System

Abstract

A system is provided.SOLUTION: A system comprising: means for allowing a user to designate a destination country or region and a law category to be investigated; means for allowing a server to research laws and precedents in the designated country or region by using generative artificial intelligence; means for allowing the server to automatically generate a material summarizing legal risks related to entry based on a research result; means for transmitting the material generated by the server to a terminal of the user; and means for allowing the terminal to display the received material.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] In today's increasingly globalized world, it is important for companies to comply with the laws and regulations of each country when expanding overseas. However, currently, researching and confirming each country's laws and precedents requires a great deal of effort and expense. Researching multiple countries is particularly costly, placing a significant burden on small and medium-sized enterprises. Furthermore, the latest laws and precedents are constantly being updated, making it necessary to gather information quickly and accurately. The present invention aims to solve these problems and provide a means to facilitate companies' expansion overseas. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems with a system that includes: a means for a user to specify a country or region to enter and a category of laws and regulations to be investigated; a means for a server to use generative artificial intelligence to research the laws and legal precedents of the specified country or region; a means for the server to automatically generate a document summarizing the legal risks associated with the entry based on the research results; a means for transmitting the generated document to the user's terminal; and a means for displaying the received document on the terminal. The system also includes a means for performing a simple format check on the user's input of the request to prevent input errors, and a means for the server to store the research results in an internal database to increase the reusability of information. This significantly reduces the cost of legal research and enables the rapid and efficient provision of legal risk-related documents.

[0006] "Users" refer to companies and individuals who use the system to conduct legal research in the countries they are entering.

[0007] "Terminal" refers to a device used by a user, such as a computer or smartphone.

[0008] "Server" refers to a computer system for running generative artificial intelligence and processing information.

[0009] "Generative artificial intelligence" refers to AI technology used to research laws and precedents and automatically generate materials.

[0010] "Law category" refers to the area of ​​law that the user specifies as the subject of the search, such as labor law or tax law.

[0011] "Research" refers to the act of investigating the laws and precedents of designated countries and regions.

[0012] "Precedent" refers to cases related to law that have been decided by courts in the past.

[0013] "Research Results" refers to information on laws and precedents collected by artificial intelligence.

[0014] "Materials" refers to documents summarizing the legal risks related to expansion based on research results.

[0015] "Simple format check" refers to the process of automatically checking the format of information entered by a user and determining whether there are any errors.

[0016] "Internal Database" refers to a database established within the server for storing research results and other data. [Brief explanation of the drawings]

[0017] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram 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

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

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

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

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

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

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

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

[0025] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0038] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in the country or region a company is expanding into when it is expanding overseas. This system includes a means for the user to specify the country or region to expand into and the legal category to be investigated, a means for the server to research the specified laws and precedents using generative artificial intelligence, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal.

[0039] Explanation of program processing

[0040] 1. User input

[0041] Using the input form on the device, users input the country or region they wish to enter and the legal category they wish to research, for example, by entering keywords such as "America, China, labor law, tax law."

[0042] 2. Data transmission by the terminal

[0043] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0044] 3. Server-based research

[0045] The server runs a generative artificial intelligence (AI) to research the laws and legal precedents of a specified country or region, for example, by retrieving information on the latest labor and tax laws in the United States from government databases and reliable legal databases.

[0046] 4. Saving your research results

[0047] The server stores the research results in an internal database, storing information such as the content of the law, its enforcement date, and related legal precedents as structured data.

[0048] 5. Automatic generation of materials

[0049] The server launches a document generation module, which automatically generates a document summarizing the legal risks associated with the expansion based on the research results. The document includes specific details about the main points, risks, and differences between Japan and the US. For example, it includes information such as the US work week limit of 40 hours and the federal minimum wage of $7.25.

[0050] 6. Submission of Materials

[0051] The server converts the generated documents into PDF or Word format and sends them to the device. The data is sent in an encoded format to ensure secure communication.

[0052] 7. Displaying and downloading materials via terminal

[0053] The terminal displays the materials received from the server so that the user can check them, and the user can download or print them as necessary.

[0054] Specific examples

[0055] As a concrete example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America, China, labor law, tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. The user can review the document and use it to help them make a decision about expanding into the country.

[0056] The present invention enables users to grasp the legal risks of the country in which they are entering at low cost and efficiently, and to obtain investigation results with speed and accuracy that could not be achieved with conventional methods.

[0057] The processing flow will be explained below.

[0058] Step 1: The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, the user might enter keywords such as "America," "China," "Labor Law," or "Tax Law."

[0059] Step 2: The device reviews the user's input and performs a quick check to ensure there are no formatting issues, such as whether the entered country name is spelled correctly or whether the legal category being investigated is included in an existing list.

[0060] Step 3: The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0061] Step 4: The server analyzes the information received from the user and passes it to the generative AI research module. This analysis includes selecting a database of laws and regulations for the input country or region.

[0062] Step 5: The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region. For example, it collects the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0063] Step 6: The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0064] Step 7: The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. For example, under US labor law, this includes information such as "working hours limited to 40 hours per week" and "federal minimum wage is $7.25."

[0065] Step 8: The server converts the generated document into PDF or Word format and sends it to the device in an encoded format, ensuring secure communication.

[0066] Step 9: The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to view the data.

[0067] Step 10: The user checks the displayed materials and downloads or prints them as necessary. This allows the user to obtain specific information about the legal risks in the country in which they are entering.

[0068] Example 1

[0069] 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."

[0070] When a company expands overseas, it is important to investigate the legal risks of the country it is expanding into quickly and at low cost. However, traditional methods require a lot of time and money, placing a heavy burden on small and medium-sized enterprises. In addition, there was a problem in that there was no system that could quickly collect reliable information and automatically generate documents based on that information.

[0071] 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.

[0072] In this invention, the server includes means for searching for regulations and case studies in a designated area using generative artificial intelligence, means for automatically generating materials summarizing regulatory risks related to expansion based on the results of the search, and means for transmitting the generated materials to the user's information processing device, thereby enabling companies to efficiently understand the legal risks of their expansion destinations at low cost.

[0073] A "user" is an individual or entity that uses the system to specify the geographical area in which to operate and the regulatory category to be investigated.

[0074] "Region" refers to the specific country or region in which the company plans to expand.

[0075] "Regulatory category" refers to the classification of laws and regulations (e.g., labor laws, tax laws, etc.) in the country in which a company wishes to enter and investigate.

[0076] The term "means" refers to a method or apparatus for realizing a specific function. In this context, it refers to a device or system part having a specific function such as input, transmission, or display.

[0077] "Generative AI" refers to an AI model that can automatically generate text in response to a given prompt.

[0078] "Regulation" means any law, ordinance or rule enacted by a government or related authority.

[0079] "Case studies" refer to actual legal events in Europe, such as past precedents and examples.

[0080] "Exploration" refers to the act of searching for and collecting specific information based on specified criteria.

[0081] "Materials" refers to reports and documents generated based on research results.

[0082] The term "information processing device" refers to a device such as a computer or smartphone used by a user.

[0083] A "database" refers to a system for systematically organizing and storing collected information.

[0084] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in a country where a company is expanding overseas. This system includes a means for a user to specify the region to expand into and the regulatory categories to be investigated, a means for a server to use generative artificial intelligence to search for the specified regulations and examples, a means for automatically generating documents summarizing the regulatory risks related to the expansion based on the results of the search, a means for transmitting the generated documents to the user's information processing device, and a means for displaying the documents received by the information processing device.

[0085] Specifically, the system is constructed using the following hardware and software.

[0086] Hardware and software used

[0087] 1. Terminal

[0088] A terminal is an information processing device that allows users to input information and receive and display materials from the server. Examples include PCs, smartphones, and tablets. A web browser is installed on the terminal, and users input information through an input form.

[0089] 2. Server

[0090] The server requires high-performance hardware to run generative artificial intelligence (e.g., GPT-4). The server also has an internal database (e.g., MySQL) and template engine (e.g., Jinja2) for generating materials and storing data.

[0091] System Operation

[0092] 1. Enter information

[0093] Using the device's web browser, the user enters the region of the country they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, the user enters "America, China, Labor Law, Tax Law" and clicks the submit button.

[0094] 2. Data transmission and check

[0095] The terminal performs a simple format check of the entered information, and if there are no errors, sends it to the server. At this time, it checks that the entered data is in the correct format, and if necessary, displays an error message to prompt the user to re-enter the data.

[0096] 3. Conduct research

[0097] The server runs generative artificial intelligence to explore regulations and cases in a given region, for example, gathering information on the latest US labor and tax laws from a reliable database.

[0098] 4. Saving results and generating documents

[0099] The server stores the acquired information as structured data in an internal database, and then uses a document generation module to automatically generate documents summarizing the regulatory risks associated with the company's expansion. Specifically, a template engine (e.g., Jinja2) is used to insert the collected data into a document and convert it into PDF or Word format.

[0100] 5. Submitting and Displaying Materials

[0101] The server sends the generated documents to the user's terminal, which receives and displays them. The user can then check the documents on the terminal and download or print them as needed.

[0102] Specific examples

[0103] As a concrete example, consider the case of a Japanese company considering expanding into the United States and China. The user enters "United States, China, labor law, tax law" into an input form on their device and requests a survey. In response, the server collects the latest information on labor and tax laws in both countries, generates a document detailing the regulatory risks in each country, and sends it to the user's device. The user then reviews the document and uses it to help them make a decision about expanding into the country.

[0104] Prompt Sentence Examples

[0105] Below are some examples of prompts for generative artificial intelligence:

[0106] Please research the US, China, labor laws, and tax laws and create a document outlining the regulatory risks for each country. Specifically, please provide detailed data including the latest information on labor and tax laws, enforcement dates, and related cases.

[0107] Using this prompt, the generative AI can research detailed regulatory risks based on the specified region and regulatory category, and efficiently create the necessary materials.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] Using the web browser on their device, the user enters the region they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, they enter "America, China, Labor Law, Tax Law" and click the submit button. The data entered is the region name and regulatory category. Specifically, the user enters keywords using the input form and then submits the form.

[0111] Step 2:

[0112] The terminal performs a simple format check on the information entered by the user to ensure there are no errors. This is a process that checks whether the input data is in the correct format. The input is the region name and regulatory category entered by the user, and the output is the checked data. Specifically, the terminal validates the input information, and if any invalid input is found, it displays an error message and prompts the user to re-enter the information.

[0113] Step 3:

[0114] The terminal sends the checked data to the server. The input is the checked region name and regulatory category data, and the output is a request including this data that is sent to the server. Specifically, the terminal sends an HTTP request to the server.

[0115] Step 4:

[0116] The server receives the request and launches a generative AI to initiate a search process based on the specified region and regulatory category. The input is the received region name and regulatory category, and the output is regulatory and case information. Specifically, the server provides prompts to the generative AI model (e.g., GPT-4) and collects relevant data.

[0117] Step 5:

[0118] The server stores the information obtained from the generative artificial intelligence in an internal database. The input is the collected regulatory and case information, and the output is structured data stored in the database. Specifically, the server uses a database management system (e.g., MySQL) to insert the data into tables in the correct format.

[0119] Step 6:

[0120] The server launches a document generation module that automatically generates documents summarizing the regulatory risks associated with the company's expansion based on the research results. The input is regulatory and case information stored in the database, and the output is the generated document (PDF or Word format). Specifically, the server uses a template engine (e.g., Jinja2) to embed the collected data into a document template and convert it into the final document format.

[0121] Step 7:

[0122] The server encodes the generated data and sends it to the user's terminal using a secure communication protocol (e.g., SSL / TLS). The input is the generated document, and the output is the transmission to the user's terminal. Specifically, the server encodes the data and sends it to the user's terminal using a mail server.

[0123] Step 8:

[0124] The device saves the data received from the server and displays it to the user. The input is the data from the server, and the output is the display and saved file for the user. Specifically, the device opens the received email, saves the attachment to local storage, and displays it in a dedicated viewer application.

[0125] Step 9:

[0126] The user checks the documents on the terminal and downloads or prints them as necessary. The input is the displayed documents, and the output is the downloaded and printed documents. Specifically, the user clicks the download link, saves the file, and then prints the documents using a printer.

[0127] (Application example 1)

[0128] 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."

[0129] When a company expands overseas, it is extremely important to quickly and inexpensively investigate the legal risks of the host country or region and prepare documents for risk management. However, traditional methods require significant time and cost to investigate legal risks, and the accuracy of the documents often remains an issue. Furthermore, conducting international legal research requires specialized knowledge, which small and medium-sized enterprises find difficult to secure. To solve these issues, there is a need for a system that uses generative artificial intelligence to efficiently and accurately investigate legal risks and automatically generate documents. Legal compliance is particularly important in security services, and quickly understanding legal information in the host country is required as part of security measures.

[0130] 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.

[0131] In this invention, the server includes: means for providing an input form for users to enter information on countries, regions, and legal categories specified by the user; data transmission means for transmitting the input information to a cloud server; means for researching the input country, region, and legal category information using generative artificial intelligence and storing the acquired data in an internal database; means for generating a document summarizing legal risks related to the expansion from the research results and creating it as a PDF document; means for transmitting the generated PDF to the user's device; and means for the user to display, review, and download the PDF on their device. This allows companies to quickly and accurately grasp the legal risks of the country or region they are expanding into and automatically generate the document at low cost. It also facilitates risk assessment for legal compliance in security services, which can lead to smooth expansion and business operations.

[0132] "User" is a general term for an individual or organization that uses the system to specify the country or region to enter and the legal category to be investigated.

[0133] "Destination" refers to the country or region where the user intends to develop business or carry out activities.

[0134] A "legal category" is a classification that indicates the type of law or regulation related to a particular field.

[0135] "Generative artificial intelligence" refers to a general term for artificial intelligence technology that has the ability to learn large amounts of data and generate new information.

[0136] "Research" refers to the act of investigating and collecting specific information in detail.

[0137] "Materials" refers to documents and data compiled based on research results.

[0138] A "server" is a system that provides central functions of a computer system, such as data processing and storage.

[0139] "Transmission" refers to the act of sending data or information to another system or device.

[0140] "Terminal" refers to devices such as computers, smartphones, and tablets that are directly operated by users.

[0141] "Input Form" means an online form containing screens and fields for a user to enter information.

[0142] "Data transmission means" refers to the method or technology used to send input information to other systems.

[0143] "Research results" refers to the results of research obtained using generative artificial intelligence.

[0144] "Internal database" refers to a database used to store and manage data within the system.

[0145] "PDF format" is an abbreviation for Portable Document Format and refers to a specific document format standard.

[0146] "Downloading" refers to the act of importing data or materials from a server to a terminal.

[0147] The present invention provides a specific embodiment of a system that uses generative artificial intelligence to efficiently investigate and prepare documents regarding legal risks in the countries where a company is expanding. The detailed configuration and operating procedures of the system for implementing the invention are described below.

[0148] System Configuration

[0149] Hardware and software used

[0150] Hardware: Smartphone (iOS / Android), cloud server

[0151] software:

[0152] Frontend: React Native

[0153] Backend: Node.js, Express

[0154] Database: MongoDB

[0155] AI model: OpenAI GPT-4 API

[0156] PDF generation: pdf-lib

[0157] Program processing

[0158] 1. User input

[0159] Users enter the country or region they are expanding into and the legal category they are investigating into an input form on the smartphone app (React Native).

[0160] A typical example input would use keywords such as "America, GDPR, labor law."

[0161] 2. Data Transmission

[0162] The terminal (smartphone) sends the entered information to a cloud server (Node.js / Express).

[0163] When sending data, a format check is performed to prevent input errors.

[0164] 3. Research using generative AI models

[0165] The server launches generative artificial intelligence (OpenAI GPT-4 API) and researches the laws and precedents of the country or region specified by the user.

[0166] Typical research topics include information on the latest GDPR and labor laws in the United States.

[0167] 4. Saving your research results

[0168] The server stores the research results as structured data in an internal database (MongoDB).

[0169] The data to be stored includes the content of the law, the date of enforcement, related precedents, etc.

[0170] 5. Automatic generation of materials

[0171] The server starts a document generation module and generates a document summarizing the legal risks related to expansion from the research results.

[0172] The generated document will be converted to PDF format and will contain all the necessary information, such as the federal minimum wage of $7.25 per US labor law.

[0173] 6. Submission of Materials

[0174] The server sends the generated PDF to the user's smartphone.

[0175] Data is transmitted securely (HTTPS).

[0176] 7. Viewing and Downloading Materials

[0177] Users can view the PDF on their smartphone app and download or print it as needed.

[0178] Examples of concrete examples and prompts

[0179] Specific examples

[0180] For example, when a Japanese company expands into the US, the user can enter "USA, GDPR, labor law" into the app's input form. Based on this, the server will collect the latest information on the US GDPR and labor law, generate documents based on that information, and provide them to the user's smartphone.

[0181] Prompt Sentence Examples

[0182] As an example of text format, a user enters the following content into the app.

[0183] America

[0184] GDPR

[0185] Labor Law

[0186] This allows users to quickly and at low cost understand the legal risks in the country they are entering and efficiently obtain the necessary information. This system is particularly effective for security services, and supports users in quickly conducting risk assessments for legal compliance.

[0187] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0188] Step 1:

[0189] Users enter the country or region they wish to expand into and the legal category they wish to research into an input form on the smartphone app. The user inputs specific keywords such as "America, GDPR, labor law." Once the input is complete, the device generates data to send this information to a cloud server.

