System

Abstract

A system is provided.SOLUTION: A system for providing gender AI support services using generated equities, comprising: means for accepting user registration and creating a user account; means for providing educational content and collecting and analyzing user learning progress; means for performing unanimous bias checks and providing improvement suggestions to users; means for analyzing consultation content and presenting solutions; and means for collecting user feedback and improving services.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] The gender gap in Japan is a serious issue, and there is a need to achieve gender equality. However, unconscious bias and pointless arguments act as obstacles, making it difficult for organizations and individuals to take concrete action. In particular, spreading the concept of gender equity in educational settings and the workplace and translating it into actual action is a major challenge. Furthermore, existing education systems and bias-checking systems are often not functioning effectively, and improvements are needed. [Means for solving the problem]

[0005] This invention provides a system that uses generative AI to provide gender equity support services. The system includes a means for accepting user registrations and creating user accounts, a means for providing educational content and collecting and analyzing users' learning progress, a means for conducting unconscious bias checks and providing users with improvement suggestions, a means for analyzing consultation content and presenting solutions, and a means for collecting user feedback and improving the service. This system enables a wide range of people, from children to adults, to understand the importance of gender equity and take concrete action. It also reduces unconscious bias and creates a favorable communication environment.

[0006] "Generative AI" is an artificial intelligence system that analyzes data based on information entered by users and automatically generates learning materials, bias check reports, solutions to consultation questions, and more.

[0007] "Gender equity" is a concept that refers to a state in which all people have equal opportunities and are treated fairly, regardless of gender.

[0008] "Support services" refers to systems and tools that provide various functions and support to promote the realization of gender equity.

[0009] "User registration" is the process of creating an account by entering personal information required to use the system.

[0010] "Educational Content" refers to interactive learning materials that help users learn about gender equity, including videos, quizzes, and textbooks.

[0011] An "unconscious bias check" is a process that helps users identify unconscious biases and provides suggestions for mitigating them.

[0012] "Solution presentation" is the process in which the generating AI presents the optimal solution to the inquiry or problem received from the user.

[0013] "User feedback" refers to the input of opinions and improvements felt by users after using the system, and is data used to improve the quality of the service. [Brief explanation of the drawings]

[0014] [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

[0015] 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.

[0016] First, the terms used in the following description will be explained.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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."

[0022] [First embodiment]

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0024] 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.

[0025] 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).

[0026] 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.

[0027] 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.

[0028] 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.

[0029] 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.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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."

[0035] To implement this invention, a system with the following configuration is required. The main elements are a server containing the generation AI, a terminal accessed by the user, and the user who uses the service.

[0036] User Registration and Login

[0037] User Registration:

[0038] When a user registers, he or she enters personal information such as name, email address, and password.

[0039] The terminal sends this information to the server, which then creates a user account based on the received information.

[0040] The terminal notifies the user that the account creation is complete.

[0041] Login:

[0042] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[0043] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[0044] The device receives the authentication token and redirects the user to the home screen.

[0045] Providing gender equity education content

[0046] View content:

[0047] A user accesses a catalog page to select the educational content they wish to study.

[0048] The terminal displays a list of educational content and sends the content ID selected by the user to the server.

[0049] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[0050] The terminal displays educational content to the user, and the user progresses with his / her studies.

[0051] Unconscious Bias Check

[0052] Checks performed:

[0053] Users visit the Unconscious Bias Check page and answer the necessary questions.

[0054] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[0055] The server generates analysis results and improvement suggestions and sends them to the terminal.

[0056] The terminal displays this to the user.

[0057] Communication Support

[0058] Input and analysis of consultation content:

[0059] The user inputs the content of the consultation into the chat interface.

[0060] The device sends the content to the server, which then analyzes it using a generating AI.

[0061] The server generates an appropriate solution and sends it to the terminal.

[0062] The terminal presents a solution to the user.

[0063] Feedback and Improvements

[0064] Feedback collection and analysis:

[0065] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0066] The terminal sends this to the server, which analyzes the feedback data.

[0067] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[0068] Specific examples

[0069] Providing educational content for children:

[0070] Users (children) learn about gender equity using a dedicated educational app.

[0071] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[0072] The server receives learning data and generates progress reports to provide to parents and educators.

[0073] Unconscious Bias Check:

[0074] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[0075] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[0076] The server analyzes the response data and provides an assessment of bias and suggestions for improvement.

[0077] This system provides comprehensive support for gender equity issues and facilitates the education, evaluation, and improvement processes.

[0078] The processing flow will be explained below.

[0079] User Registration and Login

[0080] New Registration

[0081] Step 1:

[0082] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[0083] Step 2:

[0084] The terminal transmits the input information to the server.

[0085] Step 3:

[0086] The server stores the received user information in a database and creates a new account.

[0087] Step 4:

[0088] The terminal displays a message to the user indicating that registration is complete.

[0089] Log in

[0090] Step 1:

[0091] The user enters their email address and password into the login form on their device.

[0092] Step 2:

[0093] The terminal transmits the input information to the server.

[0094] Step 3:

[0095] The server checks the account information against the database and performs authentication.

[0096] Step 4:

[0097] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[0098] Step 5:

[0099] The device receives the authentication token and redirects the user to the dashboard or home screen.

[0100] Providing gender equity education content

[0101] View content

[0102] Step 1:

[0103] The user accesses the educational content catalog page from the terminal.

[0104] Step 2:

[0105] The device displays a list of educational content.

[0106] Step 3:

[0107] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[0108] Step 4:

[0109] The server retrieves the corresponding educational content from the database based on the received content ID.

[0110] Step 5:

[0111] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[0112] Step 6:

[0113] The terminal displays the educational content to the user.

[0114] Unconscious Bias Check

[0115] Check implementation

[0116] Step 1:

[0117] A user accesses the Unconscious Bias Check page on their device.

[0118] Step 2:

[0119] The terminal provides an interface for displaying the check questions.

[0120] Step 3:

[0121] The user enters an answer to each question.

[0122] Step 4:

[0123] The terminal transmits the response data to the server.

[0124] Step 5:

[0125] The server analyzes the response data and assesses whether or not there is unconscious bias.

[0126] Step 6:

[0127] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[0128] Step 7:

[0129] The terminal displays the evaluation results and improvement suggestions to the user.

[0130] Communication Support

[0131] Input and analysis of consultation details

[0132] Step 1:

[0133] The user uses the chat interface to input the consultation content.

[0134] Step 2:

[0135] The terminal transmits the input consultation content to the server.

[0136] Step 3:

[0137] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[0138] Step 4:

[0139] The server sends the solution to the terminal.

[0140] Step 5:

[0141] The terminal displays the solution to the user.

[0142] Feedback and Improvements

[0143] Feedback collection and analysis

[0144] Step 1:

[0145] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0146] Step 2:

[0147] The terminal transmits the input feedback to the server.

[0148] Step 3:

[0149] The server analyzes the feedback data and extracts areas for improvement.

[0150] Step 4:

[0151] The server updates the system based on the extracted improvements.

[0152] This step will ensure that the Gender Equity Support System operates smoothly and provides appropriate support for each use case.

[0153] Example 1

[0154] 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."

[0155] Gender equity is an important issue in modern society, but solving it is not easy because many people have unconscious biases. Existing education systems and corporate training programs often do not provide effective approaches to individual needs and issues. Furthermore, there are limitations to achieving gender equity because there is a lack of mechanisms in place to collect user feedback and continuously improve services. There is a need to provide a system that can solve these issues and effectively support gender equity.

[0156] 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.

[0157] In this invention, the server includes means for accepting user registration and creating a user account, means for users to log in and generate an authentication token, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation details and presenting solutions, and means for collecting user feedback and improving the service. This enables learning, assessment, and improvement suggestions that meet the needs of diverse users, contributing to the improvement of gender equity.

[0158] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate, analyze, and evaluate data.

[0159] "Gender equity" refers to a situation in which discrimination and inequity based on gender are eliminated and equal opportunities and treatment are provided to all.

[0160] "User registration" refers to the process by which a system user creates a new account on the system by providing personal information such as name, email address, and password.

[0161] "User account" refers to a data set used to individually identify a user in the system, including the user's personal information and usage history.

[0162] An "authentication token" refers to an electronic certificate that indicates a user has been properly authenticated and is used to grant access to a system.

[0163] "Educational content" refers to educational materials and information provided for users to learn from, and may include formats such as text, video, and quizzes.

[0164] "Study progress" refers to an indicator that indicates how much a user has progressed in their studies through educational content.

[0165] An "unconscious bias check" is a test that allows users to assess their own unconscious biases, often in the form of a questionnaire or survey.

[0166] "Improvement Suggestions" are specific advice to provide effective solutions to users' unconscious biases and other challenges.

[0167] "Consultation content" refers to questions and issues raised by users through the system, which are analyzed by the generation AI.

[0168] "Solutions" refer to specific solutions or advice for the problems or questions users are facing.

[0169] "User Feedback" refers to opinions and suggestions for improvement collected from users after using the Service.

[0170] "Means for improving the service" refers to the process for modifying and improving the system and the content provided based on user feedback.

[0171] To implement this invention, the following main components are required: a server containing the generative AI, a terminal accessed by the user, and the user who uses the service. These components work together to provide a gender equity support service.

[0172] System Configuration

[0173] This system consists of a server, a terminal, and a user. The server contains a generative AI model and analyzes data provided by the user to provide educational content and analyze the results of bias checks. The terminal provides the user interface and acts as a medium for the user to communicate with the server.

[0174] User Registration and Login

[0175] When a user registers, they enter personal information such as their name, email address, and password. The device sends this information to the server, and the server creates a user account based on the received information. The user also logs in with an already created account, and the server verifies the user's identity by comparing it with information in the database, then generates and returns an authentication token. The device receives the authentication token and redirects the user to the home screen.

[0176] Providing gender equity education content

[0177] When a user accesses the catalog page to select the educational content they wish to study, the device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device, which then displays it to the user.

[0178] As a concrete example, when providing educational content for children, users (children) use a dedicated educational app to learn about gender equity. The device displays educational materials in the form of videos and quizzes and monitors the learning progress. The server receives the learning data, generates a progress report, and provides it to the educator.

[0179] Unconscious Bias Check

[0180] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which then analyzes the received data using a generative AI model to evaluate whether it contains unconscious bias. The server generates analysis results and improvement suggestions, which are then sent to the device, which displays them to the user.

[0181] An example prompt is:

[0182] "Please evaluate how your unconscious biases are manifested in your responses to the bias check questions and provide specific suggestions for improvement."

[0183] Communication Support

[0184] The user inputs the content of their inquiry into the chat interface. The device sends the content to the server, which analyzes it using a generative AI. The server generates an appropriate solution and sends it to the device. The device then presents the solution to the user.

[0185] An example prompt is:

[0186] "Analyze the consultation about communication problems in the workplace and propose solutions."

[0187] Feedback and Improvements

[0188] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data using a generative AI model. The server then uses the analysis results to identify areas for improvement in the system and makes appropriate updates.

[0189] This system will enable learning, evaluation, and improvement suggestions that meet the needs of diverse users, contributing to improving gender equality.

[0190] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0191] Step 1:

[0192] The user enters their name, email address, and password into the new registration form.

[0193] Input: Name, Email Address, Password

[0194] Output: User registration information

[0195] Specifically, the user enters "Yamada Taro," "taro.yamada@example.com," and "password123" into the form.

[0196] Step 2:

[0197] The terminal sends the entered information to the server using an HTTP POST request.

[0198] Input: User registration information

[0199] Output: HTTP POST request to the server

[0200] The device sends this information to the server in JSON format.

[0201] Step 3:

[0202] The server verifies the received information and registers the new user account in its database.

[0203] Input: User registration information data

[0204] Output: Insertion result into database

[0205] The server uses an SQL query to insert the user information into a database.

[0206] Step 4:

[0207] The terminal notifies the user that the account creation is complete.

[0208] Input: Account creation completion notification

[0209] Output: A message to inform the user

[0210] The device will display the message "Account created successfully."

[0211] Step 5:

[0212] The user enters their email address and password into the login form.

[0213] Input: Email address, password

[0214] Output: Login information

[0215] For example, the user enters "taro.yamada@example.com" and "password123".

[0216] Step 6:

[0217] The device sends the entered login information to the server via an HTTP POST request.

[0218] Input: Login information

[0219] Output: HTTP POST request to the server

[0220] The device sends the information to the server in JSON format.

[0221] Step 7:

[0222] The server checks the database and generates an authentication token if authentication is successful.

[0223] Input: Login information data

[0224] Output: Authentication token

[0225] The server compares the received information with the user information in its database and generates a JWT (JSON Web Token) if there is a match.

[0226] Step 8:

[0227] The device receives the authentication token and redirects the user to the home screen.

[0228] Input: Authentication Token

[0229] Output: Redirect to home screen

[0230] The device stores the authentication token in local storage and redirects to the home screen.

[0231] Step 9:

[0232] The user accesses the educational content catalog page.

[0233] Input: Access to catalog page

[0234] Output: Catalog page display

[0235] A user opens the catalog page URL in a browser.

[0236] Step 10:

[0237] The terminal obtains a list of educational content from the server and displays it.

[0238] Input: Content data from the server

[0239] Output: List of educational content

[0240] The terminal displays the content information obtained from the server in a list format in HTML.

[0241] Step 11:

[0242] The user selects the content they wish to study and sends the content ID to the server.

[0243] Input: Selected Content ID

[0244] Output: Content ID sent to server

[0245] For example, a user selects a content item called "Gender History" and sends its ID to the server.

[0246] Step 12:

[0247] The server retrieves the relevant educational content from the database and sends it to the terminal.

[0248] Input: Content ID

[0249] Output: Acquired educational content data

[0250] The server retrieves the content data using an SQL query and then sends it to the terminal as an API response.

[0251] Step 13:

[0252] The terminal displays the acquired educational content to the user.

[0253] Input: Educational content data

[0254] Output: Displayed educational content

[0255] The device displays the content using a video player and quiz-style interface.

[0256] Step 14:

[0257] Users visit the Unconscious Bias Check page and answer questions.

[0258] Input: Bias Check Questions and Answers

[0259] Output: Response data

[0260] The user accesses the bias check questionnaire form and enters answers to the questions.

[0261] Step 15:

[0262] The terminal transmits the user's answer to the server.

[0263] Input: Answer data

[0264] Output: Send response data to the server

[0265] The device sends the response data to the server in JSON format.

[0266] Step 16:

[0267] The server analyzes the received data using a generative AI model to assess whether it contains unconscious bias.

[0268] Input: Answer data

[0269] Output: Analysis results and evaluation

[0270] The server uses a generative AI model to analyze the received response data.

[0271] Step 17:

[0272] The server generates analysis results and improvement suggestions and sends them to the terminal.

[0273] Input: Analysis results and evaluation

[0274] Output: Improvement proposal data

[0275] The server sends the analysis results and corresponding improvement suggestions to the terminal in JSON format.

[0276] Step 18:

[0277] The device displays the analysis results and improvement suggestions to the user.

[0278] Input: Improvement proposal data

[0279] Output: Display of analysis results and improvement suggestions

[0280] The terminal displays the analysis results and improvement suggestions in a user interface.

[0281] Step 19:

[0282] The user inputs the content of the consultation into the chat interface.

[0283] Input: Consultation details

[0284] Output: Input consultation content data

[0285] A user types in chat about "communication challenges at work."

[0286] Step 20:

[0287] The terminal transmits the consultation content data to the server.

[0288] Input: Consultation content data

[0289] Output: Send consultation details to the server

[0290] The device sends the chat content to the server in JSON format.

[0291] Step 21:

[0292] The server uses the generation AI to analyze the consultation content data.

[0293] Input: Consultation content data

[0294] Output: Analyzed result data

[0295] The server uses the generative AI model to analyze the received consultation data.

[0296] Step 22:

[0297] The server generates an appropriate solution and sends it to the terminal.

[0298] Input: Analysis result data

[0299] Output: Solution data

[0300] The server generates a solution and sends it to the device as an API response.

[0301] Step 23:

[0302] The terminal presents the generated solutions to the user.

[0303] Input: Solution data

[0304] Output: Displayed solution

[0305] The terminal displays the generated solution in a chat interface.

[0306] Step 24:

[0307] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0308] Input: Feedback data

[0309] Output: Input feedback data

[0310] Users enter their opinions and suggestions for improvement in the feedback form.

[0311] Step 25:

[0312] The terminal transmits the feedback data to the server.

[0313] Input: Feedback data

[0314] Output: Send feedback to the server

[0315] The device sends the feedback content to the server in JSON format.

[0316] Step 26:

[0317] The server analyzes the feedback data using a generative AI model.

[0318] Input: Feedback data

[0319] Output: Parsed feedback results

[0320] The server uses a generative AI model to analyze the feedback data and generate results.

[0321] Step 27:

[0322] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[0323] Input: Analysis result data

[0324] Output: System improvements and updates

[0325] Based on the analysis results, the server designs improvements to the system and implements necessary updates.

[0326] The above are the specific processing steps of the program of this system.

[0327] (Application example 1)

[0328] 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."

[0329] As gender equity becomes increasingly important in modern society, there is a need for efficient support methods to promote individual awareness and behavioral improvement. Furthermore, systems that provide a wide range of services, such as educational content, unconscious bias checks, and consultation content analysis, require user-friendly and effective interactions. In particular, when providing this support in a virtual environment, there is a need for methods that facilitate the process of users becoming aware of their own unconscious biases and seeking solutions. Our goal is to provide a comprehensive system to solve these issues.

[0330] 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.

[0331] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation content and presenting solutions, means for collecting user feedback and improving services, means for providing educational content in a virtual environment and supporting an interactive learning experience, means for employees in the virtual environment to conduct bias checks and promote self-improvement, and means for providing customer support in the virtual environment and providing solutions to consultation content using a generative AI model. This enables users to learn about gender equity and improve themselves within the virtual environment, and allows them to receive efficient and effective support.

[0332] "Generative AI" is a system that uses artificial intelligence to generate, analyze, and predict data.

[0333] "Gender equity" is a concept that refers to a state in which men and women receive equal opportunities and treatment socially, economically, and culturally.

[0334] "Support services" refers to a series of services provided to solve problems and issues faced by users.

[0335] "User registration" is the process by which a new user enters the necessary personal information into the system and obtains eligibility to use the system.

[0336] "User Account" refers to the individual authentication information and data assigned to each User for use of the System.

[0337] "Educational content" refers to information and instructional materials designed to help learners acquire specific knowledge or skills.

[0338] "User's learning progress" refers to the user's level of achievement and understanding in the process of learning educational content.

[0339] "Unconscious bias check" refers to a method or checklist for assessing and detecting the prejudices and stereotypes that individuals unconsciously hold.

[0340] "Means for providing users with improvement suggestions" refers to features within the system that provide specific suggestions or advice to help users reduce their unconscious biases or improve their behavior.

[0341] "Consultation content" refers to information that indicates questions, problems, or concerns that a user inputs to the system.

[0342] "Solution" refers to the method or means provided to the user in response to their inquiry based on the results of analysis conducted by the system using generated AI.

[0343] "User feedback" refers to opinions from users, such as impressions after using the service, areas for improvement, and suggestions.

[0344] "Virtual environment" refers to a virtual space or simulated environment, including digital experiential spaces provided over the Internet.

[0345] An "interactive learning experience" refers to a learning method or experience in which the user actively participates and progresses interactively.

[0346] An "employee" refers to an individual employed by a company or organization to perform specific tasks or roles.

[0347] "Customer support" refers to the business activities that provide assistance and support to customers who use products or services.

[0348] A "generative AI model" refers to an artificial intelligence algorithm or framework built to learn from large amounts of data and generate new data or perform specific tasks.

[0349] This invention describes a system that uses generative AI to provide gender equity support services within a virtual environment, including user registration, educational content provision, unconscious bias checks, customer support consultation and resolution, and feedback collection.

[0350] 1. User Registration and Login

[0351] Users access the system using a terminal and register by entering personal information such as name, email address, and password. This information is sent to the server, which then creates a user account based on the received information. When logging in, the user enters their email address and password, which the terminal then sends to the server, which then compares them with the information in the database to verify that the user is a legitimate user.

[0352] 2. Providing educational content

[0353] The system interactively provides educational content related to gender equity that the user wishes to learn about within a virtual environment. The device displays a list of educational content and sends the content ID of the user's selection to the server. The server retrieves the corresponding educational content from a database and sends it to the device, which then displays it to the user.

[0354] 3. Unconscious bias check

[0355] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The server generates analysis results and improvement suggestions and sends them to the device.

