0543] ---

[0544] This invention is a system that enables minors and their guardians with concerns about gender identity and gender identity to receive reliable support. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, more appropriate support can be provided. This system receives input data from the user, analyzes it, recognizes emotions, generates answers, evaluates and transmits them, collects and analyzes data, visualizes it, and makes career suggestions.

[0545] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0546] The server then receives the input data and recognizes the user's emotions using an emotion engine, which analyzes emotions from the user's text input to detect emotional states such as "anxiety" or "excitement."

[0547] The server passes the recognized emotion data to a generative AI model, which then begins analyzing the data. The generative AI model generates appropriate answers to the user's questions based on specialized knowledge of sexual identity and gender. Based on the emotion data, the answer is revised, adding phrases that take emotion into consideration, such as "Don't worry," to provide more appropriate support to the user.

[0548] The server evaluates the generated answers and determines the most appropriate one. If necessary, it requests reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes anxiety, it makes decisions based on the level of urgency, such as increasing the priority of connecting to a specialist.

[0549] The server then sends the best possible answer to the device, which displays it to the user, sometimes including reassuring words and specific guidelines for action, taking into consideration the user's feelings.

[0550] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0551] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0552] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0553] For example:

[0554] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0555] The device sends this text to the server.

[0556] The server analyzes the text using an emotion engine to detect emotions such as "anxiety."

[0557] The server analyzes this text using a generative AI model and generates a response: "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0558] The server evaluates this response and sends it to the terminal.

[0559] The terminal displays this response to the user.

[0560] In this way, users can quickly and accurately obtain the information and support they need, promoting mental health management and early intervention. The system provides emotionally sensitive and reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0561] The processing flow will be explained below.

[0562] Step 1:

[0563] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0564] Step 2:

[0565] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0566] Step 3:

[0567] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0568] Step 4:

[0569] The server passes the received input data to the emotion engine, which then uses natural language processing technology to analyze the user's text data and detect emotions such as "anxiety" or "sadness."

[0570] Step 5:

[0571] The server then passes the recognized emotion data to the generative AI model, which then uses a text analysis algorithm to understand the intent and gist of the questions about gender identity and gender identity.

[0572] Step 6:

[0573] The generative AI model generates answers based on the user's input data and emotional data, such as "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0574] Step 7:

[0575] The server evaluates the generated answers and determines the best answer, automatically filtering and scoring them based on evaluation criteria, and, if necessary, requests review by medical professionals or psychological counselors.

[0576] Step 8:

[0577] The server sends the optimal answer to the device, which then displays it to the user, for example, "Don't worry. It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0578] Step 9:

[0579] The server anonymizes the user's input data and generated responses, collects them in a database, removes personal information, and generates statistics for analysis.

[0580] Step 10:

[0581] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0582] Step 11:

[0583] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0584] Step 12:

[0585] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0586] These are the specific processing steps of the system that combines the emotion engine. This process allows users to quickly and accurately obtain the information and support they need, promoting mental health management and early response.

[0587] Example 2

[0588] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0589] There is a problem that minors and their guardians who are concerned about gender identity and gender identity have difficulty receiving appropriate and reliable support. Furthermore, answers generated without consideration for the user's feelings may further aggravate the user's feelings. Therefore, there is a need for a system that provides fast and accurate support in a way that takes the user's feelings into consideration.

[0590] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0591] In this invention, the server includes: means for receiving input data from a user; emotion recognition means for analyzing the received input data and recognizing the user's emotions; data analysis means including a generative AI model for generating appropriate answers based on the analysis data and emotion data; evaluation means for evaluating the generated answers and determining an optimal answer; means for submitting the answers for expert review and, if necessary, making a decision to correspond to the level of urgency; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; and means for suggesting appropriate career paths based on the user's profile information and analysis data. This makes it possible to provide prompt and appropriate support while taking the user's emotions into consideration.

[0592] A "user" is someone who uses this system to input questions or concerns about gender identity and gender.

[0593] A "terminal" is a device used by a user to communicate with the system, such as a smartphone, tablet, or PC.

[0594] The "server" is a computer system that receives data sent by users and performs analysis, emotion recognition, answer generation, evaluation, transmission, data collection and analysis, visualization, and career suggestions.

[0595] "Emotion recognition means" refers to a technical means for detecting and analyzing emotions from user input data, and includes an emotion engine.

[0596] A "generative AI model" is an artificial intelligence model used for data analysis that generates answers to users' questions and concerns based on specialized knowledge.

[0597] "Data analysis means" refers to technical means, including generative AI models, that generate appropriate answers based on user input data and emotional data.

[0598] The "evaluation means" is a technical means for evaluating the generated answers and determining the optimal answer.

[0599] "Means for sending answers for expert review and, if necessary, making a determination as to the level of urgency" refers to means for sending the generated answers to medical professionals or psychological counselors and for improving the accuracy of the answers as necessary.

[0600] "Data Collection Measures" are technical measures that anonymize and securely collect user input data and generated responses.

[0601] "Visualization tools" are technical means for analyzing collected data and displaying trends and issues related to gender identity and gender in the form of graphs and charts.

[0602] The "career suggestion means" is a technical means for suggesting suitable career paths and educational institutions based on the user's profile information and analysis data.

[0603] This invention is a system designed to provide reliable support to minors and their guardians who are concerned about gender identity and gender identity. The system provides more appropriate support by incorporating an emotion engine that recognizes the user's emotions.

[0604] First, a user uses a device such as a smartphone, tablet, or PC to input questions or concerns about gender identity and gender through a chat-style interface. This interface is designed to be intuitive and easy to use. Consider the example of a user typing, "Recently, I've been feeling uncomfortable with my gender. What should I do?"

[0605] The device then transmits the input data to the server in real time via an API, for example by converting the input text to JSON format and sending an HTTP POST request to the server.

[0606] The server analyzes the received data and uses an emotion engine to recognize the user's emotion. Specifically, the server parses the received JSON data and extracts the text portion. This is then sent to an emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) to analyze the user's emotional state, such as "anxiety."

[0607] The server passes the emotion data to a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an appropriate answer based on the user's question. The generated answer adds emotion-sensitive phrases such as "Don't worry," based on the emotion data. For example, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0608] The server then evaluates the generated answers to determine the best fit. In some cases, it may request reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes "anxiety," it prioritizes connecting with experts.

[0609] The server then sends the best evaluated answer to the device, which then displays it to the user, including reassuring words and specific guidelines for action that take the user's feelings into consideration.

[0610] The server then anonymizes the user's input data and generated responses and securely stores them in a database. This anonymization process ensures the protection of personal information. The server then analyzes the collected data and visualizes trends and issues related to gender identity and gender in the form of graphs and charts.

[0611] Finally, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0612] An example prompt is:

[0613] "I've been feeling uncomfortable with my gender lately. What should I do?"

[0614] "My child is struggling with gender identity, how should I address this?"

[0615] In this way, users can quickly and accurately obtain the information and support they need. The system not only takes into consideration users' feelings and provides a sense of security, but also contributes to improving understanding in society as a whole by analyzing the data.

[0616] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0617] Step 1:

[0618] Users input questions and concerns about gender identity and gender identity through a chat-style interface. The input is text data such as, "Recently, I've been feeling uncomfortable with my gender. What should I do?" The input text data is sent to the device as output.

[0619] Step 2:

[0620] The terminal receives text data entered by the user and sends it to the server in real time. As input, the text data entered in step 1 is provided to the terminal. Specifically, the input text is converted into JSON format and sent to the server using an HTTP POST request. As output, the text data is sent to the server in JSON format.

[0621] Step 3:

[0622] The server receives the received text data and uses an emotion engine to recognize the user's emotions. JSON-formatted text data is provided to the server as input. Specifically, the received data is parsed and the text portion is extracted. An emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) is used to analyze emotions and detect emotional states such as "anxiety" or "excitement." Emotion data is generated as output.

[0623] Step 4:

[0624] The server passes the generated emotion data and text data to a generative AI model, which generates an appropriate answer based on the user's question. The emotion data and text data are provided as input. Specifically, the data is input into a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an answer based on the question. Based on the emotion data, a phrase such as "Don't worry" is added. The generated answer text is obtained as output.

[0625] Step 5:

[0626] The server evaluates the generated answers and determines the best answer. As input, the generated answer text is provided. Specifically, it uses an internal evaluation algorithm to evaluate the quality of the answer and, in some cases, requests an expert for review. In particular, if the emotion engine recognizes the answer as "anxious," it increases the priority of connecting to an expert. As output, the evaluated best answer is determined.

[0627] Step 6:

[0628] The server sends the evaluated best answer to the terminal. The best answer text is provided as input. Specifically, the best answer is sent to the terminal as an HTTP response. The best answer data is sent to the terminal in JSON format as output.

[0629] Step 7:

[0630] The terminal displays the received answer to the user. The answer data sent from the server is provided as input. Specifically, the received data is analyzed and displayed to the user in a chat format. The answer text is displayed to the user as output.

[0631] Step 8:

[0632] The server anonymizes the user's input data and generated answers and securely collects them in a database. As input, the user's input data and generated answer data are provided. Specifically, personal identifying information is removed and the data is anonymized. As output, the anonymized data is stored in a database.

[0633] Step 9:

[0634] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Anonymized data is provided as input. Specifically, the server analyzes the data using data analysis algorithms and generates graphs and charts using visualization tools (e.g., Google Charts, D3.js). The analysis results are displayed as graphs and charts as output.

[0635] Step 10:

[0636] The server proposes suitable career paths and schools based on the user's profile information and analytical data. The user's profile information and analytical data are provided as input. Specifically, the server evaluates information such as the user's age, grade, and school, and generates a list of optimal career paths and educational institutions by referring to the collected data. The server provides information on the proposed career paths and schools as output.

[0637] (Application example 2)

[0638] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0639] Conventional systems have had difficulty providing appropriate support that takes into account emotions to minors and their guardians who have concerns about gender identity or gender. Furthermore, when customer service staff in brick-and-mortar stores deal with customers who have concerns about gender identity or gender, it is difficult to respond appropriately and with consideration for emotions in real time, resulting in a decline in customer satisfaction and trust. Furthermore, real-time emotion recognition and feedback-based responses have been difficult due to the lack of appropriate technology.

[0640] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0641] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting appropriate career paths based on the user's profile information and analysis data; emotion recognition means for recognizing the customer's emotional state; means for generating appropriate answers using the generative AI model based on the emotional state; and display means for providing feedback to staff in real time. This enables real-time, emotion-sensitive support to customers with concerns about gender identity and gender, even in physical stores.

[0642] The "means for receiving input data from a user" refers to an interface and communication device for transmitting text data input by a user through a terminal to a server.

[0643] "Data analysis means" refers to software and hardware that analyzes received input data and generates appropriate answers using a generative AI model.

[0644] An "evaluation means" is a software algorithm that compares and evaluates multiple answer candidates generated by a generative AI model to determine the optimal answer.

[0645] The "means for transmitting and displaying to the user" refers to a device and software that transmits the determined optimal answer to the user's terminal in real time and displays it.

[0646] "Data collection means" refers to technology for anonymizing user input data and generated responses, and collecting data while protecting personal information.

[0647] "Visualization tools" are software that analyzes collected data and displays trends and issues related to gender identity and gender as graphs and charts.

