system

Abstract

We provide the system. [Solution] A computer that includes a source of information that regularly updates legal information and past case law information, A means of digitizing on-site events and generating them as instruction documents, A means for generating advice based on the command statement, using multiple generative AI models, each acting as an assistant, A means of exchanging and discussing the advice generated by each assistant to form the optimal solution, A means of finalizing the agreed-upon response plan, A system installed on smart devices that provides a means to deliver immediate legal decisions on-site.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] A judge needs to quickly and accurately process extensive legal knowledge and a vast amount of past case information, which is a heavy burden. Also, it is difficult to completely eliminate a judge's personal preconceptions and biases, and ensuring fairness is an issue. The present invention solves these problems and provides a system for making fair and unbiased judgments in a trial.

Means for Solving the Problems

[0005] This invention includes a server with a database that periodically updates legal information and past case precedents, and a means for digitizing court records and generating prompts. Furthermore, it utilizes multiple generative AI models as agents, with each agent generating and exchanging opinions based on the prompts, and forming a draft judgment through deliberation. The final draft judgment is then finalized and reported to the court. This configuration makes it possible to improve fairness and efficiency in trials.

[0006] "Legal information" is a general term for information such as laws, articles, and ordinances that are referenced in trials and legal judgments.

[0007] "Past case law information" refers to records of judgments in past trials and the legal decisions that formed the basis of those judgments.

[0008] A "database" is a digital information aggregation system built to effectively manage and retrieve information.

[0009] A "server" is a computer system that provides information and services over a network.

[0010] "Court records" is a general term for all records and information related to a trial, including documents, papers, and testimonies.

[0011] "Digitalization" is the process of converting analog information into digital data that can be processed by a computer.

[0012] "Prompt" is a term that refers to the tasks or instructions given to an AI as input.

[0013] A "generative AI model" is a machine learning model designed to automatically generate appropriate outputs for specific inputs.

[0014] An "agent" refers to a program that independently performs a specific task or function, and in this case, an AI model fulfills that role.

[0015] "合议" refers to a process in which multiple members reach a common conclusion or decision through discussion.

[0016] "Judgment draft" refers to a provisional conclusion indicating the final legal judgment in a lawsuit.

[0017] "Report" is a document that summarizes specific information or results and is created for the purpose of communicating with interested parties.

Brief Description of Drawings

[0018] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which multiple emotions are mapped. [Figure 10] It shows an emotion map to which multiple emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12]It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when combined with an emotion engine. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when combined with an emotion engine.

Mode for Carrying Out the Invention

[0019] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0020] First, the terms used in the following description will be explained.

[0021] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), APU (Accelerated Processing Unit), and the like.

[0022] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0023] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0024] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0025] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0026] [First Embodiment]

[0027] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0028] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0029] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0030] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0031] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0033] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0034] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0036] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0037] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0038] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0039] This invention is an AI agent-based court judgment system that utilizes legal information and past case precedents. To realize this, the server, terminals, and users work together to operate the system as follows.

[0040] The server first periodically updates legal information and past case precedents, and stores them in a database. This information is all the data that the generating AI model agent needs in the context of a trial.

[0041] Users use their devices to convert court-related documents, evidence, and witness testimonies into digital format and send them to a server. These digitized court records are analyzed on the server and provided to an AI agent as prompts.

[0042] The server prompts agents to exchange opinions and reach a consensus based on prompts. Each agent generates an individual opinion using the provided legal information and past case law. This allows multiple AI agents to grasp the overall picture of the trial and engage in discussions to reach a fair judgment.

[0043] The draft judgment, formed through discussions among agents, is finalized via the server and reported to the court. Users then consider adopting this report as their final court decision. This system enhances objectivity and fairness in the judicial process and enables faster judgments.

[0044] As a concrete example, consider a murder trial. The server provides the agent with precedents from similar past cases and relevant laws. The agent identifies several possibilities based on the details of the case and discusses which judgment would be appropriate in accordance with current laws. As a result, an unbiased and objective draft judgment is created.

[0045] The following describes the processing flow.

[0046] Step 1:

[0047] The server collects the latest legal information and past case law information from the internet and relevant databases, and stores it in its internal database. This data is updated regularly to ensure that the AI ​​agent always makes decisions based on the most up-to-date information.

[0048] Step 2:

[0049] Users upload all court documents, evidence, and testimonies as digital data to the server using their devices. This includes scanning documents and transcribing audio into text.

[0050] Step 3:

[0051] The server analyzes the uploaded digital data and generates prompts for the AI ​​agent. These prompts include court records such as a case summary, evidence list, and witness testimonies.

[0052] Step 4:

[0053] The server sends the generated prompt to multiple AI agents. Each AI agent generates an opinion based on the prompt and independently forms an initial draft judgment.

[0054] Step 5:

[0055] AI agents exchange opinions via a server. Each agent receives feedback on the opinions of other agents and modifies its own views as needed.

[0056] Step 6:

[0057] Through discussions among the agents, an agreement on the draft judgment is reached. The agreed-upon draft judgment is reported to the server as the final judgment.

[0058] Step 7:

[0059] The server automatically generates the agreed-upon judgment as a final report and provides it to the user, a court-related party. This report includes the basis for the judgment and a record of the exchange of opinions among the agents.

[0060] (Example 1)

[0061] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0062] In the traditional judicial process, there has been a challenge in ensuring fairness and objectivity in trials while simultaneously delivering swift judgments. In particular, the difficulty in efficiently utilizing vast amounts of legal information and past precedents has led to lengthy decision-making processes and increased costs.

[0063] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0064] In this invention, the server includes means including an information storage device that periodically updates legal information and past case law information; processing means that digitizes materials related to a trial and generates them as input instructions; and processing means that uses multiple generating artificial intelligence models as intermediary devices to generate opinions based on the input instructions. This makes it possible to make quick and objective judgments based on data of laws and precedents.

[0065] An "information storage device" is a data management device for storing legal information and past case law information, and for periodically updating it.

[0066] An "information processing device" is a primary device used to process legal information and manage and analyze various types of digitized data.

[0067] "Processing means" refers to a technical method or device used to perform a specific function or task.

[0068] "Input instructions" refer to the presentation of information to organize court-related information and provide it to a generative artificial intelligence model.

[0069] A "generative artificial intelligence model" is a type of artificial intelligence technology used to generate judgments and opinions based on provided data.

[0070] A "mediating device" is a function or device that plays a central role in facilitating the exchange of various types of information and the aggregation of opinions using a generated artificial intelligence model.

[0071] "Viewpoint" refers to judgments or opinions generated based on the information provided.

[0072] "Judgment" refers to the final conclusion or decision formed based on various pieces of information.

[0073] A "report document" is a document prepared for judicial institutions to explain the results of a ruling.

[0074] "Judge" refers to an individual or institution that has the authority to make judicial decisions.

[0075] An embodiment of the present invention is a court judgment support system based on legal information and past case law information. This system is operated by coordinating an information processing device and a terminal device.

[0076] The server first functions as an "information storage device," storing legal information and past case precedents. It also periodically updates this information as an "information processing device," ensuring that necessary data is always up-to-date. Specifically, it retrieves data from online legal information platforms. An example of such a platform is a legal information retrieval system commonly used in the industry.

[0077] Users digitize court-related documents using a terminal. They convert documents, evidence, and witness testimonies into digital format using a scanner and speech recognition software connected to the terminal. This process utilizes common document digitization software and speech recognition tools.

[0078] The digitized documents on the terminal are sent to the server. The server analyzes the received data and uses it as a prompt for the generating AI model. An example of a prompt might be, "Based on the following documents related to the trial, please generate a draft judgment considering the relevant laws and past precedents."

[0079] The server uses these prompts to run multiple generative artificial intelligence models. Each AI model generates insights based on the assigned prompt. The generative artificial intelligence models can utilize software with mature generative algorithms.

[0080] This will enable users to achieve greater fairness and efficiency in legal decisions and the judicial process. It is expected that legal work will be carried out more quickly and accurately through the use of this system.

[0081] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0082] Step 1:

[0083] The server retrieves legal and case law information from an online legal information service. It receives update commands for already stored legal information as input. The server retrieves this update information and stores it in the information storage device. This ensures the database always maintains the latest legal information. The output is the updated legal information database. Each data item is organized by category in preparation for subsequent processing.

[0084] Step 2:

[0085] Users digitize court-related documents using a terminal. Input includes paper documents, evidence, and audio testimonies. The terminal converts documents to PDF or image formats via a scanner and converts audio to text using speech recognition software. The output is a digitized court document file, which is sent to a server.

[0086] Step 3:

[0087] The server receives digitized documents submitted by users. It accepts multiple digital files as input. The server uses natural language processing techniques to analyze the document content and extract key keywords and evidence. The output is a prompt message for a generative AI model, containing a summary of the trial and relevant legal matters.

[0088] Step 4:

[0089] The server sends prompts to multiple generative AI models. The input, in the form of a prompt statement, contains information including a case summary, relevant laws and regulations, and past precedents. Based on this, the AI ​​models process the data to generate opinions and predicted judgments. The output is a generated document containing the opinions of each AI model.

[0090] Step 5:

[0091] The server aggregates the outputs from the AI ​​models and verifies the consistency of their opinions. The input consists of each AI model's proposed judgment. The server integrates these to generate the most appropriate ruling. It then creates a final report. The output is a carefully prepared report for the court. This report is provided to the user and serves as important reference material for court decisions.

[0092] (Application Example 1)

[0093] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0094] There is a need to provide swift and appropriate legal judgments in various situations that arise on the ground, but current methods make it difficult to make quick decisions based on legal information and past precedents. Therefore, a support system is needed to enable on-site personnel to take appropriate action immediately.

[0095] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0096] In this invention, the server includes a computer containing a source of information that periodically updates legal information and past case law information, means for digitizing on-site events and generating them as command statements, and means installed on a smart device to provide immediate legal judgments on-site. This makes it possible to make legal judgments quickly on-site.

[0097] "Legal information" refers to data and materials related to the law, and includes relevant information such as precedents and legal provisions.

[0098] "Past case law information" refers to records and judgments from past trials, and is information that can be used as a reference for legal decisions.

[0099] A "directive document" is a digitized instruction or command document used when making legal decisions in a specific situation.

[0100] A "generative AI model" is a type of artificial intelligence designed to perform a specific task, and it is an algorithm that generates appropriate output from input information.

[0101] An "assistant" is a system element that uses a generative AI model to assist in performing specific tasks.

[0102] "Consensus" refers to discussions and consultations aimed at reconciling multiple opinions and finding the optimal solution.

[0103] A "smart device" refers to a portable terminal that has internet connectivity and can run a variety of applications, and includes smartphones and tablets.

[0104] "Immediate legal judgment" refers to the act of making a swift and appropriate judgment based on laws and regulations in a given situation.

[0105] To realize this application, the server periodically updates legal information and past case precedents, maintaining them as information sources. It also digitizes on-site events via smart devices, generates them as command statements, and transmits them. The generated command statements are used as foundational information to provide specific legal judgments using a generative AI model.

[0106] The terminal captures events at the scene and quickly transmits them to the server. This enables real-time information processing and supports appropriate decision-making at the scene.

[0107] Users can use their smart devices to receive legal judgments provided by the server and apply them to on-site responses. Through this process, users can take appropriate legal action immediately.

[0108] The generative AI model uses multiple assistants to generate relevant legal advice based on the given instructions. Through deliberation among the assistants, the optimal course of action is formed and provided to the user.

[0109] For example, if a security guard spots a suspicious person in a commercial facility, they can input the incident details into their smartphone, and the server will provide relevant legal information to the AI, which will then suggest a legally appropriate course of action.

[0110] Example prompt for the generating AI model: "Immediately provide legal responses to intruders at the facility. Suggest appropriate actions based on past intrusion case precedents and relevant laws."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] The server regularly updates its database with legal information and past case precedents. This information is collected from external legal databases and stored in the server's storage system. This ensures that the latest legal resources are always available for use by the generative AI model. The input is legal data obtained from external sources, and the output is the updated internal database.