[0356] 4. Customer support and analysis of inquiries

[0357] The user enters the content of their inquiry into the chat interface, and the device sends the content to the server. The server analyzes it using generative AI, generates an appropriate solution, and sends it to the device. The device then presents the solution to the user.

[0358] 5. Collecting feedback and improving our services

[0359] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data and identifies areas for improvement in the service.

[0360] The system is implemented using Python and the Flask framework, with the SQLite database and the SHA-256 hash function for password security.

[0361] For example, consider the following prompt:

[0362] Sample unconscious bias check questions:

[0363] "To assess your own unconscious biases, answer these questions:

[0364] 1. Do you ever feel that one gender is superior, even when there are objective standards of evaluation?

[0365] 2. Do you unconsciously stereotype certain genders in your daily life or at work?

[0366] Example start prompts for gender equity education content:

[0367] Get started with educational content on gender equity. Study the following materials:

[0368] 1. What is gender equity?

[0369] 2. How to promote gender equity in the workplace

[0370] In this way, users can learn about gender equity and improve themselves within a virtual environment, receiving efficient and effective support.

[0371] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0372] Step 1:

[0373] A user accesses the system using a terminal and registers by entering personal information such as name, email address, and password. The terminal sends the entered information to the server, which then creates a user account based on the received information. The input data includes name, email address, and password (SHA-256 hashed), and the output data is the created user account.

[0374] Step 2:

[0375] When logging in, the user enters their email address and password. The device sends this to the server, which checks it against information in a database to verify the user is a valid user. The input data is the email address and hashed password, and the output data is an authentication token. The device receives the authentication token and redirects the user to the home screen.

[0376] Step 3:

[0377] The user browses gender equity educational content provided in a virtual environment. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The input data is the content ID, and the output data is the educational content. The device displays the educational content to the user, allowing the user to progress with their learning.

[0378] Step 4:

[0379] The user accesses the unconscious bias check page and answers the required questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The input data is the user's answers, and the output data is the analysis results and improvement suggestions. The server generates the analysis results and improvement suggestions and sends them to the device, which displays them to the user.

[0380] Step 5:

[0381] The user inputs the details of their customer support inquiry into the chat interface. The device sends the details to the server, which analyzes them using a generative AI model. The input data is the inquiry details, and the output data is an appropriate solution. The server generates a solution and sends it to the device. The device presents the solution to the user.

[0382] Step 6:

[0383] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data and identifies areas for improvement in the system. The input data is the feedback content, and the output data is the analysis results and improvement suggestions. The server then performs appropriate system updates based on this.

[0384] 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.

[0385] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[0386] User Registration and Login

[0387] User Registration:

[0388] When a user registers, he or she enters personal information such as name, email address, and password.

[0389] The terminal sends this information to the server, which then creates a user account based on the received information.

[0390] The terminal notifies the user that the account creation is complete.

[0391] Login:

[0392] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[0393] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[0394] The device receives the authentication token and redirects the user to the home screen.

[0395] Providing gender equity education content

[0396] View content:

[0397] A user accesses a catalog page to select the educational content they wish to study.

[0398] The terminal displays a list of educational content and transmits the content ID selected by the user to the server.

[0399] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[0400] The terminal displays educational content to the user, and the user progresses with his / her studies.

[0401] The emotion engine recognizes the user's emotions in real time and transmits the data to the server.

[0402] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[0403] Unconscious Bias Check

[0404] Checks performed:

[0405] Users visit the Unconscious Bias Check page and answer the necessary questions.

[0406] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[0407] The server also analyzes the emotion data received from the emotion engine to generate more accurate evaluation results.

[0408] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[0409] The terminal displays this to the user.

[0410] Communication Support

[0411] Input and analysis of consultation content:

[0412] The user inputs the content of the consultation into the chat interface.

[0413] The device sends the content to the server, which then analyzes it using a generating AI.

[0414] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[0415] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[0416] The terminal presents a solution to the user.

[0417] Feedback and Improvements

[0418] Feedback collection and analysis:

[0419] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0420] The terminal sends this to the server, which analyzes the feedback data.

[0421] The emotion engine collects the user's emotional state during feedback input and also sends it to the server.

[0422] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[0423] The server updates the system based on the extracted improvements.

[0424] Specific examples

[0425] Providing educational content for children:

[0426] Users (children) learn about gender equity using a dedicated educational app.

[0427] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[0428] The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server.

[0429] The server uses emotional data to assess stress and interest levels during learning and adjusts the content accordingly.

[0430] The device displays tailored content to optimize the user's learning experience.

[0431] Unconscious Bias Check:

[0432] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[0433] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[0434] The emotion engine recognizes the user's emotion in the response and transmits it to the server.

[0435] The server analyzes the response data and sentiment data, and provides an assessment of bias and suggestions for improvement.

[0436] This system provides comprehensive support for gender equity issues, facilitating the education, assessment, and improvement processes. In addition, by combining it with an emotion engine, it provides optimal support according to the user's individual emotional state.

[0437] The processing flow will be explained below.

[0438] User Registration and Login

[0439] New Registration

[0440] Step 1:

[0441] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[0442] Step 2:

[0443] The terminal transmits the input information to the server.

[0444] Step 3:

[0445] The server stores the received user information in a database and creates a new account.

[0446] Step 4:

[0447] The terminal displays a message to the user indicating that registration is complete.

[0448] Log in

[0449] Step 1:

[0450] The user enters their email address and password into the login form on their device.

[0451] Step 2:

[0452] The terminal transmits the input information to the server.

[0453] Step 3:

[0454] The server checks the account information against the database and performs authentication.

[0455] Step 4:

[0456] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[0457] Step 5:

[0458] The device receives the authentication token and redirects the user to the dashboard or home screen.

[0459] Providing gender equity education content

[0460] View content

[0461] Step 1:

[0462] The user accesses the educational content catalog page from the terminal.

[0463] Step 2:

[0464] The device displays a list of educational content.

[0465] Step 3:

[0466] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[0467] Step 4:

[0468] The server retrieves the corresponding educational content from the database based on the received content ID.

[0469] Step 5:

[0470] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[0471] Step 6:

[0472] The terminal displays the educational content to the user.

[0473] Utilizing Emotional Data

[0474] Step 1:

[0475] The emotion engine recognizes emotions in real time from the user's facial expressions and tone of voice.

[0476] Step 2:

[0477] The emotion engine sends the emotion data to the server.

[0478] Step 3:

[0479] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[0480] Step 4:

[0481] The server transmits the adjusted content data to the terminal.

[0482] Step 5:

[0483] The terminal displays the tailored educational content to the user.

[0484] Unconscious Bias Check

[0485] Check implementation

[0486] Step 1:

[0487] A user accesses the Unconscious Bias Check page on their device.

[0488] Step 2:

[0489] The terminal provides an interface for displaying the check questions.

[0490] Step 3:

[0491] The user enters an answer to each question.

[0492] Step 4:

[0493] The terminal transmits the response data to the server.

[0494] Step 5:

[0495] The server analyzes the response data and assesses whether or not there is unconscious bias.

[0496] Step 6:

[0497] The emotion engine recognizes the user's emotion in the response and sends the data to the server.

[0498] Step 7:

[0499] The server integrates and analyzes the response data and emotion data to generate bias evaluation results.

[0500] Step 8:

[0501] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[0502] Step 9:

[0503] The terminal displays the evaluation results and improvement suggestions to the user.

[0504] Communication Support

[0505] Input and analysis of consultation details

[0506] Step 1:

[0507] The user inputs the content of the consultation into the chat interface.

[0508] Step 2:

[0509] The terminal transmits the contents to the server.

[0510] Step 3:

[0511] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[0512] Step 4:

[0513] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[0514] Step 5:

[0515] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[0516] Step 6:

[0517] The terminal presents a solution to the user.

[0518] Feedback and Improvements

[0519] Feedback collection and analysis

[0520] Step 1:

[0521] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0522] Step 2:

[0523] The terminal transmits the input feedback to the server.

[0524] Step 3:

[0525] The emotion engine recognizes the user's emotions during feedback input and sends the data to the server.

[0526] Step 4:

[0527] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement.

[0528] Step 5:

[0529] The server updates the system based on the extracted improvements.

[0530] Step 6:

[0531] The server notifies the terminal of the update contents and displays them to the user.

[0532] Through this process, the gender equity support system can provide users with appropriate support and an optimal learning experience according to their emotional state.

[0533] Example 2

[0534] 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."

[0535] Promoting gender equality is becoming increasingly important in modern society. However, traditional education and support services provide uniform content without considering the user's emotional state, making it difficult to provide optimal support for each individual user. Furthermore, because emotional data is not taken into account when assessing unconscious bias or making suggestions for improvement, there are limitations to the accuracy and effectiveness of these services. Furthermore, educational content delivery lacks interactivity, making it ineffective, especially for children.

[0536] 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.

[0537] In this invention, the server includes a means for accepting user registration and creating a user account, a means for providing educational content and collecting and analyzing the user's learning progress, a means for conducting unconscious bias checks and providing improvement suggestions to the user, a means for collecting emotional data in real time and adjusting the content content and difficulty level based on the collected data, and a means for using the emotional data to evaluate unconscious bias and generate improvement suggestions. This makes it possible to provide gender equity support that is optimal for each individual user based on their emotional state, which is expected to be highly accurate and effective in terms of educational effectiveness and the reduction of unconscious bias. It also improves the interactivity of educational content for children, significantly improving the quality of the learning experience.

[0538] "User registration" refers to the process by which a new user of the system enters personal information and creates a user account based on that information.

[0539] "User Account" is a digital identifier generated by the system to manage a user's personal information and authentication information.

[0540] "Educational content" refers to learning materials and educational materials related to gender equity, including videos, quizzes, articles, etc.

[0541] "Study progress" is information indicating how much learning the user has completed through educational content.

[0542] An "unconscious bias check" is a process that involves asking questions or taking tests to assess whether a user has any unconscious biases.

[0543] "Improvement suggestions" are specific advice and guidelines for improving the user's perceived biases, generated based on the results of the unconscious bias check.

[0544] "Consultation" refers to the text information or question a user enters to seek assistance with gender equity.

[0545] "Emotional data" is information about the user's emotional state, collected from the user's facial expressions, tone of voice, and the like.

[0546] "Real-time" means that information is obtained and processed immediately, and refers to a response without delay.

[0547] An "unconscious bias assessment" is the process of analyzing the results of a user's unconscious bias check to determine whether unconscious bias is present.

[0548] An "interactive learning experience" is a learning method in which users actively interact with educational content and exchange information in a two-way manner, promoting deep understanding.

[0549] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. This system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[0550] Hardware and Software Configuration

[0551] Terminal: A device operated by the user, and can be a variety of devices such as a PC, smartphone, tablet, etc. The terminal accesses the system via a web browser or dedicated application.

[0552] Server: A central system that manages and processes generative AI and various data. The server includes a database management system (DBMS) and emotion engine, and is expected to be a cloud server or on-premise server.

[0553] Generative AI: An artificial intelligence model used to analyze user inquiries and feedback and generate appropriate responses and suggestions.

[0554] Emotion engine: A software engine that analyzes the user's facial expressions and voice tone in real time to collect emotional data.

[0555] System processing overview

[0556] The system performs the following main processes:

[0557] User Registration and Login

[0558] A user registers by entering personal information such as name, email address, and password. The device sends this information to the server, which then creates a user account. Once the account creation is complete, the device notifies the user. When logging in, the user enters their email address and password, which the device sends to the server. The server compares the information with that in the database, generates an authentication token, and sends it back. The device then redirects the user to the home screen.

[0559] Providing educational content

[0560] The user accesses the catalog page to select the educational content they wish to study. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The device displays the educational content to the user, who then proceeds with their study. The emotion engine recognizes the user's emotions in real time and sends that data to the server. The server analyzes the emotion data and adjusts the content and difficulty of the content to be displayed.

[0561] Unconscious Bias Check

[0562] The user accesses the unconscious bias check page and answers the necessary questions. The device sends the user's answers to the server. The server analyzes the received data and evaluates whether it contains unconscious bias. The server also analyzes the emotional data received from the emotion engine to generate a more accurate evaluation result. The server generates the evaluation result and improvement suggestions and sends them to the device. The device displays them to the user.

[0563] Communication Support

[0564] The user inputs the content of their consultation into the chat interface. The device sends the content to the server, which analyzes it using generative AI. The emotion engine monitors the user's emotional state in real time during the consultation and sends the data to the server. The server takes the emotional data into consideration to generate an optimal solution and sends it to the device. The device then presents the solution to the user.

[0565] Feedback and Improvements

[0566] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data. The emotion engine collects the user's emotional state while they are entering feedback and sends this to the server. The server then integrates and analyzes the feedback data and emotion data to identify areas for improvement in the service. The server then updates the system based on the identified areas for improvement.

[0567] Specific examples

[0568] Providing educational content for children: Users (children) learn about gender equity using a dedicated educational app. The device displays learning materials in the form of videos and quizzes and monitors learning progress. The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server. The server uses the emotion data to assess stress and interest levels during learning and adjusts the content accordingly. The device displays the adjusted content, optimizing the user's learning experience.

[0569] Unconscious Bias Check: After a job interview, a user (e.g., a human resources officer) performs a bias check for self-evaluation. The terminal displays a questionnaire in the form of questions, and the user enters their answers. The emotion engine recognizes the user's emotions while answering and sends them to the server. The server analyzes the response data and emotion data, and presents an assessment of bias and suggestions for improvement.

[0570] Example prompt sentence:

[0571] "In a job interview, you will assess your unconscious biases against candidates of a certain gender or background and provide feedback based on that. Please answer the following questions."

[0572] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0573] User Registration and Login

[0574] User Registration

[0575] Step 1:

[0576] The user enters their name, email address, password, etc. into the registration form. The device performs a simple check to verify the validity of the entered information (input format and required fields) and confirms that it is appropriate.

[0577] Input: Name, Email Address, Password

[0578] Output: Validity check result

[0579] Step 2:

[0580] The terminal transmits the authenticated information to the server.

[0581] Input: Name, Email Address, Password

[0582] Output: Send information to the server

[0583] Step 3:

[0584] The server creates a new user account in the database based on the received information. Once the account creation is complete, the server notifies the terminal that the account was created successfully.

[0585] Input: User information (name, email address, password)

[0586] Output: Account creation success notification

[0587] Step 4:

[0588] The terminal notifies the user that the account creation is complete.

[0589] Input: Account creation success notification

[0590] Output: User notification

[0591] Log in

[0592] Step 1:

[0593] The user enters their email address and password into the login form. The device performs a simple check to verify the validity of the information entered and verifies that it is correct.

[0594] Input: Email address, password

[0595] Output: Validity check result

[0596] Step 2:

[0597] The terminal transmits the authenticated information to the server.

[0598] Input: Email address, password

[0599] Output: Send authentication information to the server

[0600] Step 3:

[0601] The server compares the received authentication information with the registered information in the database, and if it is correct, it generates an authentication token and sends it to the terminal.

[0602] Input: Authentication information (email address, password)

[0603] Output: Authentication token

[0604] Step 4:

[0605] The device receives the authentication token and redirects the user to the home screen.

[0606] Input: Authentication Token

[0607] Output: Redirect to home screen

[0608] Providing gender equity education content

[0609] Step 1:

[0610] The user selects the educational content they want to study from the catalog page. The device sends the selected content ID to the server.

[0611] Input: Selected Content ID

[0612] Output: Send content ID to server

[0613] Step 2:

[0614] The server retrieves the relevant educational content from the database.

[0615] Input: Content ID

[0616] Output: Educational content data

[0617] Step 3:

[0618] The terminal displays the acquired educational content to the user.

[0619] Input: Educational content data

[0620] Output: Displaying content to the user

[0621] Step 4:

[0622] The user browses the content and progresses with their learning. The emotion engine analyzes the user's facial expressions and tone of voice in real time and sends the emotional data to the server.

[0623] Input: User facial expressions and tone of voice

[0624] Output: Emotion data

[0625] Step 5:

[0626] The server analyzes the emotional data and adjusts the content and difficulty level based on the user's emotional state, and then transmits the adjusted content data to the terminal.

[0627] Input: Emotion data

[0628] Output: Adjusted content data

[0629] Step 6:

[0630] The device then displays the tailored educational content back to the user, optimizing the learning experience.

[0631] Input: Adjusted content data

[0632] Output: Redisplay to user

[0633] Unconscious Bias Check

[0634] Step 1:

[0635] Users access the unconscious bias check page and answer the necessary questions. The device then sends the answers to the server.

[0636] Input: User's answer

[0637] Output: Send response to server

[0638] Step 2:

[0639] The server analyzes the received response data and evaluates whether it contains unconscious bias.

[0640] Input: Answer data

[0641] Output: Bias evaluation result

[0642] Step 3:

[0643] The emotion engine monitors the user's emotional state during the response and transmits the emotion data to the server.

[0644] Input: User's emotional state

[0645] Output: Emotion data

[0646] Step 4:

[0647] The server integrates and analyzes the response data and emotional data to generate more accurate evaluation results and improvement suggestions.

[0648] Input: Answer data, emotion data

[0649] Output: Evaluation results, improvement proposals

[0650] Step 5:

[0651] The server sends the generated evaluation results and improvement suggestions to the terminal, which displays them to the user.

[0652] Input: Evaluation results, improvement proposals

[0653] Output: What is displayed to the user

[0654] Communication Support

[0655] Step 1:

[0656] The user inputs the content of the consultation into the chat interface, and the terminal sends the content to the server.

[0657] Input: Consultation details

[0658] Output: Send consultation details to the server

[0659] Step 2:

[0660] The server uses generative AI to analyze the consultation content.

[0661] Input: Consultation details

[0662] Output: Analysis results

[0663] Step 3:

[0664] The emotion engine monitors the user's emotional state during the consultation and transmits the data to the server.

[0665] Input: User's emotional state

[0666] Output: Emotion data

[0667] Step 4:

[0668] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[0669] Input: consultation details, emotional data

[0670] Output: Solution

[0671] Step 5:

[0672] The terminal presents a solution to the user.

[0673] Input: Solution

[0674] Output: Presented to the user

[0675] Feedback and Improvements

[0676] Step 1:

[0677] After using the service, users enter their opinions and suggestions for improvement into a feedback form, which is then sent from the device to the server.

[0678] Input: Feedback

[0679] Output: Send feedback to the server

[0680] Step 2:

[0681] The server analyzes the feedback data. The emotion engine also collects the user's emotional state during the feedback input and sends it to the server.

[0682] Input: Feedback data, emotion data

[0683] Output: Analysis results

[0684] Step 3:

[0685] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[0686] Input: Feedback data, emotion data

[0687] Output: Improvements

[0688] Step 4:

[0689] The server updates the system based on the extracted improvements, thereby improving the user experience.

[0690] Input: Improvements

[0691] Output: System Update

[0692] Step 5:

[0693] The terminal applies the updated system contents to the user and the contents are reflected the next time the terminal is used.

[0694] Enter: System Update

[0695] Output: Apply to user

[0696] (Application example 2)

[0697] 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."

[0698] While interest in gender equity has grown in recent years, existing educational systems and support services have not adequately addressed this issue. Furthermore, gender bias exists in electronic payment systems, creating a need for fair support for diverse users. Interfaces and product recommendations tailored to the user's emotional state are particularly needed, but few systems offer such functionality. Therefore, a system is needed that integrates educational support to promote gender equity and electronic payment support that reflects the user's emotional state.

[0699] 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.

[0700] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing the user's learning progress, means for conducting unconscious bias checks and providing the user with improvement suggestions, means for analyzing the content of the consultation and presenting solutions, means for collecting user feedback and improving the service, means for monitoring the user's emotional state in real time and having the data analyzed by a generation AI, and means for supporting electronic payments by adjusting the display interface and recommended products based on the emotional data. This enables gender equity education and electronic payment support based on the user's individual emotional state.

[0701] "Generative AI" is an artificial intelligence technology that uses machine learning algorithms to generate new data and information.

[0702] "Gender equity" is the state of providing fair and equal opportunities and treatment regardless of gender.

[0703] A "support service" is a system or program that provides support to meet a user's specific needs.

[0704] "User Registration" is the process by which a user provides personal information to create a new account on the system.

[0705] A "user account" is a unique identification for accessing the system and using various services.

[0706] "Educational content" refers to information and materials for learning that users use to acquire knowledge and skills.

[0707] "Study progress" is a status indicating how much the user has studied the educational content.

[0708] The "Unconscious Bias Check" is a test designed to assess the biases users may have without even realizing it.

[0709] "Improvement proposals" are specific proposals for changing the user's behavior or way of thinking based on the evaluation results.

[0710] "Consultation content" refers to the content or question that the user inquires about the system.

