System

Abstract

A system is provided.SOLUTION: A system comprising: means for presenting choices to a user; a production AI agent supporting each choice, the production AI agent generating a reason for support for each respective choice; means for presenting the generated reason for support of each choice to the user; means for generating counterarguments for other choices; and means for presenting the generated counterarguments to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional decision support systems are inadequate in helping users make the right decision when faced with multiple options, and lack a way to fully understand the advantages and disadvantages of each option. In many cases, users are forced to rely on a single source of information, making it difficult to gain an objective, multifaceted perspective. This can lead to biased decision-making, regret, or mistakes.

[0005] This invention aims to solve the problems of the past by using a generative AI agent that supports multiple options to help users make more comprehensive and balanced decisions. [Means for solving the problem]

[0006] The present invention is a system for supporting a user's decision making, and includes the following means.

[0007] First, a means is provided for presenting options to the user, so that the user can compare and consider multiple options.

[0008] Next, a generating AI agent is included to support each option, and a means is provided for the generating AI agent to generate reasons for supporting each option, allowing the user to concretely understand the advantages of each option.

[0009] Furthermore, a means is provided for presenting the reasons for supporting each generated option to the user, thereby enabling the user to directly confirm the agent's opinion on each option.

[0010] Additionally, it provides a means for generating counterarguments to other options, allowing agents to point out the shortcomings of other options and promote deeper understanding.

[0011] Finally, we provide a means for presenting the generated counterarguments to the user, allowing them to weigh the pros and cons of each option and make the most appropriate decision.

[0012] Overall, this invention is a system that aims to assist users who are struggling between multiple options in their decision-making by using a generative AI agent to present reasons supporting and counterarguments for each option.

[0013] "Choices" are multiple possible outcomes or actions that a user can consider when making a decision.

[0014] "User" means an individual or organization that makes decisions using the system.

[0015] A "generative AI agent" is a program that uses artificial intelligence to generate text based on specific prompts, providing reasons for and counterarguments to a particular option.

[0016] "Reasons for" are arguments or evidence that justify a particular option and recommend that choice.

[0017] A "rebuttal" is an argument that points out the criticisms and flaws of other options and demonstrates the superiority of the option that one supports.

[0018] A "system" is a technical construct that includes a set of means and processes for generating and presenting arguments for and against alternatives.

[0019] A "means" is a method, device, or software used to achieve a particular function or role. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0028] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0041] The following describes a specific embodiment of the present invention. The present invention is a system for supporting user decision-making, and in particular, provides a method for supporting a user who is struggling between multiple options by having a generation AI agent that supports each option exchange opinions to support the user's decision-making.

[0042] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, and a means for presenting the generated reasons for supporting and counterarguments to the user.

[0043] System Operation

[0044] 1. Setting options

[0045] The server receives as input the multiple options the user is considering. These options are set in list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0046] 2. Initial setup of the generated AI agent

[0047] The server prepares a generative AI agent for each option. The generative AI agent is designed to support each option and generates text using a generative AI model.

[0048] 3. Generating reasons for support

[0049] For each option, the server sends a command to the generating AI agent to generate reasons for each option. Each agent generates text explaining the merits and validity of each option and sends it to the server.

[0050] 4. Presentation of reasons for support

[0051] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0052] 5. Generating and Presenting Counterarguments

[0053] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also presented to the user.

[0054] Specific examples

[0055] Campaign banner wording selection

[0056] The server sets the following options:

[0057] Option A: "Flash Sale - 50% OFF!"

[0058] Option B: "Limited Time Offer - Buy One, Get One Free"

[0059] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0060] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0061] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0062] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0063] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0064] The server presents these reasons to the user's device, and the user compares and considers each reason. Furthermore, counterarguments to other options are also generated and presented to the user. This allows the user to deeply understand the advantages and disadvantages of each option and make a final decision.

[0065] The present invention provides users with comprehensive support for selecting the most appropriate option from among multiple options, thereby aiming to improve the accuracy and satisfaction of decision-making.

[0066] The processing flow will be explained below.

[0067] Step 1:

[0068] The server receives multiple options from the user's terminal, which are presented in the form of a list based on a specific theme, such as selecting a campaign banner or choosing a specific product.

[0069] Step 2:

[0070] The server prepares generative AI agents according to the number of options received, each configured to support a particular option using a specified generative AI model.

[0071] Step 3:

[0072] The server sends a prompt to each agent, instructing them to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of each option.

[0073] Step 4:

[0074] The server aggregates the generated support reasons and sends them to the user's terminal, where the user can view the support reasons presented by each agent.

[0075] Step 5:

[0076] The server generates counterarguments to other options as needed, sending prompts to each agent to criticize or point out flaws in the other options, and each agent generates a counterargument.

[0077] Step 6:

[0078] The server collects the generated counterarguments and sends them to the user's terminal, where the user can view the counterarguments for each option.

[0079] Step 7:

[0080] The user compares the arguments for and against each agent presented on the device, allowing them to gain a balanced perspective on multiple options.

[0081] Step 8:

[0082] The user can decide the most appropriate option based on the information presented and provide feedback of that decision to the server.

[0083] Example 1

[0084] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0085] Conventional decision support systems often lack the information necessary to make an appropriate decision between multiple options. Furthermore, there are limited means to provide users with sufficient information to properly compare the supporting and counterargumentative arguments for each option and make the optimal choice. This can lead to problems such as users being confused and reducing the accuracy and satisfaction of their decision-making.

[0086] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0087] In this invention, the server includes means for presenting options to a user, a generation AI agent supporting each option, means for the generation AI agent to generate reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments for other options, means for presenting the generated counterarguments to the user, and means for generating reasons for supporting each option based on a prompt sentence using a generative AI model. This allows the user to easily compare the reasons for supporting and counterarguments for each option, and provides sufficient information for making an optimal decision.

[0088] A "means for presenting options to a user" is a system element that provides multiple options to a user in visual or text format, allowing the user to compare and consider the options.

[0089] A "generative AI agent" is an artificial intelligence program or algorithm that generates reasons and counterarguments in support of each option.

[0090] "Means for generating supporting reasons" is a function that allows the generative AI agent to use the generative AI model to generate reasons and advantages in favor of a given option in text format.

[0091] The "means for presenting the generated reasons for supporting each option to the user" is a system element that visualizes and displays to the user the reasons for supporting each option generated by the generating AI agent.

[0092] "Means for generating counterarguments to alternative options" refers to the ability of a generative AI agent to use a generative AI model to generate, in text form, reasons for opposing or shortcomings of alternative options.

[0093] The "means for presenting the generated counterargument to the user" is a system element that visualizes and displays the counterargument generated by the generating AI agent to the user.

[0094] A "generative AI model" is an artificial intelligence algorithm or program that automatically generates text, specifically a model trained for natural language processing.

[0095] A "prompt sentence" is an input sentence that instructs a generative AI model to generate a specific text.

[0096] This invention is a system that supports user decision-making, and provides a method for users who are struggling to decide between multiple options by having a generating AI agent that supports each option exchange opinions to support the user's decision-making. This system has the following specific configuration and functions.

[0097] System Overview

[0098] The system primarily includes the following hardware and software components:

[0099] Server: Handles data processing and manages generated AI agents.

[0100] User terminal: A device through which a user can input their choices and view the generated supporting and counterargumentative reasons.

[0101] Generative AI models: AI models for natural language processing and text generation (e.g., GPT-4).

[0102] Specific operation of the system

[0103] 1. Enter your choices

[0104] The server receives multiple options from the user as input. These options are set in a list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0105] 2. Initial setup of the generated AI agent

[0106] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option and generates text using a generative AI model (e.g., GPT-4). The prompt text is also set at this stage.

[0107] 3. Generating reasons for support

[0108] For each option, the server sends a prompt to the generating AI agent, which generates a reason for each option and sends the generated text to the server.

[0109] 4. Presentation of reasons for support

[0110] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0111] 5. Generating and Presenting Counterarguments

[0112] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option look more favorable. The generated counterarguments are also presented to the user.

[0113] Specific examples

[0114] Scenario for selecting campaign banner wording

[0115] 1. Setting options

[0116] The server sets the following options:

[0117] Option A: "Flash Sale - 50% OFF!"

[0118] Option B: "Limited Time Offer - Buy One, Get One Free"

[0119] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0120] 2. Initial setup of the generated AI agent

[0121] The server prepares a generating AI agent to support each option, with each prompt set as follows:

[0122] "Generate a 3-5 sentence reasoning in support of the following option: 'Flash Sale - 50% OFF!'"