[0114] Step 2:

[0115] The terminal digitizes events at the scene and inputs detailed information. Users use smart devices to input incident details via text or voice. This data is formatted and sent to the server. The input is the incident details provided by the user, and the output is the digitized data sent to the server.

[0116] Step 3:

[0117] The server generates prompts from the digitized data received from the terminal. These generated prompts are used as foundational information for subsequent AI processing. This step cleanses and structures the data, facilitating processing by the AI ​​model. The input is digitized incident information, and the output is the generated prompts.

[0118] Step 4:

[0119] The generative AI model generates relevant legal advice based on prompt messages received from the server. The AI ​​model generates the most appropriate legal judgment by referring to an internal legal information database. The input consists of prompt messages and legal information, while the output is the legal advice generated by each AI assistant.

[0120] Step 5:

[0121] The server aggregates legal advice generated by multiple assistants and forms an optimal response plan through deliberation. It weights and prioritizes each assistant's opinion to select the most appropriate plan. The input is multiple legal advice, and the output is the agreed-upon optimal response plan.

[0122] Step 6:

[0123] The user receives the optimal response plan from the server and confirms it via a smart device. This allows the user to take appropriate legal action quickly on-site. The input is the response plan sent from the server, and the output is the specific action to be taken on-site.

[0124] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0125] This invention is a court judgment system that combines legal information and past case law information with an emotion engine that recognizes the user's emotions. The operation of this system is carried out through the cooperation of the server, terminal, and user.

[0126] The server continuously updates legal information and case law data, storing it in a database. This provides the foundation for AI agents to always make decisions based on the latest information.

[0127] Users digitize court documents, evidence, and testimonies and upload them from their devices to a server. This digital data includes not only text but also video and audio. The uploaded data is analyzed on the server and compiled into prompts for the AI ​​agent.

[0128] This process incorporates an emotion engine. The emotion engine recognizes the emotions of witnesses and those involved through audio and video analysis, and includes this information in the data. This emotional information is treated as a factor to consider when generating prompts.

[0129] The generated prompts are provided to multiple AI agents, and each agent forms an opinion based on them. Because the opinions generated by the AI ​​agents take recognized emotional information into consideration, more multifaceted judgments are possible. In opinion exchanges and discussions among agents, emotional information is also incorporated as a factor in reaching a consensus.

[0130] Ultimately, the agreed-upon judgment is automatically generated as a report for the court via the server. This report includes, in addition to the legal basis, supplementary emotional data recorded by the emotional engine. This helps judges and stakeholders gain a deeper understanding of the case's context.

[0131] As a concrete example, consider a trial concerning domestic violence. In this case, the audio and video of the witnesses are analyzed by an emotion engine to recognize feelings of tension and fear. This emotional information becomes an important element in judging and is taken into consideration by an AI agent. In this way, the present invention realizes a system that supports trials from both legal and human emotional perspectives.

[0132] The following describes the processing flow.

[0133] Step 1:

[0134] The server collects legal information and past case law data from the internet and related databases, and stores it in a database. This data forms the basis for the decisions of the generative AI model and is updated regularly.

[0135] Step 2:

[0136] Users use their devices to convert court records into digital format and upload them to the server. These court records include scanned images of documents, as well as audio and video.

[0137] Step 3:

[0138] The server analyzes the uploaded digital data. During this process, it uses an emotion engine to analyze the emotions of witnesses and related parties from audio and video, and extracts emotional information.

[0139] Step 4:

[0140] The server generates prompts for the AI ​​agent based on the analysis. These prompts include legal information, case law information, court records, and sentiment information.

[0141] Step 5:

[0142] The server provides the generated prompt to multiple AI agents, and each agent generates its own opinion based on this prompt. The generated opinion takes into account recognized sentiment information.

[0143] Step 6:

[0144] AI agents exchange opinions, incorporating emotional information, and proceed through a deliberative process to construct a draft judgment. This process involves adjusting opinions and clarifying points of contention in order to reach an agreement.

[0145] Step 7:

[0146] The agreed-upon judgment draft is automatically generated by the server as a final report. This report includes the legal basis for the judgment, precedents, and perceived sentiment information.

[0147] Step 8:

[0148] Judges and lawyers, who are users of the system, review the final reports provided by the server to help them make their final decisions. The reports include detailed emotional information to deepen their understanding of the case's context.

[0149] (Example 2)

[0150] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0151] In the decision-making process in court, it is necessary to handle legal information and past precedents quickly and accurately. However, the current system has challenges in that it does not adequately update relevant information and process sentiment information, resulting in insufficient multifaceted support for decision-making.

[0152] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0153] In this invention, the server includes means for continuously updating and accumulating legal information and past case law information, means for converting evidence and testimonies into digital information and processing them, and means for recognizing emotions and incorporating them into relevant data. This enables multifaceted and comprehensive support in the decision-making process.

[0154] "Legal information" refers to the collective term for articles of law, statutes, regulations, and related information.

[0155] "Case law information" refers to information about cases decided in court in the past, and includes data on judgments and their interpretations.

[0156] "Information aggregation" refers to the process of continuously collecting and storing data and information necessary for a specific purpose.

[0157] "Evidence" refers to any form of information, such as documents, photographs, and physical evidence, provided in court to prove the facts.

[0158] "Digital information" refers to information data in a form that can be handled by a computer, and includes formats that can be stored, transferred, and processed electronically.

[0159] "The process of recognizing emotions and incorporating them into related data" refers to the process of analyzing audio and video to extract emotional states and processing them together with other data.

[0160] The "decision-making process" is the process of making a final decision after going through a series of steps to find a solution to a particular problem.

[0161] "Comprehensive support" refers to assistance and support provided by taking into account multiple aspects and needs as a whole.

[0162] This invention is a court support system that processes legal information and past case law information, and is operated collaboratively by a server, terminals, and users. The server is responsible for continuously acquiring and updating legal information and case law information and storing it in a database. This provides a foundation for always utilizing the latest information within the system.

[0163] Users digitize documents and evidence necessary for trials and upload them to the server via their devices. The digitized data can take various forms, including text, audio, and video. The server analyzes this data and generates prompts for use by a generative AI model. This process utilizes natural language processing and image recognition technologies.

[0164] Furthermore, emotion recognition software embedded in the server analyzes audio and video to extract emotional information and incorporate it into the analysis data. This provides the generative AI model with a multifaceted perspective that takes emotional information into account when forming opinions.

[0165] As a concrete example, consider a trial dealing with domestic disputes. In the process of digitizing the audio and video of witnesses on a terminal and analyzing them on a server, the emotion engine extracts emotions such as fear and tension. This information is used by the AI ​​agent to make the best possible decisions.

[0166] An example of a prompt message from this system would be, "Analyze the testimony regarding the domestic dispute and form your judgment considering the perceived emotional information." This system integrates legal information with human emotions to enable more objective and detailed legal support.

[0167] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0168] Step 1:

[0169] Users prepare court-related documents and evidence, and digitize this information using a terminal. Users convert documents into image data using scanners and cameras, and prepare testimonies as digital audio or video data using audio and video recording devices. These digital data are then uploaded from the terminal to a server. Physical documents, audio, and video are used as input, and digital data files are generated as output.

[0170] Step 2:

[0171] The server receives uploaded digital data and performs analysis using natural language processing and image recognition technologies. The server extracts text data, detects important scenes from video data, and transcribes audio data. Through this analysis process, prompt sentences are generated for use by the AI ​​agent. Digital data files are used as input, and the analyzed information and prompt sentences are generated as output.

[0172] Step 3:

[0173] The emotion recognition software embedded in the server analyzes audio and video from digital data to extract the emotional state of the speaker or character. It evaluates elements such as tone of voice, facial expressions, and gestures to identify emotional information. This information is added to the analysis data, forming the basis for the AI ​​agent to make multifaceted judgments. Audio and video data are used as input, and emotional information is generated as output.

[0174] Step 4:

[0175] The server provides prompt text and attached sentiment information to multiple generative AI models (agents). Each agent forms an opinion based on the provided information, considering legal and emotional factors. Opinions are exchanged among the agents, and a final opinion is aggregated through consensus. Prompt text and sentiment information are used as input, and a collective opinion is generated as output.

[0176] Step 5:

[0177] The server automatically generates reports for the court based on opinions determined by the AI ​​agent. These reports include not only legal grounds but also emotional information as background to the judgment. The reports are created in digital format and provided to judges and other relevant parties. Collective opinions are used as input, and the reports are generated as output.

[0178] (Application Example 2)

[0179] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0180] The current judicial judgment system allows for decisions based on legal information and past precedents, but it struggles to make multifaceted judgments that take into account the emotional states of those involved. Furthermore, even in enhancing security at public facilities, the system lacks the ability to analyze visitors' emotions in real time and detect anomalies. This makes it difficult to gain a deeper understanding of the background of an incident and to respond quickly to unusual situations.

[0181] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0182] This invention includes an information processing device that periodically updates legal data and past case precedent data, a mechanism that digitizes court records and generates them as prompts, and a method for analyzing visitors' emotional states in real time and detecting anomalies. This improves the quality of legal judgments and strengthens security management.

[0183] "Legal data" refers to a collection of information including the latest legal information and related laws and regulations, which forms the basis for the system to make legal decisions.

[0184] "Past case data" refers to records of past judicial decisions, which are referenced by the system when generating opinions based on similar cases.

[0185] An "information processing device" is a computer system for storing and updating legal data and past case law data, and is an element for performing analytical processing.

[0186] "Digitalization" is the process of converting information in analog format into electronic data, and it is a method that enables data storage and analysis.

[0187] A "prompt" is a format of text or data that acts as a trigger when providing information to an AI module, and it plays a role in inducing the generation of opinions.

[0188] A "generative AI module" is a group of artificial intelligence programs that generate opinions and judgments based on prompts, and has the function of making decisions within the system.

[0189] A "knowledge processing unit" is an information processing unit used by a generative AI module when forming specific opinions, and it is the foundation for deriving the optimal opinion through deliberation.

[0190] "Visitor's emotional state" refers to an individual's psychological state analyzed from audio and video, and serves as an indicator for the system to detect anomalies.

[0191] "Anomaly detection" is the process of identifying unusual emotional states or behaviors and generating alerts to take preventative measures, thereby contributing to improved security.

[0192] This invention is a novel system that renders multifaceted court judgments by using legal data, past case precedent data, and analyzing visitors' emotional states in real time. This system operates with the cooperation of an information processing device, a terminal, and the user.

[0193] The server includes an information processing device for regularly updating legal data and historical case precedent data. This ensures that the latest legal information is always available, forming the basis for judgment formation.

[0194] The terminal is equipped with a mechanism for digitizing court records and generating prompt text. This allows users to easily input relevant data and generate comprehensive opinions that combine legal and emotional data.

[0195] The system utilizes multiple generative AI modules as knowledge processing units to generate prompt-based opinions. In this process, techniques applied to analyze visitor emotions can identify abnormal emotional states, aiding in preventative measures and enhanced safety management.

[0196] As a concrete example, in a public facility's safety management system, this system can be used to monitor visitors' levels of tension and excitement in real time and issue warnings to security staff.

[0197] An example of a prompt message to provide to a generative AI model is: "Create a sentiment analysis report of today's visitors and issue a warning if there are any anomalies. Here are the visitors' audio and video data."

[0198] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0199] Step 1:

[0200] The terminal receives court records and visitor audio / video data provided by the user. This input data is digitized and converted into an easily analyzable format. The digitized data is stored in the terminal's storage and prepared for use in subsequent processing steps.

[0201] Step 2:

[0202] The server generates prompt text based on the received digital data. This prompt text is used as input for the generative AI model to generate opinions. In this process, the digital data is processed into a format suitable for the prompt and passed to the AI ​​model as textual information.