[0648] The "means for suggesting suitable career paths" refers to algorithms and systems that suggest the most suitable career paths and schools for users based on the user's profile information and analysis data.

[0649] "Emotion Recognition Means" means software and AI engines for recognizing the emotional state of a user or customer from input text or voice data.

[0650] The "means for generating appropriate responses" is an algorithm for generating emotion-sensitive responses using a generative AI model based on the perceived emotional state.

[0651] The "display means for providing feedback to staff in real time" refers to a device and software for providing and displaying the generated appropriate response to the wait staff in real time.

[0652] This invention is a system for providing appropriate support to minors and their guardians who are concerned about gender identity and gender identity. This system has functions for receiving input data from users, analyzing it, recognizing emotions, generating answers, evaluating, transmitting, collecting and analyzing data, visualizing it, and making career suggestions. Furthermore, by applying this system to customer service in brick-and-mortar stores, it can realize real-time, emotion-sensitive responses.

[0653] System configuration

[0654] The system is configured as follows:

[0655] 1. A means for receiving input data from the user: Text data entered by the user through a device (such as a smartphone or PC) is sent to the server in real time. The hardware used at this stage includes smartphones, tablets, and PCs.

[0656] 2. Data analysis: The data received from the user is analyzed on the server, and a generative AI model is used to generate an appropriate answer based on the user's input. The software used includes OpenAI's generative models (e.g., GPT-3) and TextBlob.

[0657] 3. Evaluation methods: Comparing multiple candidate answers generated by the generative AI model to determine the best answer. This evaluation can include automated evaluation using algorithms and expert review.

[0658] 4. Means of sending and displaying to the user: The determined optimal answer is sent to the user's terminal in real time and displayed appropriately.

[0659] 5. Data collection method: The data entered by the user and the responses generated are anonymized and collected while protecting personal information. This data is stored for future analysis.

[0660] 6. Visualization methods: Based on the collected data, trends and issues related to gender identity and gender will be visualized using graphs and charts.

[0661] 7. Career Recommendation: Based on the user's profile information and analytical data, the system will suggest suitable career paths for the user, including career counseling and school introductions.

[0662] 8. Emotion Recognition: Analyze the emotional state from the user or customer's input text and use an emotion engine to recognize emotions such as "anxiety" or "relief."

[0663] 9. Means of generating appropriate answers: Based on the perceived emotional state, generative AI models are used to generate emotion-sensitive answers.

[0664] 10. Display means for providing feedback to staff in real time: Smart glasses or head-mounted displays can be used to display the generated appropriate answers to the waiting staff in real time.

[0665] Example of operation

[0666] As an example of a brick-and-mortar application, it works as follows:

[0667] The user inputs a question such as, "I feel uncomfortable with my gender. What should I do?" This question is sent to the server via the device.

[0668] The server receives this input data and recognizes the emotion of "anxiety" through an emotion engine.

[0669] The server uses a generative AI model to generate the answer, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0670] The server evaluates this answer to determine if it is the best answer.

[0671] The generated answers are provided to the wait staff in real time through smart glasses.

[0672] Customer service staff will refer to the answers displayed on the smart glasses and respond appropriately to the customer.

[0673] Prompt Sentence Examples

[0674] "Answer the following question to emotionally anxious users: I feel uncomfortable with my gender. What should I do? Answer:"

[0675] In this way, users can receive fast and reliable support for their mental health care, and brick-and-mortar stores can provide emotionally sensitive customer service.

[0676] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0677] Step 1:

[0678] The user inputs a question, and the terminal receives the input data and sends it to the server.

[0679] Input: The text entered by the user.

[0680] Output: The text data received by the server.

[0681] Specific operation: The user types "I feel uncomfortable with my gender. What should I do?" into the chat-style UI on their smartphone or PC and presses the send button. The device then sends this text data to the server.

[0682] Step 2:

[0683] To analyze the input data received by the server, an emotion engine is used to recognize the user's emotional state.

[0684] Input: Received text data.

[0685] Output: Emotional state (e.g., "anxious," "relieved," etc.).

[0686] What it does: The server analyzes the input text using an emotion recognition algorithm such as TextBlob and detects the emotional state as "anxiety."

[0687] Step 3:

[0688] The server uses a generative AI model based on the perceived emotional state to generate an appropriate response.

[0689] Input: Text data, emotional state.

[0690] Output: The generated answer text.

[0691] Specific operation: The server uses OpenAI's generative model (e.g., GPT-3) and inputs the prompt "For a user who is emotionally anxious, please answer the following question: I feel uncomfortable with my gender. What should I do? Answer:" into the model, generating the answer "Don't worry. It's natural to feel uncomfortable with your gender identity."

[0692] Step 4:

[0693] The server evaluates the generated answers and determines the best answer.

[0694] Input: Multiple generated answer candidates.

[0695] Output: The best answer.

[0696] What it does: The server runs the generated answers through a rating algorithm to select the most appropriate answer, adding expert review if necessary.

[0697] Step 5:

[0698] The server sends the best answer to the user's device and displays it.

[0699] Input: Best answer.

[0700] Output: The answer displayed on the user's terminal.

[0701] Specific operation: The server sends the best answer to the user's device, and the device displays the answer on the screen.

[0702] Step 6:

[0703] The server anonymizes the user's input data and generated answers and collects them in a database.

[0704] Input: User input data, generated answers.

[0705] Output: Anonymized data.

[0706] What it does: The server uses a data anonymization algorithm to remove personally identifiable information such as your name and address, generating anonymized data that is then stored in a database.

[0707] Step 7:

[0708] The server analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[0709] Input: Anonymized data.

[0710] Output: Visualized graphs and charts.

[0711] What it does: The server uses data analysis software to analyze the collected data to find trends and issues, and displays the results in graphs and charts.

[0712] Step 8:

[0713] The server suggests suitable paths based on the user's profile information and analytical data.

[0714] Input: User profile information, analytics data.

[0715] Output:Career suggestions.

[0716] Specific operation: The server uses a career suggestion algorithm to suggest suitable career paths and schools to the user based on profile information such as the user's age, grade, and current school, as well as the results of data analysis.

[0717] Step 9:

[0718] The server uses the emotion recognition means to recognize the emotional state of the customer in the physical store.

[0719] Input: Customer statements and behavior data in physical stores.

[0720] Output: Emotional state.

[0721] Specific operation: The server applies an emotion recognition algorithm to data input from microphones and cameras installed in physical stores to recognize the customer's emotional state.

[0722] Step 10:

[0723] The server uses generative AI models to generate appropriate responses based on emotional state and provide feedback to staff in real time.

[0724] Input: Emotional state, customer question.

[0725] Output: Feedback display to staff.

[0726] How it works: The server inputs prompts into the generative AI model based on the customer's emotional state and question, and displays the generated answers in real time on smart glasses or a head-mounted display.

[0727] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0728] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0730] [Third embodiment]

[0731] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0732] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0733] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0734] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0735] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0736] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0737] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0738] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0739] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0740] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0741] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0742] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0743] The following describes a "form for carrying out the invention."

[0744] ---

[0745] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0746] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0747] The server then receives the input data and analyzes it using a generative AI model, which uses specialized knowledge about gender identity and gender to generate appropriate answers to the user's questions.

[0748] The server evaluates the generated answers, determines the best answer, and, if necessary, requests review from medical professionals or psychological counselors to improve the accuracy of the answer.

[0749] The server then sends the best answer to the device, which then displays it to the user, allowing the user to quickly receive the information or support they need.

[0750] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0751] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0752] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0753] For example:

[0754] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0755] The device sends this text to the server.

[0756] The server analyzes this text using a generative AI model and generates a response that reads, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0757] The server evaluates this response and sends it to the terminal.

[0758] The terminal displays this response to the user.

[0759] In this way, users can easily obtain support regarding gender identity and gender issues, promoting mental health management and early intervention. This system provides reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0760] The processing flow will be explained below.

[0761] Step 1:

[0762] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0763] Step 2:

[0764] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0765] Step 3:

[0766] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0767] Step 4:

[0768] The server passes the received input data to the generative AI model, which then uses a text analysis algorithm to understand the intent of the input and the gist of the question.

[0769] Step 5:

[0770] The generative AI model generates an answer based on the user's input data, such as "It is natural to feel uncomfortable about your gender identity."

[0771] Step 6:

[0772] The server evaluates the generated answers, automatically filtering and scoring them based on evaluation criteria, and, if necessary, sending them to medical professionals or psychological counselors for review.

[0773] Step 7:

[0774] The server determines the best answer based on the scoring results if review is not required, or expert feedback if required.

[0775] Step 8:

[0776] The server sends the best answer to the device, including contact details for appropriate experts and additional resources if necessary.

[0777] Step 9:

[0778] The device displays the answer received from the server to the user. For example, it displays, "It is natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0779] Step 10:

[0780] The server anonymizes the user's input data and generated answers, stores them in a database, removes personal information, and generates statistics for analysis.

[0781] Step 11:

[0782] The server analyzes the stored data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0783] Step 12:

[0784] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0785] Step 13:

[0786] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0787] The above are the specific processes and actions at each step. This process will enable minors and their guardians to receive prompt and appropriate support regarding issues related to gender identity and gender.

[0788] Example 1

[0789] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0790] There is a lack of a system that allows minors and their guardians who are concerned about gender identity and gender issues to receive reliable support quickly and safely. In particular, there are difficulties in providing information in real time, protecting personal information, and connecting with appropriate medical professionals and psychological counselors.

[0791] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0792] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting an appropriate career path based on the user's profile information and analysis data; and means for requesting reviews from optimal medical professionals or psychological counselors based on the user's input data. This allows users to receive reliable support in real time, ensures the protection of their personal information, and enables smooth collaboration with appropriate professionals.

[0793] A "user" is someone who inputs questions or concerns about gender identity or sexual identity through a chat-style UI.

[0794] A "terminal" is a device used by a user that provides a chat-style UI for inputting questions and concerns and transmits the input data to a server.

[0795] The "server" is a system that receives input data sent by the user, analyzes it, uses a generative AI model to generate an appropriate answer, and sends it to the user.

[0796] A "generative AI model" is an artificial intelligence model that analyzes data based on specialized knowledge about sexual identity and gender and generates appropriate answers.

[0797] A "prompt" is a textual instruction used to pass input data to a generative AI model.

[0798] "Data analysis means" means a means for analyzing input data received from a user using a generative AI model.

[0799] "Evaluation means" refers to a means for evaluating the answers generated by a generative AI model, requesting expert review if necessary, and determining the optimal answer.

[0800] The "data collection means" is a means for anonymizing the user's input data and generated responses and collecting them in a database.

[0801] "Visualization tools" are means of analyzing collected data and displaying trends and issues related to sexual identity and gender in the form of graphs and charts.

[0802] The "career suggestion means" is a means for suggesting suitable career paths and schools based on the user's profile information and analysis data.

[0803] The "review request means" is a means for requesting a review from the most suitable medical expert or psychological counselor based on the data input by the user.

[0804] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[0805] Users use a chat-style user interface (UI) to input questions and concerns about gender identity and gender. Devices that provide this UI include PCs, smartphones, and tablets. Specifically, users input questions such as, "I feel uncomfortable with my gender. What should I do?"

[0806] The device sends the entered questions to the server in real time, using a secure protocol (e.g., HTTPS) for data transmission.