[0123] "Generate 3-5 sentences supporting the following option: 'Limited Time Offer - Buy One, Get One Free'"

[0124] "Generate 3-5 sentences supporting the following option: 'Exclusive Deal - Free Shipping on Orders Over $50'"

[0125] 3. Generating reasons for support

[0126] The generating AI agent uses the prompt sentence to generate reasons for support such as:

[0127] Agent A: "Flash Sale - 50% OFF!" will motivate customers to buy and contribute to immediate sales.

[0128] Agent B: "Limited Time Offer - Buy One, Get One Free" increases sales and smooths inventory flow.

[0129] Agent C: "Exclusive Deal - Free Shipping on Orders Over $50" encourages customers to buy and reduces shipping costs, increasing their motivation to buy.

[0130] 4. Presentation of reasons for support

[0131] The server transmits these reasons for support to the user's terminal, and the user compares and considers each reason for support on the terminal.

[0132] 5. Generating and Presenting Counterarguments

[0133] The server also generates a rebuttal as follows:

[0134] Agent A argues against the "Limited Time Offer - Buy One, Get One Free" by pointing out that it would make inventory management difficult.

[0135] Agent B argues that the "Exclusive Deal - Free Shipping on Orders Over $50" offer is not as impressive a discount.

[0136] This allows users to deeply understand the advantages and disadvantages of each option and make optimal decisions. This system aims to improve the accuracy and satisfaction of users' decision-making.

[0137] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0138] Step 1: User inputs choices

[0139] The server provides an interface for the user to input multiple options via the terminal. The options to be input may be, for example, campaign banner text or product features, and once the user has completed the input, the server receives it. The received data is structured and stored in a database. The input data is often in the form of a list or JSON.

[0140] Specific behavior:

[0141] The user enters options such as "Flash Sale - 50% OFF!" or "Limited Time Offer - Buy One, Get One Free" into the terminal, and the server receives it and stores it in the database.

[0142] Step 2: Initializing the generated AI agent

[0143] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option, and the server sets a prompt sentence that is adapted to it. Specifically, it sets it up to generate text using a generative AI model (e.g., GPT-4).

[0144] Input and Output:

[0145] The server takes the choice data as input and generates the initial settings and prompt sentences for the generated AI agent based on it. The output is the generated AI agent with the initial settings completed.

[0146] Specific behavior:

[0147] For the option "Flash Sale - 50% OFF!", the server sets the prompt text "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'" to the generating AI agent.

[0148] Step 3: Generate supporting reasons

[0149] The server commands the generative AI agent to generate supporting reasons for each option. The generative AI model generates text explaining the merits and validity of each option based on the specified prompt. The generated supporting reasons are sent to the server.

[0150] Input and Output:

[0151] The input is the prompt sentence and option data set in Step 2. This is processed by the generative AI model, and the output is a text of the reasons for support.

[0152] Specific behavior:

[0153] In response to the prompt, "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'", the AI ​​model generates text such as "'Flash Sale - 50% OFF!' will increase customer purchasing intent and contribute to immediate sales growth."

[0154] Step 4: Present your reasons for support

[0155] The server sends the generated reasons for support to the user's device, where these reasons are visually displayed, allowing the user to compare and consider the reasons for support for each option.

[0156] Input and Output:

[0157] The input is the text of the support reasons generated by the generative AI model, and the output is the support reasons displayed on the user's device.

[0158] Specific behavior:

[0159] The server transmits the reason for support, such as "'Flash Sale - 50% OFF!' will increase customers' desire to purchase and contribute to an immediate increase in sales," to the user's terminal, which then displays the reason.

[0160] Step 5: Generate and present a counterargument

[0161] The server commands the generative AI agent to generate a counterargument against the other options. This counterargument is generated by the generative AI model and is a text that points out the shortcomings and problems of the other options. The generated counterargument is also sent to the user's device.

[0162] Input and Output:

[0163] The input is a set of alternatives and a corresponding prompt, which is processed by a generative AI model, and the output is a counterargument text.

[0164] Specific behavior:

[0165] The server inputs a prompt such as "Generate a three-sentence counterargument to the following option, 'Limited Time Offer - Buy One, Get One Free'" into the generative AI model, and the generated text, such as "Inventory management will become more difficult" or "Profit margins may decline," is sent to the user's device, where it is displayed.

[0166] Through these steps, users can compare the reasons for and counterarguments of each option and make the best decision.

[0167] (Application example 1)

[0168] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0169] Currently, when users select the optimal product from multiple product options, it is difficult for them to objectively evaluate the advantages and disadvantages of each product. In particular, e-commerce platforms are overwhelmed with a wide variety of product information, making it difficult for users to properly compare and consider this information. Furthermore, the lack of a system that effectively supports the user selection process leads to problems such as incorrect selection and time-consuming selection.

[0170] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0171] In this invention, the server includes a means for presenting options to a user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments for other options, a means for presenting the generated counterarguments to the user, and a means for generating reasons for supporting and counterarguments for different products and displaying them to the user in the product selection process, thereby enabling the user to understand the advantages and disadvantages of each product option and select the optimal option quickly and efficiently.

[0172] "Choice" refers to each item or option that a user considers to select from multiple choices.

[0173] "User" refers to an individual or corporation that makes decisions using this system.

[0174] "Means" refers to the methods or processes used to achieve a particular goal.

[0175] A "generative AI agent" is a program that uses a generative AI model to support specific options and has the ability to generate text about the advantages and disadvantages of each option.

[0176] "Generated reasons for support" refers to text generated by the generating AI agent explaining the benefits or validity of a particular option.

[0177] "Rebuttal" refers to text generated to point out the flaws or problems of an alternative.

[0178] The "product selection process" refers to a series of actions or steps a user takes to select the optimal product from multiple product options.

[0179] "Display means" refers to a method or device that allows a user to visually view information generated by the system.

[0180] This invention provides a system that helps users select the most suitable product from multiple product options. The system's main hardware configuration is a server and a user terminal. The server uses a generation AI agent to generate reasons for and counterarguments for each option and presents them to the user terminal.

[0181] System Operation

[0182] 1. Setting options

[0183] The user device receives as input multiple product options that the user wants to compare, such as product models like "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6."

[0184] 2. Initial setup of the generated AI agent

[0185] The server prepares a generative AI agent for each product option, each of which uses a specific generative AI model.

[0186] 3. Generating reasons for support

[0187] The server sends commands to each generative AI agent to generate reasons in favor of each option. For example, the generative AI model might generate reasons that the iPhone 13 has the latest processor and offers better performance to users.

[0188] 4. Presentation of reasons for support

[0189] The server transmits the generated reasons for support to the user terminal for the user to view, allowing the user to compare the merits of each product option.

[0190] 5. Generating and Presenting Counterarguments

[0191] The server instructs each generative AI agent to generate a counterargument to the other options. For example, the generative AI model generates a counterargument pointing out that a disadvantage of the Samsung Galaxy S21 is its short battery life.

[0192] These counterarguments are also sent to the user's terminal, allowing the user to weigh the drawbacks of each option.

[0193] Specific usage

[0194] For example, if a user wants to use a shopping site to choose the best smartphone, they might enter the following prompt:

[0195] I want to choose the best smartphone.

[0196] My options are the iPhone 13, the Samsung Galaxy S21, and the Google Pixel 6. What are the advantages of each?

[0197] In response, the generating AI agent generates the following reasons for support:

[0198] Reasons for choosing the iPhone 13: The iPhone 13 is equipped with the latest chipset, offering effective battery management and excellent performance, and is highly compatible with other devices thanks to the Apple ecosystem.

[0199] Reasons for choosing the Samsung Galaxy S21: The Samsung Galaxy S21 has a high-resolution display that is ideal for watching videos and playing games. It also has an excellent camera.

[0200] Reasons for choosing the Google Pixel 6: The Google Pixel 6 receives the latest Android updates early and has smooth integration with Google services. Its competitive price makes it a great value for money.

[0201] Software used and data processing

[0202] The server handles the main data processing and runs generative AI models, particularly those using OpenAI GPT-3. The user device is used to input data and display the generated reasons and counterarguments. Data processing and calculations are performed by scripts (e.g., Python scripts) running on the server.

[0203] Users can understand the advantages and disadvantages of each product option based on specific supporting and counterargumentative reasons, and make the best choice. This system makes users' decision-making quick and effective.