[0711] "Solution" refers to the specific response or advice that the system presents in response to the consultation content.

[0712] "Feedback" refers to opinions and impressions provided by users after using the service.

[0713] An "emotion engine" is a technology that recognizes a user's emotional state by analyzing their facial expressions, voice, etc.

[0714] "Real time" means that processing or response is carried out immediately at the present time.

[0715] "Monitoring" is the act of continuously observing and recording specific data or conditions.

[0716] "Electronic payments" are methods of paying for goods and services over the Internet.

[0717] An "interface" is a point of contact or operation screen through which a user and a system can interact.

[0718] "Recommended products" are products that are suggested based on the user's needs and preferences.

[0719] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[0720] When registering for the first time, a user uses a device to send personal information such as name, email address, and password to the server to create a user account. The server receives this information, creates the user account, and sends a completion notification to the device. Existing users can also log in to the service by entering their account information into their device, sending it to the server, and obtaining an authentication token.

[0721] When providing educational content, the server utilizes an emotion engine that grasps the user's emotional state in real time. When a user selects content from the catalog page, that information is sent to the server via the device, and the server sends the corresponding educational content back to the device. The device displays the educational content to the user, and as the user progresses with their learning, the emotion engine analyzes facial expressions and voice data and sends the user's emotional state. Based on this emotional data, the server adjusts the display content and difficulty level to optimize the learning experience.

[0722] To conduct an unconscious bias check, the user answers questions via their device. The device sends the answer data to a server, which then analyzes the data using generative AI. Meanwhile, the emotion engine also collects the user's emotional data in real time and sends this data to the server. The server then comprehensively evaluates the data, generates improvement suggestions for the user, and presents them to the user via their device.

[0723] Furthermore, in the electronic payment support function, the server uses generative AI to provide optimal display interfaces and recommended products based on the emotional state obtained from the emotion engine when the user uses the terminal to purchase a product. By monitoring emotional data, for example, if the user is feeling stressed, the server can improve the user experience by recommending relaxation items.

[0724] For example, if the user is in an "angry" emotional state while using the service, the server will recommend products such as "stress balls" and "cushions." In this case, the prompt to the generative AI model will be as follows:

[0725] "The user is currently angry. Please recommend a relaxation item."

[0726] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0727] Step 1:

[0728] A user registers or logs in. The device receives the user's input (name, email address, password) and sends it to the server. The server receives this data and creates a user account in the case of a new registration, or generates an authentication token in the case of an existing user and sends it back to the device. The device receives a completion notification or authentication token and displays it to the user.

[0729] Input: User personal or login information

[0730] Output: New account creation notification or authentication token

[0731] Step 2:

[0732] The user selects educational content. The device sends the user's selection data (content ID) to the server. The server retrieves the corresponding educational content from the database and sends it back to the device.

[0733] Input: Content selection data

[0734] Output: Corresponding educational content

[0735] Step 3:

[0736] The user browses educational content. The device displays the educational content, and as the user progresses with their learning, the emotion engine collects the user's emotional data (facial expressions, voice, etc.) and sends it to the server in real time. The server analyzes this emotional data and adjusts the display content and difficulty level. The device continues to display the adjusted content.

[0737] Input: Emotion data

[0738] Output: Tailored educational content

[0739] Step 4:

[0740] The user performs an unconscious bias check. The device sends the user's answers (answer data to questions) to the server. The server analyzes them, evaluates unconscious bias along with emotional data from the emotion engine, generates improvement suggestions, and sends them to the device. The device displays them to the user.

[0741] Input: Answer data and sentiment data

[0742] Output: Bias assessment and improvement suggestions

[0743] Step 5:

[0744] The user inputs the content of the consultation into the chat interface. The device sends the content (consultation content data) to the server. The server analyzes the content using generative AI and takes into account the emotional data from the emotion engine to generate the optimal solution, which is then sent to the device. The device then presents the solution to the user.

[0745] Input: Consultation content data and emotion data

[0746] Output: Optimal solution

[0747] Step 6:

[0748] A user attempts to purchase a product on the payment screen. The terminal initiates the payment process (purchase data), and the emotion engine monitors the user's emotional state (emotion data). The server uses generative AI to generate an appropriate display interface and recommended products based on the emotion data, and sends them to the terminal. The terminal displays the recommended products and adjusted interface.

[0749] Input: Purchase and sentiment data

[0750] Output: Recommended products and tailored interface

[0751] As a concrete example, if the emotion engine determines that the user's emotional state is "angry," it sends the following prompt to the generative AI model:

[0752] "The user is currently angry. Please recommend a relaxation item."

[0753] 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.

[0754] 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.

[0755] 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.

[0756] [Second embodiment]

[0757] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0758] 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.

[0759] 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).

[0760] 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.

[0761] 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.

[0762] 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).

[0763] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0764] 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.

[0765] 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.

[0766] 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.

[0767] 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.

[0768] 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."

[0769] To implement this invention, a system with the following configuration is required. The main elements are a server containing the generation AI, a terminal accessed by the user, and the user who uses the service.

[0770] User Registration and Login

[0771] User Registration:

[0772] When a user registers, he or she enters personal information such as name, email address, and password.

[0773] The terminal sends this information to the server, which then creates a user account based on the received information.

[0774] The terminal notifies the user that the account creation is complete.

[0775] Login:

[0776] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[0777] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[0778] The device receives the authentication token and redirects the user to the home screen.

[0779] Providing gender equity education content

[0780] View content:

[0781] A user accesses a catalog page to select the educational content they wish to study.

[0782] The terminal displays a list of educational content and sends the content ID selected by the user to the server.

[0783] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[0784] The terminal displays educational content to the user, and the user progresses with his / her studies.

[0785] Unconscious Bias Check

[0786] Checks performed:

[0787] Users visit the Unconscious Bias Check page and answer the necessary questions.

[0788] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[0789] The server generates analysis results and improvement suggestions and sends them to the terminal.

[0790] The terminal displays this to the user.

[0791] Communication Support

[0792] Input and analysis of consultation content:

[0793] The user inputs the content of the consultation into the chat interface.

[0794] The device sends the content to the server, which then analyzes it using a generating AI.

[0795] The server generates an appropriate solution and sends it to the terminal.

[0796] The terminal presents a solution to the user.

[0797] Feedback and Improvements

[0798] Feedback collection and analysis:

[0799] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0800] The terminal sends this to the server, which analyzes the feedback data.

[0801] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[0802] Specific examples

[0803] Providing educational content for children:

[0804] Users (children) learn about gender equity using a dedicated educational app.

[0805] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[0806] The server receives learning data and generates progress reports to provide to parents and educators.

[0807] Unconscious Bias Check:

[0808] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[0809] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[0810] The server analyzes the response data and provides an assessment of bias and suggestions for improvement.

[0811] This system provides comprehensive support for gender equity issues and facilitates the education, evaluation, and improvement processes.

[0812] The processing flow will be explained below.

[0813] User Registration and Login

[0814] New Registration

[0815] Step 1:

[0816] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[0817] Step 2:

[0818] The terminal transmits the input information to the server.

[0819] Step 3:

[0820] The server stores the received user information in a database and creates a new account.

[0821] Step 4:

[0822] The terminal displays a message to the user indicating that registration is complete.

[0823] Log in

[0824] Step 1:

[0825] The user enters their email address and password into the login form on their device.

[0826] Step 2:

[0827] The terminal transmits the input information to the server.

[0828] Step 3:

[0829] The server checks the account information against the database and performs authentication.

[0830] Step 4:

[0831] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[0832] Step 5:

[0833] The device receives the authentication token and redirects the user to the dashboard or home screen.

[0834] Providing gender equity education content

[0835] View content

[0836] Step 1:

[0837] The user accesses the educational content catalog page from the terminal.

[0838] Step 2:

[0839] The device displays a list of educational content.

[0840] Step 3:

[0841] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[0842] Step 4:

[0843] The server retrieves the corresponding educational content from the database based on the received content ID.

[0844] Step 5:

[0845] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[0846] Step 6:

[0847] The terminal displays the educational content to the user.

[0848] Unconscious Bias Check

[0849] Check implementation

[0850] Step 1:

[0851] A user accesses the Unconscious Bias Check page on their device.

[0852] Step 2:

[0853] The terminal provides an interface for displaying the check questions.

[0854] Step 3:

[0855] The user enters an answer to each question.

[0856] Step 4:

[0857] The terminal transmits the response data to the server.

[0858] Step 5:

[0859] The server analyzes the response data and assesses whether or not there is unconscious bias.

[0860] Step 6:

[0861] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[0862] Step 7:

[0863] The terminal displays the evaluation results and improvement suggestions to the user.

[0864] Communication Support

[0865] Input and analysis of consultation details

[0866] Step 1:

[0867] The user uses the chat interface to input the consultation content.

[0868] Step 2:

[0869] The terminal transmits the input consultation content to the server.

[0870] Step 3:

[0871] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[0872] Step 4:

[0873] The server sends the solution to the terminal.

[0874] Step 5:

[0875] The terminal displays the solution to the user.

[0876] Feedback and Improvements

[0877] Feedback collection and analysis

[0878] Step 1:

[0879] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[0880] Step 2:

[0881] The terminal transmits the input feedback to the server.

[0882] Step 3:

[0883] The server analyzes the feedback data and extracts areas for improvement.

[0884] Step 4:

[0885] The server updates the system based on the extracted improvements.

[0886] This step will ensure that the Gender Equity Support System operates smoothly and provides appropriate support for each use case.

[0887] Example 1

[0888] 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."

[0889] Gender equity is an important issue in modern society, but solving it is not easy because many people have unconscious biases. Existing education systems and corporate training programs often do not provide effective approaches to individual needs and issues. Furthermore, there are limitations to achieving gender equity because there is a lack of mechanisms in place to collect user feedback and continuously improve services. There is a need to provide a system that can solve these issues and effectively support gender equity.

[0890] 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.

[0891] In this invention, the server includes means for accepting user registration and creating a user account, means for users to log in and generate an authentication token, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation details and presenting solutions, and means for collecting user feedback and improving the service. This enables learning, assessment, and improvement suggestions that meet the needs of diverse users, contributing to the improvement of gender equity.

[0892] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate, analyze, and evaluate data.

[0893] "Gender equity" refers to a situation in which discrimination and inequity based on gender are eliminated and equal opportunities and treatment are provided to all.

[0894] "User registration" refers to the process by which a system user creates a new account on the system by providing personal information such as name, email address, and password.

[0895] "User account" refers to a data set used to individually identify a user in the system, including the user's personal information and usage history.

[0896] An "authentication token" refers to an electronic certificate that indicates a user has been properly authenticated and is used to grant access to a system.

[0897] "Educational content" refers to educational materials and information provided for users to learn from, and may include formats such as text, video, and quizzes.

[0898] "Study progress" refers to an indicator that indicates how much a user has progressed in their studies through educational content.

[0899] An "unconscious bias check" is a test that allows users to assess their own unconscious biases, often in the form of a questionnaire or survey.

[0900] "Improvement Suggestions" are specific advice to provide effective solutions to users' unconscious biases and other challenges.

[0901] "Consultation content" refers to questions and issues raised by users through the system, which are analyzed by the generation AI.

[0902] "Solutions" refer to specific solutions or advice for the problems or questions users are facing.

[0903] "User Feedback" refers to opinions and suggestions for improvement collected from users after using the Service.

[0904] "Means for improving the service" refers to the process for modifying and improving the system and the content provided based on user feedback.

[0905] To implement this invention, the following main components are required: a server containing the generative AI, a terminal accessed by the user, and the user who uses the service. These components work together to provide a gender equity support service.

[0906] System Configuration

[0907] This system consists of a server, a terminal, and a user. The server contains a generative AI model and analyzes data provided by the user to provide educational content and analyze the results of bias checks. The terminal provides the user interface and acts as a medium for the user to communicate with the server.

[0908] User Registration and Login

[0909] When a user registers, they enter personal information such as their name, email address, and password. The device sends this information to the server, and the server creates a user account based on the received information. The user also logs in with an already created account, and the server verifies the user's identity by comparing it with information in the database, then generates and returns an authentication token. The device receives the authentication token and redirects the user to the home screen.

[0910] Providing gender equity education content

[0911] When a user accesses the catalog page to select the educational content they wish to study, the device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device, which then displays it to the user.

[0912] As a concrete example, when providing educational content for children, users (children) use a dedicated educational app to learn about gender equity. The device displays educational materials in the form of videos and quizzes and monitors the learning progress. The server receives the learning data, generates a progress report, and provides it to the educator.

[0913] Unconscious Bias Check

[0914] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which then analyzes the received data using a generative AI model to evaluate whether it contains unconscious bias. The server generates analysis results and improvement suggestions, which are then sent to the device, which displays them to the user.

[0915] An example prompt is:

[0916] "Please evaluate how your unconscious biases are manifested in your responses to the bias check questions and provide specific suggestions for improvement."

[0917] Communication Support

[0918] The user inputs the content of their inquiry into the chat interface. The device sends the content to the server, which analyzes it using a generative AI. The server generates an appropriate solution and sends it to the device. The device then presents the solution to the user.

[0919] An example prompt is:

[0920] "Analyze the consultation about communication problems in the workplace and propose solutions."

[0921] Feedback and Improvements

[0922] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data using a generative AI model. The server then uses the analysis results to identify areas for improvement in the system and makes appropriate updates.

[0923] This system will enable learning, evaluation, and improvement suggestions that meet the needs of diverse users, contributing to improving gender equality.

[0924] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0925] Step 1:

[0926] The user enters their name, email address, and password into the new registration form.

[0927] Input: Name, Email Address, Password

[0928] Output: User registration information

[0929] Specifically, the user enters "Yamada Taro," "taro.yamada@example.com," and "password123" into the form.

[0930] Step 2:

[0931] The terminal sends the entered information to the server using an HTTP POST request.

[0932] Input: User registration information

[0933] Output: HTTP POST request to the server

[0934] The device sends this information to the server in JSON format.

[0935] Step 3:

[0936] The server verifies the received information and registers the new user account in its database.

[0937] Input: User registration information data

[0938] Output: Insertion result into database

[0939] The server uses an SQL query to insert the user information into a database.

[0940] Step 4:

[0941] The terminal notifies the user that the account creation is complete.

[0942] Input: Account creation completion notification

[0943] Output: A message to inform the user

[0944] The device will display the message "Account created successfully."

[0945] Step 5:

[0946] The user enters their email address and password into the login form.

[0947] Input: Email address, password

[0948] Output: Login information

[0949] For example, the user enters "taro.yamada@example.com" and "password123".

[0950] Step 6:

[0951] The device sends the entered login information to the server via an HTTP POST request.

[0952] Input: Login information

[0953] Output: HTTP POST request to the server

[0954] The device sends the information to the server in JSON format.

[0955] Step 7:

[0956] The server checks the database and generates an authentication token if authentication is successful.

[0957] Input: Login information data

[0958] Output: Authentication token

[0959] The server compares the received information with the user information in its database and generates a JWT (JSON Web Token) if there is a match.

[0960] Step 8:

[0961] The device receives the authentication token and redirects the user to the home screen.

[0962] Input: Authentication Token

[0963] Output: Redirect to home screen

[0964] The device stores the authentication token in local storage and redirects to the home screen.

[0965] Step 9:

[0966] The user accesses the educational content catalog page.

[0967] Input: Access to catalog page

[0968] Output: Catalog page display

[0969] A user opens the catalog page URL in a browser.

[0970] Step 10:

[0971] The terminal obtains a list of educational content from the server and displays it.

[0972] Input: Content data from the server

[0973] Output: List of educational content

[0974] The terminal displays the content information obtained from the server in a list format in HTML.

[0975] Step 11:

[0976] The user selects the content they wish to study and sends the content ID to the server.

[0977] Input: Selected Content ID

[0978] Output: Content ID sent to server

[0979] For example, a user selects a content item called "Gender History" and sends its ID to the server.

[0980] Step 12:

[0981] The server retrieves the relevant educational content from the database and sends it to the terminal.

[0982] Input: Content ID

[0983] Output: Acquired educational content data

[0984] The server retrieves the content data using an SQL query and then sends it to the terminal as an API response.

[0985] Step 13:

[0986] The terminal displays the acquired educational content to the user.

[0987] Input: Educational content data

[0988] Output: Displayed educational content

[0989] The device displays the content using a video player and quiz-style interface.

[0990] Step 14:

[0991] Users visit the Unconscious Bias Check page and answer questions.

[0992] Input: Bias Check Questions and Answers

[0993] Output: Response data

[0994] The user accesses the bias check questionnaire form and enters answers to the questions.

[0995] Step 15:

[0996] The terminal transmits the user's answer to the server.

[0997] Input: Answer data

[0998] Output: Send response data to the server

[0999] The device sends the response data to the server in JSON format.

[1000] Step 16:

[1001] The server analyzes the received data using a generative AI model to assess whether it contains unconscious bias.

[1002] Input: Answer data

[1003] Output: Analysis results and evaluation

[1004] The server uses a generative AI model to analyze the received response data.

[1005] Step 17:

[1006] The server generates analysis results and improvement suggestions and sends them to the terminal.

[1007] Input: Analysis results and evaluation

[1008] Output: Improvement proposal data

[1009] The server sends the analysis results and corresponding improvement suggestions to the terminal in JSON format.

[1010] Step 18:

[1011] The device displays the analysis results and improvement suggestions to the user.

[1012] Input: Improvement proposal data

[1013] Output: Display of analysis results and improvement suggestions

[1014] The terminal displays the analysis results and improvement suggestions in a user interface.

[1015] Step 19:

[1016] The user inputs the content of the consultation into the chat interface.

[1017] Input: Consultation details

[1018] Output: Input consultation content data

[1019] A user types in chat about "communication challenges at work."

[1020] Step 20:

[1021] The terminal transmits the consultation content data to the server.

[1022] Input: Consultation content data

[1023] Output: Send consultation details to the server

[1024] The device sends the chat content to the server in JSON format.

[1025] Step 21:

[1026] The server uses the generation AI to analyze the consultation content data.

[1027] Input: Consultation content data

[1028] Output: Analyzed result data

[1029] The server uses the generative AI model to analyze the received consultation data.

[1030] Step 22:

[1031] The server generates an appropriate solution and sends it to the terminal.

[1032] Input: Analysis result data

[1033] Output: Solution data

[1034] The server generates a solution and sends it to the device as an API response.

[1035] Step 23:

[1036] The terminal presents the generated solutions to the user.

[1037] Input: Solution data

[1038] Output: Displayed solution

[1039] The terminal displays the generated solution in a chat interface.

[1040] Step 24:

[1041] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1042] Input: Feedback data

[1043] Output: Input feedback data

[1044] Users enter their opinions and suggestions for improvement in the feedback form.

[1045] Step 25:

[1046] The terminal transmits the feedback data to the server.

[1047] Input: Feedback data

[1048] Output: Send feedback to the server

[1049] The device sends the feedback content to the server in JSON format.

[1050] Step 26:

[1051] The server analyzes the feedback data using a generative AI model.

[1052] Input: Feedback data

[1053] Output: Parsed feedback results

[1054] The server uses a generative AI model to analyze the feedback data and generate results.

[1055] Step 27:

[1056] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[1057] Input: Analysis result data

[1058] Output: System improvements and updates

[1059] Based on the analysis results, the server designs improvements to the system and implements necessary updates.

[1060] The above are the specific processing steps of the program of this system.

[1061] (Application example 1)

[1062] 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."

[1063] As gender equity becomes increasingly important in modern society, there is a need for efficient support methods to promote individual awareness and behavioral improvement. Furthermore, systems that provide a wide range of services, such as educational content, unconscious bias checks, and consultation content analysis, require user-friendly and effective interactions. In particular, when providing this support in a virtual environment, there is a need for methods that facilitate the process of users becoming aware of their own unconscious biases and seeking solutions. Our goal is to provide a comprehensive system to solve these issues.

[1064] 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.

[1065] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation content and presenting solutions, means for collecting user feedback and improving services, means for providing educational content in a virtual environment and supporting an interactive learning experience, means for employees in the virtual environment to conduct bias checks and promote self-improvement, and means for providing customer support in the virtual environment and providing solutions to consultation content using a generative AI model. This enables users to learn about gender equity and improve themselves within the virtual environment, and allows them to receive efficient and effective support.

[1066] "Generative AI" is a system that uses artificial intelligence to generate, analyze, and predict data.

[1067] "Gender equity" is a concept that refers to a state in which men and women receive equal opportunities and treatment socially, economically, and culturally.

[1068] "Support services" refers to a series of services provided to solve problems and issues faced by users.

[1069] "User registration" is the process by which a new user enters the necessary personal information into the system and obtains eligibility to use the system.