[0203] Step 3:

[0204] The terminal sends the generated prompt text to the server, which then supplies it to multiple generative AI models. The server uses the prompt text to perform data calculations in the generative AI models, generating anomaly detection considerations based on legal opinions and visitor sentiment.

[0205] Step 4:

[0206] The server aggregates the opinions obtained from the generated AI models and facilitates consensus-building among the models. During this consensus-building process, an attempt is made to construct a draft judgment based on the generated opinions. Throughout this process, the output opinions of each model are compared and adjusted.

[0207] Step 5:

[0208] The final agreed-upon judgment is finalized within the system and reported to the judge or security staff via the terminal. The report includes information related to anomaly detection, as well as other materials to assist in decision-making and security measures.

[0209] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0210] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0211] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0215] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0216] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0217] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0218] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0219] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0220] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0221] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0222] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0223] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0224] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0225] This invention is an AI agent-based court judgment system that utilizes legal information and past case precedents. To realize this, the server, terminals, and users work together to operate the system as follows.

[0226] The server first periodically updates legal information and past case precedents, and stores them in a database. This information is all the data that the generating AI model agent needs in the context of a trial.

[0227] Users use their devices to convert court-related documents, evidence, and witness testimonies into digital format and send them to a server. These digitized court records are analyzed on the server and provided to an AI agent as prompts.

[0228] The server prompts agents to exchange opinions and reach a consensus based on prompts. Each agent generates an individual opinion using the provided legal information and past case law. This allows multiple AI agents to grasp the overall picture of the trial and engage in discussions to reach a fair judgment.

[0229] The draft judgment, formed through discussions among agents, is finalized via the server and reported to the court. Users then consider adopting this report as their final court decision. This system enhances objectivity and fairness in the judicial process and enables faster judgments.

[0230] As a concrete example, consider a murder trial. The server provides the agent with precedents from similar past cases and relevant laws. The agent identifies several possibilities based on the details of the case and discusses which judgment would be appropriate in accordance with current laws. As a result, an unbiased and objective draft judgment is created.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The server collects the latest legal information and past case law information from the internet and relevant databases, and stores it in its internal database. This data is updated regularly to ensure that the AI ​​agent always makes decisions based on the most up-to-date information.

[0234] Step 2:

[0235] Users upload all court documents, evidence, and testimonies as digital data to the server using their devices. This includes scanning documents and transcribing audio into text.

[0236] Step 3:

[0237] The server analyzes the uploaded digital data and generates prompts for the AI ​​agent. These prompts include court records such as a case summary, evidence list, and witness testimonies.

[0238] Step 4:

[0239] The server sends the generated prompt to multiple AI agents. Each AI agent generates an opinion based on the prompt and independently forms an initial draft judgment.

[0240] Step 5:

[0241] AI agents exchange opinions via a server. Each agent receives feedback on the opinions of other agents and modifies its own views as needed.

[0242] Step 6:

[0243] Through discussions among the agents, an agreement on the draft judgment is reached. The agreed-upon draft judgment is reported to the server as the final judgment.

[0244] Step 7:

[0245] The server automatically generates the agreed-upon judgment as a final report and provides it to the user, a court-related party. This report includes the basis for the judgment and a record of the exchange of opinions among the agents.

[0246] (Example 1)

[0247] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0248] In the traditional judicial process, there has been a challenge in ensuring fairness and objectivity in trials while simultaneously delivering swift judgments. In particular, the difficulty in efficiently utilizing vast amounts of legal information and past precedents has led to lengthy decision-making processes and increased costs.

[0249] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0250] In this invention, the server includes means including an information storage device that periodically updates legal information and past case law information; processing means that digitizes materials related to a trial and generates them as input instructions; and processing means that uses multiple generating artificial intelligence models as intermediary devices to generate opinions based on the input instructions. This makes it possible to make quick and objective judgments based on data of laws and precedents.

[0251] An "information storage device" is a data management device for storing legal information and past case law information, and for periodically updating it.

[0252] An "information processing device" is a primary device used to process legal information and manage and analyze various types of digitized data.

[0253] "Processing means" refers to a technical method or device used to perform a specific function or task.

[0254] "Input instructions" refer to the presentation of information to organize court-related information and provide it to a generative artificial intelligence model.

[0255] A "generative artificial intelligence model" is a type of artificial intelligence technology used to generate judgments and opinions based on provided data.

[0256] A "mediating device" is a function or device that plays a central role in facilitating the exchange of various types of information and the aggregation of opinions using a generated artificial intelligence model.

[0257] "Viewpoint" refers to judgments or opinions generated based on the information provided.

[0258] "Judgment" refers to the final conclusion or decision formed based on various pieces of information.

[0259] A "report document" is a document prepared for judicial institutions to explain the results of a ruling.

[0260] "Judge" refers to an individual or institution that has the authority to make judicial decisions.

[0261] An embodiment of the present invention is a court judgment support system based on legal information and past case law information. This system is operated by coordinating an information processing device and a terminal device.

[0262] The server first functions as an "information storage device," storing legal information and past case precedents. It also periodically updates this information as an "information processing device," ensuring that necessary data is always up-to-date. Specifically, it retrieves data from online legal information platforms. An example of such a platform is a legal information retrieval system commonly used in the industry.

[0263] Users digitize court-related documents using a terminal. They convert documents, evidence, and witness testimonies into digital format using a scanner and speech recognition software connected to the terminal. This process utilizes common document digitization software and speech recognition tools.

[0264] The digitized documents on the terminal are sent to the server. The server analyzes the received data and uses it as a prompt for the generating AI model. An example of a prompt might be, "Based on the following documents related to the trial, please generate a draft judgment considering the relevant laws and past precedents."

[0265] The server uses these prompts to run multiple generative artificial intelligence models. Each AI model generates insights based on the assigned prompt. The generative artificial intelligence models can utilize software with mature generative algorithms.

[0266] This will enable users to achieve greater fairness and efficiency in legal decisions and the judicial process. It is expected that legal work will be carried out more quickly and accurately through the use of this system.

[0267] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0268] Step 1:

[0269] The server retrieves legal and case law information from an online legal information service. It receives update commands for already stored legal information as input. The server retrieves this update information and stores it in the information storage device. This ensures the database always maintains the latest legal information. The output is the updated legal information database. Each data item is organized by category in preparation for subsequent processing.

[0270] Step 2:

[0271] Users digitize court-related documents using a terminal. Input includes paper documents, evidence, and audio testimonies. The terminal converts documents to PDF or image formats via a scanner and converts audio to text using speech recognition software. The output is a digitized court document file, which is sent to a server.

[0272] Step 3:

[0273] The server receives digitized documents submitted by users. It accepts multiple digital files as input. The server uses natural language processing techniques to analyze the document content and extract key keywords and evidence. The output is a prompt message for a generative AI model, containing a summary of the trial and relevant legal matters.

[0274] Step 4:

[0275] The server sends prompts to multiple generative AI models. The input, in the form of a prompt statement, contains information including a case summary, relevant laws and regulations, and past precedents. Based on this, the AI ​​models process the data to generate opinions and predicted judgments. The output is a generated document containing the opinions of each AI model.

[0276] Step 5:

[0277] The server aggregates the outputs from the AI ​​models and verifies the consistency of their opinions. The input consists of each AI model's proposed judgment. The server integrates these to generate the most appropriate ruling. It then creates a final report. The output is a carefully prepared report for the court. This report is provided to the user and serves as important reference material for court decisions.

[0278] (Application Example 1)

[0279] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0280] There is a need to provide swift and appropriate legal judgments in various situations that arise on the ground, but current methods make it difficult to make quick decisions based on legal information and past precedents. Therefore, a support system is needed to enable on-site personnel to take appropriate action immediately.

[0281] The specific processing by the specific processing unit 290 of the data processing apparatus 12 in Application Example 1 is realized by the following respective means.

[0282] In this invention, the server includes a computer including an information source that periodically updates legal information and past case information, means for digitizing on-site events and generating them as command texts, and means installed in a smart device for providing immediate legal judgments at the site. Thereby, it becomes possible to quickly make legal judgments at the site.

[0283] "Legal information" refers to data and materials related to laws, and includes related information such as cases and articles.

[0284] "Past case information" refers to the records of past trials and the contents of judgments, and is information for reference in legal judgments.

[0285] "Command text" refers to a digitized instruction or command text used when making a legal judgment in a specific situation.

[0286] "Generative AI model" is a type of artificial intelligence designed to execute a specific task, and is an algorithm that generates an appropriate output from the input information.

[0287] "Assistant" is a system element that has the role of assisting in executing a specific task using a generative AI model.

[0288] "Deliberation" refers to discussions and consultations for adjusting multiple opinions and finding an optimal solution.

[0289] "Smart device" refers to a portable terminal having an Internet connection function and capable of executing various applications, including smartphones and tablets.

[0290] "Immediate legal judgment" refers to the act of quickly and appropriately making a judgment based on laws and regulations in a given situation.

[0291] To realize this application, the server periodically updates legal information and past case precedents, maintaining them as information sources. It also digitizes on-site events via smart devices, generates them as command statements, and transmits them. The generated command statements are used as foundational information to provide specific legal judgments using a generative AI model.

[0292] The terminal captures events at the scene and quickly transmits them to the server. This enables real-time information processing and supports appropriate decision-making at the scene.

[0293] Users can use their smart devices to receive legal judgments provided by the server and apply them to on-site responses. Through this process, users can take appropriate legal action immediately.

[0294] The generative AI model uses multiple assistants to generate relevant legal advice based on the given instructions. Through deliberation among the assistants, the optimal course of action is formed and provided to the user.

[0295] For example, if a security guard spots a suspicious person in a commercial facility, they can input the incident details into their smartphone, and the server will provide relevant legal information to the AI, which will then suggest a legally appropriate course of action.

[0296] Example prompt for the generating AI model: "Immediately provide legal responses to intruders at the facility. Suggest appropriate actions based on past intrusion case precedents and relevant laws."

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The server regularly updates its database with legal information and past case precedents. This information is collected from external legal databases and stored in the server's storage system. This ensures that the latest legal resources are always available for use by the generative AI model. The input is legal data obtained from external sources, and the output is the updated internal database.

[0300] Step 2:

[0301] The terminal digitizes events at the scene and inputs detailed information. Users use smart devices to input incident details via text or voice. This data is formatted and sent to the server. The input is the incident details provided by the user, and the output is the digitized data sent to the server.

[0302] Step 3:

[0303] The server generates prompts from the digitized data received from the terminal. These generated prompts are used as foundational information for subsequent AI processing. This step cleanses and structures the data, facilitating processing by the AI ​​model. The input is digitized incident information, and the output is the generated prompts.

[0304] Step 4:

[0305] The generative AI model generates relevant legal advice based on prompt messages received from the server. The AI ​​model generates the most appropriate legal judgment by referring to an internal legal information database. The input consists of prompt messages and legal information, while the output is the legal advice generated by each AI assistant.

[0306] Step 5:

[0307] The server aggregates the legal advice generated by multiple assistants and forms an optimal response plan through deliberation. It weights and prioritizes the opinions of each assistant and selects the most appropriate plan. The input is multiple legal advices, and the output is the deliberated optimal response plan.

[0308] Step 6:

[0309] The user receives the optimal response plan provided by the server and checks the plan through the smart device. As a result, the user can promptly take appropriate legal action on-site. The input is the response plan sent from the server, and the output is the specific action on-site.

[0310] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0311] The present invention is a judgment system that combines legal information, past case information, and an emotion engine for recognizing the user's emotion. The operation of this system is carried out through the cooperation of the server, terminal, and user.

[0312] The server continuously updates legal information and case data and stores them in the database. This serves as the basis for the AI agent to always make judgments based on the latest information.

[0313] The user digitizes documents, evidence, and testimonies related to the lawsuit and uploads them from the terminal to the server. This digital data includes not only text but also videos, sounds, etc. The uploaded data is analyzed on the server and compiled as a prompt for the AI agent.