[0204] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0205] Step 1:

[0206] The user inputs product options. The user device receives as input the multiple product options the user wants to compare. This input includes specific product names such as "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6." The server begins processing based on this input.

[0207] Step 2:

[0208] The server presents the options to the user. The server generates a list of products received from the user and sends it to the user's terminal. This allows the user to check the options and obtain information about each option.

[0209] Step 3:

[0210] Prepare the generative AI agents. The server configures a generative AI agent for each product option. Each generative AI agent is configured to utilize a generative AI model (e.g., OpenAI GPT-3) to support a specific product.

[0211] Step 4:

[0212] Generate reasons for support. The server sends each generation AI agent an instruction to generate reasons for support for a specified product. For example, a prompt sentence such as "I want to choose the best smartphone. The options are 'iPhone 13', 'Samsung Galaxy S21', and 'Google Pixel 6'. Please tell me the advantages of each." is input into the generation AI model, which then outputs specific reasons for support. This output is text information about the advantages of each product.

[0213] Step 5:

[0214] The reasons for support are presented to the user. The server sends the generated text of the reasons for support to the user's terminal. The user's terminal displays this, allowing the user to view the reasons for support for each product. Based on this, the user can consider which option is best.

[0215] Step 6:

[0216] Generate counterarguments. The server sends each generation AI agent an instruction to generate counterarguments about other options. For example, the generation AI model receives a prompt such as "What are the disadvantages of the iPhone 13?" and generates a counterargument. This output is text information about the shortcomings and problems of other products.

[0217] Step 7:

[0218] The rebuttals are presented to the user. The server sends the generated rebuttal text to the user's terminal. The user's terminal displays it, allowing the user to view the rebuttal information for each product. Based on this, the user can make the optimal selection, taking into account the drawbacks of each product.

[0219] Step 8:

[0220] The user decides on an option. Based on the presented reasons for and counterarguments, the user selects the most suitable product. Through this process, the user can comprehensively assess the advantages and disadvantages of each product and select the most suitable option.

[0221] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0222] The following describes a specific embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generation AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[0223] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, a means for presenting the generated supporting reasons and counterarguments to the user, and an emotion engine that recognizes the user's emotions and adjusts the information accordingly.

[0224] System Operation

[0225] 1. Setting options

[0226] The server receives multiple options from the user's device. These options are set in list format and are provided in a variety of forms depending on individual usage scenarios, such as selecting the wording for a campaign banner or choosing a Mother's Day gift.

[0227] 2. Initial setup of the generated AI agent

[0228] The server prepares generative AI agents according to the number of options received, each designed to support a specific option using a specified generative AI model.

[0229] 3. Generating reasons for support

[0230] For each option, the server sends a command to the generating AI agent to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of that option and sends it to the server.

[0231] 4. Emotional Engine Adjustment

[0232] Before presenting the generated supporting and counterargumentative arguments, the server uses an emotion engine to analyze the user's emotional state. The emotion engine collects real-time emotional data from the user and adjusts the output of each agent based on this data. For example, if the user is feeling stressed, the agent will emphasize more reassuring information.

[0233] 5. Presentation of reasons for support

[0234] The server presents the reasons for supporting each agent, adjusted by the emotion engine, to the user's terminal, where the user can view the reasons for supporting each agent through the terminal.

[0235] 6. Generating and Presenting Counterarguments

[0236] Furthermore, the server commands the AI ​​agent to create counterarguments against other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also adjusted by the emotion engine and presented to the user.

[0237] Specific examples

[0238] Example of using the emotion engine: Selecting campaign banner text

[0239] The server sets the following options:

[0240] Option A: "Flash Sale - 50% OFF!"

[0241] Option B: "Limited Time Offer - Buy One, Get One Free"

[0242] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0243] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0244] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0245] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0246] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0247] The generated reasons for support are adjusted by the emotion engine based on the user's emotional state before being presented to the user. For example, if the user shows signs of impatience, Agent A's emphasis on "urgency" is adjusted, and other benefits that provide a sense of security are added.

[0248] Through these steps, users will have more balanced information and be able to make optimal decisions based on their emotional state.

[0249] The processing flow will be explained below.

[0250] Step 1:

[0251] The user inputs options using the terminal. For example, when selecting the banner wording for a campaign, the user inputs options such as "Flash Sale - 50% OFF," "Limited Time Offer - Buy One, Get One Free," and "Exclusive Deal - Free Shipping on Orders Over $50."

[0252] Step 2:

[0253] The server keeps a list of the choices received from the user, so that a generative AI agent can be applied to each choice in the subsequent process.

[0254] Step 3:

[0255] The server prepares generative AI agents according to the number of options. Each agent uses a specified generative AI model (e.g., GPT-3.5-turbo) and configures it to support a specific option.

[0256] Step 4:

[0257] The server sends prompts to each AI agent to generate reasons for each option. The prompts include questions such as "Why is this option better?". Each agent generates text based on the prompts.

[0258] Step 5:

[0259] The server collects and stores the generated reasons for support in order to organize the text output by each agent and use it in the next step.

[0260] Step 6:

[0261] The server invokes an emotion engine to analyze the user's emotional state, determining the user's current emotion based on, for example, facial expression recognition, voice tone analysis, and the content of the text input.

[0262] Step 7:

[0263] Based on the emotional state analyzed by the emotion engine, the server adjusts the generated support reasons. For example, if the user is feeling stressed, the server adds expressions that alleviate the stress, providing a sense of relief.

[0264] Step 8:

[0265] The server sends the support reasons adjusted by the emotion engine to the user's terminal and displays them. The user can view the support reasons for each agent through the terminal.

[0266] Step 9:

[0267] The server again sends commands to the generating AI agents to generate counterarguments against the other options. Each agent generates a counterargument by setting prompts to point out the shortcomings and problems of the other options.

[0268] Step 10:

[0269] The server collects and stores the generated counterarguments. These counterarguments are also analyzed by the emotion engine and adjusted to fit the user's emotional state.

[0270] Step 11:

[0271] The server sends the counterarguments adjusted by the emotion engine to the user's device and displays them. The user can view the counterarguments of each agent through the device.

[0272] Step 12:

[0273] The user compares the reasons for and counterarguments of each agent displayed on the terminal and decides on the option that they feel is most appropriate.

[0274] The above is the specific flow of operation of the system according to the present invention.

[0275] Example 2

[0276] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0277] Conventional decision support systems simply present options to users, and it is difficult to explain why one option is superior or to provide counterarguments to other options. Furthermore, because they provide information without taking into account the user's emotional state, they are unable to provide appropriate support when the user is feeling stressed or impatient. As a result, there is the issue of inadequate support for user decision-making.

[0278] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for presenting options to the user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments against other options, a means for presenting the generated counterarguments to the user, and an emotion engine that analyzes the user's emotional state and adjusts the reasons for support and counterarguments. This makes it possible to provide the user with the optimal option together with information based on the analysis of the emotional state.

[0279] "Means for presenting options to the user" means the technical elements that display and provide options in a list or other format so that the user can select from multiple options.

[0280] A "generative AI agent" is a software agent designed to generate reasons and counterarguments for a given option using a specific generative AI model.

[0281] The "means for generating supporting reasons" is a function that allows the generating AI agent to generate text that explains the benefits and advantages of an option using a prompt sentence.

[0282] The "means for presenting the generated reasons for supporting each option to the user" refers to a technical element for displaying the generated reasons for supporting on the user's terminal so that the user can view them.

[0283] "Means for generating counterarguments to other options" is a feature that allows the generative AI agent to generate text that points out the counterarguments or flaws of a particular option.

[0284] The "means for presenting the generated rebuttal to the user" refers to the technical elements for displaying the generated rebuttal on the user's terminal so that the user can view it.

[0285] The "emotion engine" is a software component that collects and analyzes real-time user emotion data and adjusts the output of the generative AI agent based on the results.

[0286] The following describes an embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generative AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[0287] The system includes the following main components:

[0288] 1. A means of presenting options to the user

[0289] 2. Generative AI agent supporting each option

[0290] 3. A method for presenting the generated support reasons to the user

[0291] 4. A means of generating counterarguments to alternatives

[0292] 5. A means for presenting generated rebuttals to the user

[0293] 6. Emotion engine that analyzes the user's emotional state and adjusts information accordingly

[0294] System configuration

[0295] Presenting options

[0296] The server receives multiple options from the user's device and sets these options in a list format. The options are provided in a format that corresponds to a specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0297] Initial settings for generated AI agents

[0298] The server prepares generative AI agents according to the number of options received, with each agent designed to support a specific option using a generative AI model such as GPT-3 or ChatGPT.