[0190] Input: Country or region of operation, legal category

[0191] Output: Data to send to the cloud server

[0192] Step 2:

[0193] The device sends the information entered by the user to the cloud server. When the data is sent, the format of the entered data is checked and validation is performed to prevent formatting errors and input mistakes. If the data is in the correct format, it is sent to the server.

[0194] Input: What the user types

[0195] Output: Data sent to the server

[0196] Step 3:

[0197] The server receives the incoming information and activates generative artificial intelligence (OpenAI GPT-4 API) to research the laws and precedents of the specified country or region. The server then references various reliable legal databases to collect the necessary information and compile it as structured data.

[0198] Input: User-specified information

[0199] Output: Structured data of research results

[0200] Step 4:

[0201] The server stores the acquired research results in an internal database (MongoDB). The database is structured to include detailed information such as the content of the law, its implementation date, and related legal precedents. When saving, the server checks the integrity of the data and generates the necessary indexes.

[0202] Input: Research results

[0203] Output: Legal data stored in an internal database

[0204] Step 5:

[0205] Based on the saved research results, the server launches a document generation module and automatically generates a PDF document summarizing the legal risks associated with the expansion. This document lists the main risk factors and points that differ from those in Japan.

[0206] Input: Data from the internal database

[0207] Output: Automatically generated PDF document

[0208] Step 6:

[0209] The server then sends the generated PDF file to the user's smartphone via a secure method (HTTPS), using encoding and security protocols to prevent external access.

[0210] Input: PDF format documents

[0211] Output: PDF file sent to the user's device

[0212] Step 7:

[0213] The terminal displays the received PDF file to the user, who can then review it and download or print it as needed. The terminal also provides functions for managing the content of the document appropriately.

[0214] Input: Received PDF file

[0215] Output: Viewable and downloadable PDF file

[0216] Through the above processing steps, users can quickly and at low cost understand the legal risks of the country they are entering and obtain the necessary documents, which will enable them to smoothly proceed with their company's entry plans.

[0217] 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.

[0218] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0219] Explanation of program processing

[0220] 1. User input

[0221] Using the input form on the device, users input the country or region they wish to expand into and the legal category they wish to research, for example, by entering keywords such as "America," "China," "labor law," and "tax law."

[0222] 2. Data transmission by the terminal

[0223] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0224] 3. Server-based research

[0225] The server runs a generative artificial intelligence (AI) to research the laws and precedents of the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0226] 4. Saving your research results

[0227] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0228] 5. Sentiment analysis using an emotion engine

[0229] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0230] 6. Automatically generate materials and adjust them based on emotions

[0231] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the research results based on the analysis results of the emotion engine. For example, if the user is anxious, it will prioritize presenting a summary of the risks.

[0232] 7. Submission of Materials

[0233] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0234] 8. Displaying and downloading materials via terminal

[0235] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0236] 9. Users can review the materials and download or print them as needed.

[0237] The user can check the displayed materials and download or print them as necessary, thereby obtaining specific information about the legal risks in the country where the user is entering.

[0238] Specific examples

[0239] For example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America," "China," "labor law," and "tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. If the emotion engine detects the user's impatience or anxiety, the server will prioritize generating a summary document that succinctly summarizes the risks. The user can review the document and use it to help make a decision about expanding into those countries.

[0240] This invention allows users to efficiently grasp the legal risks of the country they are entering at low cost, and enables them to obtain investigation results with speed and accuracy that could not be achieved with conventional methods. Furthermore, the introduction of an emotion engine enables flexible responses according to the user's psychological state, providing a better user experience.

[0241] The processing flow will be explained below.

[0242] Step 1:

[0243] The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, they enter keywords such as "America," "China," "labor law," and "tax law."

[0244] Step 2:

[0245] The device reviews the user's input and performs a quick check to ensure the format is correct: it checks whether the country name entered is spelled correctly and whether the legal category being investigated is included in an existing list.

[0246] Step 3:

[0247] The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0248] Step 4:

[0249] The server analyzes the information received from the user and passes it to the generative AI research module, which includes selecting a database of laws and regulations for the input country or region.

[0250] Step 5:

[0251] The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0252] Step 6:

[0253] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0254] Step 7:

[0255] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0256] Step 8:

[0257] The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The method of presenting the research results and their details are adjusted based on the analysis results of the emotion engine. For example, if the user is anxious, a summary version that briefly summarizes the risks can be presented first.

[0258] Step 9:

[0259] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0260] Step 10:

[0261] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0262] Step 11:

[0263] The user can check the displayed materials and download or print them as necessary, enabling them to obtain specific information about the legal risks in the country they are entering.

[0264] Example 2

[0265] 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."

[0266] When a company expands overseas, it is difficult to quickly and cost-effectively research and prepare documents to identify legal risks in the country of entry. Furthermore, there are limited ways to tailor the way information is provided and research results are presented to suit the user's psychological state, resulting in a poor user experience. To solve these problems, efficient and flexible research and response methods are required.

[0267] 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.

[0268] In this invention, the server includes means including an emotion engine for analyzing the user's emotional state, means for researching the laws and precedents of a designated country or region using generative artificial intelligence, and means for adjusting the presentation method of materials based on the analysis results of the emotion engine. This enables flexible and rapid legal risk investigation and information provision according to the user's psychological state.

[0269] "User" refers to an entity that uses the system to investigate legal risks in the country where the company is expanding.

[0270] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[0271] "Server" means a central processing unit that runs the generative artificial intelligence and emotion engine and performs research based on user input.

[0272] "Generative AI" is AI that has the ability to generate appropriate information based on specified data.

[0273] "Laws" includes laws and regulations enacted by national or local government agencies.

[0274] "Precedent" includes past decisions and rulings made by the court.

[0275] "Research Results" includes data on laws and precedents obtained by generative artificial intelligence through research.

[0276] The "materials" are documents generated based on research results that provide a detailed summary of the legal risks associated with expanding into the country.

[0277] An "emotion engine" is a software module that analyzes a user's emotional state and adjusts how information is presented.

[0278] "Reception" is the process by which a terminal receives data or materials sent from a server.

[0279] "Display" means displaying the data or materials received by the terminal on the screen in a format that can be viewed by the user.

[0280] "Downloading" is the process of saving material to your device so that it can be accessed offline.

[0281] "Printing" is the process of outputting materials onto paper media from a terminal using a printer.

[0282] A "simple format check" is a process that verifies whether the information entered by the user conforms to a specified format.

[0283] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0284] The system's program is structured as follows: First, the user is provided with an interface via their terminal to input the country or region they wish to enter and the legal category they wish to research. Once the user has entered the necessary information, it is sent to the server. The server then launches a generative artificial intelligence (e.g., OpenAI's GPT-4) to research the laws and precedents of the specified country or region. Multiple reliable legal databases (e.g., Westlaw, LexisNexis) are used as sources of research.

[0285] The research results are stored as structured data in an internal database, and the user's emotions are analyzed using an emotion engine (e.g., Microsoft Azure's Emotion API). For example, if the user is feeling anxious or impatient, the server will adjust the way the research results are presented based on that information, providing the information in a format that is easy for the user to understand. Finally, a document generation module automatically generates a document summarizing legal risks based on the research results, converts it to PDF or Word format, and sends it to the device. During this process, AES encryption technology is used to ensure communication security.

[0286] The terminal decodes the transmitted material and displays it to the user using viewer software, allowing the user to review the material in detail and download or print it as desired.

[0287] As a concrete example, consider the case where a Japanese company is considering expanding into the United States and China. The user enters keywords such as "America," "China," "labor law," and "tax law" into their device. The server uses this information to comprehensively research the specified laws and precedents and generates a document summarizing the legal risks in detail. If the emotion engine detects the user's impatience, the server generates a summary document that succinctly summarizes the risks and provides it to the user. Based on this document, the user can quickly obtain specific information to help them make a decision about expanding into the country.

[0288] An example prompt sentence would be entered as follows:

[0289] "A Japanese company is considering expanding into the United States and China. Please research the latest laws and precedents regarding American labor and tax laws, as well as Chinese labor and tax laws."

[0290] In this way, the present invention allows users to grasp the legal risks of the country they are entering efficiently and at low cost, and the emotion engine enables flexible responses according to the user's psychological state.

[0291] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0292] Step 1:

[0293] The user uses the input form on the device to input the country or region they are expanding into and the legal category they are investigating. Specifically, they enter keywords such as "America," "China," "Labor Law," and "Tax Law." This information is provided to the device as input. The input form checks the input in real time, checking for typos and formatting errors, and provides feedback to the user.

[0294] Step 2:

[0295] The terminal sends the information entered by the user to the server. A simple format check is performed to ensure the input conforms to the specified format. During this process, the input data is checked for errors, and if it is not in the correct format, an error message is returned to the user. If the format is correct, the input data is sent to the server.

[0296] Step 3:

[0297] The server launches a generative artificial intelligence (e.g., OpenAI's GPT-4) and researches the laws and precedents of the specified country or region based on the input data it receives. Specifically, the server first connects to the Internet and collects relevant information from multiple reliable legal databases (e.g., Westlaw, LexisNexis). The results of this research are stored in a database. Based on the keywords provided as input data, the generative AI searches for relevant information and generates research results as output.

[0298] Step 4:

[0299] The server stores the research results in an internal database, which is maintained in a structured data format and includes information such as the content of the law, its implementation date, relevant legal precedents, and citation sources. During this storage process, the data is indexed for efficient access.

[0300] Step 5:

[0301] The server launches an emotion engine (e.g., Microsoft Azure's Emotion API) and analyzes the user's emotions based on their input and usage. The analysis is performed based on input text, operation speed, click patterns, etc. If emotions such as impatience or anxiety are detected as a result of the analysis, that information is tagged and used for the next step.

[0302] Step 6:

[0303] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the documents based on the analysis results of the emotion engine. For example, if it detects that the user is anxious, it will prioritize generating a summary version that summarizes the information concisely. The generated documents are then converted into PDF or Word format.

[0304] Step 7:

[0305] The server encodes the generated data and sends it to the terminal. The encoding uses AES encryption technology to ensure the security of the communication, thereby protecting the privacy of user data.

[0306] Step 8:

[0307] The terminal decodes the material received from the server and displays it to the user using the appropriate viewer software, which allows the user to zoom, scroll, add annotations, etc., allowing the user to examine the material in detail.

[0308] Step 9:

[0309] Users can check the displayed materials and download or print them as needed. Download and print buttons are displayed on the device, allowing these operations to be performed with a single click. Downloaded materials can also be accessed offline.

[0310] (Application example 2)

[0311] 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."

[0312] In the past, companies needed to investigate legal risks when expanding overseas, which was time-consuming and costly. Furthermore, because information was provided uniformly without taking into account the user's emotional state, there was a problem in that the information provided could not be appropriate for the user's psychological state. In particular, for companies that provide security services, it is important to understand the legal risks of each country, and it is required that such investigations be carried out quickly and efficiently.

[0313] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to specify the country or region to enter and the legal category to be investigated, means for researching the laws and precedents of the specified country or region using generative artificial intelligence, means for automatically generating materials summarizing the legal risks related to the entry based on the research results, and means for analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of the materials based on that. This enables flexible legal risk investigation and provision of materials according to the user's psychological state, enabling quick and efficient information gathering and appropriate decision-making.

[0314] "Means for users to specify the country or region they wish to expand into and the categories of laws and regulations to be investigated" refers to an interface or input system that allows users to input or select the specific country or region and the type of laws and regulations they wish to investigate when a company expands overseas.

[0315] "Means for researching laws and precedents of designated countries or regions using generative artificial intelligence" refers to algorithms and software designed to use generative artificial intelligence (AI) to search for and collect laws and precedents related to countries or regions designated by users.

[0316] "Means for automatically generating documents summarizing legal risks related to expansion based on research results" refers to a system that automatically generates documents that systematically summarize legal risks related to a company's expansion destination based on information collected by AI.

[0317] "A means of analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of materials based on that" refers to a system that analyzes the user's input and behavior, identifies the emotions the user is feeling (anxiety, impatience, etc.), and changes the way research results and materials are displayed depending on those emotions.

[0318] This invention uses a system that combines generative artificial intelligence (AI) and an emotion engine to quickly and inexpensively investigate legal risks in the country of expansion and to assist in the creation of documents when a company expands overseas. An embodiment of this invention is described below.

[0319] System configuration

[0320] The system consists of the following major components:

[0321] 1. User Input Interface:

[0322] Users use an input form on their device (smartphone, tablet, PC, etc.) to input the country or region they are entering and the legal category they are investigating. This specifies the legal information of the country or region they are entering into the system.

[0323] 2. Data transmission module:

[0324] The information entered by the user is sent from the terminal to the server, where a simple format check is performed to prevent input errors.

[0325] 3. Generative Artificial Intelligence (AI) Module:

[0326] The AI ​​module installed on the server researches the laws and relevant precedents of the country or region specified by the user, collecting the latest information from reliable databases and websites.

[0327] 4. Research Results Storage Module:

[0328] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0329] 5. Emotion Engine Module:

[0330] The emotion engine analyzes the user's emotions based on their input and system usage, detecting and responding to emotions such as anxiety and impatience.

[0331] 6. Document generation module:

[0332] Based on the research results and the analysis results of the emotion engine, the server automatically creates a document summarizing the legal risks associated with the move in. If the user feels anxious, the server adjusts the details of the document and the way it is presented, for example, by creating a summary version of the document that briefly summarizes the risks, depending on the user's emotions.

[0333] 7. Data transmission and display module:

[0334] The generated documents are sent to the terminal in PDF or Word format and displayed on the terminal, where the user can review them and download or print them as needed.

[0335] Processing Description

[0336] In this system, users first enter the country or region they wish to enter and the legal category into an input form on their device. This information is sent to the server, and the generative AI researches the laws and related precedents based on the specified conditions. The research results are stored in an internal database.

[0337] Next, the emotion engine analyzes the user's emotions based on their input and system usage, and generates documents that reflect the user's psychological state. Based on the research results and the emotion engine's analysis, the server automatically generates documents summarizing the legal risks associated with the expansion and sends them to the user's device. The user can review the documents and download or print them as needed.

[0338] Specific examples

[0339] For example, if a Japanese company providing security services is looking to expand into the US, the user would input "USA" and "security law." Based on this information, the server would research the latest US security regulations and generate materials. If the emotion engine detects the user's impatience, it will prioritize generating a concise summary of the information, providing information appropriate to the user's psychological state.

[0340] Example of an input prompt for a generative AI model:

[0341] Research the latest in international security regulations.

[0342] This invention allows companies to quickly and efficiently grasp the legal risks of the country they are entering, and to obtain investigation results with speed and accuracy that were not possible with conventional methods.In addition, the introduction of an emotion engine enables flexible responses based on the user's psychological state, providing a better user experience.

[0343] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0344] Step 1:

[0345] The user enters the country or region they are entering and the legal category they are investigating into an input form on their device. For example, input contents could be "America" ​​and "Security Law." The input data is sent to the system. This input includes information specified by the user.

[0346] Step 2:

[0347] The device sends the information entered by the user to the server. At this time, a simple format check is performed to ensure the input is valid. After confirming that the input is in the correct format, the information is forwarded to the server. Input: Country and legal category entered by the user. Output: Data sent after validity check.

[0348] Step 3:

[0349] The server uses a generative AI model to research the laws and related precedents of the specified country or region. The server searches for the latest information from multiple reliable databases and related websites to collect the necessary data. Input: Country and legal category specified by the user. Output: Research data.

[0350] Step 4:

[0351] The server stores the research results in an internal database. The stored data includes the content of the law, the date of enforcement, and related legal precedents. This data is used for subsequent processing. Input: Researched data, Output: Research results stored in the database.

[0352] Step 5:

[0353] The emotion engine analyzes the user's emotions based on the user's input and system usage. The emotion engine detects emotions such as impatience or anxiety, and performs further processing based on the results. Input: User input data, Output: Analyzed emotional state.

[0354] Step 6:

[0355] The server uses a document generation module to automatically generate documents based on the research results and the analysis results of the emotion engine. The format and details of the documents are adjusted based on the emotion analysis results. For example, if the user is feeling anxious, a summary document that briefly summarizes the risks will be created first. Input: Research results and emotion analysis results, Output: Automatically generated documents.

[0356] Step 7:

[0357] The server converts the generated documents into PDF or Word format and sends them to the terminal. The documents are encoded to ensure communication security. Input: Generated documents, Output: Sent document file.

[0358] Step 8:

[0359] The terminal decodes the data received from the server and displays it to the user. The user can check the data and download or print it as needed. Input: Data file sent from the server. Output: Data that can be displayed and downloaded.

[0360] Examples:

[0361] For example, if a Japanese company providing security services is looking to expand into the US, the user would enter "America" ​​and "security law," which would be step 1. In step 2, this input data is sent to the server. In step 3, the server uses a generative AI model to collect the latest information on US security laws. In step 4, this information is stored in an internal database. In step 5, an emotion engine analyzes emotions from the user's input, and in step 6, a document is automatically generated based on the results. In step 7, the document is sent to the device, and in step 8, the user reviews and downloads the document.

[0362] 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.

[0363] 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.

[0364] 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.

[0365] [Second embodiment]

[0366] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0367] 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.

[0368] 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).

[0369] 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.

[0370] 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.

[0371] 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).

[0372] 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.

[0373] 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.