[0807] The server uses a generative AI model to analyze the received input data. This generative AI model generates an answer based on specialized knowledge about gender identity and gender. The server first generates a prompt. The prompt contains the text entered by the user and may take the form, for example, "The user is asking the following question: I feel uncomfortable with my gender. What should I do?"

[0808] The generative AI model analyzes this prompt and generates an appropriate response, such as, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0809] The server evaluates the generated answers and, if necessary, requests review from medical professionals or psychological counselors. Once the optimal answer is determined, the server sends it to the device. The device displays the answer to the user and quickly provides the necessary information and support.

[0810] The server also anonymizes the user's input data and generated answers and collects them in a database. The anonymized data is stored in a manner that ensures the protection of personal information.

[0811] The collected data is then analyzed by the server, and trends and issues related to gender identity and gender are visualized using graphs and charts, and presented as information to deepen understanding in society as a whole.

[0812] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that is right for them.

[0813] For example, a user enters a question such as, "I feel uncomfortable with my gender. What should I do?" and the device sends this to the server. The server analyzes the text using a generative AI model and generates a response such as, "It's natural to feel uncomfortable with your gender identity. We recommend that you first consult with an expert." The server evaluates this response, and after expert review, sends the optimal response to the device, which then displays it to the user. This series of actions allows the user to receive fast and reliable support.

[0814] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0815] Step 1:

[0816] Users use a chat-style user interface (UI) to input questions or concerns about gender identity and gender identity. The input data is in text format and includes content such as, "I feel uncomfortable with my gender. What should I do?" The input text data is passed to the device, and the device is ready to proceed to the next step.

[0817] Step 2:

[0818] The device sends the text data entered by the user to the server in real time. A secure protocol (e.g., HTTPS) is used to transmit the data, ensuring the integrity and confidentiality of the data during transmission. The input data is passed to the server in the following format: "I'm feeling uncomfortable with my gender. What should I do?"

[0819] Step 3:

[0820] The server receives the input data. Since the received data cannot be used for analysis as is, it first generates a prompt to be passed to the generative AI model. The prompt is processed into a format such as "The user is asking the following question: I feel uncomfortable with my gender. What should I do?" This prompt is then used to proceed to the next step.

[0821] Step 4:

[0822] The server passes the prompt to the generative AI model for analysis. The generative AI model analyzes the prompt based on specialized knowledge about gender identity and gender, and generates an appropriate response. For example, the response output might be, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[0823] Step 5:

[0824] The server evaluates the answers generated by the generative AI model, checks whether the generated answers are appropriate, and, if necessary, requests review by medical professionals or psychological counselors. Experts can check and correct the accuracy and appropriateness of the answers, resulting in high-quality answers. For example, experts may add additional information such as, "If you would like a more detailed consultation, you can make an appointment using the link below."

[0825] Step 6:

[0826] The server then sends the best answer after evaluation to the device. This is again done using a secure protocol. The data sent to the device will be in the form of a message saying, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist. If you would like a more detailed consultation, you can make an appointment using the link below."

[0827] Step 7:

[0828] The device then displays the received response data to the user, allowing them to quickly receive the appropriate answer to their question and, if necessary, to view links to further support.

[0829] Step 8:

[0830] The server anonymizes the user's input data and generated answers and collects them in a database. The anonymization process removes any personally identifiable information, and the collected data is stored in a manner that complies with the Personal Information Protection Act. This anonymized data is used for the next analysis step.

[0831] Step 9:

[0832] The server analyzes the collected anonymized data, and the results are used to identify trends and issues related to gender identity and gender, and are visualized in graphs and charts, providing useful information for policymakers and researchers.

[0833] Step 10:

[0834] The server suggests suitable career paths and schools based on the user's profile information (e.g., age, grade, current school, etc.) and analysis results. These career suggestions help users make the best choices for themselves. The results of the career suggestions are also sent to the user's device, allowing the user to view them and make career decisions.

[0835] (Application example 1)

[0836] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0837] In today's information society, security knowledge and countermeasures are becoming increasingly important. However, many users lack adequate security knowledge and are vulnerable to threats such as phishing emails and the leakage of personal information. Furthermore, access to security experts with specialized knowledge is generally difficult, making it difficult for users to solve problems on their own. This creates a need for a system that provides efficient and reliable security support.

[0838] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0839] In this invention, the server includes means for receiving input data from a user, data analysis means including a generative AI model that analyzes the received input data, evaluation means for evaluating answers generated by the generative AI model to determine the optimal answer, data collection means for anonymizing and collecting the user's input data and the generated answers, visualization means for analyzing the collected data and visualizing security trends and issues, and means for proposing appropriate security measures based on the user's profile information and analysis data. This allows users to easily receive professional security support, enabling the protection of personal information and the strengthening of security measures.

[0840] "User" means an individual or entity that uses the System and receives security-related support.

[0841] "Input data" is the textual information of security questions and concerns that users provide to the system.

[0842] A "generative AI model" is an artificial intelligence model that has specialized knowledge about security and analyzes user input data to generate appropriate answers.

[0843] "Data analysis means" is a function that analyzes received input data and generates appropriate answers using a generative AI model.

[0844] The "evaluation means" is a function that evaluates the answers generated by the generative AI model and determines the best answer for the user.

[0845] The "transmission means" is a function for transmitting the optimal answer to the user and displaying it on the terminal.

[0846] The "data collection means" is a function for anonymizing and collecting user input data and generated responses.

[0847] "Visualization means" is a function that analyzes collected data and displays security trends and issues in graphs and charts.

[0848] "Profile Information" refers to personal information about a user, such as their age, occupation, and the device they use.

[0849] "Security measures" are specific actions and settings that users take to protect themselves from cyber attacks and information leaks.

[0850] The system for implementing this invention allows users to input security-related questions or concerns, and generates and provides information to resolve those questions. The major components required to implement this system and their functions are described below.

[0851] 1. A means of receiving input data from the user

[0852] The device (smartphone app) provides a chat-style UI that allows users to enter security questions. For example, the user might enter a question like, "How can I spot a phishing email?"

[0853] 2. A data analysis method that includes a generative AI model that analyzes the received input data.

[0854] The device sends the input question in real time to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the received question and generate an appropriate answer.

[0855] 3. An evaluation tool to evaluate the generated answers and determine the best answer.

[0856] The server evaluates the answers generated by the generative AI model, and if necessary, requests a security expert for review to determine the best answer. This evaluation method improves the accuracy and reliability of the answers.

[0857] 4. A means to send and display the best answer to the user

[0858] The server generates the optimal answer, which is then sent to the user's device and displayed to them, allowing the user to quickly receive practical advice on security measures.

[0859] 5. Data collection method to anonymize and collect user input data and generated responses

[0860] The server anonymizes the user's input data and generated answers and collects them in a database, thereby protecting personal information.

[0861] 6. A visualization tool to analyze collected data and visualize security trends and issues.

[0862] The server analyzes the collected data and visualizes security trends and issues. The visualized data is displayed in graphs and charts, making it easier to understand the overall security situation and issues.

[0863] 7. A method for suggesting appropriate security measures based on user profile information and analytical data

[0864] The server proposes appropriate security measures based on the user's profile information (e.g., age, occupation, device used, etc.) and analysis data, allowing users to implement specific measures tailored to their individual circumstances.

[0865] Examples of concrete examples and prompts

[0866] For example, if a user types the question "How can I spot a phishing email?", the system will process it as follows:

[0867] The user's terminal sends this question to the server.

[0868] The server analyzes this question using a generative AI model and generates the answer, "Phishing emails typically encourage you to click on a link. Be careful of links in suspicious emails."

[0869] The server evaluates the answers and sends the best answer to the terminal.

[0870] The terminal displays this response to the user.

[0871] Example prompt sentence:

[0872] "User Question: How do I spot a phishing email?

[0873] Generate the best security answers:

[0874] In this way, the system of the present invention allows users to instantly acquire security expertise and contributes to strengthening security measures. Furthermore, by analyzing and visualizing the collected data, it is possible to grasp the overall security situation and provide valuable information for taking further measures.

[0875] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0876] Step 1:

[0877] A user inputs a question into a smartphone device. For example, the user inputs a question such as "How can I identify a phishing email?" into a chat-style UI. This input data is sent from the device to the server.

[0878] Step 2:

[0879] The terminal transmits the user's input data in real time to the server, which receives the data and passes it to the data analysis means.

[0880] Step 3:

[0881] The server sends the received input data to the generative AI model, which analyzes the input data based on its pre-trained security expertise and generates an appropriate answer. In this process, the AI ​​model extracts key keywords and context from the input data and generates an answer based on that.

[0882] Step 4:

[0883] The server passes the answers generated by the generative AI model to an evaluation method, which may then be verified by security experts to assess the reliability and appropriateness of the generated answers. Once the evaluation is complete, the best answer is determined.

[0884] Step 5:

[0885] After the server determines the optimal answer, it sends it back to the device, where it is displayed to the user, allowing the user to receive specific security advice.

[0886] Step 6:

[0887] The server anonymizes the user's input data and generated responses and stores them in a data collection tool, processing the data in a way that ensures appropriate protection of personal information.

[0888] Step 7:

[0889] The server uses the collected data to analyze security trends and issues, and displays them in the form of graphs and charts using visualization tools. This visualization data is used to understand the overall security situation and issues.

[0890] Step 8:

[0891] The server then proposes appropriate security measures to the user based on the user's profile information and analytical data, providing personalized advice based on the user's age, occupation, device used, etc.

[0892] The above is a specific flow of the processing steps of the system that realizes the application example.

[0893] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0894] ---

[0895] This invention is a system that enables minors and their guardians with concerns about gender identity and gender identity to receive reliable support. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, more appropriate support can be provided. This system receives input data from the user, analyzes it, recognizes emotions, generates answers, evaluates and transmits them, collects and analyzes data, visualizes it, and makes career suggestions.

[0896] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[0897] The server then receives the input data and recognizes the user's emotions using an emotion engine, which analyzes emotions from the user's text input to detect emotional states such as "anxiety" or "excitement."

[0898] The server passes the recognized emotion data to a generative AI model, which then begins analyzing the data. The generative AI model generates appropriate answers to the user's questions based on specialized knowledge of sexual identity and gender. Based on the emotion data, the answer is revised, adding phrases that take emotion into consideration, such as "Don't worry," to provide more appropriate support to the user.

[0899] The server evaluates the generated answers and determines the most appropriate one. If necessary, it requests reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes anxiety, it makes decisions based on the level of urgency, such as increasing the priority of connecting to a specialist.

[0900] The server then sends the best possible answer to the device, which displays it to the user, sometimes including reassuring words and specific guidelines for action, taking into consideration the user's feelings.

[0901] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[0902] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[0903] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0904] For example:

[0905] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[0906] The device sends this text to the server.

[0907] The server analyzes the text using an emotion engine to detect emotions such as "anxiety."

[0908] The server analyzes this text using a generative AI model and generates a response: "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0909] The server evaluates this response and sends it to the terminal.

[0910] The terminal displays this response to the user.

[0911] In this way, users can quickly and accurately obtain the information and support they need, promoting mental health management and early intervention. The system provides emotionally sensitive and reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[0912] The processing flow will be explained below.

[0913] Step 1:

[0914] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[0915] Step 2:

[0916] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[0917] Step 3:

[0918] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[0919] Step 4:

[0920] The server passes the received input data to the emotion engine, which then uses natural language processing technology to analyze the user's text data and detect emotions such as "anxiety" or "sadness."