[0299] Generating reasons for and counterarguments

[0300] Each agent uses a specified generative AI model to generate reasons for each option. The prompt is in the form of a question such as "Why is this option better?", for example, "Please explain why 'Flash Sale - 50% OFF!' is better."

[0301] Emotional engine regulation

[0302] The server analyzes the user's emotional state using an emotion engine before presenting the generated supporting and counterargumentative reasons. The emotion engine collects the user's emotional data in real time and adjusts the output of each agent based on this data, for example, by emphasizing reassuring information if the user is feeling stressed.

[0303] Presenting reasons for support and counterarguments

[0304] The server then presents the adjusted reasons for and counterarguments to the user's terminal. The user can then view the information provided by each agent through their terminal and use it as a reference for making the best choice.

[0305] Specific examples

[0306] Choosing campaign banner text using an emotion engine

[0307] As a concrete example, consider a scenario where you are selecting the banner text for a campaign. The server sets the following options:

[0308] Option A: "Flash Sale - 50% OFF!"

[0309] Option B: "Limited Time Offer - Buy One, Get One Free"

[0310] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0311] The server initializes a generating AI agent that supports each option. The agent generates reasons for supporting each option. An example prompt is:

[0312] To Agent A, "Explain why 'Flash Sale - 50% OFF!' is a great offer."

[0313] To Agent B, "Explain why 'Limited Time Offer - Buy One, Get One Free' is a great option."

[0314] To Agent C, "Please explain why 'Exclusive Deal - Free Shipping on Orders Over $50' is a great offer."

[0315] Each generative AI agent generates a reason for support, and the emotion engine adjusts the output based on the user's emotional state. The server then presents the adjusted information to the user's device, allowing the user to choose the optimal option.

[0316] In this way, users can make better decisions based on balanced information that takes into account their emotional state.

[0317] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0318] Step 1: Receive your choices

[0319] The server receives multiple options from the user via the terminal.

[0320] Specifically, the user inputs a list of options into the device, for example, the following campaign banner text:

[0321] "Flash Sale - 50% OFF!"

[0322] "Limited Time Offer - Buy One, Get One Free"

[0323] "Exclusive Deal - Free Shipping on Orders Over $50"

[0324] Input: A list of choices the user has entered into the device

[0325] Output: List of options received by the server

[0326] Step 2: Initializing the generated AI agent

[0327] The server prepares generative AI agents according to the number of options received, assigning each agent to a different option and configuring them using a generative AI model (e.g., GPT-3 or ChatGPT).

[0328] Specifically, the server generates three generation AI agents and assigns them to options A, B, and C, respectively.

[0329] Input: list of options

[0330] Output: A set of generated AI agents with initial settings

[0331] Step 3: Generate supporting reasons

[0332] The server issues a command to each generating AI agent to generate supporting reasons, using a prompt phrase to ask "Why is this choice better?"

[0333] Specifically, for example, Agent A is prompted with "Please explain why 'Flash Sale - 50% OFF!' is a good product." The generating AI agent generates supporting reasons based on this prompt and sends them to the server.

[0334] Input: prompt, initialised generated AI agents

[0335] Output: Text data of reasons for supporting each option

[0336] Step 4: Emotional Engine Adjustment

[0337] The server analyzes the user's emotional state using an emotion engine before presenting the generated support reasons and counterarguments. The emotion engine collects the user's emotional data in real time and adjusts the support reasons and counterarguments.

[0338] Specifically, the device uses a camera and microphone to analyze the user's facial expressions and voice, and sends the emotional data to the server. The server then uses this data to adjust the output of the generated AI agent. For example, if the user is feeling stressed, it adds information that emphasizes a sense of security to the output.

[0339] Input: Text data of generated support reasons, user emotion data

[0340] Output: Text data of adjusted support and counterarguments

[0341] Step 5: Present your reasons for support

[0342] The server presents the adjusted reasons for support to the user's terminal, and the user can view the reasons for support provided by each agent through the terminal.

[0343] Specifically, the server sends the adjusted reasons for support to the terminal, and the terminal displays them on the screen, for example, displaying the benefits of "Flash Sale - 50% OFF!", such as the immediate customer attraction effect.

[0344] Input: Text data of adjusted reasons for support

[0345] Output: The reason for support displayed on the user's terminal

[0346] Step 6: Generate and present a counterargument

[0347] The server commands the generator AI agent to create counterarguments against the other options, which point out the shortcomings and problems of the other options.

[0348] Specifically, the server generates a counterargument for Agent A explaining why 'Limited Time Offer - Buy One, Get One Free' is inferior. This information is also adjusted by the emotion engine and then presented to the user.

[0349] Input: Rebuttal prompt, emotion data

[0350] Output: Text data of the adjusted rebuttal, and the rebuttal displayed on the user's device

[0351] This system allows users to make better decisions by receiving information that corresponds to their emotional state.

[0352] (Application example 2)

[0353] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0354] Conventional decision support systems do not take into account the user's emotional state when selecting the optimal option from multiple options, resulting in insufficient support for the user. Furthermore, the generated reasons and counterarguments are not adjusted to reflect the user's emotions, making it difficult for the user to make a decision with confidence. To solve these problems, a system that provides information based on the user's emotional state and supports more appropriate decision-making is needed.

[0355] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting options to the user, a generating AI agent that supports each option and the generating AI agent generates reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments against other options, means for presenting the generated counterarguments to the user, and means including an emotion engine that recognizes the user's emotional state and adjusts information. This makes it possible to provide information according to the user's emotional state, allowing the user to make the optimal choice with greater confidence.

[0356] A "means for presenting options to a user" is a system or method that clearly displays and presents to a user multiple options that the user is considering.

[0357] A "generative AI agent" is an entity or software that uses artificial intelligence techniques to generate reasons in support of a particular choice.

[0358] A "means for generating reasons for support" is a system or method that uses a generative AI agent to automatically generate reasons for support in order to present the advantages and merits of options to a user.

[0359] "Means for presenting the generated reasons for supporting each option to the user" refers to a system or method that displays and presents the reasons for supporting each option generated by the generating AI agent in an easy-to-understand manner to the user.

[0360] A "means for generating arguments against alternatives" is a system or method for generating arguments that point out the shortcomings or problems of alternatives in order to support a particular alternative.

[0361] "Means for presenting generated counterarguments to the user" refers to a system or method for displaying and presenting the counterarguments generated by the generating AI agent in an easy-to-understand manner to the user.

[0362] An "emotion engine" is software or a system for recognizing a user's emotional state in real time and adjusting information based on this data.

[0363] "User's emotional state" refers to the user's current mental and emotional state, including, for example, feelings such as stress, joy, relief, etc.

[0364] This invention is an interactive system that supports decision-making by providing reasons for and counterarguments to options while taking into account the user's emotional state. The system consists of a user terminal and a server that includes an emotion engine and a generative AI agent.

[0365] First, a user inputs multiple options using a terminal. For example, imagine a situation where a user must choose from multiple products on an online shopping website. These options are sent to the server, and the system prepares a generative AI agent that supports each option. The generative AI agent uses a generative AI model to generate reasons for supporting each option.

[0366] The server uses an emotion engine to generate support reasons before presenting them to the user's device. The emotion engine collects real-time emotional data from the user and adjusts the generated support reasons based on this data. For example, if the user is feeling stressed, it will emphasize reassuring information in the support reasons. Counterarguments against other options are also generated by the generative AI agent, adjusted by the emotion engine, and presented to the user.

[0367] As a concrete example, consider a situation where a user has to choose between the following options:

[0368] Option A: Premium earphones that offer high-quality sound

[0369] Option B: The best value wireless earphones

[0370] Option C: Waterproof sports earphones

[0371] In this case, an example prompt would be:

[0372] "Help the user choose from the following options:

[0373] Product A: High-quality earphones that provide high-quality sound

[0374] Product B: The best value wireless earphones

[0375] Product C: Highly waterproof sports earphones

[0376] Tell users which option they should choose, why that option is better, and why based on their emotional state.”

[0377] The generated reasons and counterarguments are then adjusted by the emotion engine and optimized to provide the user with a sense of security and satisfaction, allowing the user to receive information tailored to their emotional state and make better decisions.