[0374] 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.

[0375] 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.

[0376] 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.

[0377] 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."

[0378] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in the country or region a company is expanding into when it is expanding overseas. This system includes a means for the user to specify the country or region to expand into and the legal category to be investigated, a means for the server to research the specified laws and precedents using generative artificial intelligence, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal.

[0379] Explanation of program processing

[0380] 1. User input

[0381] Using the input form on the device, users input the country or region they wish to enter and the legal category they wish to research, for example, by entering keywords such as "America, China, labor law, tax law."

[0382] 2. Data transmission by the terminal

[0383] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0384] 3. Server-based research

[0385] The server runs a generative artificial intelligence (AI) to research the laws and legal precedents of a specified country or region, for example, by retrieving information on the latest labor and tax laws in the United States from government databases and reliable legal databases.

[0386] 4. Saving your research results

[0387] The server stores the research results in an internal database, storing information such as the content of the law, its enforcement date, and related legal precedents as structured data.

[0388] 5. Automatic generation of materials

[0389] The server launches a document generation module, which automatically generates a document summarizing the legal risks associated with the expansion based on the research results. The document includes specific details about the main points, risks, and differences between Japan and the US. For example, it includes information such as the US work week limit of 40 hours and the federal minimum wage of $7.25.

[0390] 6. Submission of Materials

[0391] The server converts the generated documents into PDF or Word format and sends them to the device. The data is sent in an encoded format to ensure secure communication.

[0392] 7. Displaying and downloading materials via terminal

[0393] The terminal displays the materials received from the server so that the user can check them, and the user can download or print them as necessary.

[0394] Specific examples

[0395] As a concrete example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America, China, labor law, tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. The user can review the document and use it to help them make a decision about expanding into the country.

[0396] The present invention enables users to grasp the legal risks of the country in which they are entering at low cost and efficiently, and to obtain investigation results with speed and accuracy that could not be achieved with conventional methods.

[0397] The processing flow will be explained below.

[0398] Step 1: The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, the user might enter keywords such as "America," "China," "Labor Law," or "Tax Law."

[0399] Step 2: The device reviews the user's input and performs a quick check to ensure there are no formatting issues, such as whether the entered country name is spelled correctly or whether the legal category being investigated is included in an existing list.

[0400] Step 3: The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0401] Step 4: The server analyzes the information received from the user and passes it to the generative AI research module. This analysis includes selecting a database of laws and regulations for the input country or region.

[0402] Step 5: The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region. For example, it collects the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0403] Step 6: The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0404] Step 7: The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. For example, under US labor law, this includes information such as "working hours limited to 40 hours per week" and "federal minimum wage is $7.25."

[0405] Step 8: The server converts the generated document into PDF or Word format and sends it to the device in an encoded format, ensuring secure communication.

[0406] Step 9: The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to view the data.

[0407] Step 10: The user checks the displayed materials and downloads or prints them as necessary. This allows the user to obtain specific information about the legal risks in the country in which they are entering.

[0408] Example 1

[0409] 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."

[0410] When a company expands overseas, it is important to investigate the legal risks of the country it is expanding into quickly and at low cost. However, traditional methods require a lot of time and money, placing a heavy burden on small and medium-sized enterprises. In addition, there was a problem in that there was no system that could quickly collect reliable information and automatically generate documents based on that information.

[0411] 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.

[0412] In this invention, the server includes means for searching for regulations and case studies in a designated area using generative artificial intelligence, means for automatically generating materials summarizing regulatory risks related to expansion based on the results of the search, and means for transmitting the generated materials to the user's information processing device, thereby enabling companies to efficiently understand the legal risks of their expansion destinations at low cost.

[0413] A "user" is an individual or entity that uses the system to specify the geographical area in which to operate and the regulatory category to be investigated.

[0414] "Region" refers to the specific country or region in which the company plans to expand.

[0415] "Regulatory category" refers to the classification of laws and regulations (e.g., labor laws, tax laws, etc.) in the country in which a company wishes to enter and investigate.

[0416] The term "means" refers to a method or apparatus for realizing a specific function. In this context, it refers to a device or system part having a specific function such as input, transmission, or display.

[0417] "Generative AI" refers to an AI model that can automatically generate text in response to a given prompt.

[0418] "Regulation" means any law, ordinance or rule enacted by a government or related authority.

[0419] "Case studies" refer to actual legal events in Europe, such as past precedents and examples.

[0420] "Exploration" refers to the act of searching for and collecting specific information based on specified criteria.

[0421] "Materials" refers to reports and documents generated based on research results.

[0422] The term "information processing device" refers to a device such as a computer or smartphone used by a user.

[0423] A "database" refers to a system for systematically organizing and storing collected information.

[0424] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in a country where a company is expanding overseas. This system includes a means for a user to specify the region to expand into and the regulatory categories to be investigated, a means for a server to use generative artificial intelligence to search for the specified regulations and examples, a means for automatically generating documents summarizing the regulatory risks related to the expansion based on the results of the search, a means for transmitting the generated documents to the user's information processing device, and a means for displaying the documents received by the information processing device.

[0425] Specifically, the system is constructed using the following hardware and software.

[0426] Hardware and software used

[0427] 1. Terminal

[0428] A terminal is an information processing device that allows users to input information and receive and display materials from the server. Examples include PCs, smartphones, and tablets. A web browser is installed on the terminal, and users input information through an input form.

[0429] 2. Server

[0430] The server requires high-performance hardware to run generative artificial intelligence (e.g., GPT-4). The server also has an internal database (e.g., MySQL) and template engine (e.g., Jinja2) for generating materials and storing data.

[0431] System Operation

[0432] 1. Enter information

[0433] Using the device's web browser, the user enters the region of the country they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, the user enters "America, China, Labor Law, Tax Law" and clicks the submit button.

[0434] 2. Data transmission and check

[0435] The terminal performs a simple format check of the entered information, and if there are no errors, sends it to the server. At this time, it checks that the entered data is in the correct format, and if necessary, displays an error message to prompt the user to re-enter the data.

[0436] 3. Conduct research

[0437] The server runs generative artificial intelligence to explore regulations and cases in a given region, for example, gathering information on the latest US labor and tax laws from a reliable database.

[0438] 4. Saving results and generating documents

[0439] The server stores the acquired information as structured data in an internal database, and then uses a document generation module to automatically generate documents summarizing the regulatory risks associated with the company's expansion. Specifically, a template engine (e.g., Jinja2) is used to insert the collected data into a document and convert it into PDF or Word format.

[0440] 5. Submitting and Displaying Materials

[0441] The server sends the generated documents to the user's terminal, which receives and displays them. The user can then check the documents on the terminal and download or print them as needed.

[0442] Specific examples

[0443] As a concrete example, consider the case of a Japanese company considering expanding into the United States and China. The user enters "United States, China, labor law, tax law" into an input form on their device and requests a survey. In response, the server collects the latest information on labor and tax laws in both countries, generates a document detailing the regulatory risks in each country, and sends it to the user's device. The user then reviews the document and uses it to help them make a decision about expanding into the country.

[0444] Prompt Sentence Examples

[0445] Below are some examples of prompts for generative artificial intelligence:

[0446] Please research the US, China, labor laws, and tax laws and create a document outlining the regulatory risks for each country. Specifically, please provide detailed data including the latest information on labor and tax laws, enforcement dates, and related cases.

[0447] Using this prompt, the generative AI can research detailed regulatory risks based on the specified region and regulatory category, and efficiently create the necessary materials.

[0448] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0449] Step 1:

[0450] Using the web browser on their device, the user enters the region they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, they enter "America, China, Labor Law, Tax Law" and click the submit button. The data entered is the region name and regulatory category. Specifically, the user enters keywords using the input form and then submits the form.

[0451] Step 2:

[0452] The terminal performs a simple format check on the information entered by the user to ensure there are no errors. This is a process that checks whether the input data is in the correct format. The input is the region name and regulatory category entered by the user, and the output is the checked data. Specifically, the terminal validates the input information, and if any invalid input is found, it displays an error message and prompts the user to re-enter the information.

[0453] Step 3:

[0454] The terminal sends the checked data to the server. The input is the checked region name and regulatory category data, and the output is a request including this data that is sent to the server. Specifically, the terminal sends an HTTP request to the server.

[0455] Step 4:

[0456] The server receives the request and launches a generative AI to initiate a search process based on the specified region and regulatory category. The input is the received region name and regulatory category, and the output is regulatory and case information. Specifically, the server provides prompts to the generative AI model (e.g., GPT-4) and collects relevant data.

[0457] Step 5:

[0458] The server stores the information obtained from the generative artificial intelligence in an internal database. The input is the collected regulatory and case information, and the output is structured data stored in the database. Specifically, the server uses a database management system (e.g., MySQL) to insert the data into tables in the correct format.

[0459] Step 6:

[0460] The server launches a document generation module that automatically generates documents summarizing the regulatory risks associated with the company's expansion based on the research results. The input is regulatory and case information stored in the database, and the output is the generated document (PDF or Word format). Specifically, the server uses a template engine (e.g., Jinja2) to embed the collected data into a document template and convert it into the final document format.

[0461] Step 7:

[0462] The server encodes the generated data and sends it to the user's terminal using a secure communication protocol (e.g., SSL / TLS). The input is the generated document, and the output is the transmission to the user's terminal. Specifically, the server encodes the data and sends it to the user's terminal using a mail server.

[0463] Step 8:

[0464] The device saves the data received from the server and displays it to the user. The input is the data from the server, and the output is the display and saved file for the user. Specifically, the device opens the received email, saves the attachment to local storage, and displays it in a dedicated viewer application.

[0465] Step 9:

[0466] The user checks the documents on the terminal and downloads or prints them as necessary. The input is the displayed documents, and the output is the downloaded and printed documents. Specifically, the user clicks the download link, saves the file, and then prints the documents using a printer.

[0467] (Application example 1)

[0468] 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."

[0469] When a company expands overseas, it is extremely important to quickly and inexpensively investigate the legal risks of the host country or region and prepare documents for risk management. However, traditional methods require significant time and cost to investigate legal risks, and the accuracy of the documents often remains an issue. Furthermore, conducting international legal research requires specialized knowledge, which small and medium-sized enterprises find difficult to secure. To solve these issues, there is a need for a system that uses generative artificial intelligence to efficiently and accurately investigate legal risks and automatically generate documents. Legal compliance is particularly important in security services, and quickly understanding legal information in the host country is required as part of security measures.

[0470] 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.

[0471] In this invention, the server includes: means for providing an input form for users to enter information on countries, regions, and legal categories specified by the user; data transmission means for transmitting the input information to a cloud server; means for researching the input country, region, and legal category information using generative artificial intelligence and storing the acquired data in an internal database; means for generating a document summarizing legal risks related to the expansion from the research results and creating it as a PDF document; means for transmitting the generated PDF to the user's device; and means for the user to display, review, and download the PDF on their device. This allows companies to quickly and accurately grasp the legal risks of the country or region they are expanding into and automatically generate the document at low cost. It also facilitates risk assessment for legal compliance in security services, which can lead to smooth expansion and business operations.

[0472] "User" is a general term for an individual or organization that uses the system to specify the country or region to enter and the legal category to be investigated.

[0473] "Destination" refers to the country or region where the user intends to develop business or carry out activities.

[0474] A "legal category" is a classification that indicates the type of law or regulation related to a particular field.

[0475] "Generative artificial intelligence" refers to a general term for artificial intelligence technology that has the ability to learn large amounts of data and generate new information.

[0476] "Research" refers to the act of investigating and collecting specific information in detail.

[0477] "Materials" refers to documents and data compiled based on research results.

[0478] A "server" is a system that provides central functions of a computer system, such as data processing and storage.

[0479] "Transmission" refers to the act of sending data or information to another system or device.

[0480] "Terminal" refers to devices such as computers, smartphones, and tablets that are directly operated by users.

[0481] "Input Form" means an online form containing screens and fields for a user to enter information.

[0482] "Data transmission means" refers to the method or technology used to send input information to other systems.

[0483] "Research results" refers to the results of research obtained using generative artificial intelligence.

[0484] "Internal database" refers to a database used to store and manage data within the system.

[0485] "PDF format" is an abbreviation for Portable Document Format and refers to a specific document format standard.

[0486] "Downloading" refers to the act of importing data or materials from a server to a terminal.

[0487] The present invention provides a specific embodiment of a system that uses generative artificial intelligence to efficiently investigate and prepare documents regarding legal risks in the countries where a company is expanding. The detailed configuration and operating procedures of the system for implementing the invention are described below.

[0488] System Configuration

[0489] Hardware and software used

[0490] Hardware: Smartphone (iOS / Android), cloud server

[0491] software:

[0492] Frontend: React Native

[0493] Backend: Node.js, Express

[0494] Database: MongoDB

[0495] AI model: OpenAI GPT-4 API

[0496] PDF generation: pdf-lib

[0497] Program processing

[0498] 1. User input

[0499] Users enter the country or region they are expanding into and the legal category they are investigating into an input form on the smartphone app (React Native).

[0500] A typical example input would use keywords such as "America, GDPR, labor law."

[0501] 2. Data Transmission

[0502] The terminal (smartphone) sends the entered information to a cloud server (Node.js / Express).

[0503] When sending data, a format check is performed to prevent input errors.

[0504] 3. Research using generative AI models

[0505] The server launches generative artificial intelligence (OpenAI GPT-4 API) and researches the laws and precedents of the country or region specified by the user.

[0506] Typical research topics include information on the latest GDPR and labor laws in the United States.

[0507] 4. Saving your research results

[0508] The server stores the research results as structured data in an internal database (MongoDB).

[0509] The data to be stored includes the content of the law, the date of enforcement, related precedents, etc.

[0510] 5. Automatic generation of materials

[0511] The server starts a document generation module and generates a document summarizing the legal risks related to expansion from the research results.

[0512] The generated document will be converted to PDF format and will contain all the necessary information, such as the federal minimum wage of $7.25 per US labor law.

[0513] 6. Submission of Materials

[0514] The server sends the generated PDF to the user's smartphone.

[0515] Data is transmitted securely (HTTPS).

[0516] 7. Viewing and Downloading Materials

[0517] Users can view the PDF on their smartphone app and download or print it as needed.

[0518] Examples of concrete examples and prompts

[0519] Specific examples

[0520] For example, when a Japanese company expands into the US, the user can enter "USA, GDPR, labor law" into the app's input form. Based on this, the server will collect the latest information on the US GDPR and labor law, generate documents based on that information, and provide them to the user's smartphone.

[0521] Prompt Sentence Examples

[0522] As an example of text format, a user enters the following content into the app.

[0523] America

[0524] GDPR

[0525] Labor Law

[0526] This allows users to quickly and at low cost understand the legal risks in the country they are entering and efficiently obtain the necessary information. This system is particularly effective for security services, and supports users in quickly conducting risk assessments for legal compliance.

[0527] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0528] Step 1:

[0529] Users enter the country or region they wish to expand into and the legal category they wish to research into an input form on the smartphone app. The user inputs specific keywords such as "America, GDPR, labor law." Once the input is complete, the device generates data to send this information to a cloud server.

[0530] Input: Country or region of operation, legal category

[0531] Output: Data to send to the cloud server

[0532] Step 2:

[0533] The device sends the information entered by the user to the cloud server. When the data is sent, the format of the entered data is checked and validation is performed to prevent formatting errors and input mistakes. If the data is in the correct format, it is sent to the server.

[0534] Input: What the user types

[0535] Output: Data sent to the server

[0536] Step 3:

[0537] The server receives the incoming information and activates generative artificial intelligence (OpenAI GPT-4 API) to research the laws and precedents of the specified country or region. The server then references various reliable legal databases to collect the necessary information and compile it as structured data.

[0538] Input: User-specified information

[0539] Output: Structured data of research results

[0540] Step 4:

[0541] The server stores the acquired research results in an internal database (MongoDB). The database is structured to include detailed information such as the content of the law, its implementation date, and related legal precedents. When saving, the server checks the integrity of the data and generates the necessary indexes.

[0542] Input: Research results

[0543] Output: Legal data stored in an internal database

[0544] Step 5:

[0545] Based on the saved research results, the server launches a document generation module and automatically generates a PDF document summarizing the legal risks associated with the expansion. This document lists the main risk factors and points that differ from those in Japan.

[0546] Input: Data from the internal database

[0547] Output: Automatically generated PDF document

[0548] Step 6:

[0549] The server then sends the generated PDF file to the user's smartphone via a secure method (HTTPS), using encoding and security protocols to prevent external access.

[0550] Input: PDF format documents

[0551] Output: PDF file sent to the user's device

[0552] Step 7:

[0553] The terminal displays the received PDF file to the user, who can then review it and download or print it as needed. The terminal also provides functions for managing the content of the document appropriately.

[0554] Input: Received PDF file

[0555] Output: Viewable and downloadable PDF file

[0556] Through the above processing steps, users can quickly and at low cost understand the legal risks of the country they are entering and obtain the necessary documents, which will enable them to smoothly proceed with their company's entry plans.

[0557] 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.

[0558] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0559] Explanation of program processing

[0560] 1. User input

[0561] Using the input form on the device, users input the country or region they wish to expand into and the legal category they wish to research, for example, by entering keywords such as "America," "China," "labor law," and "tax law."