[1070] "User Account" refers to the individual authentication information and data assigned to each User for use of the System.

[1071] "Educational content" refers to information and instructional materials designed to help learners acquire specific knowledge or skills.

[1072] "User's learning progress" refers to the user's level of achievement and understanding in the process of learning educational content.

[1073] "Unconscious bias check" refers to a method or checklist for assessing and detecting the prejudices and stereotypes that individuals unconsciously hold.

[1074] "Means for providing users with improvement suggestions" refers to features within the system that provide specific suggestions or advice to help users reduce their unconscious biases or improve their behavior.

[1075] "Consultation content" refers to information that indicates questions, problems, or concerns that a user inputs to the system.

[1076] "Solution" refers to the method or means provided to the user in response to their inquiry based on the results of analysis conducted by the system using generated AI.

[1077] "User feedback" refers to opinions from users, such as impressions after using the service, areas for improvement, and suggestions.

[1078] "Virtual environment" refers to a virtual space or simulated environment, including digital experiential spaces provided over the Internet.

[1079] An "interactive learning experience" refers to a learning method or experience in which the user actively participates and progresses interactively.

[1080] An "employee" refers to an individual employed by a company or organization to perform specific tasks or roles.

[1081] "Customer support" refers to the business activities that provide assistance and support to customers who use products or services.

[1082] A "generative AI model" refers to an artificial intelligence algorithm or framework built to learn from large amounts of data and generate new data or perform specific tasks.

[1083] This invention describes a system that uses generative AI to provide gender equity support services within a virtual environment, including user registration, educational content provision, unconscious bias checks, customer support consultation and resolution, and feedback collection.

[1084] 1. User Registration and Login

[1085] Users access the system using a terminal and register by entering personal information such as name, email address, and password. This information is sent to the server, which then creates a user account based on the received information. When logging in, the user enters their email address and password, which the terminal then sends to the server, which then compares them with the information in the database to verify that the user is a legitimate user.

[1086] 2. Providing educational content

[1087] The system interactively provides educational content related to gender equity that the user wishes to learn about within a virtual environment. The device displays a list of educational content and sends the content ID of the user's selection to the server. The server retrieves the corresponding educational content from a database and sends it to the device, which then displays it to the user.

[1088] 3. Unconscious bias check

[1089] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The server generates analysis results and improvement suggestions and sends them to the device.

[1090] 4. Customer support and analysis of inquiries

[1091] The user enters the content of their inquiry into the chat interface, and the device sends the content to the server. The server analyzes it using generative AI, generates an appropriate solution, and sends it to the device. The device then presents the solution to the user.

[1092] 5. Collecting feedback and improving our services

[1093] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data and identifies areas for improvement in the service.

[1094] The system is implemented using Python and the Flask framework, with the SQLite database and the SHA-256 hash function for password security.

[1095] For example, consider the following prompt:

[1096] Sample unconscious bias check questions:

[1097] "To assess your own unconscious biases, answer these questions:

[1098] 1. Do you ever feel that one gender is superior, even when there are objective standards of evaluation?

[1099] 2. Do you unconsciously stereotype certain genders in your daily life or at work?

[1100] Example start prompts for gender equity education content:

[1101] Get started with educational content on gender equity. Study the following materials:

[1102] 1. What is gender equity?

[1103] 2. How to promote gender equity in the workplace

[1104] In this way, users can learn about gender equity and improve themselves within a virtual environment, receiving efficient and effective support.

[1105] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1106] Step 1:

[1107] A user accesses the system using a terminal and registers by entering personal information such as name, email address, and password. The terminal sends the entered information to the server, which then creates a user account based on the received information. The input data includes name, email address, and password (SHA-256 hashed), and the output data is the created user account.

[1108] Step 2:

[1109] When logging in, the user enters their email address and password. The device sends this to the server, which checks it against information in a database to verify the user is a valid user. The input data is the email address and hashed password, and the output data is an authentication token. The device receives the authentication token and redirects the user to the home screen.

[1110] Step 3:

[1111] The user browses gender equity educational content provided in a virtual environment. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The input data is the content ID, and the output data is the educational content. The device displays the educational content to the user, allowing the user to progress with their learning.

[1112] Step 4:

[1113] The user accesses the unconscious bias check page and answers the required questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The input data is the user's answers, and the output data is the analysis results and improvement suggestions. The server generates the analysis results and improvement suggestions and sends them to the device, which displays them to the user.

[1114] Step 5:

[1115] The user inputs the details of their customer support inquiry into the chat interface. The device sends the details to the server, which analyzes them using a generative AI model. The input data is the inquiry details, and the output data is an appropriate solution. The server generates a solution and sends it to the device. The device presents the solution to the user.

[1116] Step 6:

[1117] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data and identifies areas for improvement in the system. The input data is the feedback content, and the output data is the analysis results and improvement suggestions. The server then performs appropriate system updates based on this.

[1118] 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.

[1119] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[1120] User Registration and Login

[1121] User Registration:

[1122] When a user registers, he or she enters personal information such as name, email address, and password.

[1123] The terminal sends this information to the server, which then creates a user account based on the received information.

[1124] The terminal notifies the user that the account creation is complete.

[1125] Login:

[1126] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[1127] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[1128] The device receives the authentication token and redirects the user to the home screen.

[1129] Providing gender equity education content

[1130] View content:

[1131] A user accesses a catalog page to select the educational content they wish to study.

[1132] The terminal displays a list of educational content and transmits the content ID selected by the user to the server.

[1133] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[1134] The terminal displays educational content to the user, and the user progresses with his / her studies.

[1135] The emotion engine recognizes the user's emotions in real time and transmits the data to the server.

[1136] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[1137] Unconscious Bias Check

[1138] Checks performed:

[1139] Users visit the Unconscious Bias Check page and answer the necessary questions.

[1140] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[1141] The server also analyzes the emotion data received from the emotion engine to generate more accurate evaluation results.

[1142] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[1143] The terminal displays this to the user.

[1144] Communication Support

[1145] Input and analysis of consultation content:

[1146] The user inputs the content of the consultation into the chat interface.

[1147] The device sends the content to the server, which then analyzes it using a generating AI.

[1148] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[1149] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[1150] The terminal presents a solution to the user.

[1151] Feedback and Improvements

[1152] Feedback collection and analysis:

[1153] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1154] The terminal sends this to the server, which analyzes the feedback data.

[1155] The emotion engine collects the user's emotional state during feedback input and also sends it to the server.

[1156] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[1157] The server updates the system based on the extracted improvements.

[1158] Specific examples

[1159] Providing educational content for children:

[1160] Users (children) learn about gender equity using a dedicated educational app.

[1161] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[1162] The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server.

[1163] The server uses emotional data to assess stress and interest levels during learning and adjusts the content accordingly.

[1164] The device displays tailored content to optimize the user's learning experience.

[1165] Unconscious Bias Check:

[1166] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[1167] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[1168] The emotion engine recognizes the user's emotion in the response and transmits it to the server.

[1169] The server analyzes the response data and sentiment data, and provides an assessment of bias and suggestions for improvement.

[1170] This system provides comprehensive support for gender equity issues, facilitating the education, assessment, and improvement processes. In addition, by combining it with an emotion engine, it provides optimal support according to the user's individual emotional state.

[1171] The processing flow will be explained below.

[1172] User Registration and Login

[1173] New Registration

[1174] Step 1:

[1175] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[1176] Step 2:

[1177] The terminal transmits the input information to the server.

[1178] Step 3:

[1179] The server stores the received user information in a database and creates a new account.

[1180] Step 4:

[1181] The terminal displays a message to the user indicating that registration is complete.

[1182] Log in

[1183] Step 1:

[1184] The user enters their email address and password into the login form on their device.

[1185] Step 2:

[1186] The terminal transmits the input information to the server.

[1187] Step 3:

[1188] The server checks the account information against the database and performs authentication.

[1189] Step 4:

[1190] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[1191] Step 5:

[1192] The device receives the authentication token and redirects the user to the dashboard or home screen.

[1193] Providing gender equity education content

[1194] View content

[1195] Step 1:

[1196] The user accesses the educational content catalog page from the terminal.

[1197] Step 2:

[1198] The device displays a list of educational content.

[1199] Step 3:

[1200] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[1201] Step 4:

[1202] The server retrieves the corresponding educational content from the database based on the received content ID.

[1203] Step 5:

[1204] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[1205] Step 6:

[1206] The terminal displays the educational content to the user.

[1207] Utilizing Emotional Data

[1208] Step 1:

[1209] The emotion engine recognizes emotions in real time from the user's facial expressions and tone of voice.

[1210] Step 2:

[1211] The emotion engine sends the emotion data to the server.

[1212] Step 3:

[1213] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[1214] Step 4:

[1215] The server transmits the adjusted content data to the terminal.

[1216] Step 5:

[1217] The terminal displays the tailored educational content to the user.

[1218] Unconscious Bias Check

[1219] Check implementation

[1220] Step 1:

[1221] A user accesses the Unconscious Bias Check page on their device.

[1222] Step 2:

[1223] The terminal provides an interface for displaying the check questions.

[1224] Step 3:

[1225] The user enters an answer to each question.

[1226] Step 4:

[1227] The terminal transmits the response data to the server.

[1228] Step 5:

[1229] The server analyzes the response data and assesses whether or not there is unconscious bias.

[1230] Step 6:

[1231] The emotion engine recognizes the user's emotion in the response and sends the data to the server.

[1232] Step 7:

[1233] The server integrates and analyzes the response data and emotion data to generate bias evaluation results.

[1234] Step 8:

[1235] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[1236] Step 9:

[1237] The terminal displays the evaluation results and improvement suggestions to the user.

[1238] Communication Support

[1239] Input and analysis of consultation details

[1240] Step 1:

[1241] The user inputs the content of the consultation into the chat interface.

[1242] Step 2:

[1243] The terminal transmits the contents to the server.

[1244] Step 3:

[1245] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[1246] Step 4:

[1247] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[1248] Step 5:

[1249] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[1250] Step 6:

[1251] The terminal presents a solution to the user.

[1252] Feedback and Improvements

[1253] Feedback collection and analysis

[1254] Step 1:

[1255] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1256] Step 2:

[1257] The terminal transmits the input feedback to the server.

[1258] Step 3:

[1259] The emotion engine recognizes the user's emotions during feedback input and sends the data to the server.

[1260] Step 4:

[1261] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement.

[1262] Step 5:

[1263] The server updates the system based on the extracted improvements.

[1264] Step 6:

[1265] The server notifies the terminal of the update contents and displays them to the user.

[1266] Through this process, the gender equity support system can provide users with appropriate support and an optimal learning experience according to their emotional state.

[1267] Example 2

[1268] 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."

[1269] Promoting gender equality is becoming increasingly important in modern society. However, traditional education and support services provide uniform content without considering the user's emotional state, making it difficult to provide optimal support for each individual user. Furthermore, because emotional data is not taken into account when assessing unconscious bias or making suggestions for improvement, there are limitations to the accuracy and effectiveness of these services. Furthermore, educational content delivery lacks interactivity, making it ineffective, especially for children.

[1270] 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.

[1271] In this invention, the server includes a means for accepting user registration and creating a user account, a means for providing educational content and collecting and analyzing the user's learning progress, a means for conducting unconscious bias checks and providing improvement suggestions to the user, a means for collecting emotional data in real time and adjusting the content content and difficulty level based on the collected data, and a means for using the emotional data to evaluate unconscious bias and generate improvement suggestions. This makes it possible to provide gender equity support that is optimal for each individual user based on their emotional state, which is expected to be highly accurate and effective in terms of educational effectiveness and the reduction of unconscious bias. It also improves the interactivity of educational content for children, significantly improving the quality of the learning experience.

[1272] "User registration" refers to the process by which a new user of the system enters personal information and creates a user account based on that information.

[1273] "User Account" is a digital identifier generated by the system to manage a user's personal information and authentication information.

[1274] "Educational content" refers to learning materials and educational materials related to gender equity, including videos, quizzes, articles, etc.

[1275] "Study progress" is information indicating how much learning the user has completed through educational content.

[1276] An "unconscious bias check" is a process that involves asking questions or taking tests to assess whether a user has any unconscious biases.

[1277] "Improvement suggestions" are specific advice and guidelines for improving the user's perceived biases, generated based on the results of the unconscious bias check.

[1278] "Consultation" refers to the text information or question a user enters to seek assistance with gender equity.

[1279] "Emotional data" is information about the user's emotional state, collected from the user's facial expressions, tone of voice, and the like.

[1280] "Real-time" means that information is obtained and processed immediately, and refers to a response without delay.

[1281] An "unconscious bias assessment" is the process of analyzing the results of a user's unconscious bias check to determine whether unconscious bias is present.

[1282] An "interactive learning experience" is a learning method in which users actively interact with educational content and exchange information in a two-way manner, promoting deep understanding.

[1283] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. This system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[1284] Hardware and Software Configuration

[1285] Terminal: A device operated by the user, and can be a variety of devices such as a PC, smartphone, tablet, etc. The terminal accesses the system via a web browser or dedicated application.

[1286] Server: A central system that manages and processes generative AI and various data. The server includes a database management system (DBMS) and emotion engine, and is expected to be a cloud server or on-premise server.

[1287] Generative AI: An artificial intelligence model used to analyze user inquiries and feedback and generate appropriate responses and suggestions.

[1288] Emotion engine: A software engine that analyzes the user's facial expressions and voice tone in real time to collect emotional data.

[1289] System processing overview

[1290] The system performs the following main processes:

[1291] User Registration and Login

[1292] A user registers by entering personal information such as name, email address, and password. The device sends this information to the server, which then creates a user account. Once the account creation is complete, the device notifies the user. When logging in, the user enters their email address and password, which the device sends to the server. The server compares the information with that in the database, generates an authentication token, and sends it back. The device then redirects the user to the home screen.

[1293] Providing educational content

[1294] The user accesses the catalog page to select the educational content they wish to study. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The device displays the educational content to the user, who then proceeds with their study. The emotion engine recognizes the user's emotions in real time and sends that data to the server. The server analyzes the emotion data and adjusts the content and difficulty of the content to be displayed.

[1295] Unconscious Bias Check

[1296] The user accesses the unconscious bias check page and answers the necessary questions. The device sends the user's answers to the server. The server analyzes the received data and evaluates whether it contains unconscious bias. The server also analyzes the emotional data received from the emotion engine to generate a more accurate evaluation result. The server generates the evaluation result and improvement suggestions and sends them to the device. The device displays them to the user.

[1297] Communication Support

[1298] The user inputs the content of their consultation into the chat interface. The device sends the content to the server, which analyzes it using generative AI. The emotion engine monitors the user's emotional state in real time during the consultation and sends the data to the server. The server takes the emotional data into consideration to generate an optimal solution and sends it to the device. The device then presents the solution to the user.

[1299] Feedback and Improvements

[1300] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data. The emotion engine collects the user's emotional state while they are entering feedback and sends this to the server. The server then integrates and analyzes the feedback data and emotion data to identify areas for improvement in the service. The server then updates the system based on the identified areas for improvement.

[1301] Specific examples

[1302] Providing educational content for children: Users (children) learn about gender equity using a dedicated educational app. The device displays learning materials in the form of videos and quizzes and monitors learning progress. The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server. The server uses the emotion data to assess stress and interest levels during learning and adjusts the content accordingly. The device displays the adjusted content, optimizing the user's learning experience.

[1303] Unconscious Bias Check: After a job interview, a user (e.g., a human resources officer) performs a bias check for self-evaluation. The terminal displays a questionnaire in the form of questions, and the user enters their answers. The emotion engine recognizes the user's emotions while answering and sends them to the server. The server analyzes the response data and emotion data, and presents an assessment of bias and suggestions for improvement.

[1304] Example prompt sentence:

[1305] "In a job interview, you will assess your unconscious biases against candidates of a certain gender or background and provide feedback based on that. Please answer the following questions."

[1306] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1307] User Registration and Login

[1308] User Registration

[1309] Step 1:

[1310] The user enters their name, email address, password, etc. into the registration form. The device performs a simple check to verify the validity of the entered information (input format and required fields) and confirms that it is appropriate.

[1311] Input: Name, Email Address, Password

[1312] Output: Validity check result

[1313] Step 2:

[1314] The terminal transmits the authenticated information to the server.

[1315] Input: Name, Email Address, Password

[1316] Output: Send information to the server

[1317] Step 3:

[1318] The server creates a new user account in the database based on the received information. Once the account creation is complete, the server notifies the terminal that the account was created successfully.

[1319] Input: User information (name, email address, password)

[1320] Output: Account creation success notification

[1321] Step 4:

[1322] The terminal notifies the user that the account creation is complete.

[1323] Input: Account creation success notification

[1324] Output: User notification

[1325] Log in

[1326] Step 1:

[1327] The user enters their email address and password into the login form. The device performs a simple check to verify the validity of the information entered and verifies that it is correct.

[1328] Input: Email address, password

[1329] Output: Validity check result

[1330] Step 2:

[1331] The terminal transmits the authenticated information to the server.

[1332] Input: Email address, password

[1333] Output: Send authentication information to the server

[1334] Step 3:

[1335] The server compares the received authentication information with the registered information in the database, and if it is correct, it generates an authentication token and sends it to the terminal.

[1336] Input: Authentication information (email address, password)

[1337] Output: Authentication token

[1338] Step 4:

[1339] The device receives the authentication token and redirects the user to the home screen.

[1340] Input: Authentication Token

[1341] Output: Redirect to home screen

[1342] Providing gender equity education content

[1343] Step 1:

[1344] The user selects the educational content they want to study from the catalog page. The device sends the selected content ID to the server.

[1345] Input: Selected Content ID

[1346] Output: Send content ID to server

[1347] Step 2:

[1348] The server retrieves the relevant educational content from the database.

[1349] Input: Content ID

[1350] Output: Educational content data

[1351] Step 3:

[1352] The terminal displays the acquired educational content to the user.

[1353] Input: Educational content data

[1354] Output: Displaying content to the user

[1355] Step 4:

[1356] The user browses the content and progresses with their learning. The emotion engine analyzes the user's facial expressions and tone of voice in real time and sends the emotional data to the server.

[1357] Input: User facial expressions and tone of voice

[1358] Output: Emotion data

[1359] Step 5:

[1360] The server analyzes the emotional data and adjusts the content and difficulty level based on the user's emotional state, and then transmits the adjusted content data to the terminal.

[1361] Input: Emotion data

[1362] Output: Adjusted content data

[1363] Step 6:

[1364] The device then displays the tailored educational content back to the user, optimizing the learning experience.

[1365] Input: Adjusted content data

[1366] Output: Redisplay to user

[1367] Unconscious Bias Check

[1368] Step 1:

[1369] Users access the unconscious bias check page and answer the necessary questions. The device then sends the answers to the server.

[1370] Input: User's answer

[1371] Output: Send response to server

[1372] Step 2:

[1373] The server analyzes the received response data and evaluates whether it contains unconscious bias.

[1374] Input: Answer data

[1375] Output: Bias evaluation result

[1376] Step 3:

[1377] The emotion engine monitors the user's emotional state during the response and transmits the emotion data to the server.

[1378] Input: User's emotional state

[1379] Output: Emotion data

[1380] Step 4:

[1381] The server integrates and analyzes the response data and emotional data to generate more accurate evaluation results and improvement suggestions.

[1382] Input: Answer data, emotion data

[1383] Output: Evaluation results, improvement proposals

[1384] Step 5:

[1385] The server sends the generated evaluation results and improvement suggestions to the terminal, which displays them to the user.

[1386] Input: Evaluation results, improvement proposals

[1387] Output: What is displayed to the user

[1388] Communication Support

[1389] Step 1:

[1390] The user inputs the content of the consultation into the chat interface, and the terminal sends the content to the server.

[1391] Input: Consultation details

[1392] Output: Send consultation details to the server

[1393] Step 2:

[1394] The server uses generative AI to analyze the consultation content.

[1395] Input: Consultation details

[1396] Output: Analysis results

[1397] Step 3:

[1398] The emotion engine monitors the user's emotional state during the consultation and transmits the data to the server.

[1399] Input: User's emotional state

[1400] Output: Emotion data

[1401] Step 4:

[1402] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[1403] Input: consultation details, emotional data

[1404] Output: Solution

[1405] Step 5:

[1406] The terminal presents a solution to the user.

[1407] Input: Solution

[1408] Output: Presented to the user

[1409] Feedback and Improvements

[1410] Step 1:

[1411] After using the service, users enter their opinions and suggestions for improvement into a feedback form, which is then sent from the device to the server.