[0921] Step 5:

[0922] The server then passes the recognized emotion data to the generative AI model, which then uses a text analysis algorithm to understand the intent and gist of the questions about gender identity and gender identity.

[0923] Step 6:

[0924] The generative AI model generates answers based on the user's input data and emotional data, such as "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0925] Step 7:

[0926] The server evaluates the generated answers and determines the best answer, automatically filtering and scoring them based on evaluation criteria, and, if necessary, requests review by medical professionals or psychological counselors.

[0927] Step 8:

[0928] The server sends the optimal answer to the device, which then displays it to the user, for example, "Don't worry. It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[0929] Step 9:

[0930] The server anonymizes the user's input data and generated responses, collects them in a database, removes personal information, and generates statistics for analysis.

[0931] Step 10:

[0932] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[0933] Step 11:

[0934] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[0935] Step 12:

[0936] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[0937] These are the specific processing steps of the system that combines the emotion engine. This process allows users to quickly and accurately obtain the information and support they need, promoting mental health management and early response.

[0938] Example 2

[0939] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0940] There is a problem that minors and their guardians who are concerned about gender identity and gender identity have difficulty receiving appropriate and reliable support. Furthermore, answers generated without consideration for the user's feelings may further aggravate the user's feelings. Therefore, there is a need for a system that provides fast and accurate support in a way that takes the user's feelings into consideration.

[0941] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0942] In this invention, the server includes: means for receiving input data from a user; emotion recognition means for analyzing the received input data and recognizing the user's emotions; data analysis means including a generative AI model for generating appropriate answers based on the analysis data and emotion data; evaluation means for evaluating the generated answers and determining an optimal answer; means for submitting the answers for expert review and, if necessary, making a decision to correspond to the level of urgency; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; and means for suggesting appropriate career paths based on the user's profile information and analysis data. This makes it possible to provide prompt and appropriate support while taking the user's emotions into consideration.

[0943] A "user" is someone who uses this system to input questions or concerns about gender identity and gender.

[0944] A "terminal" is a device used by a user to communicate with the system, such as a smartphone, tablet, or PC.

[0945] The "server" is a computer system that receives data sent by users and performs analysis, emotion recognition, answer generation, evaluation, transmission, data collection and analysis, visualization, and career suggestions.

[0946] "Emotion recognition means" refers to a technical means for detecting and analyzing emotions from user input data, and includes an emotion engine.

[0947] A "generative AI model" is an artificial intelligence model used for data analysis that generates answers to users' questions and concerns based on specialized knowledge.

[0948] "Data analysis means" refers to technical means, including generative AI models, that generate appropriate answers based on user input data and emotional data.

[0949] The "evaluation means" is a technical means for evaluating the generated answers and determining the optimal answer.

[0950] "Means for sending answers for expert review and, if necessary, making a determination as to the level of urgency" refers to means for sending the generated answers to medical professionals or psychological counselors and for improving the accuracy of the answers as necessary.

[0951] "Data Collection Measures" are technical measures that anonymize and securely collect user input data and generated responses.

[0952] "Visualization tools" are technical means for analyzing collected data and displaying trends and issues related to gender identity and gender in the form of graphs and charts.

[0953] The "career suggestion means" is a technical means for suggesting suitable career paths and educational institutions based on the user's profile information and analysis data.

[0954] This invention is a system designed to provide reliable support to minors and their guardians who are concerned about gender identity and gender identity. The system provides more appropriate support by incorporating an emotion engine that recognizes the user's emotions.

[0955] First, a user uses a device such as a smartphone, tablet, or PC to input questions or concerns about gender identity and gender through a chat-style interface. This interface is designed to be intuitive and easy to use. Consider the example of a user typing, "Recently, I've been feeling uncomfortable with my gender. What should I do?"

[0956] The device then transmits the input data to the server in real time via an API, for example by converting the input text to JSON format and sending an HTTP POST request to the server.

[0957] The server analyzes the received data and uses an emotion engine to recognize the user's emotion. Specifically, the server parses the received JSON data and extracts the text portion. This is then sent to an emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) to analyze the user's emotional state, such as "anxiety."

[0958] The server passes the emotion data to a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an appropriate answer based on the user's question. The generated answer adds emotion-sensitive phrases such as "Don't worry," based on the emotion data. For example, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[0959] The server then evaluates the generated answers to determine the best fit. In some cases, it may request reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes "anxiety," it prioritizes connecting with experts.

[0960] The server then sends the best evaluated answer to the device, which then displays it to the user, including reassuring words and specific guidelines for action that take the user's feelings into consideration.

[0961] The server then anonymizes the user's input data and generated responses and securely stores them in a database. This anonymization process ensures the protection of personal information. The server then analyzes the collected data and visualizes trends and issues related to gender identity and gender in the form of graphs and charts.

[0962] Finally, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[0963] An example prompt is:

[0964] "I've been feeling uncomfortable with my gender lately. What should I do?"

[0965] "My child is struggling with gender identity, how should I address this?"

[0966] In this way, users can quickly and accurately obtain the information and support they need. The system not only takes into consideration users' feelings and provides a sense of security, but also contributes to improving understanding in society as a whole by analyzing the data.

[0967] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0968] Step 1:

[0969] Users input questions and concerns about gender identity and gender identity through a chat-style interface. The input is text data such as, "Recently, I've been feeling uncomfortable with my gender. What should I do?" The input text data is sent to the device as output.

[0970] Step 2:

[0971] The terminal receives text data entered by the user and sends it to the server in real time. As input, the text data entered in step 1 is provided to the terminal. Specifically, the input text is converted into JSON format and sent to the server using an HTTP POST request. As output, the text data is sent to the server in JSON format.

[0972] Step 3:

[0973] The server receives the received text data and uses an emotion engine to recognize the user's emotions. JSON-formatted text data is provided to the server as input. Specifically, the received data is parsed and the text portion is extracted. An emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) is used to analyze emotions and detect emotional states such as "anxiety" or "excitement." Emotion data is generated as output.

[0974] Step 4:

[0975] The server passes the generated emotion data and text data to a generative AI model, which generates an appropriate answer based on the user's question. The emotion data and text data are provided as input. Specifically, the data is input into a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an answer based on the question. Based on the emotion data, a phrase such as "Don't worry" is added. The generated answer text is obtained as output.

[0976] Step 5:

[0977] The server evaluates the generated answers and determines the best answer. As input, the generated answer text is provided. Specifically, it uses an internal evaluation algorithm to evaluate the quality of the answer and, in some cases, requests an expert for review. In particular, if the emotion engine recognizes the answer as "anxious," it increases the priority of connecting to an expert. As output, the evaluated best answer is determined.

[0978] Step 6:

[0979] The server sends the evaluated best answer to the terminal. The best answer text is provided as input. Specifically, the best answer is sent to the terminal as an HTTP response. The best answer data is sent to the terminal in JSON format as output.

[0980] Step 7:

[0981] The terminal displays the received answer to the user. The answer data sent from the server is provided as input. Specifically, the received data is analyzed and displayed to the user in a chat format. The answer text is displayed to the user as output.

[0982] Step 8:

[0983] The server anonymizes the user's input data and generated answers and securely collects them in a database. As input, the user's input data and generated answer data are provided. Specifically, personal identifying information is removed and the data is anonymized. As output, the anonymized data is stored in a database.

[0984] Step 9:

[0985] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Anonymized data is provided as input. Specifically, the server analyzes the data using data analysis algorithms and generates graphs and charts using visualization tools (e.g., Google Charts, D3.js). The analysis results are displayed as graphs and charts as output.

[0986] Step 10:

[0987] The server proposes suitable career paths and schools based on the user's profile information and analytical data. The user's profile information and analytical data are provided as input. Specifically, the server evaluates information such as the user's age, grade, and school, and generates a list of optimal career paths and educational institutions by referring to the collected data. The server provides information on the proposed career paths and schools as output.

[0988] (Application example 2)

[0989] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0990] Conventional systems have had difficulty providing appropriate support that takes into account emotions to minors and their guardians who have concerns about gender identity or gender. Furthermore, when customer service staff in brick-and-mortar stores deal with customers who have concerns about gender identity or gender, it is difficult to respond appropriately and with consideration for emotions in real time, resulting in a decline in customer satisfaction and trust. Furthermore, real-time emotion recognition and feedback-based responses have been difficult due to the lack of appropriate technology.

[0991] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0992] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting appropriate career paths based on the user's profile information and analysis data; emotion recognition means for recognizing the customer's emotional state; means for generating appropriate answers using the generative AI model based on the emotional state; and display means for providing feedback to staff in real time. This enables real-time, emotion-sensitive support to customers with concerns about gender identity and gender, even in physical stores.

[0993] The "means for receiving input data from a user" refers to an interface and communication device for transmitting text data input by a user through a terminal to a server.

[0994] "Data analysis means" refers to software and hardware that analyzes received input data and generates appropriate answers using a generative AI model.

[0995] An "evaluation means" is a software algorithm that compares and evaluates multiple answer candidates generated by a generative AI model to determine the optimal answer.

[0996] The "means for transmitting and displaying to the user" refers to a device and software that transmits the determined optimal answer to the user's terminal in real time and displays it.

[0997] "Data collection means" refers to technology for anonymizing user input data and generated responses, and collecting data while protecting personal information.

[0998] "Visualization tools" are software that analyzes collected data and displays trends and issues related to gender identity and gender as graphs and charts.

[0999] The "means for suggesting suitable career paths" refers to algorithms and systems that suggest the most suitable career paths and schools for users based on the user's profile information and analysis data.

[1000] "Emotion Recognition Means" means software and AI engines for recognizing the emotional state of a user or customer from input text or voice data.

[1001] The "means for generating appropriate responses" is an algorithm for generating emotion-sensitive responses using a generative AI model based on the perceived emotional state.

[1002] The "display means for providing feedback to staff in real time" refers to a device and software for providing and displaying the generated appropriate response to the wait staff in real time.

[1003] This invention is a system for providing appropriate support to minors and their guardians who are concerned about gender identity and gender identity. This system has functions for receiving input data from users, analyzing it, recognizing emotions, generating answers, evaluating, transmitting, collecting and analyzing data, visualizing it, and making career suggestions. Furthermore, by applying this system to customer service in brick-and-mortar stores, it can realize real-time, emotion-sensitive responses.

[1004] System configuration

[1005] The system is configured as follows:

[1006] 1. A means for receiving input data from the user: Text data entered by the user through a device (such as a smartphone or PC) is sent to the server in real time. The hardware used at this stage includes smartphones, tablets, and PCs.

[1007] 2. Data analysis: The data received from the user is analyzed on the server, and a generative AI model is used to generate an appropriate answer based on the user's input. The software used includes OpenAI's generative models (e.g., GPT-3) and TextBlob.

[1008] 3. Evaluation methods: Comparing multiple candidate answers generated by the generative AI model to determine the best answer. This evaluation can include automated evaluation using algorithms and expert review.

[1009] 4. Means of sending and displaying to the user: The determined optimal answer is sent to the user's terminal in real time and displayed appropriately.

[1010] 5. Data collection method: The data entered by the user and the responses generated are anonymized and collected while protecting personal information. This data is stored for future analysis.

[1011] 6. Visualization methods: Based on the collected data, trends and issues related to gender identity and gender will be visualized using graphs and charts.