[0562] 2. Data transmission by the terminal

[0563] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0564] 3. Server-based research

[0565] The server runs a generative artificial intelligence (AI) to research the laws and precedents of the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0566] 4. Saving your research results

[0567] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0568] 5. Sentiment analysis using an emotion engine

[0569] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0570] 6. Automatically generate materials and adjust them based on emotions

[0571] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the research results based on the analysis results of the emotion engine. For example, if the user is anxious, it will prioritize presenting a summary of the risks.

[0572] 7. Submission of Materials

[0573] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0574] 8. Displaying and downloading materials via terminal

[0575] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0576] 9. Users can review the materials and download or print them as needed.

[0577] The user can check the displayed materials and download or print them as necessary, thereby obtaining specific information about the legal risks in the country where the user is entering.

[0578] Specific examples

[0579] For example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America," "China," "labor law," and "tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. If the emotion engine detects the user's impatience or anxiety, the server will prioritize generating a summary document that succinctly summarizes the risks. The user can review the document and use it to help make a decision about expanding into those countries.

[0580] This invention allows users to efficiently grasp the legal risks of the country they are entering at low cost, and enables them to obtain investigation results with speed and accuracy that could not be achieved with conventional methods. Furthermore, the introduction of an emotion engine enables flexible responses according to the user's psychological state, providing a better user experience.

[0581] The processing flow will be explained below.

[0582] Step 1:

[0583] The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, they enter keywords such as "America," "China," "labor law," and "tax law."

[0584] Step 2:

[0585] The device reviews the user's input and performs a quick check to ensure the format is correct: it checks whether the country name entered is spelled correctly and whether the legal category being investigated is included in an existing list.

[0586] Step 3:

[0587] The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0588] Step 4:

[0589] The server analyzes the information received from the user and passes it to the generative AI research module, which includes selecting a database of laws and regulations for the input country or region.

[0590] Step 5:

[0591] The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0592] Step 6:

[0593] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0594] Step 7:

[0595] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0596] Step 8:

[0597] The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The method of presenting the research results and their details are adjusted based on the analysis results of the emotion engine. For example, if the user is anxious, a summary version that briefly summarizes the risks can be presented first.

[0598] Step 9:

[0599] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0600] Step 10:

[0601] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0602] Step 11:

[0603] The user can check the displayed materials and download or print them as necessary, enabling them to obtain specific information about the legal risks in the country they are entering.

[0604] Example 2

[0605] 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."

[0606] When a company expands overseas, it is difficult to quickly and cost-effectively research and prepare documents to identify legal risks in the country of entry. Furthermore, there are limited ways to tailor the way information is provided and research results are presented to suit the user's psychological state, resulting in a poor user experience. To solve these problems, efficient and flexible research and response methods are required.

[0607] 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.

[0608] In this invention, the server includes means including an emotion engine for analyzing the user's emotional state, means for researching the laws and precedents of a designated country or region using generative artificial intelligence, and means for adjusting the presentation method of materials based on the analysis results of the emotion engine. This enables flexible and rapid legal risk investigation and information provision according to the user's psychological state.

[0609] "User" refers to an entity that uses the system to investigate legal risks in the country where the company is expanding.

[0610] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[0611] "Server" means a central processing unit that runs the generative artificial intelligence and emotion engine and performs research based on user input.

[0612] "Generative AI" is AI that has the ability to generate appropriate information based on specified data.

[0613] "Laws" includes laws and regulations enacted by national or local government agencies.

[0614] "Precedent" includes past decisions and rulings made by the court.

[0615] "Research Results" includes data on laws and precedents obtained by generative artificial intelligence through research.

[0616] The "materials" are documents generated based on research results that provide a detailed summary of the legal risks associated with expanding into the country.

[0617] An "emotion engine" is a software module that analyzes a user's emotional state and adjusts how information is presented.

[0618] "Reception" is the process by which a terminal receives data or materials sent from a server.

[0619] "Display" means displaying the data or materials received by the terminal on the screen in a format that can be viewed by the user.

[0620] "Downloading" is the process of saving material to your device so that it can be accessed offline.

[0621] "Printing" is the process of outputting materials onto paper media from a terminal using a printer.

[0622] A "simple format check" is a process that verifies whether the information entered by the user conforms to a specified format.

[0623] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0624] The system's program is structured as follows: First, the user is provided with an interface via their terminal to input the country or region they wish to enter and the legal category they wish to research. Once the user has entered the necessary information, it is sent to the server. The server then launches a generative artificial intelligence (e.g., OpenAI's GPT-4) to research the laws and precedents of the specified country or region. Multiple reliable legal databases (e.g., Westlaw, LexisNexis) are used as sources of research.

[0625] The research results are stored as structured data in an internal database, and the user's emotions are analyzed using an emotion engine (e.g., Microsoft Azure's Emotion API). For example, if the user is feeling anxious or impatient, the server will adjust the way the research results are presented based on that information, providing the information in a format that is easy for the user to understand. Finally, a document generation module automatically generates a document summarizing legal risks based on the research results, converts it to PDF or Word format, and sends it to the device. During this process, AES encryption technology is used to ensure communication security.

[0626] The terminal decodes the transmitted material and displays it to the user using viewer software, allowing the user to review the material in detail and download or print it as desired.

[0627] As a concrete example, consider the case where a Japanese company is considering expanding into the United States and China. The user enters keywords such as "America," "China," "labor law," and "tax law" into their device. The server uses this information to comprehensively research the specified laws and precedents and generates a document summarizing the legal risks in detail. If the emotion engine detects the user's impatience, the server generates a summary document that succinctly summarizes the risks and provides it to the user. Based on this document, the user can quickly obtain specific information to help them make a decision about expanding into the country.

[0628] An example prompt sentence would be entered as follows:

[0629] "A Japanese company is considering expanding into the United States and China. Please research the latest laws and precedents regarding American labor and tax laws, as well as Chinese labor and tax laws."

[0630] In this way, the present invention allows users to grasp the legal risks of the country they are entering efficiently and at low cost, and the emotion engine enables flexible responses according to the user's psychological state.

[0631] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0632] Step 1:

[0633] The user uses the input form on the device to input the country or region they are expanding into and the legal category they are investigating. Specifically, they enter keywords such as "America," "China," "Labor Law," and "Tax Law." This information is provided to the device as input. The input form checks the input in real time, checking for typos and formatting errors, and provides feedback to the user.

[0634] Step 2:

[0635] The terminal sends the information entered by the user to the server. A simple format check is performed to ensure the input conforms to the specified format. During this process, the input data is checked for errors, and if it is not in the correct format, an error message is returned to the user. If the format is correct, the input data is sent to the server.

[0636] Step 3:

[0637] The server launches a generative artificial intelligence (e.g., OpenAI's GPT-4) and researches the laws and precedents of the specified country or region based on the input data it receives. Specifically, the server first connects to the Internet and collects relevant information from multiple reliable legal databases (e.g., Westlaw, LexisNexis). The results of this research are stored in a database. Based on the keywords provided as input data, the generative AI searches for relevant information and generates research results as output.

[0638] Step 4:

[0639] The server stores the research results in an internal database, which is maintained in a structured data format and includes information such as the content of the law, its implementation date, relevant legal precedents, and citation sources. During this storage process, the data is indexed for efficient access.

[0640] Step 5:

[0641] The server launches an emotion engine (e.g., Microsoft Azure's Emotion API) and analyzes the user's emotions based on their input and usage. The analysis is performed based on input text, operation speed, click patterns, etc. If emotions such as impatience or anxiety are detected as a result of the analysis, that information is tagged and used for the next step.

[0642] Step 6:

[0643] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the documents based on the analysis results of the emotion engine. For example, if it detects that the user is anxious, it will prioritize generating a summary version that summarizes the information concisely. The generated documents are then converted into PDF or Word format.

[0644] Step 7:

[0645] The server encodes the generated data and sends it to the terminal. The encoding uses AES encryption technology to ensure the security of the communication, thereby protecting the privacy of user data.

[0646] Step 8:

[0647] The terminal decodes the material received from the server and displays it to the user using the appropriate viewer software, which allows the user to zoom, scroll, add annotations, etc., allowing the user to examine the material in detail.

[0648] Step 9:

[0649] Users can check the displayed materials and download or print them as needed. Download and print buttons are displayed on the device, allowing these operations to be performed with a single click. Downloaded materials can also be accessed offline.

[0650] (Application example 2)

[0651] 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."

[0652] In the past, companies needed to investigate legal risks when expanding overseas, which was time-consuming and costly. Furthermore, because information was provided uniformly without taking into account the user's emotional state, there was a problem in that the information provided could not be appropriate for the user's psychological state. In particular, for companies that provide security services, it is important to understand the legal risks of each country, and it is required that such investigations be carried out quickly and efficiently.

[0653] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to specify the country or region to enter and the legal category to be investigated, means for researching the laws and precedents of the specified country or region using generative artificial intelligence, means for automatically generating materials summarizing the legal risks related to the entry based on the research results, and means for analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of the materials based on that. This enables flexible legal risk investigation and provision of materials according to the user's psychological state, enabling quick and efficient information gathering and appropriate decision-making.

[0654] "Means for users to specify the country or region they wish to expand into and the categories of laws and regulations to be investigated" refers to an interface or input system that allows users to input or select the specific country or region and the type of laws and regulations they wish to investigate when a company expands overseas.

[0655] "Means for researching laws and precedents of designated countries or regions using generative artificial intelligence" refers to algorithms and software designed to use generative artificial intelligence (AI) to search for and collect laws and precedents related to countries or regions designated by users.

[0656] "Means for automatically generating documents summarizing legal risks related to expansion based on research results" refers to a system that automatically generates documents that systematically summarize legal risks related to a company's expansion destination based on information collected by AI.

[0657] "A means of analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of materials based on that" refers to a system that analyzes the user's input and behavior, identifies the emotions the user is feeling (anxiety, impatience, etc.), and changes the way research results and materials are displayed depending on those emotions.

[0658] This invention uses a system that combines generative artificial intelligence (AI) and an emotion engine to quickly and inexpensively investigate legal risks in the country of expansion and to assist in the creation of documents when a company expands overseas. An embodiment of this invention is described below.

[0659] System configuration

[0660] The system consists of the following major components:

[0661] 1. User Input Interface:

[0662] Users use an input form on their device (smartphone, tablet, PC, etc.) to input the country or region they are entering and the legal category they are investigating. This specifies the legal information of the country or region they are entering into the system.

[0663] 2. Data transmission module:

[0664] The information entered by the user is sent from the terminal to the server, where a simple format check is performed to prevent input errors.

[0665] 3. Generative Artificial Intelligence (AI) Module:

[0666] The AI ​​module installed on the server researches the laws and relevant precedents of the country or region specified by the user, collecting the latest information from reliable databases and websites.

[0667] 4. Research Results Storage Module:

[0668] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0669] 5. Emotion Engine Module:

[0670] The emotion engine analyzes the user's emotions based on their input and system usage, detecting and responding to emotions such as anxiety and impatience.

[0671] 6. Document generation module:

[0672] Based on the research results and the analysis results of the emotion engine, the server automatically creates a document summarizing the legal risks associated with the move in. If the user feels anxious, the server adjusts the details of the document and the way it is presented, for example, by creating a summary version of the document that briefly summarizes the risks, depending on the user's emotions.

[0673] 7. Data transmission and display module:

[0674] The generated documents are sent to the terminal in PDF or Word format and displayed on the terminal, where the user can review them and download or print them as needed.

[0675] Processing Description

[0676] In this system, users first enter the country or region they wish to enter and the legal category into an input form on their device. This information is sent to the server, and the generative AI researches the laws and related precedents based on the specified conditions. The research results are stored in an internal database.

[0677] Next, the emotion engine analyzes the user's emotions based on their input and system usage, and generates documents that reflect the user's psychological state. Based on the research results and the emotion engine's analysis, the server automatically generates documents summarizing the legal risks associated with the expansion and sends them to the user's device. The user can review the documents and download or print them as needed.

[0678] Specific examples

[0679] For example, if a Japanese company providing security services is looking to expand into the US, the user would input "USA" and "security law." Based on this information, the server would research the latest US security regulations and generate materials. If the emotion engine detects the user's impatience, it will prioritize generating a concise summary of the information, providing information appropriate to the user's psychological state.

[0680] Example of an input prompt for a generative AI model:

[0681] Research the latest in international security regulations.

[0682] This invention allows companies to quickly and efficiently grasp the legal risks of the country they are entering, and to obtain investigation results with speed and accuracy that were not possible with conventional methods.In addition, the introduction of an emotion engine enables flexible responses based on the user's psychological state, providing a better user experience.

[0683] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0684] Step 1:

[0685] The user enters the country or region they are entering and the legal category they are investigating into an input form on their device. For example, input contents could be "America" ​​and "Security Law." The input data is sent to the system. This input includes information specified by the user.

[0686] Step 2:

[0687] The device sends the information entered by the user to the server. At this time, a simple format check is performed to ensure the input is valid. After confirming that the input is in the correct format, the information is forwarded to the server. Input: Country and legal category entered by the user. Output: Data sent after validity check.

[0688] Step 3:

[0689] The server uses a generative AI model to research the laws and related precedents of the specified country or region. The server searches for the latest information from multiple reliable databases and related websites to collect the necessary data. Input: Country and legal category specified by the user. Output: Research data.

[0690] Step 4:

[0691] The server stores the research results in an internal database. The stored data includes the content of the law, the date of enforcement, and related legal precedents. This data is used for subsequent processing. Input: Researched data, Output: Research results stored in the database.

[0692] Step 5:

[0693] The emotion engine analyzes the user's emotions based on the user's input and system usage. The emotion engine detects emotions such as impatience or anxiety, and performs further processing based on the results. Input: User input data, Output: Analyzed emotional state.

[0694] Step 6:

[0695] The server uses a document generation module to automatically generate documents based on the research results and the analysis results of the emotion engine. The format and details of the documents are adjusted based on the emotion analysis results. For example, if the user is feeling anxious, a summary document that briefly summarizes the risks will be created first. Input: Research results and emotion analysis results, Output: Automatically generated documents.

[0696] Step 7:

[0697] The server converts the generated documents into PDF or Word format and sends them to the terminal. The documents are encoded to ensure communication security. Input: Generated documents, Output: Sent document file.

[0698] Step 8:

[0699] The terminal decodes the data received from the server and displays it to the user. The user can check the data and download or print it as needed. Input: Data file sent from the server. Output: Data that can be displayed and downloaded.

[0700] Examples:

[0701] For example, if a Japanese company providing security services is looking to expand into the US, the user would enter "America" ​​and "security law," which would be step 1. In step 2, this input data is sent to the server. In step 3, the server uses a generative AI model to collect the latest information on US security laws. In step 4, this information is stored in an internal database. In step 5, an emotion engine analyzes emotions from the user's input, and in step 6, a document is automatically generated based on the results. In step 7, the document is sent to the device, and in step 8, the user reviews and downloads the document.

[0702] 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.

[0703] 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.

[0704] 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.

[0705] [Third embodiment]

[0706] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0707] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0708] 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).

[0709] 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.

[0710] 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.

[0711] 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).

[0712] 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.

[0713] 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.

[0714] 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.

[0715] 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.

[0716] 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.

[0717] 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."

[0718] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in the country or region a company is expanding into when it is expanding overseas. This system includes a means for the user to specify the country or region to expand into and the legal category to be investigated, a means for the server to research the specified laws and precedents using generative artificial intelligence, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal.

[0719] Explanation of program processing

[0720] 1. User input

[0721] Using the input form on the device, users input the country or region they wish to enter and the legal category they wish to research, for example, by entering keywords such as "America, China, labor law, tax law."

[0722] 2. Data transmission by the terminal

[0723] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0724] 3. Server-based research

[0725] The server runs a generative artificial intelligence (AI) to research the laws and legal precedents of a specified country or region, for example, by retrieving information on the latest labor and tax laws in the United States from government databases and reliable legal databases.

[0726] 4. Saving your research results

[0727] The server stores the research results in an internal database, storing information such as the content of the law, its enforcement date, and related legal precedents as structured data.

[0728] 5. Automatic generation of materials

[0729] The server launches a document generation module, which automatically generates a document summarizing the legal risks associated with the expansion based on the research results. The document includes specific details about the main points, risks, and differences between Japan and the US. For example, it includes information such as the US work week limit of 40 hours and the federal minimum wage of $7.25.

[0730] 6. Submission of Materials

[0731] The server converts the generated documents into PDF or Word format and sends them to the device. The data is sent in an encoded format to ensure secure communication.

[0732] 7. Displaying and downloading materials via terminal

[0733] The terminal displays the materials received from the server so that the user can check them, and the user can download or print them as necessary.

[0734] Specific examples

[0735] As a concrete example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America, China, labor law, tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. The user can review the document and use it to help them make a decision about expanding into the country.

[0736] The present invention enables users to grasp the legal risks of the country in which they are entering at low cost and efficiently, and to obtain investigation results with speed and accuracy that could not be achieved with conventional methods.

[0737] The processing flow will be explained below.

[0738] Step 1: The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, the user might enter keywords such as "America," "China," "Labor Law," or "Tax Law."

[0739] Step 2: The device reviews the user's input and performs a quick check to ensure there are no formatting issues, such as whether the entered country name is spelled correctly or whether the legal category being investigated is included in an existing list.

[0740] Step 3: The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0741] Step 4: The server analyzes the information received from the user and passes it to the generative AI research module. This analysis includes selecting a database of laws and regulations for the input country or region.