[1412] Input: Feedback

[1413] Output: Send feedback to the server

[1414] Step 2:

[1415] The server analyzes the feedback data. The emotion engine also collects the user's emotional state during the feedback input and sends it to the server.

[1416] Input: Feedback data, emotion data

[1417] Output: Analysis results

[1418] Step 3:

[1419] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[1420] Input: Feedback data, emotion data

[1421] Output: Improvements

[1422] Step 4:

[1423] The server updates the system based on the extracted improvements, thereby improving the user experience.

[1424] Input: Improvements

[1425] Output: System Update

[1426] Step 5:

[1427] The terminal applies the updated system contents to the user and the contents are reflected the next time the terminal is used.

[1428] Enter: System Update

[1429] Output: Apply to user

[1430] (Application example 2)

[1431] 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."

[1432] While interest in gender equity has grown in recent years, existing educational systems and support services have not adequately addressed this issue. Furthermore, gender bias exists in electronic payment systems, creating a need for fair support for diverse users. Interfaces and product recommendations tailored to the user's emotional state are particularly needed, but few systems offer such functionality. Therefore, a system is needed that integrates educational support to promote gender equity and electronic payment support that reflects the user's emotional state.

[1433] 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.

[1434] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing the user's learning progress, means for conducting unconscious bias checks and providing the user with improvement suggestions, means for analyzing the content of the consultation and presenting solutions, means for collecting user feedback and improving the service, means for monitoring the user's emotional state in real time and having the data analyzed by a generation AI, and means for supporting electronic payments by adjusting the display interface and recommended products based on the emotional data. This enables gender equity education and electronic payment support based on the user's individual emotional state.

[1435] "Generative AI" is an artificial intelligence technology that uses machine learning algorithms to generate new data and information.

[1436] "Gender equity" is the state of providing fair and equal opportunities and treatment regardless of gender.

[1437] A "support service" is a system or program that provides support to meet a user's specific needs.

[1438] "User Registration" is the process by which a user provides personal information to create a new account on the system.

[1439] A "user account" is a unique identification for accessing the system and using various services.

[1440] "Educational content" refers to information and materials for learning that users use to acquire knowledge and skills.

[1441] "Study progress" is a status indicating how much the user has studied the educational content.

[1442] The "Unconscious Bias Check" is a test designed to assess the biases users may have without even realizing it.

[1443] "Improvement proposals" are specific proposals for changing the user's behavior or way of thinking based on the evaluation results.

[1444] "Consultation content" refers to the content or question that the user inquires about the system.

[1445] "Solution" refers to the specific response or advice that the system presents in response to the consultation content.

[1446] "Feedback" refers to opinions and impressions provided by users after using the service.

[1447] An "emotion engine" is a technology that recognizes a user's emotional state by analyzing their facial expressions, voice, etc.

[1448] "Real time" means that processing or response is carried out immediately at the present time.

[1449] "Monitoring" is the act of continuously observing and recording specific data or conditions.

[1450] "Electronic payments" are methods of paying for goods and services over the Internet.

[1451] An "interface" is a point of contact or operation screen through which a user and a system can interact.

[1452] "Recommended products" are products that are suggested based on the user's needs and preferences.

[1453] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[1454] When registering for the first time, a user uses a device to send personal information such as name, email address, and password to the server to create a user account. The server receives this information, creates the user account, and sends a completion notification to the device. Existing users can also log in to the service by entering their account information into their device, sending it to the server, and obtaining an authentication token.

[1455] When providing educational content, the server utilizes an emotion engine that grasps the user's emotional state in real time. When a user selects content from the catalog page, that information is sent to the server via the device, and the server sends the corresponding educational content back to the device. The device displays the educational content to the user, and as the user progresses with their learning, the emotion engine analyzes facial expressions and voice data and sends the user's emotional state. Based on this emotional data, the server adjusts the display content and difficulty level to optimize the learning experience.

[1456] To conduct an unconscious bias check, the user answers questions via their device. The device sends the answer data to a server, which then analyzes the data using generative AI. Meanwhile, the emotion engine also collects the user's emotional data in real time and sends this data to the server. The server then comprehensively evaluates the data, generates improvement suggestions for the user, and presents them to the user via their device.

[1457] Furthermore, in the electronic payment support function, the server uses generative AI to provide optimal display interfaces and recommended products based on the emotional state obtained from the emotion engine when the user uses the terminal to purchase a product. By monitoring emotional data, for example, if the user is feeling stressed, the server can improve the user experience by recommending relaxation items.

[1458] For example, if the user is in an "angry" emotional state while using the service, the server will recommend products such as "stress balls" and "cushions." In this case, the prompt to the generative AI model will be as follows:

[1459] "The user is currently angry. Please recommend a relaxation item."

[1460] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1461] Step 1:

[1462] A user registers or logs in. The device receives the user's input (name, email address, password) and sends it to the server. The server receives this data and creates a user account in the case of a new registration, or generates an authentication token in the case of an existing user and sends it back to the device. The device receives a completion notification or authentication token and displays it to the user.

[1463] Input: User personal or login information

[1464] Output: New account creation notification or authentication token

[1465] Step 2:

[1466] The user selects educational content. The device sends the user's selection data (content ID) to the server. The server retrieves the corresponding educational content from the database and sends it back to the device.

[1467] Input: Content selection data

[1468] Output: Corresponding educational content

[1469] Step 3:

[1470] The user browses educational content. The device displays the educational content, and as the user progresses with their learning, the emotion engine collects the user's emotional data (facial expressions, voice, etc.) and sends it to the server in real time. The server analyzes this emotional data and adjusts the display content and difficulty level. The device continues to display the adjusted content.

[1471] Input: Emotion data

[1472] Output: Tailored educational content

[1473] Step 4:

[1474] The user performs an unconscious bias check. The device sends the user's answers (answer data to questions) to the server. The server analyzes them, evaluates unconscious bias along with emotional data from the emotion engine, generates improvement suggestions, and sends them to the device. The device displays them to the user.

[1475] Input: Answer data and sentiment data

[1476] Output: Bias assessment and improvement suggestions

[1477] Step 5:

[1478] The user inputs the content of the consultation into the chat interface. The device sends the content (consultation content data) to the server. The server analyzes the content using generative AI and takes into account the emotional data from the emotion engine to generate the optimal solution, which is then sent to the device. The device then presents the solution to the user.

[1479] Input: Consultation content data and emotion data

[1480] Output: Optimal solution

[1481] Step 6:

[1482] A user attempts to purchase a product on the payment screen. The terminal initiates the payment process (purchase data), and the emotion engine monitors the user's emotional state (emotion data). The server uses generative AI to generate an appropriate display interface and recommended products based on the emotion data, and sends them to the terminal. The terminal displays the recommended products and adjusted interface.

[1483] Input: Purchase and sentiment data

[1484] Output: Recommended products and tailored interface

[1485] As a concrete example, if the emotion engine determines that the user's emotional state is "angry," it sends the following prompt to the generative AI model:

[1486] "The user is currently angry. Please recommend a relaxation item."

[1487] 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.

[1488] 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.

[1489] 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.

[1490] [Third embodiment]

[1491] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1492] 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.

[1493] 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).

[1494] 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.

[1495] 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.

[1496] 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).

[1497] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1498] 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.

[1499] 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.

[1500] 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.

[1501] 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.

[1502] 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."

[1503] To implement this invention, a system with the following configuration is required. The main elements are a server containing the generation AI, a terminal accessed by the user, and the user who uses the service.

[1504] User Registration and Login

[1505] User Registration:

[1506] When a user registers, he or she enters personal information such as name, email address, and password.

[1507] The terminal sends this information to the server, which then creates a user account based on the received information.

[1508] The terminal notifies the user that the account creation is complete.

[1509] Login:

[1510] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[1511] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[1512] The device receives the authentication token and redirects the user to the home screen.

[1513] Providing gender equity education content

[1514] View content:

[1515] A user accesses a catalog page to select the educational content they wish to study.

[1516] The terminal displays a list of educational content and sends the content ID selected by the user to the server.

[1517] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[1518] The terminal displays educational content to the user, and the user progresses with his / her studies.

[1519] Unconscious Bias Check

[1520] Checks performed:

[1521] Users visit the Unconscious Bias Check page and answer the necessary questions.

[1522] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[1523] The server generates analysis results and improvement suggestions and sends them to the terminal.

[1524] The terminal displays this to the user.

[1525] Communication Support

[1526] Input and analysis of consultation content:

[1527] The user inputs the content of the consultation into the chat interface.

[1528] The device sends the content to the server, which then analyzes it using a generating AI.

[1529] The server generates an appropriate solution and sends it to the terminal.

[1530] The terminal presents a solution to the user.

[1531] Feedback and Improvements

[1532] Feedback collection and analysis:

[1533] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1534] The terminal sends this to the server, which analyzes the feedback data.

[1535] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[1536] Specific examples

[1537] Providing educational content for children:

[1538] Users (children) learn about gender equity using a dedicated educational app.

[1539] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[1540] The server receives learning data and generates progress reports to provide to parents and educators.

[1541] Unconscious Bias Check:

[1542] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[1543] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[1544] The server analyzes the response data and provides an assessment of bias and suggestions for improvement.

[1545] This system provides comprehensive support for gender equity issues and facilitates the education, evaluation, and improvement processes.

[1546] The processing flow will be explained below.

[1547] User Registration and Login

[1548] New Registration

[1549] Step 1:

[1550] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[1551] Step 2:

[1552] The terminal transmits the input information to the server.

[1553] Step 3:

[1554] The server stores the received user information in a database and creates a new account.

[1555] Step 4:

[1556] The terminal displays a message to the user indicating that registration is complete.

[1557] Log in

[1558] Step 1:

[1559] The user enters their email address and password into the login form on their device.

[1560] Step 2:

[1561] The terminal transmits the input information to the server.

[1562] Step 3:

[1563] The server checks the account information against the database and performs authentication.

[1564] Step 4:

[1565] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[1566] Step 5:

[1567] The device receives the authentication token and redirects the user to the dashboard or home screen.

[1568] Providing gender equity education content

[1569] View content

[1570] Step 1:

[1571] The user accesses the educational content catalog page from the terminal.

[1572] Step 2:

[1573] The device displays a list of educational content.

[1574] Step 3:

[1575] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[1576] Step 4:

[1577] The server retrieves the corresponding educational content from the database based on the received content ID.

[1578] Step 5:

[1579] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[1580] Step 6:

[1581] The terminal displays the educational content to the user.

[1582] Unconscious Bias Check

[1583] Check implementation

[1584] Step 1:

[1585] A user accesses the Unconscious Bias Check page on their device.

[1586] Step 2:

[1587] The terminal provides an interface for displaying the check questions.

[1588] Step 3:

[1589] The user enters an answer to each question.

[1590] Step 4:

[1591] The terminal transmits the response data to the server.

[1592] Step 5:

[1593] The server analyzes the response data and assesses whether or not there is unconscious bias.

[1594] Step 6:

[1595] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[1596] Step 7:

[1597] The terminal displays the evaluation results and improvement suggestions to the user.

[1598] Communication Support

[1599] Input and analysis of consultation details

[1600] Step 1:

[1601] The user uses the chat interface to input the consultation content.

[1602] Step 2:

[1603] The terminal transmits the input consultation content to the server.

[1604] Step 3:

[1605] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[1606] Step 4:

[1607] The server sends the solution to the terminal.

[1608] Step 5:

[1609] The terminal displays the solution to the user.

[1610] Feedback and Improvements

[1611] Feedback collection and analysis

[1612] Step 1:

[1613] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1614] Step 2:

[1615] The terminal transmits the input feedback to the server.

[1616] Step 3:

[1617] The server analyzes the feedback data and extracts areas for improvement.

[1618] Step 4:

[1619] The server updates the system based on the extracted improvements.

[1620] This step will ensure that the Gender Equity Support System operates smoothly and provides appropriate support for each use case.

[1621] Example 1

[1622] 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."

[1623] Gender equity is an important issue in modern society, but solving it is not easy because many people have unconscious biases. Existing education systems and corporate training programs often do not provide effective approaches to individual needs and issues. Furthermore, there are limitations to achieving gender equity because there is a lack of mechanisms in place to collect user feedback and continuously improve services. There is a need to provide a system that can solve these issues and effectively support gender equity.

[1624] 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.

[1625] In this invention, the server includes means for accepting user registration and creating a user account, means for users to log in and generate an authentication token, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation details and presenting solutions, and means for collecting user feedback and improving the service. This enables learning, assessment, and improvement suggestions that meet the needs of diverse users, contributing to the improvement of gender equity.

[1626] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate, analyze, and evaluate data.

[1627] "Gender equity" refers to a situation in which discrimination and inequity based on gender are eliminated and equal opportunities and treatment are provided to all.

[1628] "User registration" refers to the process by which a system user creates a new account on the system by providing personal information such as name, email address, and password.

[1629] "User account" refers to a data set used to individually identify a user in the system, including the user's personal information and usage history.

[1630] An "authentication token" refers to an electronic certificate that indicates a user has been properly authenticated and is used to grant access to a system.

[1631] "Educational content" refers to educational materials and information provided for users to learn from, and may include formats such as text, video, and quizzes.

[1632] "Study progress" refers to an indicator that indicates how much a user has progressed in their studies through educational content.

[1633] An "unconscious bias check" is a test that allows users to assess their own unconscious biases, often in the form of a questionnaire or survey.

[1634] "Improvement Suggestions" are specific advice to provide effective solutions to users' unconscious biases and other challenges.

[1635] "Consultation content" refers to questions and issues raised by users through the system, which are analyzed by the generation AI.

[1636] "Solutions" refer to specific solutions or advice for the problems or questions users are facing.

[1637] "User Feedback" refers to opinions and suggestions for improvement collected from users after using the Service.

[1638] "Means for improving the service" refers to the process for modifying and improving the system and the content provided based on user feedback.

[1639] To implement this invention, the following main components are required: a server containing the generative AI, a terminal accessed by the user, and the user who uses the service. These components work together to provide a gender equity support service.

[1640] System Configuration

[1641] This system consists of a server, a terminal, and a user. The server contains a generative AI model and analyzes data provided by the user to provide educational content and analyze the results of bias checks. The terminal provides the user interface and acts as a medium for the user to communicate with the server.

[1642] User Registration and Login

[1643] When a user registers, they enter personal information such as their name, email address, and password. The device sends this information to the server, and the server creates a user account based on the received information. The user also logs in with an already created account, and the server verifies the user's identity by comparing it with information in the database, then generates and returns an authentication token. The device receives the authentication token and redirects the user to the home screen.

[1644] Providing gender equity education content

[1645] When a user accesses the catalog page to select the educational content they wish to study, the device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device, which then displays it to the user.

[1646] As a concrete example, when providing educational content for children, users (children) use a dedicated educational app to learn about gender equity. The device displays educational materials in the form of videos and quizzes and monitors the learning progress. The server receives the learning data, generates a progress report, and provides it to the educator.

[1647] Unconscious Bias Check

[1648] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which then analyzes the received data using a generative AI model to evaluate whether it contains unconscious bias. The server generates analysis results and improvement suggestions, which are then sent to the device, which displays them to the user.

[1649] An example prompt is:

[1650] "Please evaluate how your unconscious biases are manifested in your responses to the bias check questions and provide specific suggestions for improvement."

[1651] Communication Support

[1652] The user inputs the content of their inquiry into the chat interface. The device sends the content to the server, which analyzes it using a generative AI. The server generates an appropriate solution and sends it to the device. The device then presents the solution to the user.

[1653] An example prompt is:

[1654] "Analyze the consultation about communication problems in the workplace and propose solutions."

[1655] Feedback and Improvements

[1656] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data using a generative AI model. The server then uses the analysis results to identify areas for improvement in the system and makes appropriate updates.

[1657] This system will enable learning, evaluation, and improvement suggestions that meet the needs of diverse users, contributing to improving gender equality.

[1658] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1659] Step 1:

[1660] The user enters their name, email address, and password into the new registration form.

[1661] Input: Name, Email Address, Password

[1662] Output: User registration information

[1663] Specifically, the user enters "Yamada Taro," "taro.yamada@example.com," and "password123" into the form.

[1664] Step 2:

[1665] The terminal sends the entered information to the server using an HTTP POST request.

[1666] Input: User registration information

[1667] Output: HTTP POST request to the server

[1668] The device sends this information to the server in JSON format.

[1669] Step 3:

[1670] The server verifies the received information and registers the new user account in its database.

[1671] Input: User registration information data

[1672] Output: Insertion result into database

[1673] The server uses an SQL query to insert the user information into a database.

[1674] Step 4:

[1675] The terminal notifies the user that the account creation is complete.

[1676] Input: Account creation completion notification

[1677] Output: A message to inform the user

[1678] The device will display the message "Account created successfully."

[1679] Step 5:

[1680] The user enters their email address and password into the login form.

[1681] Input: Email address, password

[1682] Output: Login information

[1683] For example, the user enters "taro.yamada@example.com" and "password123".

[1684] Step 6:

[1685] The device sends the entered login information to the server via an HTTP POST request.

[1686] Input: Login information

[1687] Output: HTTP POST request to the server

[1688] The device sends the information to the server in JSON format.

[1689] Step 7:

[1690] The server checks the database and generates an authentication token if authentication is successful.

[1691] Input: Login information data

[1692] Output: Authentication token

[1693] The server compares the received information with the user information in its database and generates a JWT (JSON Web Token) if there is a match.

[1694] Step 8:

[1695] The device receives the authentication token and redirects the user to the home screen.

[1696] Input: Authentication Token

[1697] Output: Redirect to home screen

[1698] The device stores the authentication token in local storage and redirects to the home screen.

[1699] Step 9:

[1700] The user accesses the educational content catalog page.

[1701] Input: Access to catalog page

[1702] Output: Catalog page display

[1703] A user opens the catalog page URL in a browser.

[1704] Step 10:

[1705] The terminal obtains a list of educational content from the server and displays it.

[1706] Input: Content data from the server

[1707] Output: List of educational content

[1708] The terminal displays the content information obtained from the server in a list format in HTML.

[1709] Step 11:

[1710] The user selects the content they wish to study and sends the content ID to the server.

[1711] Input: Selected Content ID

[1712] Output: Content ID sent to server

[1713] For example, a user selects a content item called "Gender History" and sends its ID to the server.

[1714] Step 12:

[1715] The server retrieves the relevant educational content from the database and sends it to the terminal.

[1716] Input: Content ID

[1717] Output: Acquired educational content data

[1718] The server retrieves the content data using an SQL query and then sends it to the terminal as an API response.

[1719] Step 13:

[1720] The terminal displays the acquired educational content to the user.

[1721] Input: Educational content data

[1722] Output: Displayed educational content

[1723] The device displays the content using a video player and quiz-style interface.

[1724] Step 14:

[1725] Users visit the Unconscious Bias Check page and answer questions.

[1726] Input: Bias Check Questions and Answers

[1727] Output: Response data

[1728] The user accesses the bias check questionnaire form and enters answers to the questions.

[1729] Step 15:

[1730] The terminal transmits the user's answer to the server.

[1731] Input: Answer data

[1732] Output: Send response data to the server

[1733] The device sends the response data to the server in JSON format.

[1734] Step 16:

[1735] The server analyzes the received data using a generative AI model to assess whether it contains unconscious bias.

[1736] Input: Answer data

[1737] Output: Analysis results and evaluation

[1738] The server uses a generative AI model to analyze the received response data.

[1739] Step 17:

[1740] The server generates analysis results and improvement suggestions and sends them to the terminal.

[1741] Input: Analysis results and evaluation

[1742] Output: Improvement proposal data

[1743] The server sends the analysis results and corresponding improvement suggestions to the terminal in JSON format.

[1744] Step 18:

[1745] The device displays the analysis results and improvement suggestions to the user.

[1746] Input: Improvement proposal data

[1747] Output: Display of analysis results and improvement suggestions

[1748] The terminal displays the analysis results and improvement suggestions in a user interface.

[1749] Step 19:

[1750] The user inputs the content of the consultation into the chat interface.

[1751] Input: Consultation details

[1752] Output: Input consultation content data

[1753] A user types in chat about "communication challenges at work."

[1754] Step 20:

[1755] The terminal transmits the consultation content data to the server.

[1756] Input: Consultation content data

[1757] Output: Send consultation details to the server

[1758] The device sends the chat content to the server in JSON format.

[1759] Step 21:

[1760] The server uses the generation AI to analyze the consultation content data.

[1761] Input: Consultation content data

[1762] Output: Analyzed result data

[1763] The server uses the generative AI model to analyze the received consultation data.

[1764] Step 22:

[1765] The server generates an appropriate solution and sends it to the terminal.