[0314] This process incorporates an emotion engine. The emotion engine recognizes the emotions of witnesses and those involved through audio and video analysis, and includes this information in the data. This emotional information is treated as a factor to consider when generating prompts.

[0315] The generated prompts are provided to multiple AI agents, and each agent forms an opinion based on them. Because the opinions generated by the AI ​​agents take recognized emotional information into consideration, more multifaceted judgments are possible. In opinion exchanges and discussions among agents, emotional information is also incorporated as a factor in reaching a consensus.

[0316] Ultimately, the agreed-upon judgment is automatically generated as a report for the court via the server. This report includes, in addition to the legal basis, supplementary emotional data recorded by the emotional engine. This helps judges and stakeholders gain a deeper understanding of the case's context.

[0317] As a concrete example, consider a trial concerning domestic violence. In this case, the audio and video of the witnesses are analyzed by an emotion engine to recognize feelings of tension and fear. This emotional information becomes an important element in judging and is taken into consideration by an AI agent. In this way, the present invention realizes a system that supports trials from both legal and human emotional perspectives.

[0318] The following describes the processing flow.

[0319] Step 1:

[0320] The server collects legal information and past case law data from the internet and related databases, and stores it in a database. This data forms the basis for the decisions of the generative AI model and is updated regularly.

[0321] Step 2:

[0322] Users use their devices to convert court records into digital format and upload them to the server. These court records include scanned images of documents, as well as audio and video.

[0323] Step 3:

[0324] The server analyzes the uploaded digital data. During this process, it uses an emotion engine to analyze the emotions of witnesses and related parties from audio and video, and extracts emotional information.

[0325] Step 4:

[0326] The server generates prompts for the AI ​​agent based on the analysis. These prompts include legal information, case law information, court records, and sentiment information.

[0327] Step 5:

[0328] The server provides the generated prompt to multiple AI agents, and each agent generates its own opinion based on this prompt. The generated opinion takes into account recognized sentiment information.

[0329] Step 6:

[0330] AI agents exchange opinions, incorporating emotional information, and proceed through a deliberative process to construct a draft judgment. This process involves adjusting opinions and clarifying points of contention in order to reach an agreement.

[0331] Step 7:

[0332] The agreed-upon judgment draft is automatically generated by the server as a final report. This report includes the legal basis for the judgment, precedents, and perceived sentiment information.

[0333] Step 8:

[0334] Judges and lawyers, who are users of the system, review the final reports provided by the server to help them make their final decisions. The reports include detailed emotional information to deepen their understanding of the case's context.

[0335] (Example 2)

[0336] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0337] In the decision-making process in court, it is necessary to handle legal information and past precedents quickly and accurately. However, the current system has challenges in that it does not adequately update relevant information and process sentiment information, resulting in insufficient multifaceted support for decision-making.

[0338] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0339] In this invention, the server includes means for continuously updating and accumulating legal information and past case law information, means for converting evidence and testimonies into digital information and processing them, and means for recognizing emotions and incorporating them into relevant data. This enables multifaceted and comprehensive support in the decision-making process.

[0340] "Legal information" refers to the collective term for articles of law, statutes, regulations, and related information.

[0341] "Case law information" refers to information about cases decided in court in the past, and includes data on judgments and their interpretations.

[0342] "Information aggregation" refers to the process of continuously collecting and storing data and information necessary for a specific purpose.

[0343] "Evidence" refers to any form of information, such as documents, photographs, and physical evidence, provided in court to prove the facts.

[0344] "Digital information" refers to information data in a form that can be handled by a computer, and includes formats that can be stored, transferred, and processed electronically.

[0345] "The process of recognizing emotions and incorporating them into related data" refers to the process of analyzing audio and video to extract emotional states and processing them together with other data.

[0346] The "decision-making process" is the process of making a final decision after going through a series of steps to find a solution to a particular problem.

[0347] "Comprehensive support" refers to assistance and support provided by taking into account multiple aspects and needs as a whole.

[0348] This invention is a court support system that processes legal information and past case law information, and is operated collaboratively by a server, terminals, and users. The server is responsible for continuously acquiring and updating legal information and case law information and storing it in a database. This provides a foundation for always utilizing the latest information within the system.

[0349] Users digitize documents and evidence necessary for trials and upload them to the server via their devices. The digitized data can take various forms, including text, audio, and video. The server analyzes this data and generates prompts for use by a generative AI model. This process utilizes natural language processing and image recognition technologies.

[0350] Furthermore, emotion recognition software embedded in the server analyzes audio and video to extract emotional information and incorporate it into the analysis data. This provides the generative AI model with a multifaceted perspective that takes emotional information into account when forming opinions.

[0351] As a concrete example, consider a trial dealing with domestic disputes. In the process of digitizing the audio and video of witnesses on a terminal and analyzing them on a server, the emotion engine extracts emotions such as fear and tension. This information is used by the AI ​​agent to make the best possible decisions.

[0352] An example of a prompt message from this system would be, "Analyze the testimony regarding the domestic dispute and form your judgment considering the perceived emotional information." This system integrates legal information with human emotions to enable more objective and detailed legal support.

[0353] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0354] Step 1:

[0355] Users prepare court-related documents and evidence, and digitize this information using a terminal. Users convert documents into image data using scanners and cameras, and prepare testimonies as digital audio or video data using audio and video recording devices. These digital data are then uploaded from the terminal to a server. Physical documents, audio, and video are used as input, and digital data files are generated as output.

[0356] Step 2:

[0357] The server receives uploaded digital data and performs analysis using natural language processing and image recognition technologies. The server extracts text data, detects important scenes from video data, and transcribes audio data. Through this analysis process, prompt sentences are generated for use by the AI ​​agent. Digital data files are used as input, and the analyzed information and prompt sentences are generated as output.

[0358] Step 3:

[0359] The emotion recognition software embedded in the server analyzes audio and video from digital data to extract the emotional state of the speaker or character. It evaluates elements such as tone of voice, facial expressions, and gestures to identify emotional information. This information is added to the analysis data, forming the basis for the AI ​​agent to make multifaceted judgments. Audio and video data are used as input, and emotional information is generated as output.

[0360] Step 4:

[0361] The server provides prompt text and attached sentiment information to multiple generative AI models (agents). Each agent forms an opinion based on the provided information, considering legal and emotional factors. Opinions are exchanged among the agents, and a final opinion is aggregated through consensus. Prompt text and sentiment information are used as input, and a collective opinion is generated as output.

[0362] Step 5:

[0363] The server automatically generates reports for the court based on opinions determined by the AI ​​agent. These reports include not only legal grounds but also emotional information as background to the judgment. The reports are created in digital format and provided to judges and other relevant parties. Collective opinions are used as input, and the reports are generated as output.

[0364] (Application Example 2)

[0365] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0366] The current judicial judgment system allows for decisions based on legal information and past precedents, but it struggles to make multifaceted judgments that take into account the emotional states of those involved. Furthermore, even in enhancing security at public facilities, the system lacks the ability to analyze visitors' emotions in real time and detect anomalies. This makes it difficult to gain a deeper understanding of the background of an incident and to respond quickly to unusual situations.

[0367] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0368] This invention includes an information processing device that periodically updates legal data and past case precedent data, a mechanism that digitizes court records and generates them as prompts, and a method for analyzing visitors' emotional states in real time and detecting anomalies. This improves the quality of legal judgments and strengthens security management.

[0369] "Legal data" refers to a collection of information including the latest legal information and related laws and regulations, which forms the basis for the system to make legal decisions.

[0370] "Past case data" refers to records of past judicial decisions, which are referenced by the system when generating opinions based on similar cases.

[0371] An "information processing device" is a computer system for storing and updating legal data and past case law data, and is an element for performing analytical processing.

[0372] "Digitalization" is the process of converting information in analog format into electronic data, and it is a method that enables data storage and analysis.

[0373] A "prompt" is a format of text or data that acts as a trigger when providing information to an AI module, and it plays a role in inducing the generation of opinions.

[0374] A "generative AI module" is a group of artificial intelligence programs that generate opinions and judgments based on prompts, and has the function of making decisions within the system.

[0375] A "knowledge processing unit" is an information processing unit used by a generative AI module when forming specific opinions, and it is the foundation for deriving the optimal opinion through deliberation.

[0376] "Visitor's emotional state" refers to an individual's psychological state analyzed from audio and video, and serves as an indicator for the system to detect anomalies.

[0377] "Anomaly detection" is the process of identifying unusual emotional states or behaviors and generating alerts to take preventative measures, thereby contributing to improved security.

[0378] This invention is a novel system that renders multifaceted court judgments by using legal data, past case precedent data, and analyzing visitors' emotional states in real time. This system operates with the cooperation of an information processing device, a terminal, and the user.

[0379] The server includes an information processing device for regularly updating legal data and historical case precedent data. This ensures that the latest legal information is always available, forming the basis for judgment formation.

[0380] The terminal is equipped with a mechanism for digitizing court records and generating prompt text. This allows users to easily input relevant data and generate comprehensive opinions that combine legal and emotional data.

[0381] The system utilizes multiple generative AI modules as knowledge processing units to generate prompt-based opinions. In this process, techniques applied to analyze visitor emotions can identify abnormal emotional states, aiding in preventative measures and enhanced safety management.

[0382] As a concrete example, in a public facility's safety management system, this system can be used to monitor visitors' levels of tension and excitement in real time and issue warnings to security staff.

[0383] An example of a prompt message to provide to a generative AI model is: "Create a sentiment analysis report of today's visitors and issue a warning if there are any anomalies. Here are the visitors' audio and video data."

[0384] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0385] Step 1:

[0386] The terminal receives court records and visitor audio / video data provided by the user. This input data is digitized and converted into an easily analyzable format. The digitized data is stored in the terminal's storage and prepared for use in subsequent processing steps.

[0387] Step 2:

[0388] The server generates prompt text based on the received digital data. This prompt text is used as input for the generative AI model to generate opinions. In this process, the digital data is processed into a format suitable for the prompt and passed to the AI ​​model as textual information.

[0389] Step 3:

[0390] The terminal sends the generated prompt text to the server, which then supplies it to multiple generative AI models. The server uses the prompt text to perform data calculations in the generative AI models, generating anomaly detection considerations based on legal opinions and visitor sentiment.

[0391] Step 4:

[0392] The server aggregates the opinions obtained from the generated AI models and facilitates consensus-building among the models. During this consensus-building process, an attempt is made to construct a draft judgment based on the generated opinions. Throughout this process, the output opinions of each model are compared and adjusted.

[0393] Step 5:

[0394] The final agreed-upon judgment is finalized within the system and reported to the judge or security staff via the terminal. The report includes information related to anomaly detection, as well as other materials to assist in decision-making and security measures.

[0395] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0396] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0397] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0398] [Third Embodiment]

[0399] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0400] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0401] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0402] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0403] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0404] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0405] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0406] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0407] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0408] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0409] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0410] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0411] This invention is an AI agent-based court judgment system that utilizes legal information and past case precedents. To realize this, the server, terminals, and users work together to operate the system as follows.

[0412] The server first periodically updates legal information and past case precedents, and stores them in a database. This information is all the data that the generating AI model agent needs in the context of a trial.

[0413] Users use their devices to convert court-related documents, evidence, and witness testimonies into digital format and send them to a server. These digitized court records are analyzed on the server and provided to an AI agent as prompts.

[0414] The server prompts agents to exchange opinions and reach a consensus based on prompts. Each agent generates an individual opinion using the provided legal information and past case law. This allows multiple AI agents to grasp the overall picture of the trial and engage in discussions to reach a fair judgment.

[0415] The draft judgment, formed through discussions among agents, is finalized via the server and reported to the court. Users then consider adopting this report as their final court decision. This system enhances objectivity and fairness in the judicial process and enables faster judgments.