[1012] 7. Career Recommendation: Based on the user's profile information and analytical data, the system will suggest suitable career paths for the user, including career counseling and school introductions.

[1013] 8. Emotion Recognition: Analyze the emotional state from the user or customer's input text and use an emotion engine to recognize emotions such as "anxiety" or "relief."

[1014] 9. Means of generating appropriate answers: Based on the perceived emotional state, generative AI models are used to generate emotion-sensitive answers.

[1015] 10. Display means for providing feedback to staff in real time: Smart glasses or head-mounted displays can be used to display the generated appropriate answers to the waiting staff in real time.

[1016] Example of operation

[1017] As an example of a brick-and-mortar application, it works as follows:

[1018] The user inputs a question such as, "I feel uncomfortable with my gender. What should I do?" This question is sent to the server via the device.

[1019] The server receives this input data and recognizes the emotion of "anxiety" through an emotion engine.

[1020] The server uses a generative AI model to generate the answer, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[1021] The server evaluates this answer to determine if it is the best answer.

[1022] The generated answers are provided to the wait staff in real time through smart glasses.

[1023] Customer service staff will refer to the answers displayed on the smart glasses and respond appropriately to the customer.

[1024] Prompt Sentence Examples

[1025] "Answer the following question to emotionally anxious users: I feel uncomfortable with my gender. What should I do? Answer:"

[1026] In this way, users can receive fast and reliable support for their mental health care, and brick-and-mortar stores can provide emotionally sensitive customer service.

[1027] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1028] Step 1:

[1029] The user inputs a question, and the terminal receives the input data and sends it to the server.

[1030] Input: The text entered by the user.

[1031] Output: The text data received by the server.

[1032] Specific operation: The user types "I feel uncomfortable with my gender. What should I do?" into the chat-style UI on their smartphone or PC and presses the send button. The device then sends this text data to the server.

[1033] Step 2:

[1034] To analyze the input data received by the server, an emotion engine is used to recognize the user's emotional state.

[1035] Input: Received text data.

[1036] Output: Emotional state (e.g., "anxious," "relieved," etc.).

[1037] What it does: The server analyzes the input text using an emotion recognition algorithm such as TextBlob and detects the emotional state as "anxiety."

[1038] Step 3:

[1039] The server uses a generative AI model based on the perceived emotional state to generate an appropriate response.

[1040] Input: Text data, emotional state.

[1041] Output: The generated answer text.

[1042] Specific operation: The server uses OpenAI's generative model (e.g., GPT-3) and inputs the prompt "For a user who is emotionally anxious, please answer the following question: I feel uncomfortable with my gender. What should I do? Answer:" into the model, generating the answer "Don't worry. It's natural to feel uncomfortable with your gender identity."

[1043] Step 4:

[1044] The server evaluates the generated answers and determines the best answer.

[1045] Input: Multiple generated answer candidates.

[1046] Output: The best answer.

[1047] What it does: The server runs the generated answers through a rating algorithm to select the most appropriate answer, adding expert review if necessary.

[1048] Step 5:

[1049] The server sends the best answer to the user's device and displays it.

[1050] Input: Best answer.

[1051] Output: The answer displayed on the user's terminal.

[1052] Specific operation: The server sends the best answer to the user's device, and the device displays the answer on the screen.

[1053] Step 6:

[1054] The server anonymizes the user's input data and generated answers and collects them in a database.

[1055] Input: User input data, generated answers.

[1056] Output: Anonymized data.

[1057] What it does: The server uses a data anonymization algorithm to remove personally identifiable information such as your name and address, generating anonymized data that is then stored in a database.

[1058] Step 7:

[1059] The server analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1060] Input: Anonymized data.

[1061] Output: Visualized graphs and charts.

[1062] What it does: The server uses data analysis software to analyze the collected data to find trends and issues, and displays the results in graphs and charts.

[1063] Step 8:

[1064] The server suggests suitable paths based on the user's profile information and analytical data.

[1065] Input: User profile information, analytics data.

[1066] Output:Career suggestions.

[1067] Specific operation: The server uses a career suggestion algorithm to suggest suitable career paths and schools to the user based on profile information such as the user's age, grade, and current school, as well as the results of data analysis.

[1068] Step 9:

[1069] The server uses the emotion recognition means to recognize the emotional state of the customer in the physical store.

[1070] Input: Customer statements and behavior data in physical stores.

[1071] Output: Emotional state.

[1072] Specific operation: The server applies an emotion recognition algorithm to data input from microphones and cameras installed in physical stores to recognize the customer's emotional state.

[1073] Step 10:

[1074] The server uses generative AI models to generate appropriate responses based on emotional state and provide feedback to staff in real time.

[1075] Input: Emotional state, customer question.

[1076] Output: Feedback display to staff.

[1077] How it works: The server inputs prompts into the generative AI model based on the customer's emotional state and question, and displays the generated answers in real time on smart glasses or a head-mounted display.

[1078] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1079] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1080] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1081] [Fourth embodiment]

[1082] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1083] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1084] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1085] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1086] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1087] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1088] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1089] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1090] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1091] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1092] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1093] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1094] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1095] The following describes a "form for carrying out the invention."

[1096] ---

[1097] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[1098] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[1099] The server then receives the input data and analyzes it using a generative AI model, which uses specialized knowledge about gender identity and gender to generate appropriate answers to the user's questions.

[1100] The server evaluates the generated answers, determines the best answer, and, if necessary, requests review from medical professionals or psychological counselors to improve the accuracy of the answer.

[1101] The server then sends the best answer to the device, which then displays it to the user, allowing the user to quickly receive the information or support they need.

[1102] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[1103] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[1104] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[1105] For example:

[1106] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[1107] The device sends this text to the server.

[1108] The server analyzes this text using a generative AI model and generates a response that reads, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[1109] The server evaluates this response and sends it to the terminal.

[1110] The terminal displays this response to the user.

[1111] In this way, users can easily obtain support regarding gender identity and gender issues, promoting mental health management and early intervention. This system provides reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[1112] The processing flow will be explained below.

[1113] Step 1:

[1114] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[1115] Step 2:

[1116] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[1117] Step 3:

[1118] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[1119] Step 4:

[1120] The server passes the received input data to the generative AI model, which then uses a text analysis algorithm to understand the intent of the input and the gist of the question.

[1121] Step 5:

[1122] The generative AI model generates an answer based on the user's input data, such as "It is natural to feel uncomfortable about your gender identity."

[1123] Step 6:

[1124] The server evaluates the generated answers, automatically filtering and scoring them based on evaluation criteria, and, if necessary, sending them to medical professionals or psychological counselors for review.

[1125] Step 7:

[1126] The server determines the best answer based on the scoring results if review is not required, or expert feedback if required.

[1127] Step 8:

[1128] The server sends the best answer to the device, including contact details for appropriate experts and additional resources if necessary.

[1129] Step 9:

[1130] The device displays the answer received from the server to the user. For example, it displays, "It is natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[1131] Step 10:

[1132] The server anonymizes the user's input data and generated answers, stores them in a database, removes personal information, and generates statistics for analysis.

[1133] Step 11:

[1134] The server analyzes the stored data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[1135] Step 12:

[1136] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[1137] Step 13:

[1138] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[1139] The above are the specific processes and actions at each step. This process will enable minors and their guardians to receive prompt and appropriate support regarding issues related to gender identity and gender.

[1140] Example 1

[1141] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1142] There is a lack of a system that allows minors and their guardians who are concerned about gender identity and gender issues to receive reliable support quickly and safely. In particular, there are difficulties in providing information in real time, protecting personal information, and connecting with appropriate medical professionals and psychological counselors.

[1143] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1144] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting an appropriate career path based on the user's profile information and analysis data; and means for requesting reviews from optimal medical professionals or psychological counselors based on the user's input data. This allows users to receive reliable support in real time, ensures the protection of their personal information, and enables smooth collaboration with appropriate professionals.

[1145] A "user" is someone who inputs questions or concerns about gender identity or sexual identity through a chat-style UI.

[1146] A "terminal" is a device used by a user that provides a chat-style UI for inputting questions and concerns and transmits the input data to a server.

[1147] The "server" is a system that receives input data sent by the user, analyzes it, uses a generative AI model to generate an appropriate answer, and sends it to the user.

[1148] A "generative AI model" is an artificial intelligence model that analyzes data based on specialized knowledge about sexual identity and gender and generates appropriate answers.

[1149] A "prompt" is a textual instruction used to pass input data to a generative AI model.

[1150] "Data analysis means" means a means for analyzing input data received from a user using a generative AI model.

[1151] "Evaluation means" refers to a means for evaluating the answers generated by a generative AI model, requesting expert review if necessary, and determining the optimal answer.

[1152] The "data collection means" is a means for anonymizing the user's input data and generated responses and collecting them in a database.

[1153] "Visualization tools" are means of analyzing collected data and displaying trends and issues related to sexual identity and gender in the form of graphs and charts.

[1154] The "career suggestion means" is a means for suggesting suitable career paths and schools based on the user's profile information and analysis data.

[1155] The "review request means" is a means for requesting a review from the most suitable medical expert or psychological counselor based on the data input by the user.

[1156] This invention is a system that enables minors and their guardians who are concerned about gender identity and gender issues to receive reliable support. The system receives input data from users, analyzes it, generates answers, evaluates and transmits it, collects and analyzes data, visualizes it, and makes career suggestions.

[1157] Users use a chat-style user interface (UI) to input questions and concerns about gender identity and gender. Devices that provide this UI include PCs, smartphones, and tablets. Specifically, users input questions such as, "I feel uncomfortable with my gender. What should I do?"

[1158] The device sends the entered questions to the server in real time, using a secure protocol (e.g., HTTPS) for data transmission.

[1159] The server uses a generative AI model to analyze the received input data. This generative AI model generates an answer based on specialized knowledge about gender identity and gender. The server first generates a prompt. The prompt contains the text entered by the user and may take the form, for example, "The user is asking the following question: I feel uncomfortable with my gender. What should I do?"

[1160] The generative AI model analyzes this prompt and generates an appropriate response, such as, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[1161] The server evaluates the generated answers and, if necessary, requests review from medical professionals or psychological counselors. Once the optimal answer is determined, the server sends it to the device. The device displays the answer to the user and quickly provides the necessary information and support.

[1162] The server also anonymizes the user's input data and generated answers and collects them in a database. The anonymized data is stored in a manner that ensures the protection of personal information.

[1163] The collected data is then analyzed by the server, and trends and issues related to gender identity and gender are visualized using graphs and charts, and presented as information to deepen understanding in society as a whole.

[1164] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that is right for them.

[1165] For example, a user enters a question such as, "I feel uncomfortable with my gender. What should I do?" and the device sends this to the server. The server analyzes the text using a generative AI model and generates a response such as, "It's natural to feel uncomfortable with your gender identity. We recommend that you first consult with an expert." The server evaluates this response, and after expert review, sends the optimal response to the device, which then displays it to the user. This series of actions allows the user to receive fast and reliable support.

[1166] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1167] Step 1:

[1168] Users use a chat-style user interface (UI) to input questions or concerns about gender identity and gender identity. The input data is in text format and includes content such as, "I feel uncomfortable with my gender. What should I do?" The input text data is passed to the device, and the device is ready to proceed to the next step.