[0742] Step 5: The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region. For example, it collects the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0743] Step 6: The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0744] Step 7: The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. For example, under US labor law, this includes information such as "working hours limited to 40 hours per week" and "federal minimum wage is $7.25."

[0745] Step 8: The server converts the generated document into PDF or Word format and sends it to the device in an encoded format, ensuring secure communication.

[0746] Step 9: The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to view the data.

[0747] Step 10: The user checks the displayed materials and downloads or prints them as necessary. This allows the user to obtain specific information about the legal risks in the country in which they are entering.

[0748] Example 1

[0749] 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."

[0750] When a company expands overseas, it is important to investigate the legal risks of the country it is expanding into quickly and at low cost. However, traditional methods require a lot of time and money, placing a heavy burden on small and medium-sized enterprises. In addition, there was a problem in that there was no system that could quickly collect reliable information and automatically generate documents based on that information.

[0751] 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.

[0752] In this invention, the server includes means for searching for regulations and case studies in a designated area using generative artificial intelligence, means for automatically generating materials summarizing regulatory risks related to expansion based on the results of the search, and means for transmitting the generated materials to the user's information processing device, thereby enabling companies to efficiently understand the legal risks of their expansion destinations at low cost.

[0753] A "user" is an individual or entity that uses the system to specify the geographical area in which to operate and the regulatory category to be investigated.

[0754] "Region" refers to the specific country or region in which the company plans to expand.

[0755] "Regulatory category" refers to the classification of laws and regulations (e.g., labor laws, tax laws, etc.) in the country in which a company wishes to enter and investigate.

[0756] The term "means" refers to a method or apparatus for realizing a specific function. In this context, it refers to a device or system part having a specific function such as input, transmission, or display.

[0757] "Generative AI" refers to an AI model that can automatically generate text in response to a given prompt.

[0758] "Regulation" means any law, ordinance or rule enacted by a government or related authority.

[0759] "Case studies" refer to actual legal events in Europe, such as past precedents and examples.

[0760] "Exploration" refers to the act of searching for and collecting specific information based on specified criteria.

[0761] "Materials" refers to reports and documents generated based on research results.

[0762] The term "information processing device" refers to a device such as a computer or smartphone used by a user.

[0763] A "database" refers to a system for systematically organizing and storing collected information.

[0764] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in a country where a company is expanding overseas. This system includes a means for a user to specify the region to expand into and the regulatory categories to be investigated, a means for a server to use generative artificial intelligence to search for the specified regulations and examples, a means for automatically generating documents summarizing the regulatory risks related to the expansion based on the results of the search, a means for transmitting the generated documents to the user's information processing device, and a means for displaying the documents received by the information processing device.

[0765] Specifically, the system is constructed using the following hardware and software.

[0766] Hardware and software used

[0767] 1. Terminal

[0768] A terminal is an information processing device that allows users to input information and receive and display materials from the server. Examples include PCs, smartphones, and tablets. A web browser is installed on the terminal, and users input information through an input form.

[0769] 2. Server

[0770] The server requires high-performance hardware to run generative artificial intelligence (e.g., GPT-4). The server also has an internal database (e.g., MySQL) and template engine (e.g., Jinja2) for generating materials and storing data.

[0771] System Operation

[0772] 1. Enter information

[0773] Using the device's web browser, the user enters the region of the country they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, the user enters "America, China, Labor Law, Tax Law" and clicks the submit button.

[0774] 2. Data transmission and check

[0775] The terminal performs a simple format check of the entered information, and if there are no errors, sends it to the server. At this time, it checks that the entered data is in the correct format, and if necessary, displays an error message to prompt the user to re-enter the data.

[0776] 3. Conduct research

[0777] The server runs generative artificial intelligence to explore regulations and cases in a given region, for example, gathering information on the latest US labor and tax laws from a reliable database.

[0778] 4. Saving results and generating documents

[0779] The server stores the acquired information as structured data in an internal database, and then uses a document generation module to automatically generate documents summarizing the regulatory risks associated with the company's expansion. Specifically, a template engine (e.g., Jinja2) is used to insert the collected data into a document and convert it into PDF or Word format.

[0780] 5. Submitting and Displaying Materials

[0781] The server sends the generated documents to the user's terminal, which receives and displays them. The user can then check the documents on the terminal and download or print them as needed.

[0782] Specific examples

[0783] As a concrete example, consider the case of a Japanese company considering expanding into the United States and China. The user enters "United States, China, labor law, tax law" into an input form on their device and requests a survey. In response, the server collects the latest information on labor and tax laws in both countries, generates a document detailing the regulatory risks in each country, and sends it to the user's device. The user then reviews the document and uses it to help them make a decision about expanding into the country.

[0784] Prompt Sentence Examples

[0785] Below are some examples of prompts for generative artificial intelligence:

[0786] Please research the US, China, labor laws, and tax laws and create a document outlining the regulatory risks for each country. Specifically, please provide detailed data including the latest information on labor and tax laws, enforcement dates, and related cases.

[0787] Using this prompt, the generative AI can research detailed regulatory risks based on the specified region and regulatory category, and efficiently create the necessary materials.

[0788] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0789] Step 1:

[0790] Using the web browser on their device, the user enters the region they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, they enter "America, China, Labor Law, Tax Law" and click the submit button. The data entered is the region name and regulatory category. Specifically, the user enters keywords using the input form and then submits the form.

[0791] Step 2:

[0792] The terminal performs a simple format check on the information entered by the user to ensure there are no errors. This is a process that checks whether the input data is in the correct format. The input is the region name and regulatory category entered by the user, and the output is the checked data. Specifically, the terminal validates the input information, and if any invalid input is found, it displays an error message and prompts the user to re-enter the information.

[0793] Step 3:

[0794] The terminal sends the checked data to the server. The input is the checked region name and regulatory category data, and the output is a request including this data that is sent to the server. Specifically, the terminal sends an HTTP request to the server.

[0795] Step 4:

[0796] The server receives the request and launches a generative AI to initiate a search process based on the specified region and regulatory category. The input is the received region name and regulatory category, and the output is regulatory and case information. Specifically, the server provides prompts to the generative AI model (e.g., GPT-4) and collects relevant data.

[0797] Step 5:

[0798] The server stores the information obtained from the generative artificial intelligence in an internal database. The input is the collected regulatory and case information, and the output is structured data stored in the database. Specifically, the server uses a database management system (e.g., MySQL) to insert the data into tables in the correct format.

[0799] Step 6:

[0800] The server launches a document generation module that automatically generates documents summarizing the regulatory risks associated with the company's expansion based on the research results. The input is regulatory and case information stored in the database, and the output is the generated document (PDF or Word format). Specifically, the server uses a template engine (e.g., Jinja2) to embed the collected data into a document template and convert it into the final document format.

[0801] Step 7:

[0802] The server encodes the generated data and sends it to the user's terminal using a secure communication protocol (e.g., SSL / TLS). The input is the generated document, and the output is the transmission to the user's terminal. Specifically, the server encodes the data and sends it to the user's terminal using a mail server.

[0803] Step 8:

[0804] The device saves the data received from the server and displays it to the user. The input is the data from the server, and the output is the display and saved file for the user. Specifically, the device opens the received email, saves the attachment to local storage, and displays it in a dedicated viewer application.

[0805] Step 9:

[0806] The user checks the documents on the terminal and downloads or prints them as necessary. The input is the displayed documents, and the output is the downloaded and printed documents. Specifically, the user clicks the download link, saves the file, and then prints the documents using a printer.

[0807] (Application example 1)

[0808] 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."

[0809] When a company expands overseas, it is extremely important to quickly and inexpensively investigate the legal risks of the host country or region and prepare documents for risk management. However, traditional methods require significant time and cost to investigate legal risks, and the accuracy of the documents often remains an issue. Furthermore, conducting international legal research requires specialized knowledge, which small and medium-sized enterprises find difficult to secure. To solve these issues, there is a need for a system that uses generative artificial intelligence to efficiently and accurately investigate legal risks and automatically generate documents. Legal compliance is particularly important in security services, and quickly understanding legal information in the host country is required as part of security measures.

[0810] 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.

[0811] In this invention, the server includes: means for providing an input form for users to enter information on countries, regions, and legal categories specified by the user; data transmission means for transmitting the input information to a cloud server; means for researching the input country, region, and legal category information using generative artificial intelligence and storing the acquired data in an internal database; means for generating a document summarizing legal risks related to the expansion from the research results and creating it as a PDF document; means for transmitting the generated PDF to the user's device; and means for the user to display, review, and download the PDF on their device. This allows companies to quickly and accurately grasp the legal risks of the country or region they are expanding into and automatically generate the document at low cost. It also facilitates risk assessment for legal compliance in security services, which can lead to smooth expansion and business operations.

[0812] "User" is a general term for an individual or organization that uses the system to specify the country or region to enter and the legal category to be investigated.

[0813] "Destination" refers to the country or region where the user intends to develop business or carry out activities.

[0814] A "legal category" is a classification that indicates the type of law or regulation related to a particular field.

[0815] "Generative artificial intelligence" refers to a general term for artificial intelligence technology that has the ability to learn large amounts of data and generate new information.

[0816] "Research" refers to the act of investigating and collecting specific information in detail.

[0817] "Materials" refers to documents and data compiled based on research results.

[0818] A "server" is a system that provides central functions of a computer system, such as data processing and storage.

[0819] "Transmission" refers to the act of sending data or information to another system or device.

[0820] "Terminal" refers to devices such as computers, smartphones, and tablets that are directly operated by users.

[0821] "Input Form" means an online form containing screens and fields for a user to enter information.

[0822] "Data transmission means" refers to the method or technology used to send input information to other systems.

[0823] "Research results" refers to the results of research obtained using generative artificial intelligence.

[0824] "Internal database" refers to a database used to store and manage data within the system.

[0825] "PDF format" is an abbreviation for Portable Document Format and refers to a specific document format standard.

[0826] "Downloading" refers to the act of importing data or materials from a server to a terminal.

[0827] The present invention provides a specific embodiment of a system that uses generative artificial intelligence to efficiently investigate and prepare documents regarding legal risks in the countries where a company is expanding. The detailed configuration and operating procedures of the system for implementing the invention are described below.

[0828] System Configuration

[0829] Hardware and software used

[0830] Hardware: Smartphone (iOS / Android), cloud server

[0831] software:

[0832] Frontend: React Native

[0833] Backend: Node.js, Express

[0834] Database: MongoDB

[0835] AI model: OpenAI GPT-4 API

[0836] PDF generation: pdf-lib

[0837] Program processing

[0838] 1. User input

[0839] Users enter the country or region they are expanding into and the legal category they are investigating into an input form on the smartphone app (React Native).

[0840] A typical example input would use keywords such as "America, GDPR, labor law."

[0841] 2. Data Transmission

[0842] The terminal (smartphone) sends the entered information to a cloud server (Node.js / Express).

[0843] When sending data, a format check is performed to prevent input errors.

[0844] 3. Research using generative AI models

[0845] The server launches generative artificial intelligence (OpenAI GPT-4 API) and researches the laws and precedents of the country or region specified by the user.

[0846] Typical research topics include information on the latest GDPR and labor laws in the United States.

[0847] 4. Saving your research results

[0848] The server stores the research results as structured data in an internal database (MongoDB).

[0849] The data to be stored includes the content of the law, the date of enforcement, related precedents, etc.

[0850] 5. Automatic generation of materials

[0851] The server starts a document generation module and generates a document summarizing the legal risks related to expansion from the research results.

[0852] The generated document will be converted to PDF format and will contain all the necessary information, such as the federal minimum wage of $7.25 per US labor law.

[0853] 6. Submission of Materials

[0854] The server sends the generated PDF to the user's smartphone.

[0855] Data is transmitted securely (HTTPS).

[0856] 7. Viewing and Downloading Materials

[0857] Users can view the PDF on their smartphone app and download or print it as needed.

[0858] Examples of concrete examples and prompts

[0859] Specific examples

[0860] For example, when a Japanese company expands into the US, the user can enter "USA, GDPR, labor law" into the app's input form. Based on this, the server will collect the latest information on the US GDPR and labor law, generate documents based on that information, and provide them to the user's smartphone.

[0861] Prompt Sentence Examples

[0862] As an example of text format, a user enters the following content into the app.

[0863] America

[0864] GDPR

[0865] Labor Law

[0866] This allows users to quickly and at low cost understand the legal risks in the country they are entering and efficiently obtain the necessary information. This system is particularly effective for security services, and supports users in quickly conducting risk assessments for legal compliance.

[0867] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0868] Step 1:

[0869] Users enter the country or region they wish to expand into and the legal category they wish to research into an input form on the smartphone app. The user inputs specific keywords such as "America, GDPR, labor law." Once the input is complete, the device generates data to send this information to a cloud server.

[0870] Input: Country or region of operation, legal category

[0871] Output: Data to send to the cloud server

[0872] Step 2:

[0873] The device sends the information entered by the user to the cloud server. When the data is sent, the format of the entered data is checked and validation is performed to prevent formatting errors and input mistakes. If the data is in the correct format, it is sent to the server.

[0874] Input: What the user types

[0875] Output: Data sent to the server

[0876] Step 3:

[0877] The server receives the incoming information and activates generative artificial intelligence (OpenAI GPT-4 API) to research the laws and precedents of the specified country or region. The server then references various reliable legal databases to collect the necessary information and compile it as structured data.

[0878] Input: User-specified information

[0879] Output: Structured data of research results

[0880] Step 4:

[0881] The server stores the acquired research results in an internal database (MongoDB). The database is structured to include detailed information such as the content of the law, its implementation date, and related legal precedents. When saving, the server checks the integrity of the data and generates the necessary indexes.

[0882] Input: Research results

[0883] Output: Legal data stored in an internal database

[0884] Step 5:

[0885] Based on the saved research results, the server launches a document generation module and automatically generates a PDF document summarizing the legal risks associated with the expansion. This document lists the main risk factors and points that differ from those in Japan.

[0886] Input: Data from the internal database

[0887] Output: Automatically generated PDF document

[0888] Step 6:

[0889] The server then sends the generated PDF file to the user's smartphone via a secure method (HTTPS), using encoding and security protocols to prevent external access.

[0890] Input: PDF format documents

[0891] Output: PDF file sent to the user's device

[0892] Step 7:

[0893] The terminal displays the received PDF file to the user, who can then review it and download or print it as needed. The terminal also provides functions for managing the content of the document appropriately.

[0894] Input: Received PDF file

[0895] Output: Viewable and downloadable PDF file

[0896] Through the above processing steps, users can quickly and at low cost understand the legal risks of the country they are entering and obtain the necessary documents, which will enable them to smoothly proceed with their company's entry plans.

[0897] 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.

[0898] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0899] Explanation of program processing

[0900] 1. User input

[0901] Using the input form on the device, users input the country or region they wish to expand into and the legal category they wish to research, for example, by entering keywords such as "America," "China," "labor law," and "tax law."

[0902] 2. Data transmission by the terminal

[0903] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[0904] 3. Server-based research

[0905] The server runs a generative artificial intelligence (AI) to research the laws and precedents of the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0906] 4. Saving your research results

[0907] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0908] 5. Sentiment analysis using an emotion engine

[0909] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0910] 6. Automatically generate materials and adjust them based on emotions

[0911] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the research results based on the analysis results of the emotion engine. For example, if the user is anxious, it will prioritize presenting a summary of the risks.

[0912] 7. Submission of Materials

[0913] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0914] 8. Displaying and downloading materials via terminal

[0915] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0916] 9. Users can review the materials and download or print them as needed.

[0917] The user can check the displayed materials and download or print them as necessary, thereby obtaining specific information about the legal risks in the country where the user is entering.

[0918] Specific examples

[0919] For example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America," "China," "labor law," and "tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. If the emotion engine detects the user's impatience or anxiety, the server will prioritize generating a summary document that succinctly summarizes the risks. The user can review the document and use it to help make a decision about expanding into those countries.

[0920] This invention allows users to efficiently grasp the legal risks of the country they are entering at low cost, and enables them to obtain investigation results with speed and accuracy that could not be achieved with conventional methods. Furthermore, the introduction of an emotion engine enables flexible responses according to the user's psychological state, providing a better user experience.

[0921] The processing flow will be explained below.

[0922] Step 1:

[0923] The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, they enter keywords such as "America," "China," "labor law," and "tax law."

[0924] Step 2:

[0925] The device reviews the user's input and performs a quick check to ensure the format is correct: it checks whether the country name entered is spelled correctly and whether the legal category being investigated is included in an existing list.

[0926] Step 3:

[0927] The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[0928] Step 4:

[0929] The server analyzes the information received from the user and passes it to the generative AI research module, which includes selecting a database of laws and regulations for the input country or region.

[0930] Step 5:

[0931] The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[0932] Step 6:

[0933] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[0934] Step 7:

[0935] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[0936] Step 8:

[0937] The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The method of presenting the research results and their details are adjusted based on the analysis results of the emotion engine. For example, if the user is anxious, a summary version that briefly summarizes the risks can be presented first.

[0938] Step 9:

[0939] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[0940] Step 10:

[0941] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[0942] Step 11:

[0943] The user can check the displayed materials and download or print them as necessary, enabling them to obtain specific information about the legal risks in the country they are entering.

[0944] Example 2

[0945] 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."