[0378] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0379] Step 1:

[0380] The server receives multiple options from the user's device. In this step, the user inputs their options via their device, which are then sent to the server in list form. For example, suppose the user submits the following options: "High-end earphones that provide high-quality sound," "Wireless earphones with the best value for money," and "Waterproof sports earphones." The input option list arrives at the server and is saved in its original format.

[0381] Step 2:

[0382] The server prepares generative AI agents according to the number of options received. Each agent generates reasons for supporting a particular option. In this step, the server invokes the generative AI model and configures an agent for each option. For example, Agent A is configured to support "high-quality earphones that provide high-quality sound," and Agent B is configured to support "wireless earphones with the best cost performance."

[0383] Step 3:

[0384] The server sends a command to the generative AI agent to generate reasons for each option, including a prompt such as, "Why is this option superior?" The prompt is input to the generative AI model, which outputs reasons for support. For example, the prompt for Agent A might be, "Why are high-end earphones that provide high-quality sound superior?", and the output would be a reason such as, "The sound quality is very clear and provides a superior hearing experience compared to other products."

[0385] Step 4:

[0386] The server passes the generated support reasons to the emotion engine, which adjusts them based on the user's emotional state. In this step, the emotion engine analyzes the user's emotional data in real time and adjusts the support reasons based on that data. For example, if the user is feeling stressed, the emotion engine adjusts the support reasons to emphasize a sense of relief.

[0387] Step 5:

[0388] The server then presents the support reasons for each agent, adjusted by the emotion engine, to the user's device. In this step, the adjusted support reasons are sent to the device and displayed to the user. For example, the support reason for "luxury earphones that provide high-quality sound" is presented as "The sound quality is very clear and provides a superior hearing experience compared to other products. Don't worry, we guarantee that it is the best choice."

[0389] Step 6:

[0390] The server generates counterarguments to the other options, which are similarly adjusted by the emotion engine and then presented to the user. In this step, the generation AI agent generates a counterargument, with a prompt that includes, "Why are the other options inferior?" For example, a counterargument from Agent A might be, "The best value-for-money earphones are inferior to high-end earphones in terms of sound quality." The counterargument, adjusted by the emotion engine, is then presented to the user.

[0391] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0392] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0393] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0394] [Second embodiment]

[0395] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0396] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0397] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0398] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0399] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0400] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0401] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0402] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0403] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0404] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0405] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0406] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0407] The following describes a specific embodiment of the present invention. The present invention is a system for supporting user decision-making, and in particular, provides a method for supporting a user who is struggling between multiple options by having a generation AI agent that supports each option exchange opinions to support the user's decision-making.

[0408] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, and a means for presenting the generated reasons for supporting and counterarguments to the user.

[0409] System Operation

[0410] 1. Setting options

[0411] The server receives as input the multiple options the user is considering. These options are set in list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0412] 2. Initial setup of the generated AI agent

[0413] The server prepares a generative AI agent for each option. The generative AI agent is designed to support each option and generates text using a generative AI model.

[0414] 3. Generating reasons for support

[0415] For each option, the server sends a command to the generating AI agent to generate reasons for each option. Each agent generates text explaining the merits and validity of each option and sends it to the server.

[0416] 4. Presentation of reasons for support

[0417] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0418] 5. Generating and Presenting Counterarguments

[0419] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also presented to the user.

[0420] Specific examples

[0421] Campaign banner wording selection

[0422] The server sets the following options:

[0423] Option A: "Flash Sale - 50% OFF!"

[0424] Option B: "Limited Time Offer - Buy One, Get One Free"

[0425] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0426] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0427] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0428] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0429] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0430] The server presents these reasons to the user's device, and the user compares and considers each reason. Furthermore, counterarguments to other options are also generated and presented to the user. This allows the user to deeply understand the advantages and disadvantages of each option and make a final decision.

[0431] The present invention provides users with comprehensive support for selecting the most appropriate option from among multiple options, thereby aiming to improve the accuracy and satisfaction of decision-making.

[0432] The processing flow will be explained below.

[0433] Step 1:

[0434] The server receives multiple options from the user's terminal, which are presented in the form of a list based on a specific theme, such as selecting a campaign banner or choosing a specific product.

[0435] Step 2:

[0436] The server prepares generative AI agents according to the number of options received, each configured to support a particular option using a specified generative AI model.

[0437] Step 3:

[0438] The server sends a prompt to each agent, instructing them to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of each option.

[0439] Step 4:

[0440] The server aggregates the generated support reasons and sends them to the user's terminal, where the user can view the support reasons presented by each agent.

[0441] Step 5:

[0442] The server generates counterarguments to other options as needed, sending prompts to each agent to criticize or point out flaws in the other options, and each agent generates a counterargument.

[0443] Step 6:

[0444] The server collects the generated counterarguments and sends them to the user's terminal, where the user can view the counterarguments for each option.

[0445] Step 7:

[0446] The user compares the arguments for and against each agent presented on the device, allowing them to gain a balanced perspective on multiple options.

[0447] Step 8:

[0448] The user can decide the most appropriate option based on the information presented and provide feedback of that decision to the server.

[0449] Example 1

[0450] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0451] Conventional decision support systems often lack the information necessary to make an appropriate decision between multiple options. Furthermore, there are limited means to provide users with sufficient information to properly compare the supporting and counterargumentative arguments for each option and make the optimal choice. This can lead to problems such as users being confused and reducing the accuracy and satisfaction of their decision-making.

[0452] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0453] In this invention, the server includes means for presenting options to a user, a generation AI agent supporting each option, means for the generation AI agent to generate reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments for other options, means for presenting the generated counterarguments to the user, and means for generating reasons for supporting each option based on a prompt sentence using a generative AI model. This allows the user to easily compare the reasons for supporting and counterarguments for each option, and provides sufficient information for making an optimal decision.

[0454] A "means for presenting options to a user" is a system element that provides multiple options to a user in visual or text format, allowing the user to compare and consider the options.

[0455] A "generative AI agent" is an artificial intelligence program or algorithm that generates reasons and counterarguments in support of each option.

[0456] "Means for generating supporting reasons" is a function that allows the generative AI agent to use the generative AI model to generate reasons and advantages in favor of a given option in text format.

[0457] The "means for presenting the generated reasons for supporting each option to the user" is a system element that visualizes and displays to the user the reasons for supporting each option generated by the generating AI agent.

[0458] "Means for generating counterarguments to alternative options" refers to the ability of a generative AI agent to use a generative AI model to generate, in text form, reasons for opposing or shortcomings of alternative options.

[0459] The "means for presenting the generated counterargument to the user" is a system element that visualizes and displays the counterargument generated by the generating AI agent to the user.

[0460] A "generative AI model" is an artificial intelligence algorithm or program that automatically generates text, specifically a model trained for natural language processing.

[0461] A "prompt sentence" is an input sentence that instructs a generative AI model to generate a specific text.

[0462] This invention is a system that supports user decision-making, and provides a method for users who are struggling to decide between multiple options by having a generating AI agent that supports each option exchange opinions to support the user's decision-making. This system has the following specific configuration and functions.

[0463] System Overview

[0464] The system primarily includes the following hardware and software components:

[0465] Server: Handles data processing and manages generated AI agents.

[0466] User terminal: A device through which a user can input their choices and view the generated supporting and counterargumentative reasons.

[0467] Generative AI models: AI models for natural language processing and text generation (e.g., GPT-4).

[0468] Specific operation of the system

[0469] 1. Enter your choices

[0470] The server receives multiple options from the user as input. These options are set in a list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0471] 2. Initial setup of the generated AI agent

[0472] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option and generates text using a generative AI model (e.g., GPT-4). The prompt text is also set at this stage.

[0473] 3. Generating reasons for support

[0474] For each option, the server sends a prompt to the generating AI agent, which generates a reason for each option and sends the generated text to the server.

[0475] 4. Presentation of reasons for support

[0476] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0477] 5. Generating and Presenting Counterarguments

[0478] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option look more favorable. The generated counterarguments are also presented to the user.

[0479] Specific examples

[0480] Scenario for selecting campaign banner wording

[0481] 1. Setting options

[0482] The server sets the following options:

[0483] Option A: "Flash Sale - 50% OFF!"

[0484] Option B: "Limited Time Offer - Buy One, Get One Free"

[0485] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0486] 2. Initial setup of the generated AI agent

[0487] The server prepares a generating AI agent to support each option, with each prompt set as follows:

[0488] "Generate a 3-5 sentence reasoning in support of the following option: 'Flash Sale - 50% OFF!'"