[1766] Input: Analysis result data

[1767] Output: Solution data

[1768] The server generates a solution and sends it to the device as an API response.

[1769] Step 23:

[1770] The terminal presents the generated solutions to the user.

[1771] Input: Solution data

[1772] Output: Displayed solution

[1773] The terminal displays the generated solution in a chat interface.

[1774] Step 24:

[1775] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1776] Input: Feedback data

[1777] Output: Input feedback data

[1778] Users enter their opinions and suggestions for improvement in the feedback form.

[1779] Step 25:

[1780] The terminal transmits the feedback data to the server.

[1781] Input: Feedback data

[1782] Output: Send feedback to the server

[1783] The device sends the feedback content to the server in JSON format.

[1784] Step 26:

[1785] The server analyzes the feedback data using a generative AI model.

[1786] Input: Feedback data

[1787] Output: Parsed feedback results

[1788] The server uses a generative AI model to analyze the feedback data and generate results.

[1789] Step 27:

[1790] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[1791] Input: Analysis result data

[1792] Output: System improvements and updates

[1793] Based on the analysis results, the server designs improvements to the system and implements necessary updates.

[1794] The above are the specific processing steps of the program of this system.

[1795] (Application example 1)

[1796] 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."

[1797] As gender equity becomes increasingly important in modern society, there is a need for efficient support methods to promote individual awareness and behavioral improvement. Furthermore, systems that provide a wide range of services, such as educational content, unconscious bias checks, and consultation content analysis, require user-friendly and effective interactions. In particular, when providing this support in a virtual environment, there is a need for methods that facilitate the process of users becoming aware of their own unconscious biases and seeking solutions. Our goal is to provide a comprehensive system to solve these issues.

[1798] 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.

[1799] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation content and presenting solutions, means for collecting user feedback and improving services, means for providing educational content in a virtual environment and supporting an interactive learning experience, means for employees in the virtual environment to conduct bias checks and promote self-improvement, and means for providing customer support in the virtual environment and providing solutions to consultation content using a generative AI model. This enables users to learn about gender equity and improve themselves within the virtual environment, and allows them to receive efficient and effective support.

[1800] "Generative AI" is a system that uses artificial intelligence to generate, analyze, and predict data.

[1801] "Gender equity" is a concept that refers to a state in which men and women receive equal opportunities and treatment socially, economically, and culturally.

[1802] "Support services" refers to a series of services provided to solve problems and issues faced by users.

[1803] "User registration" is the process by which a new user enters the necessary personal information into the system and obtains eligibility to use the system.

[1804] "User Account" refers to the individual authentication information and data assigned to each User for use of the System.

[1805] "Educational content" refers to information and instructional materials designed to help learners acquire specific knowledge or skills.

[1806] "User's learning progress" refers to the user's level of achievement and understanding in the process of learning educational content.

[1807] "Unconscious bias check" refers to a method or checklist for assessing and detecting the prejudices and stereotypes that individuals unconsciously hold.

[1808] "Means for providing users with improvement suggestions" refers to features within the system that provide specific suggestions or advice to help users reduce their unconscious biases or improve their behavior.

[1809] "Consultation content" refers to information that indicates questions, problems, or concerns that a user inputs to the system.

[1810] "Solution" refers to the method or means provided to the user in response to their inquiry based on the results of analysis conducted by the system using generated AI.

[1811] "User feedback" refers to opinions from users, such as impressions after using the service, areas for improvement, and suggestions.

[1812] "Virtual environment" refers to a virtual space or simulated environment, including digital experiential spaces provided over the Internet.

[1813] An "interactive learning experience" refers to a learning method or experience in which the user actively participates and progresses interactively.

[1814] An "employee" refers to an individual employed by a company or organization to perform specific tasks or roles.

[1815] "Customer support" refers to the business activities that provide assistance and support to customers who use products or services.

[1816] A "generative AI model" refers to an artificial intelligence algorithm or framework built to learn from large amounts of data and generate new data or perform specific tasks.

[1817] This invention describes a system that uses generative AI to provide gender equity support services within a virtual environment, including user registration, educational content provision, unconscious bias checks, customer support consultation and resolution, and feedback collection.

[1818] 1. User Registration and Login

[1819] Users access the system using a terminal and register by entering personal information such as name, email address, and password. This information is sent to the server, which then creates a user account based on the received information. When logging in, the user enters their email address and password, which the terminal then sends to the server, which then compares them with the information in the database to verify that the user is a legitimate user.

[1820] 2. Providing educational content

[1821] The system interactively provides educational content related to gender equity that the user wishes to learn about within a virtual environment. The device displays a list of educational content and sends the content ID of the user's selection to the server. The server retrieves the corresponding educational content from a database and sends it to the device, which then displays it to the user.

[1822] 3. Unconscious bias check

[1823] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The server generates analysis results and improvement suggestions and sends them to the device.

[1824] 4. Customer support and analysis of inquiries

[1825] The user enters the content of their inquiry into the chat interface, and the device sends the content to the server. The server analyzes it using generative AI, generates an appropriate solution, and sends it to the device. The device then presents the solution to the user.

[1826] 5. Collecting feedback and improving our services

[1827] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data and identifies areas for improvement in the service.

[1828] The system is implemented using Python and the Flask framework, with the SQLite database and the SHA-256 hash function for password security.

[1829] For example, consider the following prompt:

[1830] Sample unconscious bias check questions:

[1831] "To assess your own unconscious biases, answer these questions:

[1832] 1. Do you ever feel that one gender is superior, even when there are objective standards of evaluation?

[1833] 2. Do you unconsciously stereotype certain genders in your daily life or at work?

[1834] Example start prompts for gender equity education content:

[1835] Get started with educational content on gender equity. Study the following materials:

[1836] 1. What is gender equity?

[1837] 2. How to promote gender equity in the workplace

[1838] In this way, users can learn about gender equity and improve themselves within a virtual environment, receiving efficient and effective support.

[1839] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1840] Step 1:

[1841] A user accesses the system using a terminal and registers by entering personal information such as name, email address, and password. The terminal sends the entered information to the server, which then creates a user account based on the received information. The input data includes name, email address, and password (SHA-256 hashed), and the output data is the created user account.

[1842] Step 2:

[1843] When logging in, the user enters their email address and password. The device sends this to the server, which checks it against information in a database to verify the user is a valid user. The input data is the email address and hashed password, and the output data is an authentication token. The device receives the authentication token and redirects the user to the home screen.

[1844] Step 3:

[1845] The user browses gender equity educational content provided in a virtual environment. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The input data is the content ID, and the output data is the educational content. The device displays the educational content to the user, allowing the user to progress with their learning.

[1846] Step 4:

[1847] The user accesses the unconscious bias check page and answers the required questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The input data is the user's answers, and the output data is the analysis results and improvement suggestions. The server generates the analysis results and improvement suggestions and sends them to the device, which displays them to the user.

[1848] Step 5:

[1849] The user inputs the details of their customer support inquiry into the chat interface. The device sends the details to the server, which analyzes them using a generative AI model. The input data is the inquiry details, and the output data is an appropriate solution. The server generates a solution and sends it to the device. The device presents the solution to the user.

[1850] Step 6:

[1851] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data and identifies areas for improvement in the system. The input data is the feedback content, and the output data is the analysis results and improvement suggestions. The server then performs appropriate system updates based on this.

[1852] 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.

[1853] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[1854] User Registration and Login

[1855] User Registration:

[1856] When a user registers, he or she enters personal information such as name, email address, and password.

[1857] The terminal sends this information to the server, which then creates a user account based on the received information.

[1858] The terminal notifies the user that the account creation is complete.

[1859] Login:

[1860] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[1861] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[1862] The device receives the authentication token and redirects the user to the home screen.

[1863] Providing gender equity education content

[1864] View content:

[1865] A user accesses a catalog page to select the educational content they wish to study.

[1866] The terminal displays a list of educational content and transmits the content ID selected by the user to the server.

[1867] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[1868] The terminal displays educational content to the user, and the user progresses with his / her studies.

[1869] The emotion engine recognizes the user's emotions in real time and transmits the data to the server.

[1870] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[1871] Unconscious Bias Check

[1872] Checks performed:

[1873] Users visit the Unconscious Bias Check page and answer the necessary questions.

[1874] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[1875] The server also analyzes the emotion data received from the emotion engine to generate more accurate evaluation results.

[1876] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[1877] The terminal displays this to the user.

[1878] Communication Support

[1879] Input and analysis of consultation content:

[1880] The user inputs the content of the consultation into the chat interface.

[1881] The device sends the content to the server, which then analyzes it using a generating AI.

[1882] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[1883] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[1884] The terminal presents a solution to the user.

[1885] Feedback and Improvements

[1886] Feedback collection and analysis:

[1887] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1888] The terminal sends this to the server, which analyzes the feedback data.

[1889] The emotion engine collects the user's emotional state during feedback input and also sends it to the server.

[1890] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[1891] The server updates the system based on the extracted improvements.

[1892] Specific examples

[1893] Providing educational content for children:

[1894] Users (children) learn about gender equity using a dedicated educational app.

[1895] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[1896] The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server.

[1897] The server uses emotional data to assess stress and interest levels during learning and adjusts the content accordingly.

[1898] The device displays tailored content to optimize the user's learning experience.

[1899] Unconscious Bias Check:

[1900] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[1901] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[1902] The emotion engine recognizes the user's emotion in the response and transmits it to the server.

[1903] The server analyzes the response data and sentiment data, and provides an assessment of bias and suggestions for improvement.

[1904] This system provides comprehensive support for gender equity issues, facilitating the education, assessment, and improvement processes. In addition, by combining it with an emotion engine, it provides optimal support according to the user's individual emotional state.

[1905] The processing flow will be explained below.

[1906] User Registration and Login

[1907] New Registration

[1908] Step 1:

[1909] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[1910] Step 2:

[1911] The terminal transmits the input information to the server.

[1912] Step 3:

[1913] The server stores the received user information in a database and creates a new account.

[1914] Step 4:

[1915] The terminal displays a message to the user indicating that registration is complete.

[1916] Log in

[1917] Step 1:

[1918] The user enters their email address and password into the login form on their device.

[1919] Step 2:

[1920] The terminal transmits the input information to the server.

[1921] Step 3:

[1922] The server checks the account information against the database and performs authentication.

[1923] Step 4:

[1924] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[1925] Step 5:

[1926] The device receives the authentication token and redirects the user to the dashboard or home screen.

[1927] Providing gender equity education content

[1928] View content

[1929] Step 1:

[1930] The user accesses the educational content catalog page from the terminal.

[1931] Step 2:

[1932] The device displays a list of educational content.

[1933] Step 3:

[1934] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[1935] Step 4:

[1936] The server retrieves the corresponding educational content from the database based on the received content ID.

[1937] Step 5:

[1938] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[1939] Step 6:

[1940] The terminal displays the educational content to the user.

[1941] Utilizing Emotional Data

[1942] Step 1:

[1943] The emotion engine recognizes emotions in real time from the user's facial expressions and tone of voice.

[1944] Step 2:

[1945] The emotion engine sends the emotion data to the server.

[1946] Step 3:

[1947] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[1948] Step 4:

[1949] The server transmits the adjusted content data to the terminal.

[1950] Step 5:

[1951] The terminal displays the tailored educational content to the user.

[1952] Unconscious Bias Check

[1953] Check implementation

[1954] Step 1:

[1955] A user accesses the Unconscious Bias Check page on their device.

[1956] Step 2:

[1957] The terminal provides an interface for displaying the check questions.

[1958] Step 3:

[1959] The user enters an answer to each question.

[1960] Step 4:

[1961] The terminal transmits the response data to the server.

[1962] Step 5:

[1963] The server analyzes the response data and assesses whether or not there is unconscious bias.

[1964] Step 6:

[1965] The emotion engine recognizes the user's emotion in the response and sends the data to the server.

[1966] Step 7:

[1967] The server integrates and analyzes the response data and emotion data to generate bias evaluation results.

[1968] Step 8:

[1969] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[1970] Step 9:

[1971] The terminal displays the evaluation results and improvement suggestions to the user.

[1972] Communication Support

[1973] Input and analysis of consultation details

[1974] Step 1:

[1975] The user inputs the content of the consultation into the chat interface.

[1976] Step 2:

[1977] The terminal transmits the contents to the server.

[1978] Step 3:

[1979] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[1980] Step 4:

[1981] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[1982] Step 5:

[1983] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[1984] Step 6:

[1985] The terminal presents a solution to the user.

[1986] Feedback and Improvements

[1987] Feedback collection and analysis

[1988] Step 1:

[1989] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[1990] Step 2:

[1991] The terminal transmits the input feedback to the server.

[1992] Step 3:

[1993] The emotion engine recognizes the user's emotions during feedback input and sends the data to the server.

[1994] Step 4:

[1995] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement.

[1996] Step 5:

[1997] The server updates the system based on the extracted improvements.

[1998] Step 6:

[1999] The server notifies the terminal of the update contents and displays them to the user.

[2000] Through this process, the gender equity support system can provide users with appropriate support and an optimal learning experience according to their emotional state.

[2001] Example 2

[2002] 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."

[2003] Promoting gender equality is becoming increasingly important in modern society. However, traditional education and support services provide uniform content without considering the user's emotional state, making it difficult to provide optimal support for each individual user. Furthermore, because emotional data is not taken into account when assessing unconscious bias or making suggestions for improvement, there are limitations to the accuracy and effectiveness of these services. Furthermore, educational content delivery lacks interactivity, making it ineffective, especially for children.

[2004] 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.

[2005] In this invention, the server includes a means for accepting user registration and creating a user account, a means for providing educational content and collecting and analyzing the user's learning progress, a means for conducting unconscious bias checks and providing improvement suggestions to the user, a means for collecting emotional data in real time and adjusting the content content and difficulty level based on the collected data, and a means for using the emotional data to evaluate unconscious bias and generate improvement suggestions. This makes it possible to provide gender equity support that is optimal for each individual user based on their emotional state, which is expected to be highly accurate and effective in terms of educational effectiveness and the reduction of unconscious bias. It also improves the interactivity of educational content for children, significantly improving the quality of the learning experience.

[2006] "User registration" refers to the process by which a new user of the system enters personal information and creates a user account based on that information.

[2007] "User Account" is a digital identifier generated by the system to manage a user's personal information and authentication information.

[2008] "Educational content" refers to learning materials and educational materials related to gender equity, including videos, quizzes, articles, etc.

[2009] "Study progress" is information indicating how much learning the user has completed through educational content.

[2010] An "unconscious bias check" is a process that involves asking questions or taking tests to assess whether a user has any unconscious biases.

[2011] "Improvement suggestions" are specific advice and guidelines for improving the user's perceived biases, generated based on the results of the unconscious bias check.

[2012] "Consultation" refers to the text information or question a user enters to seek assistance with gender equity.

[2013] "Emotional data" is information about the user's emotional state, collected from the user's facial expressions, tone of voice, and the like.

[2014] "Real-time" means that information is obtained and processed immediately, and refers to a response without delay.

[2015] An "unconscious bias assessment" is the process of analyzing the results of a user's unconscious bias check to determine whether unconscious bias is present.

[2016] An "interactive learning experience" is a learning method in which users actively interact with educational content and exchange information in a two-way manner, promoting deep understanding.

[2017] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. This system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[2018] Hardware and Software Configuration

[2019] Terminal: A device operated by the user, and can be a variety of devices such as a PC, smartphone, tablet, etc. The terminal accesses the system via a web browser or dedicated application.

[2020] Server: A central system that manages and processes generative AI and various data. The server includes a database management system (DBMS) and emotion engine, and is expected to be a cloud server or on-premise server.

[2021] Generative AI: An artificial intelligence model used to analyze user inquiries and feedback and generate appropriate responses and suggestions.

[2022] Emotion engine: A software engine that analyzes the user's facial expressions and voice tone in real time to collect emotional data.

[2023] System processing overview

[2024] The system performs the following main processes:

[2025] User Registration and Login

[2026] A user registers by entering personal information such as name, email address, and password. The device sends this information to the server, which then creates a user account. Once the account creation is complete, the device notifies the user. When logging in, the user enters their email address and password, which the device sends to the server. The server compares the information with that in the database, generates an authentication token, and sends it back. The device then redirects the user to the home screen.

[2027] Providing educational content

[2028] The user accesses the catalog page to select the educational content they wish to study. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The device displays the educational content to the user, who then proceeds with their study. The emotion engine recognizes the user's emotions in real time and sends that data to the server. The server analyzes the emotion data and adjusts the content and difficulty of the content to be displayed.

[2029] Unconscious Bias Check

[2030] The user accesses the unconscious bias check page and answers the necessary questions. The device sends the user's answers to the server. The server analyzes the received data and evaluates whether it contains unconscious bias. The server also analyzes the emotional data received from the emotion engine to generate a more accurate evaluation result. The server generates the evaluation result and improvement suggestions and sends them to the device. The device displays them to the user.

[2031] Communication Support

[2032] The user inputs the content of their consultation into the chat interface. The device sends the content to the server, which analyzes it using generative AI. The emotion engine monitors the user's emotional state in real time during the consultation and sends the data to the server. The server takes the emotional data into consideration to generate an optimal solution and sends it to the device. The device then presents the solution to the user.

[2033] Feedback and Improvements

[2034] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data. The emotion engine collects the user's emotional state while they are entering feedback and sends this to the server. The server then integrates and analyzes the feedback data and emotion data to identify areas for improvement in the service. The server then updates the system based on the identified areas for improvement.

[2035] Specific examples

[2036] Providing educational content for children: Users (children) learn about gender equity using a dedicated educational app. The device displays learning materials in the form of videos and quizzes and monitors learning progress. The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server. The server uses the emotion data to assess stress and interest levels during learning and adjusts the content accordingly. The device displays the adjusted content, optimizing the user's learning experience.

[2037] Unconscious Bias Check: After a job interview, a user (e.g., a human resources officer) performs a bias check for self-evaluation. The terminal displays a questionnaire in the form of questions, and the user enters their answers. The emotion engine recognizes the user's emotions while answering and sends them to the server. The server analyzes the response data and emotion data, and presents an assessment of bias and suggestions for improvement.

[2038] Example prompt sentence:

[2039] "In a job interview, you will assess your unconscious biases against candidates of a certain gender or background and provide feedback based on that. Please answer the following questions."

[2040] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2041] User Registration and Login

[2042] User Registration

[2043] Step 1:

[2044] The user enters their name, email address, password, etc. into the registration form. The device performs a simple check to verify the validity of the entered information (input format and required fields) and confirms that it is appropriate.

[2045] Input: Name, Email Address, Password

[2046] Output: Validity check result

[2047] Step 2:

[2048] The terminal transmits the authenticated information to the server.

[2049] Input: Name, Email Address, Password

[2050] Output: Send information to the server

[2051] Step 3:

[2052] The server creates a new user account in the database based on the received information. Once the account creation is complete, the server notifies the terminal that the account was created successfully.

[2053] Input: User information (name, email address, password)

[2054] Output: Account creation success notification

[2055] Step 4:

[2056] The terminal notifies the user that the account creation is complete.

[2057] Input: Account creation success notification

[2058] Output: User notification

[2059] Log in

[2060] Step 1:

[2061] The user enters their email address and password into the login form. The device performs a simple check to verify the validity of the information entered and verifies that it is correct.

[2062] Input: Email address, password

[2063] Output: Validity check result

[2064] Step 2:

[2065] The terminal transmits the authenticated information to the server.

[2066] Input: Email address, password

[2067] Output: Send authentication information to the server

[2068] Step 3:

[2069] The server compares the received authentication information with the registered information in the database, and if it is correct, it generates an authentication token and sends it to the terminal.

[2070] Input: Authentication information (email address, password)

[2071] Output: Authentication token

[2072] Step 4:

[2073] The device receives the authentication token and redirects the user to the home screen.

[2074] Input: Authentication Token

[2075] Output: Redirect to home screen

[2076] Providing gender equity education content

[2077] Step 1:

[2078] The user selects the educational content they want to study from the catalog page. The device sends the selected content ID to the server.

[2079] Input: Selected Content ID

[2080] Output: Send content ID to server

[2081] Step 2:

[2082] The server retrieves the relevant educational content from the database.

[2083] Input: Content ID

[2084] Output: Educational content data

[2085] Step 3:

[2086] The terminal displays the acquired educational content to the user.

[2087] Input: Educational content data

[2088] Output: Displaying content to the user

[2089] Step 4:

[2090] The user browses the content and progresses with their learning. The emotion engine analyzes the user's facial expressions and tone of voice in real time and sends the emotional data to the server.