[1169] Step 2:

[1170] The device sends the text data entered by the user to the server in real time. A secure protocol (e.g., HTTPS) is used to transmit the data, ensuring the integrity and confidentiality of the data during transmission. The input data is passed to the server in the following format: "I'm feeling uncomfortable with my gender. What should I do?"

[1171] Step 3:

[1172] The server receives the input data. Since the received data cannot be used for analysis as is, it first generates a prompt to be passed to the generative AI model. The prompt is processed into a format such as "The user is asking the following question: I feel uncomfortable with my gender. What should I do?" This prompt is then used to proceed to the next step.

[1173] Step 4:

[1174] The server passes the prompt to the generative AI model for analysis. The generative AI model analyzes the prompt based on specialized knowledge about gender identity and gender, and generates an appropriate response. For example, the response output might be, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with an expert."

[1175] Step 5:

[1176] The server evaluates the answers generated by the generative AI model, checks whether the generated answers are appropriate, and, if necessary, requests review by medical professionals or psychological counselors. Experts can check and correct the accuracy and appropriateness of the answers, resulting in high-quality answers. For example, experts may add additional information such as, "If you would like a more detailed consultation, you can make an appointment using the link below."

[1177] Step 6:

[1178] The server then sends the best answer after evaluation to the device. This is again done using a secure protocol. The data sent to the device will be in the form of a message saying, "It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist. If you would like a more detailed consultation, you can make an appointment using the link below."

[1179] Step 7:

[1180] The device then displays the received response data to the user, allowing them to quickly receive the appropriate answer to their question and, if necessary, to view links to further support.

[1181] Step 8:

[1182] The server anonymizes the user's input data and generated answers and collects them in a database. The anonymization process removes any personally identifiable information, and the collected data is stored in a manner that complies with the Personal Information Protection Act. This anonymized data is used for the next analysis step.

[1183] Step 9:

[1184] The server analyzes the collected anonymized data, and the results are used to identify trends and issues related to gender identity and gender, and are visualized in graphs and charts, providing useful information for policymakers and researchers.

[1185] Step 10:

[1186] The server suggests suitable career paths and schools based on the user's profile information (e.g., age, grade, current school, etc.) and analysis results. These career suggestions help users make the best choices for themselves. The results of the career suggestions are also sent to the user's device, allowing the user to view them and make career decisions.

[1187] (Application example 1)

[1188] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1189] In today's information society, security knowledge and countermeasures are becoming increasingly important. However, many users lack adequate security knowledge and are vulnerable to threats such as phishing emails and the leakage of personal information. Furthermore, access to security experts with specialized knowledge is generally difficult, making it difficult for users to solve problems on their own. This creates a need for a system that provides efficient and reliable security support.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1191] In this invention, the server includes means for receiving input data from a user, data analysis means including a generative AI model that analyzes the received input data, evaluation means for evaluating answers generated by the generative AI model to determine the optimal answer, data collection means for anonymizing and collecting the user's input data and the generated answers, visualization means for analyzing the collected data and visualizing security trends and issues, and means for proposing appropriate security measures based on the user's profile information and analysis data. This allows users to easily receive professional security support, enabling the protection of personal information and the strengthening of security measures.

[1192] "User" means an individual or entity that uses the System and receives security-related support.

[1193] "Input data" is the textual information of security questions and concerns that users provide to the system.

[1194] A "generative AI model" is an artificial intelligence model that has specialized knowledge about security and analyzes user input data to generate appropriate answers.

[1195] "Data analysis means" is a function that analyzes received input data and generates appropriate answers using a generative AI model.

[1196] The "evaluation means" is a function that evaluates the answers generated by the generative AI model and determines the best answer for the user.

[1197] The "transmission means" is a function for transmitting the optimal answer to the user and displaying it on the terminal.

[1198] The "data collection means" is a function for anonymizing and collecting user input data and generated responses.

[1199] "Visualization means" is a function that analyzes collected data and displays security trends and issues in graphs and charts.

[1200] "Profile Information" refers to personal information about a user, such as their age, occupation, and the device they use.

[1201] "Security measures" are specific actions and settings that users take to protect themselves from cyber attacks and information leaks.

[1202] The system for implementing this invention allows users to input security-related questions or concerns, and generates and provides information to resolve those questions. The major components required to implement this system and their functions are described below.

[1203] 1. A means of receiving input data from the user

[1204] The device (smartphone app) provides a chat-style UI that allows users to enter security questions. For example, the user might enter a question like, "How can I spot a phishing email?"

[1205] 2. A data analysis method that includes a generative AI model that analyzes the received input data.

[1206] The device sends the input question in real time to the server, which uses a generative AI model (e.g., OpenAI GPT-3) to analyze the received question and generate an appropriate answer.

[1207] 3. An evaluation tool to evaluate the generated answers and determine the best answer.

[1208] The server evaluates the answers generated by the generative AI model, and if necessary, requests a security expert for review to determine the best answer. This evaluation method improves the accuracy and reliability of the answers.

[1209] 4. A means to send and display the best answer to the user

[1210] The server generates the optimal answer, which is then sent to the user's device and displayed to them, allowing the user to quickly receive practical advice on security measures.

[1211] 5. Data collection method to anonymize and collect user input data and generated responses

[1212] The server anonymizes the user's input data and generated answers and collects them in a database, thereby protecting personal information.

[1213] 6. A visualization tool to analyze collected data and visualize security trends and issues.

[1214] The server analyzes the collected data and visualizes security trends and issues. The visualized data is displayed in graphs and charts, making it easier to understand the overall security situation and issues.

[1215] 7. A method for suggesting appropriate security measures based on user profile information and analytical data

[1216] The server proposes appropriate security measures based on the user's profile information (e.g., age, occupation, device used, etc.) and analysis data, allowing users to implement specific measures tailored to their individual circumstances.

[1217] Examples of concrete examples and prompts

[1218] For example, if a user types the question "How can I spot a phishing email?", the system will process it as follows:

[1219] The user's terminal sends this question to the server.

[1220] The server analyzes this question using a generative AI model and generates the answer, "Phishing emails typically encourage you to click on a link. Be careful of links in suspicious emails."

[1221] The server evaluates the answers and sends the best answer to the terminal.

[1222] The terminal displays this response to the user.

[1223] Example prompt sentence:

[1224] "User Question: How do I spot a phishing email?

[1225] Generate the best security answers:

[1226] In this way, the system of the present invention allows users to instantly acquire security expertise and contributes to strengthening security measures. Furthermore, by analyzing and visualizing the collected data, it is possible to grasp the overall security situation and provide valuable information for taking further measures.

[1227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1228] Step 1:

[1229] A user inputs a question into a smartphone device. For example, the user inputs a question such as "How can I identify a phishing email?" into a chat-style UI. This input data is sent from the device to the server.

[1230] Step 2:

[1231] The terminal transmits the user's input data in real time to the server, which receives the data and passes it to the data analysis means.

[1232] Step 3:

[1233] The server sends the received input data to the generative AI model, which analyzes the input data based on its pre-trained security expertise and generates an appropriate answer. In this process, the AI ​​model extracts key keywords and context from the input data and generates an answer based on that.

[1234] Step 4:

[1235] The server passes the answers generated by the generative AI model to an evaluation method, which may then be verified by security experts to assess the reliability and appropriateness of the generated answers. Once the evaluation is complete, the best answer is determined.

[1236] Step 5:

[1237] After the server determines the optimal answer, it sends it back to the device, where it is displayed to the user, allowing the user to receive specific security advice.

[1238] Step 6:

[1239] The server anonymizes the user's input data and generated responses and stores them in a data collection tool, processing the data in a way that ensures appropriate protection of personal information.

[1240] Step 7:

[1241] The server uses the collected data to analyze security trends and issues, and displays them in the form of graphs and charts using visualization tools. This visualization data is used to understand the overall security situation and issues.

[1242] Step 8:

[1243] The server then proposes appropriate security measures to the user based on the user's profile information and analytical data, providing personalized advice based on the user's age, occupation, device used, etc.

[1244] The above is a specific flow of the processing steps of the system that realizes the application example.

[1245] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1246] ---

[1247] This invention is a system that enables minors and their guardians with concerns about gender identity and gender identity to receive reliable support. Furthermore, by combining it with an emotion engine that recognizes the user's emotions, more appropriate support can be provided. This system receives input data from the user, analyzes it, recognizes emotions, generates answers, evaluates and transmits them, collects and analyzes data, visualizes it, and makes career suggestions.

[1248] First, the device used by the user provides a chat-style UI where users can input questions and concerns about their gender identity and gender identity. The device sends the input data to a server in real time.

[1249] The server then receives the input data and recognizes the user's emotions using an emotion engine, which analyzes emotions from the user's text input to detect emotional states such as "anxiety" or "excitement."

[1250] The server passes the recognized emotion data to a generative AI model, which then begins analyzing the data. The generative AI model generates appropriate answers to the user's questions based on specialized knowledge of sexual identity and gender. Based on the emotion data, the answer is revised, adding phrases that take emotion into consideration, such as "Don't worry," to provide more appropriate support to the user.

[1251] The server evaluates the generated answers and determines the most appropriate one. If necessary, it requests reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes anxiety, it makes decisions based on the level of urgency, such as increasing the priority of connecting to a specialist.

[1252] The server then sends the best possible answer to the device, which displays it to the user, sometimes including reassuring words and specific guidelines for action, taking into consideration the user's feelings.

[1253] The server also anonymizes the user's input data and generated answers and collects them in a database, ensuring the protection of personal information.

[1254] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. This data is displayed in the form of graphs and charts, providing a deeper understanding for society as a whole.

[1255] Furthermore, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[1256] For example:

[1257] A user types a question: "I feel uncomfortable with my gender. What should I do?"

[1258] The device sends this text to the server.

[1259] The server analyzes the text using an emotion engine to detect emotions such as "anxiety."

[1260] The server analyzes this text using a generative AI model and generates a response: "Don't worry. It's natural to feel uncomfortable about your gender identity."

[1261] The server evaluates this response and sends it to the terminal.

[1262] The terminal displays this response to the user.

[1263] In this way, users can quickly and accurately obtain the information and support they need, promoting mental health management and early intervention. The system provides emotionally sensitive and reassuring support to minors and their guardians, and also contributes to improving understanding in society as a whole.

[1264] The processing flow will be explained below.

[1265] Step 1:

[1266] The user can enter a question or concern in chat format. For example, "I feel uncomfortable with my gender. What should I do?"

[1267] Step 2:

[1268] The device sends the input data to the server in real time. Specifically, the input text is sent to the server via API.

[1269] Step 3:

[1270] The server receives the input data and checks the format and validity of the data to ensure there are no omissions or errors.

[1271] Step 4:

[1272] The server passes the received input data to the emotion engine, which then uses natural language processing technology to analyze the user's text data and detect emotions such as "anxiety" or "sadness."

[1273] Step 5:

[1274] The server then passes the recognized emotion data to the generative AI model, which then uses a text analysis algorithm to understand the intent and gist of the questions about gender identity and gender identity.

[1275] Step 6:

[1276] The generative AI model generates answers based on the user's input data and emotional data, such as "Don't worry. It's natural to feel uncomfortable about your gender identity."

[1277] Step 7:

[1278] The server evaluates the generated answers and determines the best answer, automatically filtering and scoring them based on evaluation criteria, and, if necessary, requests review by medical professionals or psychological counselors.