[0416] As a concrete example, consider a murder trial. The server provides the agent with precedents from similar past cases and relevant laws. The agent identifies several possibilities based on the details of the case and discusses which judgment would be appropriate in accordance with current laws. As a result, an unbiased and objective draft judgment is created.

[0417] The following describes the processing flow.

[0418] Step 1:

[0419] The server collects the latest legal information and past case law information from the internet and relevant databases, and stores it in its internal database. This data is updated regularly to ensure that the AI ​​agent always makes decisions based on the most up-to-date information.

[0420] Step 2:

[0421] Users upload all court documents, evidence, and testimonies as digital data to the server using their devices. This includes scanning documents and transcribing audio into text.

[0422] Step 3:

[0423] The server analyzes the uploaded digital data and generates prompts for the AI ​​agent. These prompts include court records such as a case summary, evidence list, and witness testimonies.

[0424] Step 4:

[0425] The server sends the generated prompt to multiple AI agents. Each AI agent generates an opinion based on the prompt and independently forms an initial draft judgment.

[0426] Step 5:

[0427] AI agents exchange opinions via a server. Each agent receives feedback on the opinions of other agents and modifies its own views as needed.

[0428] Step 6:

[0429] Through discussions among the agents, an agreement on the draft judgment is reached. The agreed-upon draft judgment is reported to the server as the final judgment.

[0430] Step 7:

[0431] The server automatically generates the agreed-upon judgment as a final report and provides it to the user, a court-related party. This report includes the basis for the judgment and a record of the exchange of opinions among the agents.

[0432] (Example 1)

[0433] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0434] In the traditional judicial process, there has been a challenge in ensuring fairness and objectivity in trials while simultaneously delivering swift judgments. In particular, the difficulty in efficiently utilizing vast amounts of legal information and past precedents has led to lengthy decision-making processes and increased costs.

[0435] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0436] In this invention, the server includes means including an information storage device that periodically updates legal information and past case law information; processing means that digitizes materials related to a trial and generates them as input instructions; and processing means that uses multiple generating artificial intelligence models as intermediary devices to generate opinions based on the input instructions. This makes it possible to make quick and objective judgments based on data of laws and precedents.

[0437] An "information storage device" is a data management device for storing legal information and past case law information, and for periodically updating it.

[0438] An "information processing device" is a primary device used to process legal information and manage and analyze various types of digitized data.

[0439] "Processing means" refers to a technical method or device used to perform a specific function or task.

[0440] "Input instructions" refer to the presentation of information to organize court-related information and provide it to a generative artificial intelligence model.

[0441] A "generative artificial intelligence model" is a type of artificial intelligence technology used to generate judgments and opinions based on provided data.

[0442] A "mediating device" is a function or device that plays a central role in facilitating the exchange of various types of information and the aggregation of opinions using a generated artificial intelligence model.

[0443] "Viewpoint" refers to judgments or opinions generated based on the information provided.

[0444] "Judgment" refers to the final conclusion or decision formed based on various pieces of information.

[0445] A "report document" is a document prepared for judicial institutions to explain the results of a ruling.

[0446] "Judge" refers to an individual or institution that has the authority to make judicial decisions.

[0447] An embodiment of the present invention is a court judgment support system based on legal information and past case law information. This system is operated by coordinating an information processing device and a terminal device.

[0448] The server first functions as an "information storage device," storing legal information and past case precedents. It also periodically updates this information as an "information processing device," ensuring that necessary data is always up-to-date. Specifically, it retrieves data from online legal information platforms. An example of such a platform is a legal information retrieval system commonly used in the industry.

[0449] Users digitize court-related documents using a terminal. They convert documents, evidence, and witness testimonies into digital format using a scanner and speech recognition software connected to the terminal. This process utilizes common document digitization software and speech recognition tools.

[0450] The digitized documents on the terminal are sent to the server. The server analyzes the received data and uses it as a prompt for the generating AI model. An example of a prompt might be, "Based on the following documents related to the trial, please generate a draft judgment considering the relevant laws and past precedents."

[0451] The server uses these prompts to run multiple generative artificial intelligence models. Each AI model generates insights based on the assigned prompt. The generative artificial intelligence models can utilize software with mature generative algorithms.

[0452] This will enable users to achieve greater fairness and efficiency in legal decisions and the judicial process. It is expected that legal work will be carried out more quickly and accurately through the use of this system.

[0453] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0454] Step 1:

[0455] The server retrieves legal and case law information from an online legal information service. It receives update commands for already stored legal information as input. The server retrieves this update information and stores it in the information storage device. This ensures the database always maintains the latest legal information. The output is the updated legal information database. Each data item is organized by category in preparation for subsequent processing.

[0456] Step 2:

[0457] Users digitize court-related documents using a terminal. Input includes paper documents, evidence, and audio testimonies. The terminal converts documents to PDF or image formats via a scanner and converts audio to text using speech recognition software. The output is a digitized court document file, which is sent to a server.

[0458] Step 3:

[0459] The server receives digitized documents submitted by users. It accepts multiple digital files as input. The server uses natural language processing techniques to analyze the document content and extract key keywords and evidence. The output is a prompt message for a generative AI model, containing a summary of the trial and relevant legal matters.

[0460] Step 4:

[0461] The server sends prompts to multiple generative AI models. The input, in the form of a prompt statement, contains information including a case summary, relevant laws and regulations, and past precedents. Based on this, the AI ​​models process the data to generate opinions and predicted judgments. The output is a generated document containing the opinions of each AI model.

[0462] Step 5:

[0463] The server aggregates the outputs from the AI ​​models and verifies the consistency of their opinions. The input consists of each AI model's proposed judgment. The server integrates these to generate the most appropriate ruling. It then creates a final report. The output is a carefully prepared report for the court. This report is provided to the user and serves as important reference material for court decisions.

[0464] (Application Example 1)

[0465] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0466] There is a need to provide swift and appropriate legal judgments in various situations that arise on the ground, but current methods make it difficult to make quick decisions based on legal information and past precedents. Therefore, a support system is needed to enable on-site personnel to take appropriate action immediately.

[0467] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0468] In this invention, the server includes a computer containing a source of information that periodically updates legal information and past case law information, means for digitizing on-site events and generating them as command statements, and means installed on a smart device to provide immediate legal judgments on-site. This makes it possible to make legal judgments quickly on-site.

[0469] "Legal information" refers to data and materials related to the law, and includes relevant information such as precedents and legal provisions.

[0470] "Past case law information" refers to records and judgments from past trials, and is information that can be used as a reference for legal decisions.

[0471] A "directive document" is a digitized instruction or command document used when making legal decisions in a specific situation.

[0472] A "generative AI model" is a type of artificial intelligence designed to perform a specific task, and it is an algorithm that generates appropriate output from input information.

[0473] An "assistant" is a system element that uses a generative AI model to assist in performing specific tasks.

[0474] "Consensus" refers to discussions and consultations aimed at reconciling multiple opinions and finding the optimal solution.

[0475] A "smart device" refers to a portable terminal that has internet connectivity and can run a variety of applications, and includes smartphones and tablets.

[0476] "Immediate legal judgment" refers to the act of making a swift and appropriate judgment based on laws and regulations in a given situation.

[0477] To realize this application, the server periodically updates legal information and past case precedents, maintaining them as information sources. It also digitizes on-site events via smart devices, generates them as command statements, and transmits them. The generated command statements are used as foundational information to provide specific legal judgments using a generative AI model.

[0478] The terminal captures events at the scene and quickly transmits them to the server. This enables real-time information processing and supports appropriate decision-making at the scene.

[0479] Users can use their smart devices to receive legal judgments provided by the server and apply them to on-site responses. Through this process, users can take appropriate legal action immediately.

[0480] The generative AI model uses multiple assistants to generate relevant legal advice based on the given instructions. Through deliberation among the assistants, the optimal course of action is formed and provided to the user.

[0481] For example, if a security guard spots a suspicious person in a commercial facility, they can input the incident details into their smartphone, and the server will provide relevant legal information to the AI, which will then suggest a legally appropriate course of action.

[0482] Example prompt for the generating AI model: "Immediately provide legal responses to intruders at the facility. Suggest appropriate actions based on past intrusion case precedents and relevant laws."

[0483] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0484] Step 1:

[0485] The server regularly updates its database with legal information and past case precedents. This information is collected from external legal databases and stored in the server's storage system. This ensures that the latest legal resources are always available for use by the generative AI model. The input is legal data obtained from external sources, and the output is the updated internal database.

[0486] Step 2:

[0487] The terminal digitizes events at the scene and inputs detailed information. Users use smart devices to input incident details via text or voice. This data is formatted and sent to the server. The input is the incident details provided by the user, and the output is the digitized data sent to the server.

[0488] Step 3:

[0489] The server generates prompts from the digitized data received from the terminal. These generated prompts are used as foundational information for subsequent AI processing. This step cleanses and structures the data, facilitating processing by the AI ​​model. The input is digitized incident information, and the output is the generated prompts.

[0490] Step 4:

[0491] The generative AI model generates relevant legal advice based on prompt messages received from the server. The AI ​​model generates the most appropriate legal judgment by referring to an internal legal information database. The input consists of prompt messages and legal information, while the output is the legal advice generated by each AI assistant.

[0492] Step 5:

[0493] The server aggregates legal advice generated by multiple assistants and forms an optimal response plan through deliberation. It weights and prioritizes each assistant's opinion to select the most appropriate plan. The input is multiple legal advice, and the output is the agreed-upon optimal response plan.

[0494] Step 6:

[0495] The user receives the optimal response plan from the server and confirms it via a smart device. This allows the user to take appropriate legal action quickly on-site. The input is the response plan sent from the server, and the output is the specific action to be taken on-site.

[0496] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0497] This invention is a court judgment system that combines legal information and past case law information with an emotion engine that recognizes the user's emotions. The operation of this system is carried out through the cooperation of the server, terminal, and user.

[0498] The server continuously updates legal information and case law data, storing it in a database. This provides the foundation for AI agents to always make decisions based on the latest information.

[0499] Users digitize court documents, evidence, and testimonies and upload them from their devices to a server. This digital data includes not only text but also video and audio. The uploaded data is analyzed on the server and compiled into prompts for the AI ​​agent.

[0500] This process incorporates an emotion engine. The emotion engine recognizes the emotions of witnesses and those involved through audio and video analysis, and includes this information in the data. This emotional information is treated as a factor to consider when generating prompts.

[0501] The generated prompts are provided to multiple AI agents, and each agent forms an opinion based on them. Because the opinions generated by the AI ​​agents take recognized emotional information into consideration, more multifaceted judgments are possible. In opinion exchanges and discussions among agents, emotional information is also incorporated as a factor in reaching a consensus.

[0502] Ultimately, the agreed-upon judgment is automatically generated as a report for the court via the server. This report includes, in addition to the legal basis, supplementary emotional data recorded by the emotional engine. This helps judges and stakeholders gain a deeper understanding of the case's context.

[0503] As a concrete example, consider a trial concerning domestic violence. In this case, the audio and video of the witnesses are analyzed by an emotion engine to recognize feelings of tension and fear. This emotional information becomes an important element in judging and is taken into consideration by an AI agent. In this way, the present invention realizes a system that supports trials from both legal and human emotional perspectives.

[0504] The following describes the processing flow.

[0505] Step 1:

[0506] The server collects legal information and past case law data from the internet and related databases, and stores it in a database. This data forms the basis for the decisions of the generative AI model and is updated regularly.

[0507] Step 2:

[0508] Users use their devices to convert court records into digital format and upload them to the server. These court records include scanned images of documents, as well as audio and video.

[0509] Step 3:

[0510] The server analyzes the uploaded digital data. During this process, it uses an emotion engine to analyze the emotions of witnesses and related parties from audio and video, and extracts emotional information.

[0511] Step 4:

[0512] The server generates prompts for the AI ​​agent based on the analysis. These prompts include legal information, case law information, court records, and sentiment information.