[0489] "Generate 3-5 sentences supporting the following option: 'Limited Time Offer - Buy One, Get One Free'"

[0490] "Generate 3-5 sentences supporting the following option: 'Exclusive Deal - Free Shipping on Orders Over $50'"

[0491] 3. Generating reasons for support

[0492] The generating AI agent uses the prompt sentence to generate reasons for support such as:

[0493] Agent A: "Flash Sale - 50% OFF!" will motivate customers to buy and contribute to immediate sales.

[0494] Agent B: "Limited Time Offer - Buy One, Get One Free" increases sales and smooths inventory flow.

[0495] Agent C: "Exclusive Deal - Free Shipping on Orders Over $50" encourages customers to buy and reduces shipping costs, increasing their motivation to buy.

[0496] 4. Presentation of reasons for support

[0497] The server transmits these reasons for support to the user's terminal, and the user compares and considers each reason for support on the terminal.

[0498] 5. Generating and Presenting Counterarguments

[0499] The server also generates a rebuttal as follows:

[0500] Agent A argues against the "Limited Time Offer - Buy One, Get One Free" by pointing out that it would make inventory management difficult.

[0501] Agent B argues that the "Exclusive Deal - Free Shipping on Orders Over $50" offer is not as impressive a discount.

[0502] This allows users to deeply understand the advantages and disadvantages of each option and make optimal decisions. This system aims to improve the accuracy and satisfaction of users' decision-making.

[0503] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0504] Step 1: User inputs choices

[0505] The server provides an interface for the user to input multiple options via the terminal. The options to be input may be, for example, campaign banner text or product features, and once the user has completed the input, the server receives it. The received data is structured and stored in a database. The input data is often in the form of a list or JSON.

[0506] Specific behavior:

[0507] The user enters options such as "Flash Sale - 50% OFF!" or "Limited Time Offer - Buy One, Get One Free" into the terminal, and the server receives it and stores it in the database.

[0508] Step 2: Initializing the generated AI agent

[0509] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option, and the server sets a prompt sentence that is adapted to it. Specifically, it sets it up to generate text using a generative AI model (e.g., GPT-4).

[0510] Input and Output:

[0511] The server takes the choice data as input and generates the initial settings and prompt sentences for the generated AI agent based on it. The output is the generated AI agent with the initial settings completed.

[0512] Specific behavior:

[0513] For the option "Flash Sale - 50% OFF!", the server sets the prompt text "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'" to the generating AI agent.

[0514] Step 3: Generate supporting reasons

[0515] The server commands the generative AI agent to generate supporting reasons for each option. The generative AI model generates text explaining the merits and validity of each option based on the specified prompt. The generated supporting reasons are sent to the server.

[0516] Input and Output:

[0517] The input is the prompt sentence and option data set in Step 2. This is processed by the generative AI model, and the output is a text of the reasons for support.

[0518] Specific behavior:

[0519] In response to the prompt, "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'", the AI ​​model generates text such as "'Flash Sale - 50% OFF!' will increase customer purchasing intent and contribute to immediate sales growth."

[0520] Step 4: Present your reasons for support

[0521] The server sends the generated reasons for support to the user's device, where these reasons are visually displayed, allowing the user to compare and consider the reasons for support for each option.

[0522] Input and Output:

[0523] The input is the text of the support reasons generated by the generative AI model, and the output is the support reasons displayed on the user's device.

[0524] Specific behavior:

[0525] The server transmits the reason for support, such as "'Flash Sale - 50% OFF!' will increase customers' desire to purchase and contribute to an immediate increase in sales," to the user's terminal, which then displays the reason.

[0526] Step 5: Generate and present a counterargument

[0527] The server commands the generative AI agent to generate a counterargument against the other options. This counterargument is generated by the generative AI model and is a text that points out the shortcomings and problems of the other options. The generated counterargument is also sent to the user's device.

[0528] Input and Output:

[0529] The input is a set of alternatives and a corresponding prompt, which is processed by a generative AI model, and the output is a counterargument text.

[0530] Specific behavior:

[0531] The server inputs a prompt such as "Generate a three-sentence counterargument to the following option, 'Limited Time Offer - Buy One, Get One Free'" into the generative AI model, and the generated text, such as "Inventory management will become more difficult" or "Profit margins may decline," is sent to the user's device, where it is displayed.

[0532] Through these steps, users can compare the reasons for and counterarguments of each option and make the best decision.

[0533] (Application example 1)

[0534] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0535] Currently, when users select the optimal product from multiple product options, it is difficult for them to objectively evaluate the advantages and disadvantages of each product. In particular, e-commerce platforms are overwhelmed with a wide variety of product information, making it difficult for users to properly compare and consider this information. Furthermore, the lack of a system that effectively supports the user selection process leads to problems such as incorrect selection and time-consuming selection.

[0536] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0537] In this invention, the server includes a means for presenting options to a user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments for other options, a means for presenting the generated counterarguments to the user, and a means for generating reasons for supporting and counterarguments for different products and displaying them to the user in the product selection process, thereby enabling the user to understand the advantages and disadvantages of each product option and select the optimal option quickly and efficiently.

[0538] "Choice" refers to each item or option that a user considers to select from multiple choices.

[0539] "User" refers to an individual or corporation that makes decisions using this system.

[0540] "Means" refers to the methods or processes used to achieve a particular goal.

[0541] A "generative AI agent" is a program that uses a generative AI model to support specific options and has the ability to generate text about the advantages and disadvantages of each option.

[0542] "Generated reasons for support" refers to text generated by the generating AI agent explaining the benefits or validity of a particular option.

[0543] "Rebuttal" refers to text generated to point out the flaws or problems of an alternative.

[0544] The "product selection process" refers to a series of actions or steps a user takes to select the optimal product from multiple product options.

[0545] "Display means" refers to a method or device that allows a user to visually view information generated by the system.

[0546] This invention provides a system that helps users select the most suitable product from multiple product options. The system's main hardware configuration is a server and a user terminal. The server uses a generation AI agent to generate reasons for and counterarguments for each option and presents them to the user terminal.

[0547] System Operation

[0548] 1. Setting options

[0549] The user device receives as input multiple product options that the user wants to compare, such as product models like "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6."

[0550] 2. Initial setup of the generated AI agent

[0551] The server prepares a generative AI agent for each product option, each of which uses a specific generative AI model.

[0552] 3. Generating reasons for support

[0553] The server sends commands to each generative AI agent to generate reasons in favor of each option. For example, the generative AI model might generate reasons that the iPhone 13 has the latest processor and offers better performance to users.

[0554] 4. Presentation of reasons for support

[0555] The server transmits the generated reasons for support to the user terminal for the user to view, allowing the user to compare the merits of each product option.

[0556] 5. Generating and Presenting Counterarguments

[0557] The server instructs each generative AI agent to generate a counterargument to the other options. For example, the generative AI model generates a counterargument pointing out that a disadvantage of the Samsung Galaxy S21 is its short battery life.

[0558] These counterarguments are also sent to the user's terminal, allowing the user to weigh the drawbacks of each option.

[0559] Specific usage

[0560] For example, if a user wants to use a shopping site to choose the best smartphone, they might enter the following prompt:

[0561] I want to choose the best smartphone.

[0562] My options are the iPhone 13, the Samsung Galaxy S21, and the Google Pixel 6. What are the advantages of each?

[0563] In response, the generating AI agent generates the following reasons for support:

[0564] Reasons for choosing the iPhone 13: The iPhone 13 is equipped with the latest chipset, offering effective battery management and excellent performance, and is highly compatible with other devices thanks to the Apple ecosystem.

[0565] Reasons for choosing the Samsung Galaxy S21: The Samsung Galaxy S21 has a high-resolution display that is ideal for watching videos and playing games. It also has an excellent camera.

[0566] Reasons for choosing the Google Pixel 6: The Google Pixel 6 receives the latest Android updates early and has smooth integration with Google services. Its competitive price makes it a great value for money.

[0567] Software used and data processing

[0568] The server handles the main data processing and runs generative AI models, particularly those using OpenAI GPT-3. The user device is used to input data and display the generated reasons and counterarguments. Data processing and calculations are performed by scripts (e.g., Python scripts) running on the server.

[0569] Users can understand the advantages and disadvantages of each product option based on specific supporting and counterargumentative reasons, and make the best choice. This system makes users' decision-making quick and effective.

[0570] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0571] Step 1:

[0572] The user inputs product options. The user device receives as input the multiple product options the user wants to compare. This input includes specific product names such as "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6." The server begins processing based on this input.