[0946] When a company expands overseas, it is difficult to quickly and cost-effectively research and prepare documents to identify legal risks in the country of entry. Furthermore, there are limited ways to tailor the way information is provided and research results are presented to suit the user's psychological state, resulting in a poor user experience. To solve these problems, efficient and flexible research and response methods are required.

[0947] 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.

[0948] In this invention, the server includes means including an emotion engine for analyzing the user's emotional state, means for researching the laws and precedents of a designated country or region using generative artificial intelligence, and means for adjusting the presentation method of materials based on the analysis results of the emotion engine. This enables flexible and rapid legal risk investigation and information provision according to the user's psychological state.

[0949] "User" refers to an entity that uses the system to investigate legal risks in the country where the company is expanding.

[0950] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[0951] "Server" means a central processing unit that runs the generative artificial intelligence and emotion engine and performs research based on user input.

[0952] "Generative AI" is AI that has the ability to generate appropriate information based on specified data.

[0953] "Laws" includes laws and regulations enacted by national or local government agencies.

[0954] "Precedent" includes past decisions and rulings made by the court.

[0955] "Research Results" includes data on laws and precedents obtained by generative artificial intelligence through research.

[0956] The "materials" are documents generated based on research results that provide a detailed summary of the legal risks associated with expanding into the country.

[0957] An "emotion engine" is a software module that analyzes a user's emotional state and adjusts how information is presented.

[0958] "Reception" is the process by which a terminal receives data or materials sent from a server.

[0959] "Display" means displaying the data or materials received by the terminal on the screen in a format that can be viewed by the user.

[0960] "Downloading" is the process of saving material to your device so that it can be accessed offline.

[0961] "Printing" is the process of outputting materials onto paper media from a terminal using a printer.

[0962] A "simple format check" is a process that verifies whether the information entered by the user conforms to a specified format.

[0963] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[0964] The system's program is structured as follows: First, the user is provided with an interface via their terminal to input the country or region they wish to enter and the legal category they wish to research. Once the user has entered the necessary information, it is sent to the server. The server then launches a generative artificial intelligence (e.g., OpenAI's GPT-4) to research the laws and precedents of the specified country or region. Multiple reliable legal databases (e.g., Westlaw, LexisNexis) are used as sources of research.

[0965] The research results are stored as structured data in an internal database, and the user's emotions are analyzed using an emotion engine (e.g., Microsoft Azure's Emotion API). For example, if the user is feeling anxious or impatient, the server will adjust the way the research results are presented based on that information, providing the information in a format that is easy for the user to understand. Finally, a document generation module automatically generates a document summarizing legal risks based on the research results, converts it to PDF or Word format, and sends it to the device. During this process, AES encryption technology is used to ensure communication security.

[0966] The terminal decodes the transmitted material and displays it to the user using viewer software, allowing the user to review the material in detail and download or print it as desired.

[0967] As a concrete example, consider the case where a Japanese company is considering expanding into the United States and China. The user enters keywords such as "America," "China," "labor law," and "tax law" into their device. The server uses this information to comprehensively research the specified laws and precedents and generates a document summarizing the legal risks in detail. If the emotion engine detects the user's impatience, the server generates a summary document that succinctly summarizes the risks and provides it to the user. Based on this document, the user can quickly obtain specific information to help them make a decision about expanding into the country.

[0968] An example prompt sentence would be entered as follows:

[0969] "A Japanese company is considering expanding into the United States and China. Please research the latest laws and precedents regarding American labor and tax laws, as well as Chinese labor and tax laws."

[0970] In this way, the present invention allows users to grasp the legal risks of the country they are entering efficiently and at low cost, and the emotion engine enables flexible responses according to the user's psychological state.

[0971] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0972] Step 1:

[0973] The user uses the input form on the device to input the country or region they are expanding into and the legal category they are investigating. Specifically, they enter keywords such as "America," "China," "Labor Law," and "Tax Law." This information is provided to the device as input. The input form checks the input in real time, checking for typos and formatting errors, and provides feedback to the user.

[0974] Step 2:

[0975] The terminal sends the information entered by the user to the server. A simple format check is performed to ensure the input conforms to the specified format. During this process, the input data is checked for errors, and if it is not in the correct format, an error message is returned to the user. If the format is correct, the input data is sent to the server.

[0976] Step 3:

[0977] The server launches a generative artificial intelligence (e.g., OpenAI's GPT-4) and researches the laws and precedents of the specified country or region based on the input data it receives. Specifically, the server first connects to the Internet and collects relevant information from multiple reliable legal databases (e.g., Westlaw, LexisNexis). The results of this research are stored in a database. Based on the keywords provided as input data, the generative AI searches for relevant information and generates research results as output.

[0978] Step 4:

[0979] The server stores the research results in an internal database, which is maintained in a structured data format and includes information such as the content of the law, its implementation date, relevant legal precedents, and citation sources. During this storage process, the data is indexed for efficient access.

[0980] Step 5:

[0981] The server launches an emotion engine (e.g., Microsoft Azure's Emotion API) and analyzes the user's emotions based on their input and usage. The analysis is performed based on input text, operation speed, click patterns, etc. If emotions such as impatience or anxiety are detected as a result of the analysis, that information is tagged and used for the next step.

[0982] Step 6:

[0983] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the documents based on the analysis results of the emotion engine. For example, if it detects that the user is anxious, it will prioritize generating a summary version that summarizes the information concisely. The generated documents are then converted into PDF or Word format.

[0984] Step 7:

[0985] The server encodes the generated data and sends it to the terminal. The encoding uses AES encryption technology to ensure the security of the communication, thereby protecting the privacy of user data.

[0986] Step 8:

[0987] The terminal decodes the material received from the server and displays it to the user using the appropriate viewer software, which allows the user to zoom, scroll, add annotations, etc., allowing the user to examine the material in detail.

[0988] Step 9:

[0989] Users can check the displayed materials and download or print them as needed. Download and print buttons are displayed on the device, allowing these operations to be performed with a single click. Downloaded materials can also be accessed offline.

[0990] (Application example 2)

[0991] 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."

[0992] In the past, companies needed to investigate legal risks when expanding overseas, which was time-consuming and costly. Furthermore, because information was provided uniformly without taking into account the user's emotional state, there was a problem in that the information provided could not be appropriate for the user's psychological state. In particular, for companies that provide security services, it is important to understand the legal risks of each country, and it is required that such investigations be carried out quickly and efficiently.

[0993] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to specify the country or region to enter and the legal category to be investigated, means for researching the laws and precedents of the specified country or region using generative artificial intelligence, means for automatically generating materials summarizing the legal risks related to the entry based on the research results, and means for analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of the materials based on that. This enables flexible legal risk investigation and provision of materials according to the user's psychological state, enabling quick and efficient information gathering and appropriate decision-making.

[0994] "Means for users to specify the country or region they wish to expand into and the categories of laws and regulations to be investigated" refers to an interface or input system that allows users to input or select the specific country or region and the type of laws and regulations they wish to investigate when a company expands overseas.

[0995] "Means for researching laws and precedents of designated countries or regions using generative artificial intelligence" refers to algorithms and software designed to use generative artificial intelligence (AI) to search for and collect laws and precedents related to countries or regions designated by users.

[0996] "Means for automatically generating documents summarizing legal risks related to expansion based on research results" refers to a system that automatically generates documents that systematically summarize legal risks related to a company's expansion destination based on information collected by AI.

[0997] "A means of analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of materials based on that" refers to a system that analyzes the user's input and behavior, identifies the emotions the user is feeling (anxiety, impatience, etc.), and changes the way research results and materials are displayed depending on those emotions.

[0998] This invention uses a system that combines generative artificial intelligence (AI) and an emotion engine to quickly and inexpensively investigate legal risks in the country of expansion and to assist in the creation of documents when a company expands overseas. An embodiment of this invention is described below.

[0999] System configuration

[1000] The system consists of the following major components:

[1001] 1. User Input Interface:

[1002] Users use an input form on their device (smartphone, tablet, PC, etc.) to input the country or region they are entering and the legal category they are investigating. This specifies the legal information of the country or region they are entering into the system.

[1003] 2. Data transmission module:

[1004] The information entered by the user is sent from the terminal to the server, where a simple format check is performed to prevent input errors.

[1005] 3. Generative Artificial Intelligence (AI) Module:

[1006] The AI ​​module installed on the server researches the laws and relevant precedents of the country or region specified by the user, collecting the latest information from reliable databases and websites.

[1007] 4. Research Results Storage Module:

[1008] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[1009] 5. Emotion Engine Module:

[1010] The emotion engine analyzes the user's emotions based on their input and system usage, detecting and responding to emotions such as anxiety and impatience.

[1011] 6. Document generation module:

[1012] Based on the research results and the analysis results of the emotion engine, the server automatically creates a document summarizing the legal risks associated with the move in. If the user feels anxious, the server adjusts the details of the document and the way it is presented, for example, by creating a summary version of the document that briefly summarizes the risks, depending on the user's emotions.

[1013] 7. Data transmission and display module:

[1014] The generated documents are sent to the terminal in PDF or Word format and displayed on the terminal, where the user can review them and download or print them as needed.

[1015] Processing Description

[1016] In this system, users first enter the country or region they wish to enter and the legal category into an input form on their device. This information is sent to the server, and the generative AI researches the laws and related precedents based on the specified conditions. The research results are stored in an internal database.

[1017] Next, the emotion engine analyzes the user's emotions based on their input and system usage, and generates documents that reflect the user's psychological state. Based on the research results and the emotion engine's analysis, the server automatically generates documents summarizing the legal risks associated with the expansion and sends them to the user's device. The user can review the documents and download or print them as needed.

[1018] Specific examples

[1019] For example, if a Japanese company providing security services is looking to expand into the US, the user would input "USA" and "security law." Based on this information, the server would research the latest US security regulations and generate materials. If the emotion engine detects the user's impatience, it will prioritize generating a concise summary of the information, providing information appropriate to the user's psychological state.

[1020] Example of an input prompt for a generative AI model:

[1021] Research the latest in international security regulations.

[1022] This invention allows companies to quickly and efficiently grasp the legal risks of the country they are entering, and to obtain investigation results with speed and accuracy that were not possible with conventional methods.In addition, the introduction of an emotion engine enables flexible responses based on the user's psychological state, providing a better user experience.

[1023] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1024] Step 1:

[1025] The user enters the country or region they are entering and the legal category they are investigating into an input form on their device. For example, input contents could be "America" ​​and "Security Law." The input data is sent to the system. This input includes information specified by the user.

[1026] Step 2:

[1027] The device sends the information entered by the user to the server. At this time, a simple format check is performed to ensure the input is valid. After confirming that the input is in the correct format, the information is forwarded to the server. Input: Country and legal category entered by the user. Output: Data sent after validity check.

[1028] Step 3:

[1029] The server uses a generative AI model to research the laws and related precedents of the specified country or region. The server searches for the latest information from multiple reliable databases and related websites to collect the necessary data. Input: Country and legal category specified by the user. Output: Research data.

[1030] Step 4:

[1031] The server stores the research results in an internal database. The stored data includes the content of the law, the date of enforcement, and related legal precedents. This data is used for subsequent processing. Input: Researched data, Output: Research results stored in the database.

[1032] Step 5:

[1033] The emotion engine analyzes the user's emotions based on the user's input and system usage. The emotion engine detects emotions such as impatience or anxiety, and performs further processing based on the results. Input: User input data, Output: Analyzed emotional state.

[1034] Step 6:

[1035] The server uses a document generation module to automatically generate documents based on the research results and the analysis results of the emotion engine. The format and details of the documents are adjusted based on the emotion analysis results. For example, if the user is feeling anxious, a summary document that briefly summarizes the risks will be created first. Input: Research results and emotion analysis results, Output: Automatically generated documents.

[1036] Step 7:

[1037] The server converts the generated documents into PDF or Word format and sends them to the terminal. The documents are encoded to ensure communication security. Input: Generated documents, Output: Sent document file.

[1038] Step 8:

[1039] The terminal decodes the data received from the server and displays it to the user. The user can check the data and download or print it as needed. Input: Data file sent from the server. Output: Data that can be displayed and downloaded.

[1040] Examples:

[1041] For example, if a Japanese company providing security services is looking to expand into the US, the user would enter "America" ​​and "security law," which would be step 1. In step 2, this input data is sent to the server. In step 3, the server uses a generative AI model to collect the latest information on US security laws. In step 4, this information is stored in an internal database. In step 5, an emotion engine analyzes emotions from the user's input, and in step 6, a document is automatically generated based on the results. In step 7, the document is sent to the device, and in step 8, the user reviews and downloads the document.

[1042] 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.

[1043] 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.

[1044] 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.

[1045] [Fourth embodiment]

[1046] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1047] 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.

[1048] 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).

[1049] 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.

[1050] 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.

[1051] 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).

[1052] 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.

[1053] 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.

[1054] 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.

[1055] 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.

[1056] 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.

[1057] 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.

[1058] 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."

[1059] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in the country or region a company is expanding into when it is expanding overseas. This system includes a means for the user to specify the country or region to expand into and the legal category to be investigated, a means for the server to research the specified laws and precedents using generative artificial intelligence, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal.

[1060] Explanation of program processing

[1061] 1. User input

[1062] Using the input form on the device, users input the country or region they wish to enter and the legal category they wish to research, for example, by entering keywords such as "America, China, labor law, tax law."

[1063] 2. Data transmission by the terminal

[1064] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[1065] 3. Server-based research

[1066] The server runs a generative artificial intelligence (AI) to research the laws and legal precedents of a specified country or region, for example, by retrieving information on the latest labor and tax laws in the United States from government databases and reliable legal databases.

[1067] 4. Saving your research results

[1068] The server stores the research results in an internal database, storing information such as the content of the law, its enforcement date, and related legal precedents as structured data.

[1069] 5. Automatic generation of materials

[1070] The server launches a document generation module, which automatically generates a document summarizing the legal risks associated with the expansion based on the research results. The document includes specific details about the main points, risks, and differences between Japan and the US. For example, it includes information such as the US work week limit of 40 hours and the federal minimum wage of $7.25.

[1071] 6. Submission of Materials

[1072] The server converts the generated documents into PDF or Word format and sends them to the device. The data is sent in an encoded format to ensure secure communication.

[1073] 7. Displaying and downloading materials via terminal

[1074] The terminal displays the materials received from the server so that the user can check them, and the user can download or print them as necessary.

[1075] Specific examples

[1076] As a concrete example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America, China, labor law, tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. The user can review the document and use it to help them make a decision about expanding into the country.

[1077] The present invention enables users to grasp the legal risks of the country in which they are entering at low cost and efficiently, and to obtain investigation results with speed and accuracy that could not be achieved with conventional methods.

[1078] The processing flow will be explained below.

[1079] Step 1: The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, the user might enter keywords such as "America," "China," "Labor Law," or "Tax Law."

[1080] Step 2: The device reviews the user's input and performs a quick check to ensure there are no formatting issues, such as whether the entered country name is spelled correctly or whether the legal category being investigated is included in an existing list.

[1081] Step 3: The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[1082] Step 4: The server analyzes the information received from the user and passes it to the generative AI research module. This analysis includes selecting a database of laws and regulations for the input country or region.

[1083] Step 5: The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region. For example, it collects the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[1084] Step 6: The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[1085] Step 7: The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. For example, under US labor law, this includes information such as "working hours limited to 40 hours per week" and "federal minimum wage is $7.25."

[1086] Step 8: The server converts the generated document into PDF or Word format and sends it to the device in an encoded format, ensuring secure communication.

[1087] Step 9: The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to view the data.

[1088] Step 10: The user checks the displayed materials and downloads or prints them as necessary. This allows the user to obtain specific information about the legal risks in the country in which they are entering.

[1089] Example 1

[1090] 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."

[1091] When a company expands overseas, it is important to investigate the legal risks of the country it is expanding into quickly and at low cost. However, traditional methods require a lot of time and money, placing a heavy burden on small and medium-sized enterprises. In addition, there was a problem in that there was no system that could quickly collect reliable information and automatically generate documents based on that information.

[1092] 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.

[1093] In this invention, the server includes means for searching for regulations and case studies in a designated area using generative artificial intelligence, means for automatically generating materials summarizing regulatory risks related to expansion based on the results of the search, and means for transmitting the generated materials to the user's information processing device, thereby enabling companies to efficiently understand the legal risks of their expansion destinations at low cost.

[1094] A "user" is an individual or entity that uses the system to specify the geographical area in which to operate and the regulatory category to be investigated.

[1095] "Region" refers to the specific country or region in which the company plans to expand.

[1096] "Regulatory category" refers to the classification of laws and regulations (e.g., labor laws, tax laws, etc.) in the country in which a company wishes to enter and investigate.

[1097] The term "means" refers to a method or apparatus for realizing a specific function. In this context, it refers to a device or system part having a specific function such as input, transmission, or display.

[1098] "Generative AI" refers to an AI model that can automatically generate text in response to a given prompt.

[1099] "Regulation" means any law, ordinance or rule enacted by a government or related authority.

[1100] "Case studies" refer to actual legal events in Europe, such as past precedents and examples.

[1101] "Exploration" refers to the act of searching for and collecting specific information based on specified criteria.

[1102] "Materials" refers to reports and documents generated based on research results.

[1103] The term "information processing device" refers to a device such as a computer or smartphone used by a user.

[1104] A "database" refers to a system for systematically organizing and storing collected information.