[0513] Step 5:

[0514] The server provides the generated prompt to multiple AI agents, and each agent generates its own opinion based on this prompt. The generated opinion takes into account recognized sentiment information.

[0515] Step 6:

[0516] AI agents exchange opinions, incorporating emotional information, and proceed through a deliberative process to construct a draft judgment. This process involves adjusting opinions and clarifying points of contention in order to reach an agreement.

[0517] Step 7:

[0518] The agreed-upon judgment draft is automatically generated by the server as a final report. This report includes the legal basis for the judgment, precedents, and perceived sentiment information.

[0519] Step 8:

[0520] Judges and lawyers, who are users of the system, review the final reports provided by the server to help them make their final decisions. The reports include detailed emotional information to deepen their understanding of the case's context.

[0521] (Example 2)

[0522] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0523] In the decision-making process in court, it is necessary to handle legal information and past precedents quickly and accurately. However, the current system has challenges in that it does not adequately update relevant information and process sentiment information, resulting in insufficient multifaceted support for decision-making.

[0524] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0525] In this invention, the server includes means for continuously updating and accumulating legal information and past case law information, means for converting evidence and testimonies into digital information and processing them, and means for recognizing emotions and incorporating them into relevant data. This enables multifaceted and comprehensive support in the decision-making process.

[0526] "Legal information" refers to the collective term for articles of law, statutes, regulations, and related information.

[0527] "Case law information" refers to information about cases decided in court in the past, and includes data on judgments and their interpretations.

[0528] "Information aggregation" refers to the process of continuously collecting and storing data and information necessary for a specific purpose.

[0529] "Evidence" refers to any form of information, such as documents, photographs, and physical evidence, provided in court to prove the facts.

[0530] "Digital information" refers to information data in a form that can be handled by a computer, and includes formats that can be stored, transferred, and processed electronically.

[0531] "The process of recognizing emotions and incorporating them into related data" refers to the process of analyzing audio and video to extract emotional states and processing them together with other data.

[0532] The "decision-making process" is the process of making a final decision after going through a series of steps to find a solution to a particular problem.

[0533] "Comprehensive support" refers to assistance and support provided by taking into account multiple aspects and needs as a whole.

[0534] This invention is a court support system that processes legal information and past case law information, and is operated collaboratively by a server, terminals, and users. The server is responsible for continuously acquiring and updating legal information and case law information and storing it in a database. This provides a foundation for always utilizing the latest information within the system.

[0535] Users digitize documents and evidence necessary for trials and upload them to the server via their devices. The digitized data can take various forms, including text, audio, and video. The server analyzes this data and generates prompts for use by a generative AI model. This process utilizes natural language processing and image recognition technologies.

[0536] Furthermore, emotion recognition software embedded in the server analyzes audio and video to extract emotional information and incorporate it into the analysis data. This provides the generative AI model with a multifaceted perspective that takes emotional information into account when forming opinions.

[0537] As a concrete example, consider a trial dealing with domestic disputes. In the process of digitizing the audio and video of witnesses on a terminal and analyzing them on a server, the emotion engine extracts emotions such as fear and tension. This information is used by the AI ​​agent to make the best possible decisions.

[0538] An example of a prompt message from this system would be, "Analyze the testimony regarding the domestic dispute and form your judgment considering the perceived emotional information." This system integrates legal information with human emotions to enable more objective and detailed legal support.

[0539] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0540] Step 1:

[0541] Users prepare court-related documents and evidence, and digitize this information using a terminal. Users convert documents into image data using scanners and cameras, and prepare testimonies as digital audio or video data using audio and video recording devices. These digital data are then uploaded from the terminal to a server. Physical documents, audio, and video are used as input, and digital data files are generated as output.

[0542] Step 2:

[0543] The server receives uploaded digital data and performs analysis using natural language processing and image recognition technologies. The server extracts text data, detects important scenes from video data, and transcribes audio data. Through this analysis process, prompt sentences are generated for use by the AI ​​agent. Digital data files are used as input, and the analyzed information and prompt sentences are generated as output.

[0544] Step 3:

[0545] The emotion recognition software embedded in the server analyzes audio and video from digital data to extract the emotional state of the speaker or character. It evaluates elements such as tone of voice, facial expressions, and gestures to identify emotional information. This information is added to the analysis data, forming the basis for the AI ​​agent to make multifaceted judgments. Audio and video data are used as input, and emotional information is generated as output.

[0546] Step 4:

[0547] The server provides prompt text and attached sentiment information to multiple generative AI models (agents). Each agent forms an opinion based on the provided information, considering legal and emotional factors. Opinions are exchanged among the agents, and a final opinion is aggregated through consensus. Prompt text and sentiment information are used as input, and a collective opinion is generated as output.

[0548] Step 5:

[0549] The server automatically generates reports for the court based on opinions determined by the AI ​​agent. These reports include not only legal grounds but also emotional information as background to the judgment. The reports are created in digital format and provided to judges and other relevant parties. Collective opinions are used as input, and the reports are generated as output.

[0550] (Application Example 2)

[0551] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0552] The current judicial judgment system allows for decisions based on legal information and past precedents, but it struggles to make multifaceted judgments that take into account the emotional states of those involved. Furthermore, even in enhancing security at public facilities, the system lacks the ability to analyze visitors' emotions in real time and detect anomalies. This makes it difficult to gain a deeper understanding of the background of an incident and to respond quickly to unusual situations.

[0553] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0554] This invention includes an information processing device that periodically updates legal data and past case precedent data, a mechanism that digitizes court records and generates them as prompts, and a method for analyzing visitors' emotional states in real time and detecting anomalies. This improves the quality of legal judgments and strengthens security management.

[0555] "Legal data" refers to a collection of information including the latest legal information and related laws and regulations, which forms the basis for the system to make legal decisions.

[0556] "Past case data" refers to records of past judicial decisions, which are referenced by the system when generating opinions based on similar cases.

[0557] An "information processing device" is a computer system for storing and updating legal data and past case law data, and is an element for performing analytical processing.

[0558] "Digitalization" is the process of converting information in analog format into electronic data, and it is a method that enables data storage and analysis.

[0559] A "prompt" is a format of text or data that acts as a trigger when providing information to an AI module, and it plays a role in inducing the generation of opinions.

[0560] A "generative AI module" is a group of artificial intelligence programs that generate opinions and judgments based on prompts, and has the function of making decisions within the system.

[0561] A "knowledge processing unit" is an information processing unit used by a generative AI module when forming specific opinions, and it is the foundation for deriving the optimal opinion through deliberation.

[0562] "Visitor's emotional state" refers to an individual's psychological state analyzed from audio and video, and serves as an indicator for the system to detect anomalies.

[0563] "Anomaly detection" is the process of identifying unusual emotional states or behaviors and generating alerts to take preventative measures, thereby contributing to improved security.

[0564] This invention is a novel system that renders multifaceted court judgments by using legal data, past case precedent data, and analyzing visitors' emotional states in real time. This system operates with the cooperation of an information processing device, a terminal, and the user.

[0565] The server includes an information processing device for regularly updating legal data and historical case precedent data. This ensures that the latest legal information is always available, forming the basis for judgment formation.

[0566] The terminal is equipped with a mechanism for digitizing court records and generating prompt text. This allows users to easily input relevant data and generate comprehensive opinions that combine legal and emotional data.

[0567] The system utilizes multiple generative AI modules as knowledge processing units to generate prompt-based opinions. In this process, techniques applied to analyze visitor emotions can identify abnormal emotional states, aiding in preventative measures and enhanced safety management.

[0568] As a concrete example, in a public facility's safety management system, this system can be used to monitor visitors' levels of tension and excitement in real time and issue warnings to security staff.

[0569] An example of a prompt message to provide to a generative AI model is: "Create a sentiment analysis report of today's visitors and issue a warning if there are any anomalies. Here are the visitors' audio and video data."

[0570] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0571] Step 1:

[0572] The terminal receives court records and visitor audio / video data provided by the user. This input data is digitized and converted into an easily analyzable format. The digitized data is stored in the terminal's storage and prepared for use in subsequent processing steps.

[0573] Step 2:

[0574] The server generates prompt text based on the received digital data. This prompt text is used as input for the generative AI model to generate opinions. In this process, the digital data is processed into a format suitable for the prompt and passed to the AI ​​model as textual information.

[0575] Step 3:

[0576] The terminal sends the generated prompt text to the server, which then supplies it to multiple generative AI models. The server uses the prompt text to perform data calculations in the generative AI models, generating anomaly detection considerations based on legal opinions and visitor sentiment.

[0577] Step 4:

[0578] The server aggregates the opinions obtained from the generated AI models and facilitates consensus-building among the models. During this consensus-building process, an attempt is made to construct a draft judgment based on the generated opinions. Throughout this process, the output opinions of each model are compared and adjusted.

[0579] Step 5:

[0580] The final agreed-upon judgment is finalized within the system and reported to the judge or security staff via the terminal. The report includes information related to anomaly detection, as well as other materials to assist in decision-making and security measures.

[0581] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0582] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0583] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0584] [Fourth Embodiment]

[0585] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0586] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0587] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0588] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0589] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0590] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0591] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0592] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0593] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0594] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0595] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0596] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0597] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0598] This invention is an AI agent-based court judgment system that utilizes legal information and past case precedents. To realize this, the server, terminals, and users work together to operate the system as follows.

[0599] The server first periodically updates legal information and past case precedents, and stores them in a database. This information is all the data that the generating AI model agent needs in the context of a trial.

[0600] Users use their devices to convert court-related documents, evidence, and witness testimonies into digital format and send them to a server. These digitized court records are analyzed on the server and provided to an AI agent as prompts.

[0601] The server prompts agents to exchange opinions and reach a consensus based on prompts. Each agent generates an individual opinion using the provided legal information and past case law. This allows multiple AI agents to grasp the overall picture of the trial and engage in discussions to reach a fair judgment.

[0602] The draft judgment, formed through discussions among agents, is finalized via the server and reported to the court. Users then consider adopting this report as their final court decision. This system enhances objectivity and fairness in the judicial process and enables faster judgments.

[0603] As a concrete example, consider a murder trial. The server provides the agent with precedents from similar past cases and relevant laws. The agent identifies several possibilities based on the details of the case and discusses which judgment would be appropriate in accordance with current laws. As a result, an unbiased and objective draft judgment is created.

[0604] The following describes the processing flow.

[0605] Step 1:

[0606] The server collects the latest legal information and past case law information from the internet and relevant databases, and stores it in its internal database. This data is updated regularly to ensure that the AI ​​agent always makes decisions based on the most up-to-date information.

[0607] Step 2:

[0608] Users upload all court documents, evidence, and testimonies as digital data to the server using their devices. This includes scanning documents and transcribing audio into text.

[0609] Step 3:

[0610] The server analyzes the uploaded digital data and generates prompts for the AI ​​agent. These prompts include court records such as a case summary, evidence list, and witness testimonies.

[0611] Step 4:

[0612] The server sends the generated prompt to multiple AI agents. Each AI agent generates an opinion based on the prompt and independently forms an initial draft judgment.

[0613] Step 5:

[0614] AI agents exchange opinions via a server. Each agent receives feedback on the opinions of other agents and modifies its own views as needed.

[0615] Step 6:

[0616] Through discussions among the agents, an agreement on the draft judgment is reached. The agreed-upon draft judgment is reported to the server as the final judgment.

[0617] Step 7:

[0618] The server automatically generates the agreed-upon judgment as a final report and provides it to the user, a court-related party. This report includes the basis for the judgment and a record of the exchange of opinions among the agents.

[0619] (Example 1)

[0620] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0621] In the traditional judicial process, there has been a challenge in ensuring fairness and objectivity in trials while simultaneously delivering swift judgments. In particular, the difficulty in efficiently utilizing vast amounts of legal information and past precedents has led to lengthy decision-making processes and increased costs.