[1279] Step 8:

[1280] The server sends the optimal answer to the device, which then displays it to the user, for example, "Don't worry. It's natural to feel uncomfortable about your gender identity. We recommend that you first consult with a specialist."

[1281] Step 9:

[1282] The server anonymizes the user's input data and generated responses, collects them in a database, removes personal information, and generates statistics for analysis.

[1283] Step 10:

[1284] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Using data mining techniques, trends are extracted and displayed in graphs and charts.

[1285] Step 11:

[1286] The server generates a candidate list to suggest suitable schools and career options for the user based on the user's profile information (age, grade, current school, etc.) and analytical data.

[1287] Step 12:

[1288] The terminal notifies the user of the career suggestions received from the server, for example, by displaying "The following schools and career paths are likely to be suitable for you."

[1289] These are the specific processing steps of the system that combines the emotion engine. This process allows users to quickly and accurately obtain the information and support they need, promoting mental health management and early response.

[1290] Example 2

[1291] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1292] There is a problem that minors and their guardians who are concerned about gender identity and gender identity have difficulty receiving appropriate and reliable support. Furthermore, answers generated without consideration for the user's feelings may further aggravate the user's feelings. Therefore, there is a need for a system that provides fast and accurate support in a way that takes the user's feelings into consideration.

[1293] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1294] In this invention, the server includes: means for receiving input data from a user; emotion recognition means for analyzing the received input data and recognizing the user's emotions; data analysis means including a generative AI model for generating appropriate answers based on the analysis data and emotion data; evaluation means for evaluating the generated answers and determining an optimal answer; means for submitting the answers for expert review and, if necessary, making a decision to correspond to the level of urgency; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; and means for suggesting appropriate career paths based on the user's profile information and analysis data. This makes it possible to provide prompt and appropriate support while taking the user's emotions into consideration.

[1295] A "user" is someone who uses this system to input questions or concerns about gender identity and gender.

[1296] A "terminal" is a device used by a user to communicate with the system, such as a smartphone, tablet, or PC.

[1297] The "server" is a computer system that receives data sent by users and performs analysis, emotion recognition, answer generation, evaluation, transmission, data collection and analysis, visualization, and career suggestions.

[1298] "Emotion recognition means" refers to a technical means for detecting and analyzing emotions from user input data, and includes an emotion engine.

[1299] A "generative AI model" is an artificial intelligence model used for data analysis that generates answers to users' questions and concerns based on specialized knowledge.

[1300] "Data analysis means" refers to technical means, including generative AI models, that generate appropriate answers based on user input data and emotional data.

[1301] The "evaluation means" is a technical means for evaluating the generated answers and determining the optimal answer.

[1302] "Means for sending answers for expert review and, if necessary, making a determination as to the level of urgency" refers to means for sending the generated answers to medical professionals or psychological counselors and for improving the accuracy of the answers as necessary.

[1303] "Data Collection Measures" are technical measures that anonymize and securely collect user input data and generated responses.

[1304] "Visualization tools" are technical means for analyzing collected data and displaying trends and issues related to gender identity and gender in the form of graphs and charts.

[1305] The "career suggestion means" is a technical means for suggesting suitable career paths and educational institutions based on the user's profile information and analysis data.

[1306] This invention is a system designed to provide reliable support to minors and their guardians who are concerned about gender identity and gender identity. The system provides more appropriate support by incorporating an emotion engine that recognizes the user's emotions.

[1307] First, a user uses a device such as a smartphone, tablet, or PC to input questions or concerns about gender identity and gender through a chat-style interface. This interface is designed to be intuitive and easy to use. Consider the example of a user typing, "Recently, I've been feeling uncomfortable with my gender. What should I do?"

[1308] The device then transmits the input data to the server in real time via an API, for example by converting the input text to JSON format and sending an HTTP POST request to the server.

[1309] The server analyzes the received data and uses an emotion engine to recognize the user's emotion. Specifically, the server parses the received JSON data and extracts the text portion. This is then sent to an emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) to analyze the user's emotional state, such as "anxiety."

[1310] The server passes the emotion data to a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an appropriate answer based on the user's question. The generated answer adds emotion-sensitive phrases such as "Don't worry," based on the emotion data. For example, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[1311] The server then evaluates the generated answers to determine the best fit. In some cases, it may request reviews from medical professionals or psychological counselors to improve the accuracy of the answers. If the emotion engine recognizes "anxiety," it prioritizes connecting with experts.

[1312] The server then sends the best evaluated answer to the device, which then displays it to the user, including reassuring words and specific guidelines for action that take the user's feelings into consideration.

[1313] The server then anonymizes the user's input data and generated responses and securely stores them in a database. This anonymization process ensures the protection of personal information. The server then analyzes the collected data and visualizes trends and issues related to gender identity and gender in the form of graphs and charts.

[1314] Finally, the server will suggest suitable career paths and schools based on the user's profile information (age, grade, current school, etc.) and analytical data, making it easier for users to find the career path that best suits them.

[1315] An example prompt is:

[1316] "I've been feeling uncomfortable with my gender lately. What should I do?"

[1317] "My child is struggling with gender identity, how should I address this?"

[1318] In this way, users can quickly and accurately obtain the information and support they need. The system not only takes into consideration users' feelings and provides a sense of security, but also contributes to improving understanding in society as a whole by analyzing the data.

[1319] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1320] Step 1:

[1321] Users input questions and concerns about gender identity and gender identity through a chat-style interface. The input is text data such as, "Recently, I've been feeling uncomfortable with my gender. What should I do?" The input text data is sent to the device as output.

[1322] Step 2:

[1323] The terminal receives text data entered by the user and sends it to the server in real time. As input, the text data entered in step 1 is provided to the terminal. Specifically, the input text is converted into JSON format and sent to the server using an HTTP POST request. As output, the text data is sent to the server in JSON format.

[1324] Step 3:

[1325] The server receives the received text data and uses an emotion engine to recognize the user's emotions. JSON-formatted text data is provided to the server as input. Specifically, the received data is parsed and the text portion is extracted. An emotion engine (e.g., Google Cloud Natural Language API, IBM Watson Tone Analyzer) is used to analyze emotions and detect emotional states such as "anxiety" or "excitement." Emotion data is generated as output.

[1326] Step 4:

[1327] The server passes the generated emotion data and text data to a generative AI model, which generates an appropriate answer based on the user's question. The emotion data and text data are provided as input. Specifically, the data is input into a generative AI model (e.g., OpenAI GPT, Google BERT) to generate an answer based on the question. Based on the emotion data, a phrase such as "Don't worry" is added. The generated answer text is obtained as output.

[1328] Step 5:

[1329] The server evaluates the generated answers and determines the best answer. As input, the generated answer text is provided. Specifically, it uses an internal evaluation algorithm to evaluate the quality of the answer and, in some cases, requests an expert for review. In particular, if the emotion engine recognizes the answer as "anxious," it increases the priority of connecting to an expert. As output, the evaluated best answer is determined.

[1330] Step 6:

[1331] The server sends the evaluated best answer to the terminal. The best answer text is provided as input. Specifically, the best answer is sent to the terminal as an HTTP response. The best answer data is sent to the terminal in JSON format as output.

[1332] Step 7:

[1333] The terminal displays the received answer to the user. The answer data sent from the server is provided as input. Specifically, the received data is analyzed and displayed to the user in a chat format. The answer text is displayed to the user as output.

[1334] Step 8:

[1335] The server anonymizes the user's input data and generated answers and securely collects them in a database. As input, the user's input data and generated answer data are provided. Specifically, personal identifying information is removed and the data is anonymized. As output, the anonymized data is stored in a database.

[1336] Step 9:

[1337] The server analyzes the collected data and visualizes trends and issues related to gender identity and gender. Anonymized data is provided as input. Specifically, the server analyzes the data using data analysis algorithms and generates graphs and charts using visualization tools (e.g., Google Charts, D3.js). The analysis results are displayed as graphs and charts as output.

[1338] Step 10:

[1339] The server proposes suitable career paths and schools based on the user's profile information and analytical data. The user's profile information and analytical data are provided as input. Specifically, the server evaluates information such as the user's age, grade, and school, and generates a list of optimal career paths and educational institutions by referring to the collected data. The server provides information on the proposed career paths and schools as output.

[1340] (Application example 2)

[1341] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1342] Conventional systems have had difficulty providing appropriate support that takes into account emotions to minors and their guardians who have concerns about gender identity or gender. Furthermore, when customer service staff in brick-and-mortar stores deal with customers who have concerns about gender identity or gender, it is difficult to respond appropriately and with consideration for emotions in real time, resulting in a decline in customer satisfaction and trust. Furthermore, real-time emotion recognition and feedback-based responses have been difficult due to the lack of appropriate technology.

[1343] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1344] In this invention, the server includes: means for receiving input data from a user; data analysis means including a generative AI model that analyzes the received input data; evaluation means for evaluating answers generated by the generative AI model to determine an optimal answer; means for sending and displaying the optimal answer to the user; data collection means for anonymizing and collecting the user's input data and the generated answers; visualization means for analyzing the collected data and visualizing trends and issues related to gender identity and gender; means for suggesting appropriate career paths based on the user's profile information and analysis data; emotion recognition means for recognizing the customer's emotional state; means for generating appropriate answers using the generative AI model based on the emotional state; and display means for providing feedback to staff in real time. This enables real-time, emotion-sensitive support to customers with concerns about gender identity and gender, even in physical stores.

[1345] The "means for receiving input data from a user" refers to an interface and communication device for transmitting text data input by a user through a terminal to a server.

[1346] "Data analysis means" refers to software and hardware that analyzes received input data and generates appropriate answers using a generative AI model.

[1347] An "evaluation means" is a software algorithm that compares and evaluates multiple answer candidates generated by a generative AI model to determine the optimal answer.

[1348] The "means for transmitting and displaying to the user" refers to a device and software that transmits the determined optimal answer to the user's terminal in real time and displays it.

[1349] "Data collection means" refers to technology for anonymizing user input data and generated responses, and collecting data while protecting personal information.

[1350] "Visualization tools" are software that analyzes collected data and displays trends and issues related to gender identity and gender as graphs and charts.

[1351] The "means for suggesting suitable career paths" refers to algorithms and systems that suggest the most suitable career paths and schools for users based on the user's profile information and analysis data.

[1352] "Emotion Recognition Means" means software and AI engines for recognizing the emotional state of a user or customer from input text or voice data.

[1353] The "means for generating appropriate responses" is an algorithm for generating emotion-sensitive responses using a generative AI model based on the perceived emotional state.

[1354] The "display means for providing feedback to staff in real time" refers to a device and software for providing and displaying the generated appropriate response to the wait staff in real time.

[1355] This invention is a system for providing appropriate support to minors and their guardians who are concerned about gender identity and gender identity. This system has functions for receiving input data from users, analyzing it, recognizing emotions, generating answers, evaluating, transmitting, collecting and analyzing data, visualizing it, and making career suggestions. Furthermore, by applying this system to customer service in brick-and-mortar stores, it can realize real-time, emotion-sensitive responses.

[1356] System configuration

[1357] The system is configured as follows:

[1358] 1. A means for receiving input data from the user: Text data entered by the user through a device (such as a smartphone or PC) is sent to the server in real time. The hardware used at this stage includes smartphones, tablets, and PCs.