[2091] Input: User facial expressions and tone of voice

[2092] Output: Emotion data

[2093] Step 5:

[2094] The server analyzes the emotional data and adjusts the content and difficulty level based on the user's emotional state, and then transmits the adjusted content data to the terminal.

[2095] Input: Emotion data

[2096] Output: Adjusted content data

[2097] Step 6:

[2098] The device then displays the tailored educational content back to the user, optimizing the learning experience.

[2099] Input: Adjusted content data

[2100] Output: Redisplay to user

[2101] Unconscious Bias Check

[2102] Step 1:

[2103] Users access the unconscious bias check page and answer the necessary questions. The device then sends the answers to the server.

[2104] Input: User's answer

[2105] Output: Send response to server

[2106] Step 2:

[2107] The server analyzes the received response data and evaluates whether it contains unconscious bias.

[2108] Input: Answer data

[2109] Output: Bias evaluation result

[2110] Step 3:

[2111] The emotion engine monitors the user's emotional state during the response and transmits the emotion data to the server.

[2112] Input: User's emotional state

[2113] Output: Emotion data

[2114] Step 4:

[2115] The server integrates and analyzes the response data and emotional data to generate more accurate evaluation results and improvement suggestions.

[2116] Input: Answer data, emotion data

[2117] Output: Evaluation results, improvement proposals

[2118] Step 5:

[2119] The server sends the generated evaluation results and improvement suggestions to the terminal, which displays them to the user.

[2120] Input: Evaluation results, improvement proposals

[2121] Output: What is displayed to the user

[2122] Communication Support

[2123] Step 1:

[2124] The user inputs the content of the consultation into the chat interface, and the terminal sends the content to the server.

[2125] Input: Consultation details

[2126] Output: Send consultation details to the server

[2127] Step 2:

[2128] The server uses generative AI to analyze the consultation content.

[2129] Input: Consultation details

[2130] Output: Analysis results

[2131] Step 3:

[2132] The emotion engine monitors the user's emotional state during the consultation and transmits the data to the server.

[2133] Input: User's emotional state

[2134] Output: Emotion data

[2135] Step 4:

[2136] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[2137] Input: consultation details, emotional data

[2138] Output: Solution

[2139] Step 5:

[2140] The terminal presents a solution to the user.

[2141] Input: Solution

[2142] Output: Presented to the user

[2143] Feedback and Improvements

[2144] Step 1:

[2145] After using the service, users enter their opinions and suggestions for improvement into a feedback form, which is then sent from the device to the server.

[2146] Input: Feedback

[2147] Output: Send feedback to the server

[2148] Step 2:

[2149] The server analyzes the feedback data. The emotion engine also collects the user's emotional state during the feedback input and sends it to the server.

[2150] Input: Feedback data, emotion data

[2151] Output: Analysis results

[2152] Step 3:

[2153] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[2154] Input: Feedback data, emotion data

[2155] Output: Improvements

[2156] Step 4:

[2157] The server updates the system based on the extracted improvements, thereby improving the user experience.

[2158] Input: Improvements

[2159] Output: System Update

[2160] Step 5:

[2161] The terminal applies the updated system contents to the user and the contents are reflected the next time the terminal is used.

[2162] Enter: System Update

[2163] Output: Apply to user

[2164] (Application example 2)

[2165] 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."

[2166] While interest in gender equity has grown in recent years, existing educational systems and support services have not adequately addressed this issue. Furthermore, gender bias exists in electronic payment systems, creating a need for fair support for diverse users. Interfaces and product recommendations tailored to the user's emotional state are particularly needed, but few systems offer such functionality. Therefore, a system is needed that integrates educational support to promote gender equity and electronic payment support that reflects the user's emotional state.

[2167] 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.

[2168] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing the user's learning progress, means for conducting unconscious bias checks and providing the user with improvement suggestions, means for analyzing the content of the consultation and presenting solutions, means for collecting user feedback and improving the service, means for monitoring the user's emotional state in real time and having the data analyzed by a generation AI, and means for supporting electronic payments by adjusting the display interface and recommended products based on the emotional data. This enables gender equity education and electronic payment support based on the user's individual emotional state.

[2169] "Generative AI" is an artificial intelligence technology that uses machine learning algorithms to generate new data and information.

[2170] "Gender equity" is the state of providing fair and equal opportunities and treatment regardless of gender.

[2171] A "support service" is a system or program that provides support to meet a user's specific needs.

[2172] "User Registration" is the process by which a user provides personal information to create a new account on the system.

[2173] A "user account" is a unique identification for accessing the system and using various services.

[2174] "Educational content" refers to information and materials for learning that users use to acquire knowledge and skills.

[2175] "Study progress" is a status indicating how much the user has studied the educational content.

[2176] The "Unconscious Bias Check" is a test designed to assess the biases users may have without even realizing it.

[2177] "Improvement proposals" are specific proposals for changing the user's behavior or way of thinking based on the evaluation results.

[2178] "Consultation content" refers to the content or question that the user inquires about the system.

[2179] "Solution" refers to the specific response or advice that the system presents in response to the consultation content.

[2180] "Feedback" refers to opinions and impressions provided by users after using the service.

[2181] An "emotion engine" is a technology that recognizes a user's emotional state by analyzing their facial expressions, voice, etc.

[2182] "Real time" means that processing or response is carried out immediately at the present time.

[2183] "Monitoring" is the act of continuously observing and recording specific data or conditions.

[2184] "Electronic payments" are methods of paying for goods and services over the Internet.

[2185] An "interface" is a point of contact or operation screen through which a user and a system can interact.

[2186] "Recommended products" are products that are suggested based on the user's needs and preferences.

[2187] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[2188] When registering for the first time, a user uses a device to send personal information such as name, email address, and password to the server to create a user account. The server receives this information, creates the user account, and sends a completion notification to the device. Existing users can also log in to the service by entering their account information into their device, sending it to the server, and obtaining an authentication token.

[2189] When providing educational content, the server utilizes an emotion engine that grasps the user's emotional state in real time. When a user selects content from the catalog page, that information is sent to the server via the device, and the server sends the corresponding educational content back to the device. The device displays the educational content to the user, and as the user progresses with their learning, the emotion engine analyzes facial expressions and voice data and sends the user's emotional state. Based on this emotional data, the server adjusts the display content and difficulty level to optimize the learning experience.

[2190] To conduct an unconscious bias check, the user answers questions via their device. The device sends the answer data to a server, which then analyzes the data using generative AI. Meanwhile, the emotion engine also collects the user's emotional data in real time and sends this data to the server. The server then comprehensively evaluates the data, generates improvement suggestions for the user, and presents them to the user via their device.

[2191] Furthermore, in the electronic payment support function, the server uses generative AI to provide optimal display interfaces and recommended products based on the emotional state obtained from the emotion engine when the user uses the terminal to purchase a product. By monitoring emotional data, for example, if the user is feeling stressed, the server can improve the user experience by recommending relaxation items.

[2192] For example, if the user is in an "angry" emotional state while using the service, the server will recommend products such as "stress balls" and "cushions." In this case, the prompt to the generative AI model will be as follows:

[2193] "The user is currently angry. Please recommend a relaxation item."

[2194] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2195] Step 1:

[2196] A user registers or logs in. The device receives the user's input (name, email address, password) and sends it to the server. The server receives this data and creates a user account in the case of a new registration, or generates an authentication token in the case of an existing user and sends it back to the device. The device receives a completion notification or authentication token and displays it to the user.

[2197] Input: User personal or login information

[2198] Output: New account creation notification or authentication token

[2199] Step 2:

[2200] The user selects educational content. The device sends the user's selection data (content ID) to the server. The server retrieves the corresponding educational content from the database and sends it back to the device.

[2201] Input: Content selection data

[2202] Output: Corresponding educational content

[2203] Step 3:

[2204] The user browses educational content. The device displays the educational content, and as the user progresses with their learning, the emotion engine collects the user's emotional data (facial expressions, voice, etc.) and sends it to the server in real time. The server analyzes this emotional data and adjusts the display content and difficulty level. The device continues to display the adjusted content.

[2205] Input: Emotion data

[2206] Output: Tailored educational content

[2207] Step 4:

[2208] The user performs an unconscious bias check. The device sends the user's answers (answer data to questions) to the server. The server analyzes them, evaluates unconscious bias along with emotional data from the emotion engine, generates improvement suggestions, and sends them to the device. The device displays them to the user.

[2209] Input: Answer data and sentiment data

[2210] Output: Bias assessment and improvement suggestions

[2211] Step 5:

[2212] The user inputs the content of the consultation into the chat interface. The device sends the content (consultation content data) to the server. The server analyzes the content using generative AI and takes into account the emotional data from the emotion engine to generate the optimal solution, which is then sent to the device. The device then presents the solution to the user.

[2213] Input: Consultation content data and emotion data

[2214] Output: Optimal solution

[2215] Step 6:

[2216] A user attempts to purchase a product on the payment screen. The terminal initiates the payment process (purchase data), and the emotion engine monitors the user's emotional state (emotion data). The server uses generative AI to generate an appropriate display interface and recommended products based on the emotion data, and sends them to the terminal. The terminal displays the recommended products and adjusted interface.

[2217] Input: Purchase and sentiment data

[2218] Output: Recommended products and tailored interface

[2219] As a concrete example, if the emotion engine determines that the user's emotional state is "angry," it sends the following prompt to the generative AI model:

[2220] "The user is currently angry. Please recommend a relaxation item."

[2221] 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.

[2222] 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.

[2223] 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.

[2224] [Fourth embodiment]

[2225] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[2226] 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.

[2227] 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).

[2228] 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.

[2229] 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.

[2230] 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).

[2231] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[2232] 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.

[2233] 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.

[2234] 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.

[2235] 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.

[2236] 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.

[2237] 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."

[2238] To implement this invention, a system with the following configuration is required. The main elements are a server containing the generation AI, a terminal accessed by the user, and the user who uses the service.

[2239] User Registration and Login

[2240] User Registration:

[2241] When a user registers, he or she enters personal information such as name, email address, and password.

[2242] The terminal sends this information to the server, which then creates a user account based on the received information.

[2243] The terminal notifies the user that the account creation is complete.

[2244] Login:

[2245] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[2246] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[2247] The device receives the authentication token and redirects the user to the home screen.

[2248] Providing gender equity education content

[2249] View content:

[2250] A user accesses a catalog page to select the educational content they wish to study.

[2251] The terminal displays a list of educational content and sends the content ID selected by the user to the server.

[2252] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[2253] The terminal displays educational content to the user, and the user progresses with his / her studies.

[2254] Unconscious Bias Check

[2255] Checks performed:

[2256] Users visit the Unconscious Bias Check page and answer the necessary questions.

[2257] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[2258] The server generates analysis results and improvement suggestions and sends them to the terminal.

[2259] The terminal displays this to the user.

[2260] Communication Support

[2261] Input and analysis of consultation content:

[2262] The user inputs the content of the consultation into the chat interface.

[2263] The device sends the content to the server, which then analyzes it using a generating AI.

[2264] The server generates an appropriate solution and sends it to the terminal.

[2265] The terminal presents a solution to the user.

[2266] Feedback and Improvements

[2267] Feedback collection and analysis:

[2268] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[2269] The terminal sends this to the server, which analyzes the feedback data.

[2270] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[2271] Specific examples

[2272] Providing educational content for children:

[2273] Users (children) learn about gender equity using a dedicated educational app.

[2274] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[2275] The server receives learning data and generates progress reports to provide to parents and educators.

[2276] Unconscious Bias Check:

[2277] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[2278] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[2279] The server analyzes the response data and provides an assessment of bias and suggestions for improvement.

[2280] This system provides comprehensive support for gender equity issues and facilitates the education, evaluation, and improvement processes.

[2281] The processing flow will be explained below.

[2282] User Registration and Login

[2283] New Registration

[2284] Step 1:

[2285] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[2286] Step 2:

[2287] The terminal transmits the input information to the server.

[2288] Step 3:

[2289] The server stores the received user information in a database and creates a new account.

[2290] Step 4:

[2291] The terminal displays a message to the user indicating that registration is complete.

[2292] Log in

[2293] Step 1:

[2294] The user enters their email address and password into the login form on their device.

[2295] Step 2:

[2296] The terminal transmits the input information to the server.

[2297] Step 3:

[2298] The server checks the account information against the database and performs authentication.

[2299] Step 4:

[2300] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[2301] Step 5:

[2302] The device receives the authentication token and redirects the user to the dashboard or home screen.

[2303] Providing gender equity education content

[2304] View content

[2305] Step 1:

[2306] The user accesses the educational content catalog page from the terminal.

[2307] Step 2:

[2308] The device displays a list of educational content.

[2309] Step 3:

[2310] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[2311] Step 4:

[2312] The server retrieves the corresponding educational content from the database based on the received content ID.

[2313] Step 5:

[2314] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[2315] Step 6:

[2316] The terminal displays the educational content to the user.

[2317] Unconscious Bias Check

[2318] Check implementation

[2319] Step 1:

[2320] A user accesses the Unconscious Bias Check page on their device.

[2321] Step 2:

[2322] The terminal provides an interface for displaying the check questions.

[2323] Step 3:

[2324] The user enters an answer to each question.

[2325] Step 4:

[2326] The terminal transmits the response data to the server.

[2327] Step 5:

[2328] The server analyzes the response data and assesses whether or not there is unconscious bias.

[2329] Step 6:

[2330] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[2331] Step 7:

[2332] The terminal displays the evaluation results and improvement suggestions to the user.

[2333] Communication Support

[2334] Input and analysis of consultation details

[2335] Step 1:

[2336] The user uses the chat interface to input the consultation content.

[2337] Step 2:

[2338] The terminal transmits the input consultation content to the server.

[2339] Step 3:

[2340] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[2341] Step 4:

[2342] The server sends the solution to the terminal.

[2343] Step 5:

[2344] The terminal displays the solution to the user.

[2345] Feedback and Improvements

[2346] Feedback collection and analysis

[2347] Step 1:

[2348] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[2349] Step 2:

[2350] The terminal transmits the input feedback to the server.

[2351] Step 3:

[2352] The server analyzes the feedback data and extracts areas for improvement.

[2353] Step 4:

[2354] The server updates the system based on the extracted improvements.

[2355] This step will ensure that the Gender Equity Support System operates smoothly and provides appropriate support for each use case.

[2356] Example 1

[2357] 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."

[2358] Gender equity is an important issue in modern society, but solving it is not easy because many people have unconscious biases. Existing education systems and corporate training programs often do not provide effective approaches to individual needs and issues. Furthermore, there are limitations to achieving gender equity because there is a lack of mechanisms in place to collect user feedback and continuously improve services. There is a need to provide a system that can solve these issues and effectively support gender equity.

[2359] 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.

[2360] In this invention, the server includes means for accepting user registration and creating a user account, means for users to log in and generate an authentication token, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation details and presenting solutions, and means for collecting user feedback and improving the service. This enables learning, assessment, and improvement suggestions that meet the needs of diverse users, contributing to the improvement of gender equity.

[2361] "Generative AI" refers to a system that uses artificial intelligence technology to automatically generate, analyze, and evaluate data.

[2362] "Gender equity" refers to a situation in which discrimination and inequity based on gender are eliminated and equal opportunities and treatment are provided to all.

[2363] "User registration" refers to the process by which a system user creates a new account on the system by providing personal information such as name, email address, and password.

[2364] "User account" refers to a data set used to individually identify a user in the system, including the user's personal information and usage history.

[2365] An "authentication token" refers to an electronic certificate that indicates a user has been properly authenticated and is used to grant access to a system.

[2366] "Educational content" refers to educational materials and information provided for users to learn from, and may include formats such as text, video, and quizzes.

[2367] "Study progress" refers to an indicator that indicates how much a user has progressed in their studies through educational content.

[2368] An "unconscious bias check" is a test that allows users to assess their own unconscious biases, often in the form of a questionnaire or survey.

[2369] "Improvement Suggestions" are specific advice to provide effective solutions to users' unconscious biases and other challenges.

[2370] "Consultation content" refers to questions and issues raised by users through the system, which are analyzed by the generation AI.

[2371] "Solutions" refer to specific solutions or advice for the problems or questions users are facing.

[2372] "User Feedback" refers to opinions and suggestions for improvement collected from users after using the Service.

[2373] "Means for improving the service" refers to the process for modifying and improving the system and the content provided based on user feedback.

[2374] To implement this invention, the following main components are required: a server containing the generative AI, a terminal accessed by the user, and the user who uses the service. These components work together to provide a gender equity support service.

[2375] System Configuration

[2376] This system consists of a server, a terminal, and a user. The server contains a generative AI model and analyzes data provided by the user to provide educational content and analyze the results of bias checks. The terminal provides the user interface and acts as a medium for the user to communicate with the server.

[2377] User Registration and Login

[2378] When a user registers, they enter personal information such as their name, email address, and password. The device sends this information to the server, and the server creates a user account based on the received information. The user also logs in with an already created account, and the server verifies the user's identity by comparing it with information in the database, then generates and returns an authentication token. The device receives the authentication token and redirects the user to the home screen.

[2379] Providing gender equity education content

[2380] When a user accesses the catalog page to select the educational content they wish to study, the device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device, which then displays it to the user.

[2381] As a concrete example, when providing educational content for children, users (children) use a dedicated educational app to learn about gender equity. The device displays educational materials in the form of videos and quizzes and monitors the learning progress. The server receives the learning data, generates a progress report, and provides it to the educator.

[2382] Unconscious Bias Check

[2383] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which then analyzes the received data using a generative AI model to evaluate whether it contains unconscious bias. The server generates analysis results and improvement suggestions, which are then sent to the device, which displays them to the user.

[2384] An example prompt is:

[2385] "Please evaluate how your unconscious biases are manifested in your responses to the bias check questions and provide specific suggestions for improvement."

[2386] Communication Support

[2387] The user inputs the content of their inquiry into the chat interface. The device sends the content to the server, which analyzes it using a generative AI. The server generates an appropriate solution and sends it to the device. The device then presents the solution to the user.

[2388] An example prompt is:

[2389] "Analyze the consultation about communication problems in the workplace and propose solutions."

[2390] Feedback and Improvements

[2391] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data using a generative AI model. The server then uses the analysis results to identify areas for improvement in the system and makes appropriate updates.

[2392] This system will enable learning, evaluation, and improvement suggestions that meet the needs of diverse users, contributing to improving gender equality.

[2393] The flow of the identification process in the first embodiment will be described with reference to FIG.

[2394] Step 1:

[2395] The user enters their name, email address, and password into the new registration form.

[2396] Input: Name, Email Address, Password

[2397] Output: User registration information

[2398] Specifically, the user enters "Yamada Taro," "taro.yamada@example.com," and "password123" into the form.

[2399] Step 2:

[2400] The terminal sends the entered information to the server using an HTTP POST request.

[2401] Input: User registration information

[2402] Output: HTTP POST request to the server

[2403] The device sends this information to the server in JSON format.

[2404] Step 3:

[2405] The server verifies the received information and registers the new user account in its database.

[2406] Input: User registration information data

[2407] Output: Insertion result into database

[2408] The server uses an SQL query to insert the user information into a database.

[2409] Step 4:

[2410] The terminal notifies the user that the account creation is complete.

[2411] Input: Account creation completion notification

[2412] Output: A message to inform the user

[2413] The device will display the message "Account created successfully."

[2414] Step 5:

[2415] The user enters their email address and password into the login form.

[2416] Input: Email address, password

[2417] Output: Login information

[2418] For example, the user enters "taro.yamada@example.com" and "password123".

[2419] Step 6:

[2420] The device sends the entered login information to the server via an HTTP POST request.

[2421] Input: Login information

[2422] Output: HTTP POST request to the server

[2423] The device sends the information to the server in JSON format.

[2424] Step 7:

[2425] The server checks the database and generates an authentication token if authentication is successful.

[2426] Input: Login information data

[2427] Output: Authentication token

[2428] The server compares the received information with the user information in its database and generates a JWT (JSON Web Token) if there is a match.

[2429] Step 8:

[2430] The device receives the authentication token and redirects the user to the home screen.

[2431] Input: Authentication Token

[2432] Output: Redirect to home screen

[2433] The device stores the authentication token in local storage and redirects to the home screen.

[2434] Step 9:

[2435] The user accesses the educational content catalog page.

[2436] Input: Access to catalog page

[2437] Output: Catalog page display

[2438] A user opens the catalog page URL in a browser.

[2439] Step 10:

[2440] The terminal obtains a list of educational content from the server and displays it.

[2441] Input: Content data from the server

[2442] Output: List of educational content

[2443] The terminal displays the content information obtained from the server in a list format in HTML.

[2444] Step 11:

[2445] The user selects the content they wish to study and sends the content ID to the server.