[0622] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0623] In this invention, the server includes means including an information storage device that periodically updates legal information and past case law information; processing means that digitizes materials related to a trial and generates them as input instructions; and processing means that uses multiple generating artificial intelligence models as intermediary devices to generate opinions based on the input instructions. This makes it possible to make quick and objective judgments based on data of laws and precedents.

[0624] An "information storage device" is a data management device for storing legal information and past case law information, and for periodically updating it.

[0625] An "information processing device" is a primary device used to process legal information and manage and analyze various types of digitized data.

[0626] "Processing means" refers to a technical method or device used to perform a specific function or task.

[0627] "Input instructions" refer to the presentation of information to organize court-related information and provide it to a generative artificial intelligence model.

[0628] A "generative artificial intelligence model" is a type of artificial intelligence technology used to generate judgments and opinions based on provided data.

[0629] A "mediating device" is a function or device that plays a central role in facilitating the exchange of various types of information and the aggregation of opinions using a generated artificial intelligence model.

[0630] "Viewpoint" refers to judgments or opinions generated based on the information provided.

[0631] "Judgment" refers to the final conclusion or decision formed based on various pieces of information.

[0632] A "report document" is a document prepared for judicial institutions to explain the results of a ruling.

[0633] "Judge" refers to an individual or institution that has the authority to make judicial decisions.

[0634] An embodiment of the present invention is a court judgment support system based on legal information and past case law information. This system is operated by coordinating an information processing device and a terminal device.

[0635] The server first functions as an "information storage device," storing legal information and past case precedents. It also periodically updates this information as an "information processing device," ensuring that necessary data is always up-to-date. Specifically, it retrieves data from online legal information platforms. An example of such a platform is a legal information retrieval system commonly used in the industry.

[0636] Users digitize court-related documents using a terminal. They convert documents, evidence, and witness testimonies into digital format using a scanner and speech recognition software connected to the terminal. This process utilizes common document digitization software and speech recognition tools.

[0637] The digitized documents on the terminal are sent to the server. The server analyzes the received data and uses it as a prompt for the generating AI model. An example of a prompt might be, "Based on the following documents related to the trial, please generate a draft judgment considering the relevant laws and past precedents."

[0638] The server uses these prompts to run multiple generative artificial intelligence models. Each AI model generates insights based on the assigned prompt. The generative artificial intelligence models can utilize software with mature generative algorithms.

[0639] This will enable users to achieve greater fairness and efficiency in legal decisions and the judicial process. It is expected that legal work will be carried out more quickly and accurately through the use of this system.

[0640] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0641] Step 1:

[0642] The server retrieves legal and case law information from an online legal information service. It receives update commands for already stored legal information as input. The server retrieves this update information and stores it in the information storage device. This ensures the database always maintains the latest legal information. The output is the updated legal information database. Each data item is organized by category in preparation for subsequent processing.

[0643] Step 2:

[0644] Users digitize court-related documents using a terminal. Input includes paper documents, evidence, and audio testimonies. The terminal converts documents to PDF or image formats via a scanner and converts audio to text using speech recognition software. The output is a digitized court document file, which is sent to a server.

[0645] Step 3:

[0646] The server receives digitized documents submitted by users. It accepts multiple digital files as input. The server uses natural language processing techniques to analyze the document content and extract key keywords and evidence. The output is a prompt message for a generative AI model, containing a summary of the trial and relevant legal matters.

[0647] Step 4:

[0648] The server sends prompts to multiple generative AI models. The input, in the form of a prompt statement, contains information including a case summary, relevant laws and regulations, and past precedents. Based on this, the AI ​​models process the data to generate opinions and predicted judgments. The output is a generated document containing the opinions of each AI model.

[0649] Step 5:

[0650] The server aggregates the outputs from the AI ​​models and verifies the consistency of their opinions. The input consists of each AI model's proposed judgment. The server integrates these to generate the most appropriate ruling. It then creates a final report. The output is a carefully prepared report for the court. This report is provided to the user and serves as important reference material for court decisions.

[0651] (Application Example 1)

[0652] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0653] There is a need to provide swift and appropriate legal judgments in various situations that arise on the ground, but current methods make it difficult to make quick decisions based on legal information and past precedents. Therefore, a support system is needed to enable on-site personnel to take appropriate action immediately.

[0654] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0655] In this invention, the server includes a computer containing a source of information that periodically updates legal information and past case law information, means for digitizing on-site events and generating them as command statements, and means installed on a smart device to provide immediate legal judgments on-site. This makes it possible to make legal judgments quickly on-site.

[0656] "Legal information" refers to data and materials related to the law, and includes relevant information such as precedents and legal provisions.

[0657] "Past case law information" refers to records and judgments from past trials, and is information that can be used as a reference for legal decisions.

[0658] A "directive document" is a digitized instruction or command document used when making legal decisions in a specific situation.

[0659] A "generative AI model" is a type of artificial intelligence designed to perform a specific task, and it is an algorithm that generates appropriate output from input information.

[0660] An "assistant" is a system element that uses a generative AI model to assist in performing specific tasks.

[0661] "Consensus" refers to discussions and consultations aimed at reconciling multiple opinions and finding the optimal solution.

[0662] A "smart device" refers to a portable terminal that has internet connectivity and can run a variety of applications, and includes smartphones and tablets.

[0663] "Immediate legal judgment" refers to the act of making a swift and appropriate judgment based on laws and regulations in a given situation.

[0664] To realize this application, the server periodically updates legal information and past case precedents, maintaining them as information sources. It also digitizes on-site events via smart devices, generates them as command statements, and transmits them. The generated command statements are used as foundational information to provide specific legal judgments using a generative AI model.

[0665] The terminal captures events at the scene and quickly transmits them to the server. This enables real-time information processing and supports appropriate decision-making at the scene.

[0666] Users can use their smart devices to receive legal judgments provided by the server and apply them to on-site responses. Through this process, users can take appropriate legal action immediately.

[0667] The generative AI model uses multiple assistants to generate relevant legal advice based on the given instructions. Through deliberation among the assistants, the optimal course of action is formed and provided to the user.

[0668] For example, if a security guard spots a suspicious person in a commercial facility, they can input the incident details into their smartphone, and the server will provide relevant legal information to the AI, which will then suggest a legally appropriate course of action.

[0669] Example prompt for the generating AI model: "Immediately provide legal responses to intruders at the facility. Suggest appropriate actions based on past intrusion case precedents and relevant laws."

[0670] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0671] Step 1:

[0672] The server regularly updates its database with legal information and past case precedents. This information is collected from external legal databases and stored in the server's storage system. This ensures that the latest legal resources are always available for use by the generative AI model. The input is legal data obtained from external sources, and the output is the updated internal database.

[0673] Step 2:

[0674] The terminal digitizes events at the scene and inputs detailed information. Users use smart devices to input incident details via text or voice. This data is formatted and sent to the server. The input is the incident details provided by the user, and the output is the digitized data sent to the server.

[0675] Step 3:

[0676] The server generates prompts from the digitized data received from the terminal. These generated prompts are used as foundational information for subsequent AI processing. This step cleanses and structures the data, facilitating processing by the AI ​​model. The input is digitized incident information, and the output is the generated prompts.

[0677] Step 4:

[0678] The generative AI model generates relevant legal advice based on prompt messages received from the server. The AI ​​model generates the most appropriate legal judgment by referring to an internal legal information database. The input consists of prompt messages and legal information, while the output is the legal advice generated by each AI assistant.

[0679] Step 5:

[0680] The server aggregates legal advice generated by multiple assistants and forms an optimal response plan through deliberation. It weights and prioritizes each assistant's opinion to select the most appropriate plan. The input is multiple legal advice, and the output is the agreed-upon optimal response plan.

[0681] Step 6:

[0682] The user receives the optimal response plan from the server and confirms it via a smart device. This allows the user to take appropriate legal action quickly on-site. The input is the response plan sent from the server, and the output is the specific action to be taken on-site.

[0683] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0684] This invention is a court judgment system that combines legal information and past case law information with an emotion engine that recognizes the user's emotions. The operation of this system is carried out through the cooperation of the server, terminal, and user.

[0685] The server continuously updates legal information and case law data, storing it in a database. This provides the foundation for AI agents to always make decisions based on the latest information.

[0686] Users digitize court documents, evidence, and testimonies and upload them from their devices to a server. This digital data includes not only text but also video and audio. The uploaded data is analyzed on the server and compiled into prompts for the AI ​​agent.

[0687] This process incorporates an emotion engine. The emotion engine recognizes the emotions of witnesses and those involved through audio and video analysis, and includes this information in the data. This emotional information is treated as a factor to consider when generating prompts.

[0688] The generated prompts are provided to multiple AI agents, and each agent forms an opinion based on them. Because the opinions generated by the AI ​​agents take recognized emotional information into consideration, more multifaceted judgments are possible. In opinion exchanges and discussions among agents, emotional information is also incorporated as a factor in reaching a consensus.

[0689] Ultimately, the agreed-upon judgment is automatically generated as a report for the court via the server. This report includes, in addition to the legal basis, supplementary emotional data recorded by the emotional engine. This helps judges and stakeholders gain a deeper understanding of the case's context.

[0690] As a concrete example, consider a trial concerning domestic violence. In this case, the audio and video of the witnesses are analyzed by an emotion engine to recognize feelings of tension and fear. This emotional information becomes an important element in judging and is taken into consideration by an AI agent. In this way, the present invention realizes a system that supports trials from both legal and human emotional perspectives.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] The server collects legal information and past case law data from the internet and related databases, and stores it in a database. This data forms the basis for the decisions of the generative AI model and is updated regularly.

[0694] Step 2:

[0695] Users use their devices to convert court records into digital format and upload them to the server. These court records include scanned images of documents, as well as audio and video.

[0696] Step 3:

[0697] The server analyzes the uploaded digital data. During this process, it uses an emotion engine to analyze the emotions of witnesses and related parties from audio and video, and extracts emotional information.

[0698] Step 4:

[0699] The server generates prompts for the AI ​​agent based on the analysis. These prompts include legal information, case law information, court records, and sentiment information.

[0700] Step 5:

[0701] The server provides the generated prompt to multiple AI agents, and each agent generates its own opinion based on this prompt. The generated opinion takes into account recognized sentiment information.

[0702] Step 6:

[0703] AI agents exchange opinions, incorporating emotional information, and proceed through a deliberative process to construct a draft judgment. This process involves adjusting opinions and clarifying points of contention in order to reach an agreement.

[0704] Step 7:

[0705] The agreed-upon judgment draft is automatically generated by the server as a final report. This report includes the legal basis for the judgment, precedents, and perceived sentiment information.

[0706] Step 8:

[0707] Judges and lawyers, who are users of the system, review the final reports provided by the server to help them make their final decisions. The reports include detailed emotional information to deepen their understanding of the case's context.

[0708] (Example 2)

[0709] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0710] In the decision-making process in court, it is necessary to handle legal information and past precedents quickly and accurately. However, the current system has challenges in that it does not adequately update relevant information and process sentiment information, resulting in insufficient multifaceted support for decision-making.

[0711] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0712] In this invention, the server includes means for continuously updating and accumulating legal information and past case law information, means for converting evidence and testimonies into digital information and processing them, and means for recognizing emotions and incorporating them into relevant data. This enables multifaceted and comprehensive support in the decision-making process.

[0713] "Legal information" refers to the collective term for articles of law, statutes, regulations, and related information.

[0714] "Case law information" refers to information about cases decided in court in the past, and includes data on judgments and their interpretations.

[0715] "Information aggregation" refers to the process of continuously collecting and storing data and information necessary for a specific purpose.

[0716] "Evidence" refers to any form of information, such as documents, photographs, and physical evidence, provided in court to prove the facts.

[0717] "Digital information" refers to information data in a form that can be handled by a computer, and includes formats that can be stored, transferred, and processed electronically.

[0718] "The process of recognizing emotions and incorporating them into related data" refers to the process of analyzing audio and video to extract emotional states and processing them together with other data.

[0719] The "decision-making process" is the process of making a final decision after going through a series of steps to find a solution to a particular problem.