[1359] 2. Data analysis: The data received from the user is analyzed on the server, and a generative AI model is used to generate an appropriate answer based on the user's input. The software used includes OpenAI's generative models (e.g., GPT-3) and TextBlob.

[1360] 3. Evaluation methods: Comparing multiple candidate answers generated by the generative AI model to determine the best answer. This evaluation can include automated evaluation using algorithms and expert review.

[1361] 4. Means of sending and displaying to the user: The determined optimal answer is sent to the user's terminal in real time and displayed appropriately.

[1362] 5. Data collection method: The data entered by the user and the responses generated are anonymized and collected while protecting personal information. This data is stored for future analysis.

[1363] 6. Visualization methods: Based on the collected data, trends and issues related to gender identity and gender will be visualized using graphs and charts.

[1364] 7. Career Recommendation: Based on the user's profile information and analytical data, the system will suggest suitable career paths for the user, including career counseling and school introductions.

[1365] 8. Emotion Recognition: Analyze the emotional state from the user or customer's input text and use an emotion engine to recognize emotions such as "anxiety" or "relief."

[1366] 9. Means of generating appropriate answers: Based on the perceived emotional state, generative AI models are used to generate emotion-sensitive answers.

[1367] 10. Display means for providing feedback to staff in real time: Smart glasses or head-mounted displays can be used to display the generated appropriate answers to the waiting staff in real time.

[1368] Example of operation

[1369] As an example of a brick-and-mortar application, it works as follows:

[1370] The user inputs a question such as, "I feel uncomfortable with my gender. What should I do?" This question is sent to the server via the device.

[1371] The server receives this input data and recognizes the emotion of "anxiety" through an emotion engine.

[1372] The server uses a generative AI model to generate the answer, "Don't worry. It's natural to feel uncomfortable about your gender identity."

[1373] The server evaluates this answer to determine if it is the best answer.

[1374] The generated answers are provided to the wait staff in real time through smart glasses.

[1375] Customer service staff will refer to the answers displayed on the smart glasses and respond appropriately to the customer.

[1376] Prompt Sentence Examples

[1377] "Answer the following question to emotionally anxious users: I feel uncomfortable with my gender. What should I do? Answer:"

[1378] In this way, users can receive fast and reliable support for their mental health care, and brick-and-mortar stores can provide emotionally sensitive customer service.

[1379] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1380] Step 1:

[1381] The user inputs a question, and the terminal receives the input data and sends it to the server.

[1382] Input: The text entered by the user.

[1383] Output: The text data received by the server.

[1384] Specific operation: The user types "I feel uncomfortable with my gender. What should I do?" into the chat-style UI on their smartphone or PC and presses the send button. The device then sends this text data to the server.

[1385] Step 2:

[1386] To analyze the input data received by the server, an emotion engine is used to recognize the user's emotional state.

[1387] Input: Received text data.

[1388] Output: Emotional state (e.g., "anxious," "relieved," etc.).

[1389] What it does: The server analyzes the input text using an emotion recognition algorithm such as TextBlob and detects the emotional state as "anxiety."

[1390] Step 3:

[1391] The server uses a generative AI model based on the perceived emotional state to generate an appropriate response.

[1392] Input: Text data, emotional state.

[1393] Output: The generated answer text.

[1394] Specific operation: The server uses OpenAI's generative model (e.g., GPT-3) and inputs the prompt "For a user who is emotionally anxious, please answer the following question: I feel uncomfortable with my gender. What should I do? Answer:" into the model, generating the answer "Don't worry. It's natural to feel uncomfortable with your gender identity."

[1395] Step 4:

[1396] The server evaluates the generated answers and determines the best answer.

[1397] Input: Multiple generated answer candidates.

[1398] Output: The best answer.

[1399] What it does: The server runs the generated answers through a rating algorithm to select the most appropriate answer, adding expert review if necessary.

[1400] Step 5:

[1401] The server sends the best answer to the user's device and displays it.

[1402] Input: Best answer.

[1403] Output: The answer displayed on the user's terminal.

[1404] Specific operation: The server sends the best answer to the user's device, and the device displays the answer on the screen.

[1405] Step 6:

[1406] The server anonymizes the user's input data and generated answers and collects them in a database.

[1407] Input: User input data, generated answers.

[1408] Output: Anonymized data.

[1409] What it does: The server uses a data anonymization algorithm to remove personally identifiable information such as your name and address, generating anonymized data that is then stored in a database.

[1410] Step 7:

[1411] The server analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1412] Input: Anonymized data.

[1413] Output: Visualized graphs and charts.

[1414] What it does: The server uses data analysis software to analyze the collected data to find trends and issues, and displays the results in graphs and charts.

[1415] Step 8:

[1416] The server suggests suitable paths based on the user's profile information and analytical data.

[1417] Input: User profile information, analytics data.

[1418] Output:Career suggestions.

[1419] Specific operation: The server uses a career suggestion algorithm to suggest suitable career paths and schools to the user based on profile information such as the user's age, grade, and current school, as well as the results of data analysis.

[1420] Step 9:

[1421] The server uses the emotion recognition means to recognize the emotional state of the customer in the physical store.

[1422] Input: Customer statements and behavior data in physical stores.

[1423] Output: Emotional state.

[1424] Specific operation: The server applies an emotion recognition algorithm to data input from microphones and cameras installed in physical stores to recognize the customer's emotional state.

[1425] Step 10:

[1426] The server uses generative AI models to generate appropriate responses based on emotional state and provide feedback to staff in real time.

[1427] Input: Emotional state, customer question.

[1428] Output: Feedback display to staff.

[1429] How it works: The server inputs prompts into the generative AI model based on the customer's emotional state and question, and displays the generated answers in real time on smart glasses or a head-mounted display.

[1430] 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 control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1431] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1432] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1433] The emotion identification model 59 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 an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1434] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1435] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1436] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1437] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1438] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs 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 a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1439] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1440] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1441] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1442] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1443] 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.

[1444] It is not necessary to store all 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 all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1445] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1446] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with 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). Also, the hardware resource that executes the specific processing may be a single processor.

[1447] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1448] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1449] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1450] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1451] The following is further disclosed regarding the above embodiment.

[1452] Of course. Below are the draft claims:

[1453] (Claim 1)

[1454] means for receiving input data from a user;

[1455] data analysis means including a generative AI model that analyzes received input data;

[1456] an evaluation means for evaluating the answers generated by the generative AI model to determine an optimal answer;

[1457] means for transmitting and displaying the best answer to the user;

[1458] a data collection means for anonymizing and collecting user input data and generated responses;

[1459] A visualization tool that analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1460] A means for suggesting suitable career paths based on the user's profile information and analytical data;

[1461] A system including:

[1462] (Claim 2)

[1463] 10. The system of claim 1, further comprising means for providing a connection with an optimal medical professional or psychological counselor based on the user's input data.

[1464] (Claim 3)

[1465] 10. The system of claim 1, including means for receiving and processing input data in real time.

[1466] The above is the draft of the patent claims, which clearly define the technical scope of the invention.

[1467] "Example 1"

[1468] (Claim 1)

[1469] means for receiving input data from a user;

[1470] data analysis means including a generative AI model that analyzes received input data;

[1471] an evaluation means for evaluating the answers generated by the generative AI model to determine an optimal answer;

[1472] means for transmitting and displaying the best answer to the user;

[1473] a data collection means for anonymizing and collecting user input data and generated responses;

[1474] A visualization tool that analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1475] A means for suggesting suitable career paths based on the user's profile information and analytical data;

[1476] A means to request reviews from the most appropriate medical experts and psychological counselors based on the user's input data, and

[1477] A system including:

[1478] (Claim 2)

[1479] 10. The system of claim 1, further comprising means for providing a connection with an optimal medical professional or psychological counselor based on the user's input data.

[1480] (Claim 3)

[1481] 10. The system of claim 1, including means for receiving and processing input data in real time.

[1482] "Application Example 1"

[1483] (Claim 1)

[1484] means for receiving input data from a user;

[1485] data analysis means including a generative AI model that analyzes received input data;

[1486] an evaluation means for evaluating the answers generated by the generative AI model to determine an optimal answer;

[1487] means for transmitting and displaying the best answer to the user;

[1488] a data collection means for anonymizing and collecting user input data and generated responses;

[1489] A visualization tool that analyzes the collected data and visualizes security trends and issues.

[1490] A means for proposing appropriate security measures based on user profile information and analysis data;

[1491] A system including:

[1492] (Claim 2)

[1493] 10. The system of claim 1, further comprising means for providing a connection with an optimal security expert based on user input data.

[1494] (Claim 3)

[1495] 10. The system of claim 1, including means for receiving and processing input data in real time.

[1496] "Example 2: Combining Emotion Engines"

[1497] (Claim 1)

[1498] means for receiving input data from a user;

[1499] emotion recognition means for analyzing received input data and recognizing the emotion of a user;

[1500] A data analysis means including a generative AI model that generates appropriate answers based on the analysis data and emotion data;

[1501] evaluation means for evaluating the generated answers to determine a best answer;

[1502] A means to submit responses for expert review and, if necessary, a determination of urgency; and

[1503] means for transmitting and displaying the best answer to the user;

[1504] a data collection means for anonymizing and collecting user input data and generated responses;

[1505] A visualization tool that analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1506] A means for suggesting suitable career paths based on the user's profile information and analytical data;

[1507] A system including:

[1508] (Claim 2)

[1509] 10. The system of claim 1, further comprising means for providing a connection with an optimal medical professional or psychological counselor based on user input data.

[1510] (Claim 3)

[1511] 10. The system of claim 1, including means for receiving and processing input data in real time.

[1512] "Application example 2 when combining emotion engines"

[1513] (Claim 1)

[1514] means for receiving input data from a user;

[1515] data analysis means including a generative AI model that analyzes received input data;

[1516] an evaluation means for evaluating the answers generated by the generative AI model to determine an optimal answer;

[1517] means for transmitting and displaying the best answer to the user;

[1518] a data collection means for anonymizing and collecting user input data and generated responses;

[1519] A visualization tool that analyzes the collected data and visualizes trends and issues related to sexual identity and gender.

[1520] A means for suggesting suitable career paths based on the user's profile information and analytical data;

[1521] an emotion recognition means for recognizing an emotional state of a customer;

[1522] a means for generating an appropriate response using a generative AI model based on the emotional state; and

[1523] a means of displaying feedback to staff in real time;

[1524] A system including:

[1525] (Claim 2)

[1526] 10. The system of claim 1, further comprising means for providing a connection with an optimal medical professional or psychological counselor based on the user's input data.

[1527] (Claim 3)

[1528] 10. The system of claim 1, including means for receiving and processing input data in real time. [Explanation of symbols]

[1529] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving input data from a user; data analysis means including a generative AI model that analyzes received input data; an evaluation means for evaluating the answers generated by the generative AI model to determine an optimal answer; means for transmitting and displaying the best answer to the user; a data collection means for anonymizing and collecting user input data and generated responses; A visualization tool that analyzes the collected data and visualizes trends and issues related to sexual identity and gender. A means for suggesting suitable career paths based on the user's profile information and analytical data; A system including:

2. The system of claim 1 further comprising means for providing a connection with an optimal medical professional or psychological counselor based on the user's input data.

3. 10. The system of claim 1, further comprising means for receiving and processing input data in real time.

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