[0573] Step 2:

[0574] The server presents the options to the user. The server generates a list of products received from the user and sends it to the user's terminal. This allows the user to check the options and obtain information about each option.

[0575] Step 3:

[0576] Prepare the generative AI agents. The server configures a generative AI agent for each product option. Each generative AI agent is configured to utilize a generative AI model (e.g., OpenAI GPT-3) to support a specific product.

[0577] Step 4:

[0578] Generate reasons for support. The server sends each generation AI agent an instruction to generate reasons for support for a specified product. For example, a prompt sentence such as "I want to choose the best smartphone. The options are 'iPhone 13', 'Samsung Galaxy S21', and 'Google Pixel 6'. Please tell me the advantages of each." is input into the generation AI model, which then outputs specific reasons for support. This output is text information about the advantages of each product.

[0579] Step 5:

[0580] The reasons for support are presented to the user. The server sends the generated text of the reasons for support to the user's terminal. The user's terminal displays this, allowing the user to view the reasons for support for each product. Based on this, the user can consider which option is best.

[0581] Step 6:

[0582] Generate counterarguments. The server sends each generation AI agent an instruction to generate counterarguments about other options. For example, the generation AI model receives a prompt such as "What are the disadvantages of the iPhone 13?" and generates a counterargument. This output is text information about the shortcomings and problems of other products.

[0583] Step 7:

[0584] The rebuttals are presented to the user. The server sends the generated rebuttal text to the user's terminal. The user's terminal displays it, allowing the user to view the rebuttal information for each product. Based on this, the user can make the optimal selection, taking into account the drawbacks of each product.

[0585] Step 8:

[0586] The user decides on an option. Based on the presented reasons for and counterarguments, the user selects the most suitable product. Through this process, the user can comprehensively assess the advantages and disadvantages of each product and select the most suitable option.

[0587] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0588] The following describes a specific embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generation AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[0589] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, a means for presenting the generated supporting reasons and counterarguments to the user, and an emotion engine that recognizes the user's emotions and adjusts the information accordingly.

[0590] System Operation

[0591] 1. Setting options

[0592] The server receives multiple options from the user's device. These options are set in list format and are provided in a variety of forms depending on individual usage scenarios, such as selecting the wording for a campaign banner or choosing a Mother's Day gift.

[0593] 2. Initial setup of the generated AI agent

[0594] The server prepares generative AI agents according to the number of options received, each designed to support a specific option using a specified generative AI model.

[0595] 3. Generating reasons for support

[0596] For each option, the server sends a command to the generating AI agent to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of that option and sends it to the server.

[0597] 4. Emotional Engine Adjustment

[0598] Before presenting the generated supporting and counterargumentative arguments, the server uses an emotion engine to analyze the user's emotional state. The emotion engine collects real-time emotional data from the user and adjusts the output of each agent based on this data. For example, if the user is feeling stressed, the agent will emphasize more reassuring information.

[0599] 5. Presentation of reasons for support

[0600] The server presents the reasons for supporting each agent, adjusted by the emotion engine, to the user's terminal, where the user can view the reasons for supporting each agent through the terminal.

[0601] 6. Generating and Presenting Counterarguments

[0602] Furthermore, the server commands the AI ​​agent to create counterarguments against other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also adjusted by the emotion engine and presented to the user.

[0603] Specific examples

[0604] Example of using the emotion engine: Selecting campaign banner text

[0605] The server sets the following options:

[0606] Option A: "Flash Sale - 50% OFF!"

[0607] Option B: "Limited Time Offer - Buy One, Get One Free"

[0608] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0609] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0610] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0611] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0612] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0613] The generated reasons for support are adjusted by the emotion engine based on the user's emotional state before being presented to the user. For example, if the user shows signs of impatience, Agent A's emphasis on "urgency" is adjusted, and other benefits that provide a sense of security are added.

[0614] Through these steps, users will have more balanced information and be able to make optimal decisions based on their emotional state.

[0615] The processing flow will be explained below.

[0616] Step 1:

[0617] The user inputs options using the terminal. For example, when selecting the banner wording for a campaign, the user inputs options such as "Flash Sale - 50% OFF," "Limited Time Offer - Buy One, Get One Free," and "Exclusive Deal - Free Shipping on Orders Over $50."

[0618] Step 2:

[0619] The server keeps a list of the choices received from the user, so that a generative AI agent can be applied to each choice in the subsequent process.

[0620] Step 3:

[0621] The server prepares generative AI agents according to the number of options. Each agent uses a specified generative AI model (e.g., GPT-3.5-turbo) and configures it to support a specific option.

[0622] Step 4:

[0623] The server sends prompts to each AI agent to generate reasons for each option. The prompts include questions such as "Why is this option better?". Each agent generates text based on the prompts.

[0624] Step 5:

[0625] The server collects and stores the generated reasons for support in order to organize the text output by each agent and use it in the next step.

[0626] Step 6:

[0627] The server invokes an emotion engine to analyze the user's emotional state, determining the user's current emotion based on, for example, facial expression recognition, voice tone analysis, and the content of the text input.

[0628] Step 7:

[0629] Based on the emotional state analyzed by the emotion engine, the server adjusts the generated support reasons. For example, if the user is feeling stressed, the server adds expressions that alleviate the stress, providing a sense of relief.

[0630] Step 8:

[0631] The server sends the support reasons adjusted by the emotion engine to the user's terminal and displays them. The user can view the support reasons for each agent through the terminal.

[0632] Step 9:

[0633] The server again sends commands to the generating AI agents to generate counterarguments against the other options. Each agent generates a counterargument by setting prompts to point out the shortcomings and problems of the other options.

[0634] Step 10:

[0635] The server collects and stores the generated counterarguments. These counterarguments are also analyzed by the emotion engine and adjusted to fit the user's emotional state.

[0636] Step 11:

[0637] The server sends the counterarguments adjusted by the emotion engine to the user's device and displays them. The user can view the counterarguments of each agent through the device.

[0638] Step 12:

[0639] The user compares the reasons for and counterarguments of each agent displayed on the terminal and decides on the option that they feel is most appropriate.

[0640] The above is the specific flow of operation of the system according to the present invention.

[0641] Example 2

[0642] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0643] Conventional decision support systems simply present options to users, and it is difficult to explain why one option is superior or to provide counterarguments to other options. Furthermore, because they provide information without taking into account the user's emotional state, they are unable to provide appropriate support when the user is feeling stressed or impatient. As a result, there is the issue of inadequate support for user decision-making.

[0644] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for presenting options to the user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments against other options, a means for presenting the generated counterarguments to the user, and an emotion engine that analyzes the user's emotional state and adjusts the reasons for support and counterarguments. This makes it possible to provide the user with the optimal option together with information based on the analysis of the emotional state.

[0645] "Means for presenting options to the user" means the technical elements that display and provide options in a list or other format so that the user can select from multiple options.

[0646] A "generative AI agent" is a software agent designed to generate reasons and counterarguments for a given option using a specific generative AI model.

[0647] The "means for generating supporting reasons" is a function that allows the generating AI agent to generate text that explains the benefits and advantages of an option using a prompt sentence.

[0648] The "means for presenting the generated reasons for supporting each option to the user" refers to a technical element for displaying the generated reasons for supporting on the user's terminal so that the user can view them.

[0649] "Means for generating counterarguments to other options" is a feature that allows the generative AI agent to generate text that points out the counterarguments or flaws of a particular option.

[0650] The "means for presenting the generated rebuttal to the user" refers to the technical elements for displaying the generated rebuttal on the user's terminal so that the user can view it.

[0651] The "emotion engine" is a software component that collects and analyzes real-time user emotion data and adjusts the output of the generative AI agent based on the results.

[0652] The following describes an embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generative AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[0653] The system includes the following main components:

[0654] 1. A means of presenting options to the user

[0655] 2. Generative AI agent supporting each option

[0656] 3. A method for presenting the generated support reasons to the user

[0657] 4. A means of generating counterarguments to alternatives

[0658] 5. A means for presenting generated rebuttals to the user

[0659] 6. Emotion engine that analyzes the user's emotional state and adjusts information accordingly

[0660] System configuration

[0661] Presenting options

[0662] The server receives multiple options from the user's device and sets these options in a list format. The options are provided in a format that corresponds to a specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0663] Initial settings for generated AI agents

[0664] The server prepares generative AI agents according to the number of options received, with each agent designed to support a specific option using a generative AI model such as GPT-3 or ChatGPT.