[1105] The present invention is a system that uses generative artificial intelligence to quickly and inexpensively investigate and prepare documents regarding legal risks in a country where a company is expanding overseas. This system includes a means for a user to specify the region to expand into and the regulatory categories to be investigated, a means for a server to use generative artificial intelligence to search for the specified regulations and examples, a means for automatically generating documents summarizing the regulatory risks related to the expansion based on the results of the search, a means for transmitting the generated documents to the user's information processing device, and a means for displaying the documents received by the information processing device.

[1106] Specifically, the system is constructed using the following hardware and software.

[1107] Hardware and software used

[1108] 1. Terminal

[1109] A terminal is an information processing device that allows users to input information and receive and display materials from the server. Examples include PCs, smartphones, and tablets. A web browser is installed on the terminal, and users input information through an input form.

[1110] 2. Server

[1111] The server requires high-performance hardware to run generative artificial intelligence (e.g., GPT-4). The server also has an internal database (e.g., MySQL) and template engine (e.g., Jinja2) for generating materials and storing data.

[1112] System Operation

[1113] 1. Enter information

[1114] Using the device's web browser, the user enters the region of the country they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, the user enters "America, China, Labor Law, Tax Law" and clicks the submit button.

[1115] 2. Data transmission and check

[1116] The terminal performs a simple format check of the entered information, and if there are no errors, sends it to the server. At this time, it checks that the entered data is in the correct format, and if necessary, displays an error message to prompt the user to re-enter the data.

[1117] 3. Conduct research

[1118] The server runs generative artificial intelligence to explore regulations and cases in a given region, for example, gathering information on the latest US labor and tax laws from a reliable database.

[1119] 4. Saving results and generating documents

[1120] The server stores the acquired information as structured data in an internal database, and then uses a document generation module to automatically generate documents summarizing the regulatory risks associated with the company's expansion. Specifically, a template engine (e.g., Jinja2) is used to insert the collected data into a document and convert it into PDF or Word format.

[1121] 5. Submitting and Displaying Materials

[1122] The server sends the generated documents to the user's terminal, which receives and displays them. The user can then check the documents on the terminal and download or print them as needed.

[1123] Specific examples

[1124] As a concrete example, consider the case of a Japanese company considering expanding into the United States and China. The user enters "United States, China, labor law, tax law" into an input form on their device and requests a survey. In response, the server collects the latest information on labor and tax laws in both countries, generates a document detailing the regulatory risks in each country, and sends it to the user's device. The user then reviews the document and uses it to help them make a decision about expanding into the country.

[1125] Prompt Sentence Examples

[1126] Below are some examples of prompts for generative artificial intelligence:

[1127] Please research the US, China, labor laws, and tax laws and create a document outlining the regulatory risks for each country. Specifically, please provide detailed data including the latest information on labor and tax laws, enforcement dates, and related cases.

[1128] Using this prompt, the generative AI can research detailed regulatory risks based on the specified region and regulatory category, and efficiently create the necessary materials.

[1129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1130] Step 1:

[1131] Using the web browser on their device, the user enters the region they wish to enter and the regulatory category they wish to investigate into a dedicated input form. For example, they enter "America, China, Labor Law, Tax Law" and click the submit button. The data entered is the region name and regulatory category. Specifically, the user enters keywords using the input form and then submits the form.

[1132] Step 2:

[1133] The terminal performs a simple format check on the information entered by the user to ensure there are no errors. This is a process that checks whether the input data is in the correct format. The input is the region name and regulatory category entered by the user, and the output is the checked data. Specifically, the terminal validates the input information, and if any invalid input is found, it displays an error message and prompts the user to re-enter the information.

[1134] Step 3:

[1135] The terminal sends the checked data to the server. The input is the checked region name and regulatory category data, and the output is a request including this data that is sent to the server. Specifically, the terminal sends an HTTP request to the server.

[1136] Step 4:

[1137] The server receives the request and launches a generative AI to initiate a search process based on the specified region and regulatory category. The input is the received region name and regulatory category, and the output is regulatory and case information. Specifically, the server provides prompts to the generative AI model (e.g., GPT-4) and collects relevant data.

[1138] Step 5:

[1139] The server stores the information obtained from the generative artificial intelligence in an internal database. The input is the collected regulatory and case information, and the output is structured data stored in the database. Specifically, the server uses a database management system (e.g., MySQL) to insert the data into tables in the correct format.

[1140] Step 6:

[1141] The server launches a document generation module that automatically generates documents summarizing the regulatory risks associated with the company's expansion based on the research results. The input is regulatory and case information stored in the database, and the output is the generated document (PDF or Word format). Specifically, the server uses a template engine (e.g., Jinja2) to embed the collected data into a document template and convert it into the final document format.

[1142] Step 7:

[1143] The server encodes the generated data and sends it to the user's terminal using a secure communication protocol (e.g., SSL / TLS). The input is the generated document, and the output is the transmission to the user's terminal. Specifically, the server encodes the data and sends it to the user's terminal using a mail server.

[1144] Step 8:

[1145] The device saves the data received from the server and displays it to the user. The input is the data from the server, and the output is the display and saved file for the user. Specifically, the device opens the received email, saves the attachment to local storage, and displays it in a dedicated viewer application.

[1146] Step 9:

[1147] The user checks the documents on the terminal and downloads or prints them as necessary. The input is the displayed documents, and the output is the downloaded and printed documents. Specifically, the user clicks the download link, saves the file, and then prints the documents using a printer.

[1148] (Application example 1)

[1149] 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."

[1150] When a company expands overseas, it is extremely important to quickly and inexpensively investigate the legal risks of the host country or region and prepare documents for risk management. However, traditional methods require significant time and cost to investigate legal risks, and the accuracy of the documents often remains an issue. Furthermore, conducting international legal research requires specialized knowledge, which small and medium-sized enterprises find difficult to secure. To solve these issues, there is a need for a system that uses generative artificial intelligence to efficiently and accurately investigate legal risks and automatically generate documents. Legal compliance is particularly important in security services, and quickly understanding legal information in the host country is required as part of security measures.

[1151] 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.

[1152] In this invention, the server includes: means for providing an input form for users to enter information on countries, regions, and legal categories specified by the user; data transmission means for transmitting the input information to a cloud server; means for researching the input country, region, and legal category information using generative artificial intelligence and storing the acquired data in an internal database; means for generating a document summarizing legal risks related to the expansion from the research results and creating it as a PDF document; means for transmitting the generated PDF to the user's device; and means for the user to display, review, and download the PDF on their device. This allows companies to quickly and accurately grasp the legal risks of the country or region they are expanding into and automatically generate the document at low cost. It also facilitates risk assessment for legal compliance in security services, which can lead to smooth expansion and business operations.

[1153] "User" is a general term for an individual or organization that uses the system to specify the country or region to enter and the legal category to be investigated.

[1154] "Destination" refers to the country or region where the user intends to develop business or carry out activities.

[1155] A "legal category" is a classification that indicates the type of law or regulation related to a particular field.

[1156] "Generative artificial intelligence" refers to a general term for artificial intelligence technology that has the ability to learn large amounts of data and generate new information.

[1157] "Research" refers to the act of investigating and collecting specific information in detail.

[1158] "Materials" refers to documents and data compiled based on research results.

[1159] A "server" is a system that provides central functions of a computer system, such as data processing and storage.

[1160] "Transmission" refers to the act of sending data or information to another system or device.

[1161] "Terminal" refers to devices such as computers, smartphones, and tablets that are directly operated by users.

[1162] "Input Form" means an online form containing screens and fields for a user to enter information.

[1163] "Data transmission means" refers to the method or technology used to send input information to other systems.

[1164] "Research results" refers to the results of research obtained using generative artificial intelligence.

[1165] "Internal database" refers to a database used to store and manage data within the system.

[1166] "PDF format" is an abbreviation for Portable Document Format and refers to a specific document format standard.

[1167] "Downloading" refers to the act of importing data or materials from a server to a terminal.

[1168] The present invention provides a specific embodiment of a system that uses generative artificial intelligence to efficiently investigate and prepare documents regarding legal risks in the countries where a company is expanding. The detailed configuration and operating procedures of the system for implementing the invention are described below.

[1169] System Configuration

[1170] Hardware and software used

[1171] Hardware: Smartphone (iOS / Android), cloud server

[1172] software:

[1173] Frontend: React Native

[1174] Backend: Node.js, Express

[1175] Database: MongoDB

[1176] AI model: OpenAI GPT-4 API

[1177] PDF generation: pdf-lib

[1178] Program processing

[1179] 1. User input

[1180] Users enter the country or region they are expanding into and the legal category they are investigating into an input form on the smartphone app (React Native).

[1181] A typical example input would use keywords such as "America, GDPR, labor law."

[1182] 2. Data Transmission

[1183] The terminal (smartphone) sends the entered information to a cloud server (Node.js / Express).

[1184] When sending data, a format check is performed to prevent input errors.

[1185] 3. Research using generative AI models

[1186] The server launches generative artificial intelligence (OpenAI GPT-4 API) and researches the laws and precedents of the country or region specified by the user.

[1187] Typical research topics include information on the latest GDPR and labor laws in the United States.

[1188] 4. Saving your research results

[1189] The server stores the research results as structured data in an internal database (MongoDB).

[1190] The data to be stored includes the content of the law, the date of enforcement, related precedents, etc.

[1191] 5. Automatic generation of materials

[1192] The server starts a document generation module and generates a document summarizing the legal risks related to expansion from the research results.

[1193] The generated document will be converted to PDF format and will contain all the necessary information, such as the federal minimum wage of $7.25 per US labor law.

[1194] 6. Submission of Materials

[1195] The server sends the generated PDF to the user's smartphone.

[1196] Data is transmitted securely (HTTPS).

[1197] 7. Viewing and Downloading Materials

[1198] Users can view the PDF on their smartphone app and download or print it as needed.

[1199] Examples of concrete examples and prompts

[1200] Specific examples

[1201] For example, when a Japanese company expands into the US, the user can enter "USA, GDPR, labor law" into the app's input form. Based on this, the server will collect the latest information on the US GDPR and labor law, generate documents based on that information, and provide them to the user's smartphone.

[1202] Prompt Sentence Examples

[1203] As an example of text format, a user enters the following content into the app.

[1204] America

[1205] GDPR

[1206] Labor Law

[1207] This allows users to quickly and at low cost understand the legal risks in the country they are entering and efficiently obtain the necessary information. This system is particularly effective for security services, and supports users in quickly conducting risk assessments for legal compliance.

[1208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1209] Step 1:

[1210] Users enter the country or region they wish to expand into and the legal category they wish to research into an input form on the smartphone app. The user inputs specific keywords such as "America, GDPR, labor law." Once the input is complete, the device generates data to send this information to a cloud server.

[1211] Input: Country or region of operation, legal category

[1212] Output: Data to send to the cloud server

[1213] Step 2:

[1214] The device sends the information entered by the user to the cloud server. When the data is sent, the format of the entered data is checked and validation is performed to prevent formatting errors and input mistakes. If the data is in the correct format, it is sent to the server.

[1215] Input: What the user types

[1216] Output: Data sent to the server

[1217] Step 3:

[1218] The server receives the incoming information and activates generative artificial intelligence (OpenAI GPT-4 API) to research the laws and precedents of the specified country or region. The server then references various reliable legal databases to collect the necessary information and compile it as structured data.

[1219] Input: User-specified information

[1220] Output: Structured data of research results

[1221] Step 4:

[1222] The server stores the acquired research results in an internal database (MongoDB). The database is structured to include detailed information such as the content of the law, its implementation date, and related legal precedents. When saving, the server checks the integrity of the data and generates the necessary indexes.

[1223] Input: Research results

[1224] Output: Legal data stored in an internal database

[1225] Step 5:

[1226] Based on the saved research results, the server launches a document generation module and automatically generates a PDF document summarizing the legal risks associated with the expansion. This document lists the main risk factors and points that differ from those in Japan.

[1227] Input: Data from the internal database

[1228] Output: Automatically generated PDF document

[1229] Step 6:

[1230] The server then sends the generated PDF file to the user's smartphone via a secure method (HTTPS), using encoding and security protocols to prevent external access.

[1231] Input: PDF format documents

[1232] Output: PDF file sent to the user's device

[1233] Step 7:

[1234] The terminal displays the received PDF file to the user, who can then review it and download or print it as needed. The terminal also provides functions for managing the content of the document appropriately.

[1235] Input: Received PDF file

[1236] Output: Viewable and downloadable PDF file

[1237] Through the above processing steps, users can quickly and at low cost understand the legal risks of the country they are entering and obtain the necessary documents, which will enable them to smoothly proceed with their company's entry plans.

[1238] 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.

[1239] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[1240] Explanation of program processing

[1241] 1. User input

[1242] Using the input form on the device, users input the country or region they wish to expand into and the legal category they wish to research, for example, by entering keywords such as "America," "China," "labor law," and "tax law."

[1243] 2. Data transmission by the terminal

[1244] The terminal sends the information entered by the user to the server, where a simple format check is performed to prevent input errors.

[1245] 3. Server-based research

[1246] The server runs a generative artificial intelligence (AI) to research the laws and precedents of the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[1247] 4. Saving your research results

[1248] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[1249] 5. Sentiment analysis using an emotion engine

[1250] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[1251] 6. Automatically generate materials and adjust them based on emotions

[1252] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the research results based on the analysis results of the emotion engine. For example, if the user is anxious, it will prioritize presenting a summary of the risks.

[1253] 7. Submission of Materials

[1254] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[1255] 8. Displaying and downloading materials via terminal

[1256] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[1257] 9. Users can review the materials and download or print them as needed.

[1258] The user can check the displayed materials and download or print them as necessary, thereby obtaining specific information about the legal risks in the country where the user is entering.

[1259] Specific examples

[1260] For example, if a Japanese company is considering expanding into the United States and China, the user can request a survey by entering the keywords "America," "China," "labor law," and "tax law." The server then collects the latest information on labor and tax laws in both countries, generates a document detailing the legal risks of each country, and sends it to the user's device. If the emotion engine detects the user's impatience or anxiety, the server will prioritize generating a summary document that succinctly summarizes the risks. The user can review the document and use it to help make a decision about expanding into those countries.

[1261] This invention allows users to efficiently grasp the legal risks of the country they are entering at low cost, and enables them to obtain investigation results with speed and accuracy that could not be achieved with conventional methods. Furthermore, the introduction of an emotion engine enables flexible responses according to the user's psychological state, providing a better user experience.

[1262] The processing flow will be explained below.

[1263] Step 1:

[1264] The user enters the country or region they wish to enter and the legal category they wish to research into the input form on their device. For example, they enter keywords such as "America," "China," "labor law," and "tax law."

[1265] Step 2:

[1266] The device reviews the user's input and performs a quick check to ensure the format is correct: it checks whether the country name entered is spelled correctly and whether the legal category being investigated is included in an existing list.

[1267] Step 3:

[1268] The device sends the verified input to the server in the appropriate format, which includes the country or region of operation and the legal category.

[1269] Step 4:

[1270] The server analyzes the information received from the user and passes it to the generative AI research module, which includes selecting a database of laws and regulations for the input country or region.

[1271] Step 5:

[1272] The server launches generative artificial intelligence to research the latest laws and precedents in the specified country or region, for example, collecting the latest laws and precedents related to U.S. labor law from multiple reliable databases.

[1273] Step 6:

[1274] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[1275] Step 7:

[1276] The server activates the emotion engine and analyzes the user's emotions based on their input and usage. For example, if the user senses impatience or anxiety from their input, it will detect this.

[1277] Step 8:

[1278] The server launches the document generation module, which automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The method of presenting the research results and their details are adjusted based on the analysis results of the emotion engine. For example, if the user is anxious, a summary version that briefly summarizes the risks can be presented first.

[1279] Step 9:

[1280] The server converts the generated documents into PDF or Word format and sends them to the terminal in an encoded format, ensuring secure communication.

[1281] Step 10:

[1282] The terminal decodes the data received from the server and displays it to the user using a viewer, allowing the user to check the data.

[1283] Step 11:

[1284] The user can check the displayed materials and download or print them as necessary, enabling them to obtain specific information about the legal risks in the country they are entering.

[1285] Example 2

[1286] 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."

[1287] When a company expands overseas, it is difficult to quickly and cost-effectively research and prepare documents to identify legal risks in the country of entry. Furthermore, there are limited ways to tailor the way information is provided and research results are presented to suit the user's psychological state, resulting in a poor user experience. To solve these problems, efficient and flexible research and response methods are required.

[1288] 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.

[1289] In this invention, the server includes means including an emotion engine for analyzing the user's emotional state, means for researching the laws and precedents of a designated country or region using generative artificial intelligence, and means for adjusting the presentation method of materials based on the analysis results of the emotion engine. This enables flexible and rapid legal risk investigation and information provision according to the user's psychological state.

[1290] "User" refers to an entity that uses the system to investigate legal risks in the country where the company is expanding.

[1291] A "terminal" is a device used by a user, such as a computer, smartphone, or tablet.

[1292] "Server" means a central processing unit that runs the generative artificial intelligence and emotion engine and performs research based on user input.

[1293] "Generative AI" is AI that has the ability to generate appropriate information based on specified data.

[1294] "Laws" includes laws and regulations enacted by national or local government agencies.

[1295] "Precedent" includes past decisions and rulings made by the court.

[1296] "Research Results" includes data on laws and precedents obtained by generative artificial intelligence through research.