[2446] Input: Selected Content ID

[2447] Output: Content ID sent to server

[2448] For example, a user selects a content item called "Gender History" and sends its ID to the server.

[2449] Step 12:

[2450] The server retrieves the relevant educational content from the database and sends it to the terminal.

[2451] Input: Content ID

[2452] Output: Acquired educational content data

[2453] The server retrieves the content data using an SQL query and then sends it to the terminal as an API response.

[2454] Step 13:

[2455] The terminal displays the acquired educational content to the user.

[2456] Input: Educational content data

[2457] Output: Displayed educational content

[2458] The device displays the content using a video player and quiz-style interface.

[2459] Step 14:

[2460] Users visit the Unconscious Bias Check page and answer questions.

[2461] Input: Bias Check Questions and Answers

[2462] Output: Response data

[2463] The user accesses the bias check questionnaire form and enters answers to the questions.

[2464] Step 15:

[2465] The terminal transmits the user's answer to the server.

[2466] Input: Answer data

[2467] Output: Send response data to the server

[2468] The device sends the response data to the server in JSON format.

[2469] Step 16:

[2470] The server analyzes the received data using a generative AI model to assess whether it contains unconscious bias.

[2471] Input: Answer data

[2472] Output: Analysis results and evaluation

[2473] The server uses a generative AI model to analyze the received response data.

[2474] Step 17:

[2475] The server generates analysis results and improvement suggestions and sends them to the terminal.

[2476] Input: Analysis results and evaluation

[2477] Output: Improvement proposal data

[2478] The server sends the analysis results and corresponding improvement suggestions to the terminal in JSON format.

[2479] Step 18:

[2480] The device displays the analysis results and improvement suggestions to the user.

[2481] Input: Improvement proposal data

[2482] Output: Display of analysis results and improvement suggestions

[2483] The terminal displays the analysis results and improvement suggestions in a user interface.

[2484] Step 19:

[2485] The user inputs the content of the consultation into the chat interface.

[2486] Input: Consultation details

[2487] Output: Input consultation content data

[2488] A user types in chat about "communication challenges at work."

[2489] Step 20:

[2490] The terminal transmits the consultation content data to the server.

[2491] Input: Consultation content data

[2492] Output: Send consultation details to the server

[2493] The device sends the chat content to the server in JSON format.

[2494] Step 21:

[2495] The server uses the generation AI to analyze the consultation content data.

[2496] Input: Consultation content data

[2497] Output: Analyzed result data

[2498] The server uses the generative AI model to analyze the received consultation data.

[2499] Step 22:

[2500] The server generates an appropriate solution and sends it to the terminal.

[2501] Input: Analysis result data

[2502] Output: Solution data

[2503] The server generates a solution and sends it to the device as an API response.

[2504] Step 23:

[2505] The terminal presents the generated solutions to the user.

[2506] Input: Solution data

[2507] Output: Displayed solution

[2508] The terminal displays the generated solution in a chat interface.

[2509] Step 24:

[2510] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[2511] Input: Feedback data

[2512] Output: Input feedback data

[2513] Users enter their opinions and suggestions for improvement in the feedback form.

[2514] Step 25:

[2515] The terminal transmits the feedback data to the server.

[2516] Input: Feedback data

[2517] Output: Send feedback to the server

[2518] The device sends the feedback content to the server in JSON format.

[2519] Step 26:

[2520] The server analyzes the feedback data using a generative AI model.

[2521] Input: Feedback data

[2522] Output: Parsed feedback results

[2523] The server uses a generative AI model to analyze the feedback data and generate results.

[2524] Step 27:

[2525] Based on the analysis results, the server identifies areas for improvement in the system and makes appropriate updates.

[2526] Input: Analysis result data

[2527] Output: System improvements and updates

[2528] Based on the analysis results, the server designs improvements to the system and implements necessary updates.

[2529] The above are the specific processing steps of the program of this system.

[2530] (Application example 1)

[2531] 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."

[2532] As gender equity becomes increasingly important in modern society, there is a need for efficient support methods to promote individual awareness and behavioral improvement. Furthermore, systems that provide a wide range of services, such as educational content, unconscious bias checks, and consultation content analysis, require user-friendly and effective interactions. In particular, when providing this support in a virtual environment, there is a need for methods that facilitate the process of users becoming aware of their own unconscious biases and seeking solutions. Our goal is to provide a comprehensive system to solve these issues.

[2533] 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.

[2534] In this invention, the server includes means for accepting user registration and creating a user account, means for providing educational content and collecting and analyzing users' learning progress, means for conducting unconscious bias checks and providing users with improvement suggestions, means for analyzing consultation content and presenting solutions, means for collecting user feedback and improving services, means for providing educational content in a virtual environment and supporting an interactive learning experience, means for employees in the virtual environment to conduct bias checks and promote self-improvement, and means for providing customer support in the virtual environment and providing solutions to consultation content using a generative AI model. This enables users to learn about gender equity and improve themselves within the virtual environment, and allows them to receive efficient and effective support.

[2535] "Generative AI" is a system that uses artificial intelligence to generate, analyze, and predict data.

[2536] "Gender equity" is a concept that refers to a state in which men and women receive equal opportunities and treatment socially, economically, and culturally.

[2537] "Support services" refers to a series of services provided to solve problems and issues faced by users.

[2538] "User registration" is the process by which a new user enters the necessary personal information into the system and obtains eligibility to use the system.

[2539] "User Account" refers to the individual authentication information and data assigned to each User for use of the System.

[2540] "Educational content" refers to information and instructional materials designed to help learners acquire specific knowledge or skills.

[2541] "User's learning progress" refers to the user's level of achievement and understanding in the process of learning educational content.

[2542] "Unconscious bias check" refers to a method or checklist for assessing and detecting the prejudices and stereotypes that individuals unconsciously hold.

[2543] "Means for providing users with improvement suggestions" refers to features within the system that provide specific suggestions or advice to help users reduce their unconscious biases or improve their behavior.

[2544] "Consultation content" refers to information that indicates questions, problems, or concerns that a user inputs to the system.

[2545] "Solution" refers to the method or means provided to the user in response to their inquiry based on the results of analysis conducted by the system using generated AI.

[2546] "User feedback" refers to opinions from users, such as impressions after using the service, areas for improvement, and suggestions.

[2547] "Virtual environment" refers to a virtual space or simulated environment, including digital experiential spaces provided over the Internet.

[2548] An "interactive learning experience" refers to a learning method or experience in which the user actively participates and progresses interactively.

[2549] An "employee" refers to an individual employed by a company or organization to perform specific tasks or roles.

[2550] "Customer support" refers to the business activities that provide assistance and support to customers who use products or services.

[2551] A "generative AI model" refers to an artificial intelligence algorithm or framework built to learn from large amounts of data and generate new data or perform specific tasks.

[2552] This invention describes a system that uses generative AI to provide gender equity support services within a virtual environment, including user registration, educational content provision, unconscious bias checks, customer support consultation and resolution, and feedback collection.

[2553] 1. User Registration and Login

[2554] Users access the system using a terminal and register by entering personal information such as name, email address, and password. This information is sent to the server, which then creates a user account based on the received information. When logging in, the user enters their email address and password, which the terminal then sends to the server, which then compares them with the information in the database to verify that the user is a legitimate user.

[2555] 2. Providing educational content

[2556] The system interactively provides educational content related to gender equity that the user wishes to learn about within a virtual environment. The device displays a list of educational content and sends the content ID of the user's selection to the server. The server retrieves the corresponding educational content from a database and sends it to the device, which then displays it to the user.

[2557] 3. Unconscious bias check

[2558] Users access the unconscious bias check page and answer the necessary questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The server generates analysis results and improvement suggestions and sends them to the device.

[2559] 4. Customer support and analysis of inquiries

[2560] The user enters the content of their inquiry into the chat interface, and the device sends the content to the server. The server analyzes it using generative AI, generates an appropriate solution, and sends it to the device. The device then presents the solution to the user.

[2561] 5. Collecting feedback and improving our services

[2562] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which then analyzes the feedback data and identifies areas for improvement in the service.

[2563] The system is implemented using Python and the Flask framework, with the SQLite database and the SHA-256 hash function for password security.

[2564] For example, consider the following prompt:

[2565] Sample unconscious bias check questions:

[2566] "To assess your own unconscious biases, answer these questions:

[2567] 1. Do you ever feel that one gender is superior, even when there are objective standards of evaluation?

[2568] 2. Do you unconsciously stereotype certain genders in your daily life or at work?

[2569] Example start prompts for gender equity education content:

[2570] Get started with educational content on gender equity. Study the following materials:

[2571] 1. What is gender equity?

[2572] 2. How to promote gender equity in the workplace

[2573] In this way, users can learn about gender equity and improve themselves within a virtual environment, receiving efficient and effective support.

[2574] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[2575] Step 1:

[2576] A user accesses the system using a terminal and registers by entering personal information such as name, email address, and password. The terminal sends the entered information to the server, which then creates a user account based on the received information. The input data includes name, email address, and password (SHA-256 hashed), and the output data is the created user account.

[2577] Step 2:

[2578] When logging in, the user enters their email address and password. The device sends this to the server, which checks it against information in a database to verify the user is a valid user. The input data is the email address and hashed password, and the output data is an authentication token. The device receives the authentication token and redirects the user to the home screen.

[2579] Step 3:

[2580] The user browses gender equity educational content provided in a virtual environment. The device displays a list of educational content and sends the content ID selected by the user to the server. The server retrieves the corresponding educational content from the database and sends it to the device. The input data is the content ID, and the output data is the educational content. The device displays the educational content to the user, allowing the user to progress with their learning.

[2581] Step 4:

[2582] The user accesses the unconscious bias check page and answers the required questions. The device sends the user's answers to the server, which analyzes the received data and evaluates unconscious bias. The input data is the user's answers, and the output data is the analysis results and improvement suggestions. The server generates the analysis results and improvement suggestions and sends them to the device, which displays them to the user.

[2583] Step 5:

[2584] The user inputs the details of their customer support inquiry into the chat interface. The device sends the details to the server, which analyzes them using a generative AI model. The input data is the inquiry details, and the output data is an appropriate solution. The server generates a solution and sends it to the device. The device presents the solution to the user.

[2585] Step 6:

[2586] After using the service, users enter their opinions and suggestions for improvement into a feedback form. The device sends this to the server, which analyzes the feedback data and identifies areas for improvement in the system. The input data is the feedback content, and the output data is the analysis results and improvement suggestions. The server then performs appropriate system updates based on this.

[2587] 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.

[2588] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. The system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[2589] User Registration and Login

[2590] User Registration:

[2591] When a user registers, he or she enters personal information such as name, email address, and password.

[2592] The terminal sends this information to the server, which then creates a user account based on the received information.

[2593] The terminal notifies the user that the account creation is complete.

[2594] Login:

[2595] The user logs in with an already created account, entering their email address and password, which the device then sends to the server.

[2596] The server checks the information in the database to verify that the user is a legitimate user, then generates and returns an authentication token.

[2597] The device receives the authentication token and redirects the user to the home screen.

[2598] Providing gender equity education content

[2599] View content:

[2600] A user accesses a catalog page to select the educational content they wish to study.

[2601] The terminal displays a list of educational content and transmits the content ID selected by the user to the server.

[2602] The server retrieves the corresponding educational content from the database and transmits it to the terminal.

[2603] The terminal displays educational content to the user, and the user progresses with his / her studies.

[2604] The emotion engine recognizes the user's emotions in real time and transmits the data to the server.

[2605] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[2606] Unconscious Bias Check

[2607] Checks performed:

[2608] Users visit the Unconscious Bias Check page and answer the necessary questions.

[2609] The device sends the user's answers to a server, which analyzes the data and assesses whether it contains any unconscious bias.

[2610] The server also analyzes the emotion data received from the emotion engine to generate more accurate evaluation results.

[2611] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[2612] The terminal displays this to the user.

[2613] Communication Support

[2614] Input and analysis of consultation content:

[2615] The user inputs the content of the consultation into the chat interface.

[2616] The device sends the content to the server, which then analyzes it using a generating AI.

[2617] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[2618] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[2619] The terminal presents a solution to the user.

[2620] Feedback and Improvements

[2621] Feedback collection and analysis:

[2622] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[2623] The terminal sends this to the server, which analyzes the feedback data.

[2624] The emotion engine collects the user's emotional state during feedback input and also sends it to the server.

[2625] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement in the service.

[2626] The server updates the system based on the extracted improvements.

[2627] Specific examples

[2628] Providing educational content for children:

[2629] Users (children) learn about gender equity using a dedicated educational app.

[2630] The device displays learning materials in the form of videos and quizzes and monitors learning progress.

[2631] The emotion engine recognizes emotions from the child's facial expressions and tone of voice and sends this to the server.

[2632] The server uses emotional data to assess stress and interest levels during learning and adjusts the content accordingly.

[2633] The device displays tailored content to optimize the user's learning experience.

[2634] Unconscious Bias Check:

[2635] A user (e.g., a human resources professional) performs a bias check for self-evaluation after a job interview.

[2636] The terminal displays a questionnaire in the form of questions, and the user inputs answers.

[2637] The emotion engine recognizes the user's emotion in the response and transmits it to the server.

[2638] The server analyzes the response data and sentiment data, and provides an assessment of bias and suggestions for improvement.

[2639] This system provides comprehensive support for gender equity issues, facilitating the education, assessment, and improvement processes. In addition, by combining it with an emotion engine, it provides optimal support according to the user's individual emotional state.

[2640] The processing flow will be explained below.

[2641] User Registration and Login

[2642] New Registration

[2643] Step 1:

[2644] The user enters the required information (name, email address, password, etc.) into the new registration form on the device.

[2645] Step 2:

[2646] The terminal transmits the input information to the server.

[2647] Step 3:

[2648] The server stores the received user information in a database and creates a new account.

[2649] Step 4:

[2650] The terminal displays a message to the user indicating that registration is complete.

[2651] Log in

[2652] Step 1:

[2653] The user enters their email address and password into the login form on their device.

[2654] Step 2:

[2655] The terminal transmits the input information to the server.

[2656] Step 3:

[2657] The server checks the account information against the database and performs authentication.

[2658] Step 4:

[2659] If the authentication is successful, the server generates an authentication token and sends it to the terminal.

[2660] Step 5:

[2661] The device receives the authentication token and redirects the user to the dashboard or home screen.

[2662] Providing gender equity education content

[2663] View content

[2664] Step 1:

[2665] The user accesses the educational content catalog page from the terminal.

[2666] Step 2:

[2667] The device displays a list of educational content.

[2668] Step 3:

[2669] The user selects the content they wish to view, and the terminal transmits the selected content ID to the server.

[2670] Step 4:

[2671] The server retrieves the corresponding educational content from the database based on the received content ID.

[2672] Step 5:

[2673] The server sends the acquired content data (video links, text information, etc.) to the terminal.

[2674] Step 6:

[2675] The terminal displays the educational content to the user.

[2676] Utilizing Emotional Data

[2677] Step 1:

[2678] The emotion engine recognizes emotions in real time from the user's facial expressions and tone of voice.

[2679] Step 2:

[2680] The emotion engine sends the emotion data to the server.

[2681] Step 3:

[2682] The server analyzes the emotional data and adjusts the content and difficulty of the content to be displayed based on the user's emotional state.

[2683] Step 4:

[2684] The server transmits the adjusted content data to the terminal.

[2685] Step 5:

[2686] The terminal displays the tailored educational content to the user.

[2687] Unconscious Bias Check

[2688] Check implementation

[2689] Step 1:

[2690] A user accesses the Unconscious Bias Check page on their device.

[2691] Step 2:

[2692] The terminal provides an interface for displaying the check questions.

[2693] Step 3:

[2694] The user enters an answer to each question.

[2695] Step 4:

[2696] The terminal transmits the response data to the server.

[2697] Step 5:

[2698] The server analyzes the response data and assesses whether or not there is unconscious bias.

[2699] Step 6:

[2700] The emotion engine recognizes the user's emotion in the response and sends the data to the server.

[2701] Step 7:

[2702] The server integrates and analyzes the response data and emotion data to generate bias evaluation results.

[2703] Step 8:

[2704] The server generates evaluation results and improvement suggestions and sends them to the terminal.

[2705] Step 9:

[2706] The terminal displays the evaluation results and improvement suggestions to the user.

[2707] Communication Support

[2708] Input and analysis of consultation details

[2709] Step 1:

[2710] The user inputs the content of the consultation into the chat interface.

[2711] Step 2:

[2712] The terminal transmits the contents to the server.

[2713] Step 3:

[2714] The emotion engine monitors the user's emotional state during a consultation in real time and transmits the data to the server.

[2715] Step 4:

[2716] The server uses generative AI to analyze the consultation content and generate relevant solutions.

[2717] Step 5:

[2718] The server generates an optimal solution taking into account the emotional data and sends it to the terminal.

[2719] Step 6:

[2720] The terminal presents a solution to the user.

[2721] Feedback and Improvements

[2722] Feedback collection and analysis

[2723] Step 1:

[2724] After using the service, users enter their opinions and suggestions for improvement in a feedback form.

[2725] Step 2:

[2726] The terminal transmits the input feedback to the server.

[2727] Step 3:

[2728] The emotion engine recognizes the user's emotions during feedback input and sends the data to the server.

[2729] Step 4:

[2730] The server integrates and analyzes the feedback data and emotional data to identify areas for improvement.

[2731] Step 5:

[2732] The server updates the system based on the extracted improvements.

[2733] Step 6:

[2734] The server notifies the terminal of the update contents and displays them to the user.

[2735] Through this process, the gender equity support system can provide users with appropriate support and an optimal learning experience according to their emotional state.

[2736] Example 2

[2737] 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."

[2738] Promoting gender equality is becoming increasingly important in modern society. However, traditional education and support services provide uniform content without considering the user's emotional state, making it difficult to provide optimal support for each individual user. Furthermore, because emotional data is not taken into account when assessing unconscious bias or making suggestions for improvement, there are limitations to the accuracy and effectiveness of these services. Furthermore, educational content delivery lacks interactivity, making it ineffective, especially for children.

[2739] 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.

[2740] In this invention, the server includes a means for accepting user registration and creating a user account, a means for providing educational content and collecting and analyzing the user's learning progress, a means for conducting unconscious bias checks and providing improvement suggestions to the user, a means for collecting emotional data in real time and adjusting the content content and difficulty level based on the collected data, and a means for using the emotional data to evaluate unconscious bias and generate improvement suggestions. This makes it possible to provide gender equity support that is optimal for each individual user based on their emotional state, which is expected to be highly accurate and effective in terms of educational effectiveness and the reduction of unconscious bias. It also improves the interactivity of educational content for children, significantly improving the quality of the learning experience.

[2741] "User registration" refers to the process by which a new user of the system enters personal information and creates a user account based on that information.

[2742] "User Account" is a digital identifier generated by the system to manage a user's personal information and authentication information.

[2743] "Educational content" refers to learning materials and educational materials related to gender equity, including videos, quizzes, articles, etc.

[2744] "Study progress" is information indicating how much learning the user has completed through educational content.

[2745] An "unconscious bias check" is a process that involves asking questions or taking tests to assess whether a user has any unconscious biases.

[2746] "Improvement suggestions" are specific advice and guidelines for improving the user's perceived biases, generated based on the results of the unconscious bias check.

[2747] "Consultation" refers to the text information or question a user enters to seek assistance with gender equity.

[2748] "Emotional data" is information about the user's emotional state, collected from the user's facial expressions, tone of voice, and the like.

[2749] "Real-time" means that information is obtained and processed immediately, and refers to a response without delay.

[2750] An "unconscious bias assessment" is the process of analyzing the results of a user's unconscious bias check to determine whether unconscious bias is present.

[2751] An "interactive learning experience" is a learning method in which users actively interact with educational content and exchange information in a two-way manner, promoting deep understanding.

[2752] A system for implementing this invention combines generative AI and an emotion engine to enhance gender equity support services. This system includes a terminal accessed by users, a server that manages and processes generative AI and various data, and an emotion engine.

[2753] Hardware and Software Configuration

[2754] ...

Claims

1. A system for providing gender equity support services using generative AI, means for accepting user registrations and creating user accounts; A means for providing educational content and collecting and analyzing users' learning progress; A means to conduct unconscious bias checks and provide users with suggestions for improvement; A means of analyzing the content of the consultation and presenting solutions, a means of collecting user feedback and improving the Service; A system including:

2. 10. The system of claim 1, further comprising means for providing gender equity educational content and facilitating interactive learning experiences for children.

3. 10. The system of claim 1, further comprising means for analyzing results of the unconscious bias check to perform an unconscious bias assessment and generate improvement suggestions.

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