[0720] "Comprehensive support" refers to assistance and support provided by taking into account multiple aspects and needs as a whole.

[0721] This invention is a court support system that processes legal information and past case law information, and is operated collaboratively by a server, terminals, and users. The server is responsible for continuously acquiring and updating legal information and case law information and storing it in a database. This provides a foundation for always utilizing the latest information within the system.

[0722] Users digitize documents and evidence necessary for trials and upload them to the server via their devices. The digitized data can take various forms, including text, audio, and video. The server analyzes this data and generates prompts for use by a generative AI model. This process utilizes natural language processing and image recognition technologies.

[0723] Furthermore, emotion recognition software embedded in the server analyzes audio and video to extract emotional information and incorporate it into the analysis data. This provides the generative AI model with a multifaceted perspective that takes emotional information into account when forming opinions.

[0724] As a concrete example, consider a trial dealing with domestic disputes. In the process of digitizing the audio and video of witnesses on a terminal and analyzing them on a server, the emotion engine extracts emotions such as fear and tension. This information is used by the AI ​​agent to make the best possible decisions.

[0725] An example of a prompt message from this system would be, "Analyze the testimony regarding the domestic dispute and form your judgment considering the perceived emotional information." This system integrates legal information with human emotions to enable more objective and detailed legal support.

[0726] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0727] Step 1:

[0728] Users prepare court-related documents and evidence, and digitize this information using a terminal. Users convert documents into image data using scanners and cameras, and prepare testimonies as digital audio or video data using audio and video recording devices. These digital data are then uploaded from the terminal to a server. Physical documents, audio, and video are used as input, and digital data files are generated as output.

[0729] Step 2:

[0730] The server receives uploaded digital data and performs analysis using natural language processing and image recognition technologies. The server extracts text data, detects important scenes from video data, and transcribes audio data. Through this analysis process, prompt sentences are generated for use by the AI ​​agent. Digital data files are used as input, and the analyzed information and prompt sentences are generated as output.

[0731] Step 3:

[0732] The emotion recognition software embedded in the server analyzes audio and video from digital data to extract the emotional state of the speaker or character. It evaluates elements such as tone of voice, facial expressions, and gestures to identify emotional information. This information is added to the analysis data, forming the basis for the AI ​​agent to make multifaceted judgments. Audio and video data are used as input, and emotional information is generated as output.

[0733] Step 4:

[0734] The server provides prompt text and attached sentiment information to multiple generative AI models (agents). Each agent forms an opinion based on the provided information, considering legal and emotional factors. Opinions are exchanged among the agents, and a final opinion is aggregated through consensus. Prompt text and sentiment information are used as input, and a collective opinion is generated as output.

[0735] Step 5:

[0736] The server automatically generates reports for the court based on opinions determined by the AI ​​agent. These reports include not only legal grounds but also emotional information as background to the judgment. The reports are created in digital format and provided to judges and other relevant parties. Collective opinions are used as input, and the reports are generated as output.

[0737] (Application Example 2)

[0738] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0739] The current judicial judgment system allows for decisions based on legal information and past precedents, but it struggles to make multifaceted judgments that take into account the emotional states of those involved. Furthermore, even in enhancing security at public facilities, the system lacks the ability to analyze visitors' emotions in real time and detect anomalies. This makes it difficult to gain a deeper understanding of the background of an incident and to respond quickly to unusual situations.

[0740] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0741] This invention includes an information processing device that periodically updates legal data and past case precedent data, a mechanism that digitizes court records and generates them as prompts, and a method for analyzing visitors' emotional states in real time and detecting anomalies. This improves the quality of legal judgments and strengthens security management.

[0742] "Legal data" refers to a collection of information including the latest legal information and related laws and regulations, which forms the basis for the system to make legal decisions.

[0743] "Past case data" refers to records of past judicial decisions, which are referenced by the system when generating opinions based on similar cases.

[0744] An "information processing device" is a computer system for storing and updating legal data and past case law data, and is an element for performing analytical processing.

[0745] "Digitalization" is the process of converting information in analog format into electronic data, and it is a method that enables data storage and analysis.

[0746] A "prompt" is a format of text or data that acts as a trigger when providing information to an AI module, and it plays a role in inducing the generation of opinions.

[0747] A "generative AI module" is a group of artificial intelligence programs that generate opinions and judgments based on prompts, and has the function of making decisions within the system.

[0748] A "knowledge processing unit" is an information processing unit used by a generative AI module when forming specific opinions, and it is the foundation for deriving the optimal opinion through deliberation.

[0749] "Visitor's emotional state" refers to an individual's psychological state analyzed from audio and video, and serves as an indicator for the system to detect anomalies.

[0750] "Anomaly detection" is the process of identifying unusual emotional states or behaviors and generating alerts to take preventative measures, thereby contributing to improved security.

[0751] This invention is a novel system that renders multifaceted court judgments by using legal data, past case precedent data, and analyzing visitors' emotional states in real time. This system operates with the cooperation of an information processing device, a terminal, and the user.

[0752] The server includes an information processing device for regularly updating legal data and historical case precedent data. This ensures that the latest legal information is always available, forming the basis for judgment formation.

[0753] The terminal is equipped with a mechanism for digitizing court records and generating prompt text. This allows users to easily input relevant data and generate comprehensive opinions that combine legal and emotional data.

[0754] The system utilizes multiple generative AI modules as knowledge processing units to generate prompt-based opinions. In this process, techniques applied to analyze visitor emotions can identify abnormal emotional states, aiding in preventative measures and enhanced safety management.

[0755] As a concrete example, in a public facility's safety management system, this system can be used to monitor visitors' levels of tension and excitement in real time and issue warnings to security staff.

[0756] An example of a prompt message to provide to a generative AI model is: "Create a sentiment analysis report of today's visitors and issue a warning if there are any anomalies. Here are the visitors' audio and video data."

[0757] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0758] Step 1:

[0759] The terminal receives court records and visitor audio / video data provided by the user. This input data is digitized and converted into an easily analyzable format. The digitized data is stored in the terminal's storage and prepared for use in subsequent processing steps.

[0760] Step 2:

[0761] The server generates prompt text based on the received digital data. This prompt text is used as input for the generative AI model to generate opinions. In this process, the digital data is processed into a format suitable for the prompt and passed to the AI ​​model as textual information.

[0762] Step 3:

[0763] The terminal sends the generated prompt text to the server, which then supplies it to multiple generative AI models. The server uses the prompt text to perform data calculations in the generative AI models, generating anomaly detection considerations based on legal opinions and visitor sentiment.

[0764] Step 4:

[0765] The server aggregates the opinions obtained from the generated AI models and facilitates consensus-building among the models. During this consensus-building process, an attempt is made to construct a draft judgment based on the generated opinions. Throughout this process, the output opinions of each model are compared and adjusted.

[0766] Step 5:

[0767] The final agreed-upon judgment is finalized within the system and reported to the judge or security staff via the terminal. The report includes information related to anomaly detection, as well as other materials to assist in decision-making and security measures.

[0768] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0769] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0770] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0771] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0772] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0773] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0774] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0775] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0776] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0777] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0778] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0779] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0780] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0781] 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.

[0782] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0783] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0784] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0785] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0786] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0787] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0788] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0789] The following is further disclosed regarding the embodiments described above.

[0790] (Claim 1)

[0791] A server containing a database that regularly updates legal information and past case law information,

[0792] A means of digitizing court records and generating them as prompts,

[0793] A means for generating opinions based on a prompt, using multiple generative AI models, each as an agent,

[0794] A means of exchanging and deliberating the opinions generated by each agent to form a draft judgment,

[0795] A system that provides a means to finalize an agreed-upon judgment as the final ruling.

[0796] (Claim 2)

[0797] The system according to claim 1, which includes means for uploading court records in digital format from a terminal to a server.

[0798] (Claim 3)

[0799] The system according to claim 1, comprising means for automatically generating a final judgment as a report to the court and providing it to the judge.

[0800] "Example 1"

[0801] (Claim 1)

[0802] An information processing device including an information storage device that periodically updates legal information and past case law information,

[0803] A processing means for digitizing court-related documents and generating them as input instructions,

[0804] A processing means that generates an opinion based on the input instruction, using multiple generative artificial intelligence models as intermediary devices,

[0805] A processing means that exchanges and aggregates the views generated by each mediating device and forms a decision proposal,

[0806] A processing means for confirming the formed decision proposal as the final decision,

[0807] A system that includes this.

[0808] (Claim 2)

[0809] The system according to claim 1, which includes processing means for transferring court-related materials from a terminal device to an information processing device in an information format.

[0810] (Claim 3)

[0811] The system according to claim 1, comprising a processing means for automatically generating a finalized judgment as a report for judicial bodies and providing it to the judge.

[0812] "Application Example 1"

[0813] (Claim 1)

[0814] A computer that includes a source of information that regularly updates legal information and past case law information,

[0815] A means of digitizing on-site events and generating them as instruction documents,

[0816] A means for generating advice based on the command statement, using multiple generative AI models, each acting as an assistant,

[0817] A means of exchanging and discussing the advice generated by each assistant to form the optimal solution,

[0818] A means of finalizing the agreed-upon response plan,

[0819] A system installed on smart devices that provides a means to deliver immediate legal decisions on-site.

[0820] (Claim 2)

[0821] The system according to claim 1, comprising means for uploading site details in a digital format from a terminal to a computer.

[0822] (Claim 3)

[0823] The system according to claim 1, which includes means for automatically generating a report for on-site personnel outlining the finalized response plan and providing it to the relevant parties.

[0824] "Example 2 of combining an emotion engine"

[0825] (Claim 1)

[0826] A means of continuously updating and accumulating legal information and past case law information,

[0827] Means for converting and processing evidence and testimonies into digital information,

[0828] A means of recognizing emotions and processing them to incorporate them into related data,

[0829] A means of seeking opinions based on prompts using multiple generating devices as agents,

[0830] A means of mutually considering and consolidating the opinions of each agent to derive a conclusion,

[0831] A system that includes means to fix an agreed-upon conclusion as the final decision.

[0832] (Claim 2)

[0833] The system according to claim 1, which includes means for transmitting court-related information in electronic format from an input device to an information accumulating device.

[0834] (Claim 3)

[0835] The system according to claim 1, comprising means for automatically compiling the finalized decision into a report for relevant organizations and providing it to the relevant parties.

[0836] "Application example 2 when combining with an emotional engine"

[0837] (Claim 1)

[0838] An information processing device that periodically updates legal data and past case precedent data,

[0839] A mechanism for digitizing court records and generating them as prompts,

[0840] A mechanism that uses multiple generative AI modules, each as a knowledge processing unit, to generate opinions based on the prompt,

[0841] A means of exchanging and deliberating the opinions generated by each knowledge processing unit and organizing a draft judgment,

[0842] A method for analyzing visitors' emotional states in real time and detecting anomalies,

[0843] An information processing system equipped with a system for finalizing agreed-upon judgments as final judgments.

[0844] (Claim 2)

[0845] The system according to claim 1, comprising means for transmitting court records in digital format from a terminal to an information processing device.

[0846] (Claim 3)

[0847] The system according to claim 1, which includes means for automatically generating a final judgment as a report for judicial bodies and providing it to jurors. [Explanation of Symbols]

[0848] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A computer that includes a source of information that regularly updates legal information and past case law information, A means of digitizing on-site events and generating them as instruction documents, A means for generating advice based on the command statement, using multiple generative AI models, each acting as an assistant, A means of exchanging and discussing the advice generated by each assistant to form the optimal solution, A means of finalizing the agreed-upon response plan, A system installed on smart devices that provides a means to deliver immediate legal decisions on-site.

2. The system according to claim 1, which includes means for uploading site details in a digital format from a terminal to a computer.

3. The system according to claim 1, which includes means for automatically generating a report for on-site personnel outlining the finalized response plan and providing it to the relevant parties.

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