[1297] The "materials" are documents generated based on research results that provide a detailed summary of the legal risks associated with expanding into the country.

[1298] An "emotion engine" is a software module that analyzes a user's emotional state and adjusts how information is presented.

[1299] "Reception" is the process by which a terminal receives data or materials sent from a server.

[1300] "Display" means displaying the data or materials received by the terminal on the screen in a format that can be viewed by the user.

[1301] "Downloading" is the process of saving material to your device so that it can be accessed offline.

[1302] "Printing" is the process of outputting materials onto paper media from a terminal using a printer.

[1303] A "simple format check" is a process that verifies whether the information entered by the user conforms to a specified format.

[1304] This invention is a system that combines generative artificial intelligence and an emotion engine to quickly and inexpensively research and create documents on legal risks in a country or region where a company is expanding overseas. The system includes a means for a user to specify the country or region to expand into and the legal category to be researched, a means for a server to use generative artificial intelligence to research the specified laws and precedents, a means for automatically generating documents summarizing the legal risks related to the expansion based on the research results, a means for transmitting the documents to the user's terminal, and a means for displaying the documents received by the terminal. The system also includes a built-in emotion engine that recognizes the user's emotions and a means for adjusting the presentation method and details of the research results based on the user's emotions.

[1305] The system's program is structured as follows: First, the user is provided with an interface via their terminal to input the country or region they wish to enter and the legal category they wish to research. Once the user has entered the necessary information, it is sent to the server. The server then launches a generative artificial intelligence (e.g., OpenAI's GPT-4) to research the laws and precedents of the specified country or region. Multiple reliable legal databases (e.g., Westlaw, LexisNexis) are used as sources of research.

[1306] The research results are stored as structured data in an internal database, and the user's emotions are analyzed using an emotion engine (e.g., Microsoft Azure's Emotion API). For example, if the user is feeling anxious or impatient, the server will adjust the way the research results are presented based on that information, providing the information in a format that is easy for the user to understand. Finally, a document generation module automatically generates a document summarizing legal risks based on the research results, converts it to PDF or Word format, and sends it to the device. During this process, AES encryption technology is used to ensure communication security.

[1307] The terminal decodes the transmitted material and displays it to the user using viewer software, allowing the user to review the material in detail and download or print it as desired.

[1308] As a concrete example, consider the case where a Japanese company is considering expanding into the United States and China. The user enters keywords such as "America," "China," "labor law," and "tax law" into their device. The server uses this information to comprehensively research the specified laws and precedents and generates a document summarizing the legal risks in detail. If the emotion engine detects the user's impatience, the server generates a summary document that succinctly summarizes the risks and provides it to the user. Based on this document, the user can quickly obtain specific information to help them make a decision about expanding into the country.

[1309] An example prompt sentence would be entered as follows:

[1310] "A Japanese company is considering expanding into the United States and China. Please research the latest laws and precedents regarding American labor and tax laws, as well as Chinese labor and tax laws."

[1311] In this way, the present invention allows users to grasp the legal risks of the country they are entering efficiently and at low cost, and the emotion engine enables flexible responses according to the user's psychological state.

[1312] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1313] Step 1:

[1314] The user uses the input form on the device to input the country or region they are expanding into and the legal category they are investigating. Specifically, they enter keywords such as "America," "China," "Labor Law," and "Tax Law." This information is provided to the device as input. The input form checks the input in real time, checking for typos and formatting errors, and provides feedback to the user.

[1315] Step 2:

[1316] The terminal sends the information entered by the user to the server. A simple format check is performed to ensure the input conforms to the specified format. During this process, the input data is checked for errors, and if it is not in the correct format, an error message is returned to the user. If the format is correct, the input data is sent to the server.

[1317] Step 3:

[1318] The server launches a generative artificial intelligence (e.g., OpenAI's GPT-4) and researches the laws and precedents of the specified country or region based on the input data it receives. Specifically, the server first connects to the Internet and collects relevant information from multiple reliable legal databases (e.g., Westlaw, LexisNexis). The results of this research are stored in a database. Based on the keywords provided as input data, the generative AI searches for relevant information and generates research results as output.

[1319] Step 4:

[1320] The server stores the research results in an internal database, which is maintained in a structured data format and includes information such as the content of the law, its implementation date, relevant legal precedents, and citation sources. During this storage process, the data is indexed for efficient access.

[1321] Step 5:

[1322] The server launches an emotion engine (e.g., Microsoft Azure's Emotion API) and analyzes the user's emotions based on their input and usage. The analysis is performed based on input text, operation speed, click patterns, etc. If emotions such as impatience or anxiety are detected as a result of the analysis, that information is tagged and used for the next step.

[1323] Step 6:

[1324] The server launches a document generation module and automatically generates documents summarizing the legal risks associated with the expansion based on the research results. The server adjusts the presentation method and details of the documents based on the analysis results of the emotion engine. For example, if it detects that the user is anxious, it will prioritize generating a summary version that summarizes the information concisely. The generated documents are then converted into PDF or Word format.

[1325] Step 7:

[1326] The server encodes the generated data and sends it to the terminal. The encoding uses AES encryption technology to ensure the security of the communication, thereby protecting the privacy of user data.

[1327] Step 8:

[1328] The terminal decodes the material received from the server and displays it to the user using the appropriate viewer software, which allows the user to zoom, scroll, add annotations, etc., allowing the user to examine the material in detail.

[1329] Step 9:

[1330] Users can check the displayed materials and download or print them as needed. Download and print buttons are displayed on the device, allowing these operations to be performed with a single click. Downloaded materials can also be accessed offline.

[1331] (Application example 2)

[1332] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1333] In the past, companies needed to investigate legal risks when expanding overseas, which was time-consuming and costly. Furthermore, because information was provided uniformly without taking into account the user's emotional state, there was a problem in that the information provided could not be appropriate for the user's psychological state. In particular, for companies that provide security services, it is important to understand the legal risks of each country, and it is required that such investigations be carried out quickly and efficiently.

[1334] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to specify the country or region to enter and the legal category to be investigated, means for researching the laws and precedents of the specified country or region using generative artificial intelligence, means for automatically generating materials summarizing the legal risks related to the entry based on the research results, and means for analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of the materials based on that. This enables flexible legal risk investigation and provision of materials according to the user's psychological state, enabling quick and efficient information gathering and appropriate decision-making.

[1335] "Means for users to specify the country or region they wish to expand into and the categories of laws and regulations to be investigated" refers to an interface or input system that allows users to input or select the specific country or region and the type of laws and regulations they wish to investigate when a company expands overseas.

[1336] "Means for researching laws and precedents of designated countries or regions using generative artificial intelligence" refers to algorithms and software designed to use generative artificial intelligence (AI) to search for and collect laws and precedents related to countries or regions designated by users.

[1337] "Means for automatically generating documents summarizing legal risks related to expansion based on research results" refers to a system that automatically generates documents that systematically summarize legal risks related to a company's expansion destination based on information collected by AI.

[1338] "A means of analyzing the user's emotional state using an emotion engine and adjusting the presentation method and details of materials based on that" refers to a system that analyzes the user's input and behavior, identifies the emotions the user is feeling (anxiety, impatience, etc.), and changes the way research results and materials are displayed depending on those emotions.

[1339] This invention uses a system that combines generative artificial intelligence (AI) and an emotion engine to quickly and inexpensively investigate legal risks in the country of expansion and to assist in the creation of documents when a company expands overseas. An embodiment of this invention is described below.

[1340] System configuration

[1341] The system consists of the following major components:

[1342] 1. User Input Interface:

[1343] Users use an input form on their device (smartphone, tablet, PC, etc.) to input the country or region they are entering and the legal category they are investigating. This specifies the legal information of the country or region they are entering into the system.

[1344] 2. Data transmission module:

[1345] The information entered by the user is sent from the terminal to the server, where a simple format check is performed to prevent input errors.

[1346] 3. Generative Artificial Intelligence (AI) Module:

[1347] The AI ​​module installed on the server researches the laws and relevant precedents of the country or region specified by the user, collecting the latest information from reliable databases and websites.

[1348] 4. Research Results Storage Module:

[1349] The server stores the research results as structured data in an internal database, including the content of the law, its implementation date, and related legal precedents.

[1350] 5. Emotion Engine Module:

[1351] The emotion engine analyzes the user's emotions based on their input and system usage, detecting and responding to emotions such as anxiety and impatience.

[1352] 6. Document generation module:

[1353] Based on the research results and the analysis results of the emotion engine, the server automatically creates a document summarizing the legal risks associated with the move in. If the user feels anxious, the server adjusts the details of the document and the way it is presented, for example, by creating a summary version of the document that briefly summarizes the risks, depending on the user's emotions.

[1354] 7. Data transmission and display module:

[1355] The generated documents are sent to the terminal in PDF or Word format and displayed on the terminal, where the user can review them and download or print them as needed.

[1356] Processing Description

[1357] In this system, users first enter the country or region they wish to enter and the legal category into an input form on their device. This information is sent to the server, and the generative AI researches the laws and related precedents based on the specified conditions. The research results are stored in an internal database.

[1358] Next, the emotion engine analyzes the user's emotions based on their input and system usage, and generates documents that reflect the user's psychological state. Based on the research results and the emotion engine's analysis, the server automatically generates documents summarizing the legal risks associated with the expansion and sends them to the user's device. The user can review the documents and download or print them as needed.

[1359] Specific examples

[1360] For example, if a Japanese company providing security services is looking to expand into the US, the user would input "USA" and "security law." Based on this information, the server would research the latest US security regulations and generate materials. If the emotion engine detects the user's impatience, it will prioritize generating a concise summary of the information, providing information appropriate to the user's psychological state.

[1361] Example of an input prompt for a generative AI model:

[1362] Research the latest in international security regulations.

[1363] This invention allows companies to quickly and efficiently grasp the legal risks of the country they are entering, and to obtain investigation results with speed and accuracy that were not possible with conventional methods.In addition, the introduction of an emotion engine enables flexible responses based on the user's psychological state, providing a better user experience.

[1364] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1365] Step 1:

[1366] The user enters the country or region they are entering and the legal category they are investigating into an input form on their device. For example, input contents could be "America" ​​and "Security Law." The input data is sent to the system. This input includes information specified by the user.

[1367] Step 2:

[1368] The device sends the information entered by the user to the server. At this time, a simple format check is performed to ensure the input is valid. After confirming that the input is in the correct format, the information is forwarded to the server. Input: Country and legal category entered by the user. Output: Data sent after validity check.

[1369] Step 3:

[1370] The server uses a generative AI model to research the laws and related precedents of the specified country or region. The server searches for the latest information from multiple reliable databases and related websites to collect the necessary data. Input: Country and legal category specified by the user. Output: Research data.

[1371] Step 4:

[1372] The server stores the research results in an internal database. The stored data includes the content of the law, the date of enforcement, and related legal precedents. This data is used for subsequent processing. Input: Researched data, Output: Research results stored in the database.

[1373] Step 5:

[1374] The emotion engine analyzes the user's emotions based on the user's input and system usage. The emotion engine detects emotions such as impatience or anxiety, and performs further processing based on the results. Input: User input data, Output: Analyzed emotional state.

[1375] Step 6:

[1376] The server uses a document generation module to automatically generate documents based on the research results and the analysis results of the emotion engine. The format and details of the documents are adjusted based on the emotion analysis results. For example, if the user is feeling anxious, a summary document that briefly summarizes the risks will be created first. Input: Research results and emotion analysis results, Output: Automatically generated documents.

[1377] Step 7:

[1378] The server converts the generated documents into PDF or Word format and sends them to the terminal. The documents are encoded to ensure communication security. Input: Generated documents, Output: Sent document file.

[1379] Step 8:

[1380] The terminal decodes the data received from the server and displays it to the user. The user can check the data and download or print it as needed. Input: Data file sent from the server. Output: Data that can be displayed and downloaded.

[1381] Examples:

[1382] For example, if a Japanese company providing security services is looking to expand into the US, the user would enter "America" ​​and "security law," which would be step 1. In step 2, this input data is sent to the server. In step 3, the server uses a generative AI model to collect the latest information on US security laws. In step 4, this information is stored in an internal database. In step 5, an emotion engine analyzes emotions from the user's input, and in step 6, a document is automatically generated based on the results. In step 7, the document is sent to the device, and in step 8, the user reviews and downloads the document.

[1383] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1384] 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.

[1385] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1386] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1387] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1388] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1389] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1390] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1391] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1392] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1393] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1394] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1395] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1396] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1397] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1398] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1399] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1400] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1401] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1402] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1403] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1404] The following is further disclosed regarding the above embodiment.

[1405] (Claim 1)

[1406] A means for users to specify the country or region they wish to enter and the legal category they wish to investigate;

[1407] A means for the server to use generative artificial intelligence to research the laws and precedents of designated countries and regions;

[1408] The server automatically generates documents summarizing legal risks related to expansion based on the research results, and

[1409] means for transmitting the server-generated materials to a user's terminal;

[1410] means for displaying the material received by the terminal;

[1411] A system including:

[1412] (Claim 2)

[1413] 10. The system of claim 1, further comprising means for performing a simple format check on the content of a request entered by a user.

[1414] (Claim 3)

[1415] 10. The system of claim 1, wherein the server further comprises means for storing the research results in an internal database.

[1416] "Example 1"

[1417] (Claim 1)

[1418] means for a user to specify the geographic region to be entered and the regulatory category to be investigated;

[1419] A means for the server to use generative artificial intelligence to search for regulations and cases in a specified area;

[1420] A means for the server to automatically generate documents summarizing regulatory risks related to expansion based on the exploration results;

[1421] means for transmitting the server-generated materials to the user's information processing device;

[1422] means for displaying the material received by the information processing device;

[1423] A system including:

[1424] (Claim 2)

[1425] 10. The system of claim 1, further comprising means for performing a simple format check on the content of a request entered by a user.

[1426] (Claim 3)

[1427] 10. The system of claim 1, further comprising means for the server to store the probe results in an internal database.

[1428] "Application Example 1"

[1429] (Claim 1)

[1430] A means for users to specify the country or region they wish to enter and the legal category they wish to investigate;

[1431] A means for the server to use generative artificial intelligence to research the laws and precedents of designated countries and regions;

[1432] The server automatically generates documents summarizing legal risks related to expansion based on the research results, and

[1433] means for transmitting the server-generated materials to a user's terminal;

[1434] means for displaying the material received by the terminal;

[1435] A means for providing an input form for inputting information on a country, region, or legal category designated by a user;

[1436] a data transmission means for transmitting input information to a cloud server;

[1437] A means of researching input country, region and legal category information using generative artificial intelligence and storing the acquired data in an internal database;

[1438] A method to generate a document summarizing the legal risks related to expansion from the research results and create it as a PDF document,

[1439] A means to send the generated PDF to the user's device,

[1440] A way for users to view, review, and download the PDF on their device;

[1441] A system including:

[1442] (Claim 2)

[1443] 10. The system of claim 1, further comprising means for performing a simple format check on the content of a request entered by a user.

[1444] (Claim 3)

[1445] 10. The system of claim 1, wherein the server further comprises means for storing the research results in an internal database.

[1446] "Example 2: Combining Emotion Engines"

[1447] (Claim 1)

[1448] A means for users to specify the country or region they wish to enter and the legal category they wish to investigate;

[1449] A means for the server to use generative artificial intelligence to research the laws and precedents of designated countries and regions;

[1450] The server automatically generates documents summarizing legal risks related to expansion based on the research results, and

[1451] means for transmitting the server-generated materials to a user's terminal;

[1452] means for displaying the material received by the terminal;

[1453] means for the server to include an emotion engine for analyzing the user's emotional state;

[1454] A means for the server to adjust the presentation method of the material based on the analysis result of the emotion engine;

[1455] a means for the device to enable downloading and printing of materials;

[1456] A system including:

[1457] (Claim 2)

[1458] 10. The system of claim 1, further comprising means for performing a simple format check on the content of a request entered by a user.

[1459] (Claim 3)

[1460] 10. The system of claim 1, wherein the server further comprises means for storing the research results in an internal database.

[1461] "Application example 2 when combining emotion engines"

[1462] (Claim 1)

[1463] A means for users to specify the country or region they wish to enter and the legal category they wish to investigate;

[1464] A means for the server to use generative artificial intelligence to research the laws and precedents of designated countries and regions;

[1465] The server automatically generates documents summarizing legal risks related to expansion based on the research results, and

[1466] means for transmitting the server-generated materials to a user's terminal;

[1467] means for displaying the material received by the terminal;

[1468] a means for analyzing a user's emotional state using an emotion engine and adjusting the presentation and details of the material based on the analysis;

[1469] A system including:

[1470] (Claim 2)

[1471] 10. The system of claim 1, further comprising means for performing a simple format check on the content of a request entered by a user.

[1472] (Claim 3)

[1473] 10. The system of claim 1, wherein the server further comprises means for storing the research results in an internal database. [Explanation of symbols]

[1474] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for users to specify the country or region they wish to enter and the legal category they wish to investigate; A means for the server to use generative artificial intelligence to research the laws and precedents of designated countries and regions; The server automatically generates documents summarizing legal risks related to expansion based on the research results, and means for transmitting the server-generated materials to a user's terminal; means for displaying the material received by the terminal; A system including:

2. 2. The system according to claim 1, further comprising means for performing a simple format check on the content of the request entered by the user.

3. 10. The system of claim 1, wherein the server further comprises means for storing the research results in an internal database.

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