[0665] Generating reasons for and counterarguments

[0666] Each agent uses a specified generative AI model to generate reasons for each option. The prompt is in the form of a question such as "Why is this option better?", for example, "Please explain why 'Flash Sale - 50% OFF!' is better."

[0667] Emotional engine regulation

[0668] The server analyzes the user's emotional state using an emotion engine before presenting the generated supporting and counterargumentative reasons. The emotion engine collects the user's emotional data in real time and adjusts the output of each agent based on this data, for example, by emphasizing reassuring information if the user is feeling stressed.

[0669] Presenting reasons for support and counterarguments

[0670] The server then presents the adjusted reasons for and counterarguments to the user's terminal. The user can then view the information provided by each agent through their terminal and use it as a reference for making the best choice.

[0671] Specific examples

[0672] Choosing campaign banner text using an emotion engine

[0673] As a concrete example, consider a scenario where you are selecting the banner text for a campaign. The server sets the following options:

[0674] Option A: "Flash Sale - 50% OFF!"

[0675] Option B: "Limited Time Offer - Buy One, Get One Free"

[0676] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0677] The server initializes a generating AI agent that supports each option. The agent generates reasons for supporting each option. An example prompt is:

[0678] To Agent A, "Explain why 'Flash Sale - 50% OFF!' is a great offer."

[0679] To Agent B, "Explain why 'Limited Time Offer - Buy One, Get One Free' is a great option."

[0680] To Agent C, "Please explain why 'Exclusive Deal - Free Shipping on Orders Over $50' is a great offer."

[0681] Each generative AI agent generates a reason for support, and the emotion engine adjusts the output based on the user's emotional state. The server then presents the adjusted information to the user's device, allowing the user to choose the optimal option.

[0682] In this way, users can make better decisions based on balanced information that takes into account their emotional state.

[0683] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0684] Step 1: Receive your choices

[0685] The server receives multiple options from the user via the terminal.

[0686] Specifically, the user inputs a list of options into the device, for example, the following campaign banner text:

[0687] "Flash Sale - 50% OFF!"

[0688] "Limited Time Offer - Buy One, Get One Free"

[0689] "Exclusive Deal - Free Shipping on Orders Over $50"

[0690] Input: A list of choices the user has entered into the device

[0691] Output: List of options received by the server

[0692] Step 2: Initializing the generated AI agent

[0693] The server prepares generative AI agents according to the number of options received, assigning each agent to a different option and configuring them using a generative AI model (e.g., GPT-3 or ChatGPT).

[0694] Specifically, the server generates three generation AI agents and assigns them to options A, B, and C, respectively.

[0695] Input: list of options

[0696] Output: A set of generated AI agents with initial settings

[0697] Step 3: Generate supporting reasons

[0698] The server issues a command to each generating AI agent to generate supporting reasons, using a prompt phrase to ask "Why is this choice better?"

[0699] Specifically, for example, Agent A is prompted with "Please explain why 'Flash Sale - 50% OFF!' is a good product." The generating AI agent generates supporting reasons based on this prompt and sends them to the server.

[0700] Input: prompt, initialised generated AI agents

[0701] Output: Text data of reasons for supporting each option

[0702] Step 4: Emotional Engine Adjustment

[0703] The server analyzes the user's emotional state using an emotion engine before presenting the generated support reasons and counterarguments. The emotion engine collects the user's emotional data in real time and adjusts the support reasons and counterarguments.

[0704] Specifically, the device uses a camera and microphone to analyze the user's facial expressions and voice, and sends the emotional data to the server. The server then uses this data to adjust the output of the generated AI agent. For example, if the user is feeling stressed, it adds information that emphasizes a sense of security to the output.

[0705] Input: Text data of generated support reasons, user emotion data

[0706] Output: Text data of adjusted support and counterarguments

[0707] Step 5: Present your reasons for support

[0708] The server presents the adjusted reasons for support to the user's terminal, and the user can view the reasons for support provided by each agent through the terminal.

[0709] Specifically, the server sends the adjusted reasons for support to the terminal, and the terminal displays them on the screen, for example, displaying the benefits of "Flash Sale - 50% OFF!", such as the immediate customer attraction effect.

[0710] Input: Text data of adjusted reasons for support

[0711] Output: The reason for support displayed on the user's terminal

[0712] Step 6: Generate and present a counterargument

[0713] The server commands the generator AI agent to create counterarguments against the other options, which point out the shortcomings and problems of the other options.

[0714] Specifically, the server generates a counterargument for Agent A explaining why 'Limited Time Offer - Buy One, Get One Free' is inferior. This information is also adjusted by the emotion engine and then presented to the user.

[0715] Input: Rebuttal prompt, emotion data

[0716] Output: Text data of the adjusted rebuttal, and the rebuttal displayed on the user's device

[0717] This system allows users to make better decisions by receiving information that corresponds to their emotional state.

[0718] (Application example 2)

[0719] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0720] Conventional decision support systems do not take into account the user's emotional state when selecting the optimal option from multiple options, resulting in insufficient support for the user. Furthermore, the generated reasons and counterarguments are not adjusted to reflect the user's emotions, making it difficult for the user to make a decision with confidence. To solve these problems, a system that provides information based on the user's emotional state and supports more appropriate decision-making is needed.

[0721] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting options to the user, a generating AI agent that supports each option and the generating AI agent generates reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments against other options, means for presenting the generated counterarguments to the user, and means including an emotion engine that recognizes the user's emotional state and adjusts information. This makes it possible to provide information according to the user's emotional state, allowing the user to make the optimal choice with greater confidence.

[0722] A "means for presenting options to a user" is a system or method that clearly displays and presents to a user multiple options that the user is considering.

[0723] A "generative AI agent" is an entity or software that uses artificial intelligence techniques to generate reasons in support of a particular choice.

[0724] A "means for generating reasons for support" is a system or method that uses a generative AI agent to automatically generate reasons for support in order to present the advantages and merits of options to a user.

[0725] "Means for presenting the generated reasons for supporting each option to the user" refers to a system or method that displays and presents the reasons for supporting each option generated by the generating AI agent in an easy-to-understand manner to the user.

[0726] A "means for generating arguments against alternatives" is a system or method for generating arguments that point out the shortcomings or problems of alternatives in order to support a particular alternative.

[0727] "Means for presenting generated counterarguments to the user" refers to a system or method for displaying and presenting the counterarguments generated by the generating AI agent in an easy-to-understand manner to the user.

[0728] An "emotion engine" is software or a system for recognizing a user's emotional state in real time and adjusting information based on this data.

[0729] "User's emotional state" refers to the user's current mental and emotional state, including, for example, feelings such as stress, joy, relief, etc.

[0730] This invention is an interactive system that supports decision-making by providing reasons for and counterarguments to options while taking into account the user's emotional state. The system consists of a user terminal and a server that includes an emotion engine and a generative AI agent.

[0731] First, a user inputs multiple options using a terminal. For example, imagine a situation where a user must choose from multiple products on an online shopping website. These options are sent to the server, and the system prepares a generative AI agent that supports each option. The generative AI agent uses a generative AI model to generate reasons for supporting each option.

[0732] The server uses an emotion engine to generate support reasons before presenting them to the user's device. The emotion engine collects real-time emotional data from the user and adjusts the generated support reasons based on this data. For example, if the user is feeling stressed, it will emphasize reassuring information in the support reasons. Counterarguments against other options are also generated by the generative AI agent, adjusted by the emotion engine, and presented to the user.

[0733] As a concrete example, consider a situation where a user has to choose between the following options:

[0734] Option A: Premium earphones that offer high-quality sound

[0735] Option B: The best value wireless earphones

[0736] Option C: Waterproof sports earphones

[0737] In this case, an example prompt would be:

[0738] "Help the user choose from the following options:

[0739] Product A: High-quality earphones that provide high-quality sound

[0740] Product B: The best value wireless earphones

[0741] Product C: Highly waterproof sports earphones

[0742] Tell users which option they should choose, why that option is better, and why based on their emotional state.”

[0743] The generated reasons and counterarguments are then adjusted by the emotion engine and optimized to provide the user with a sense of security and satisfaction, allowing the user to receive information tailored to their emotional state and make better decisions.

[0744] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0745] Step 1:

[0746] The server receives multiple options from the user's device. In this step, the user inputs their options via their device, which are then sent to the server in list form. For example, suppose the user submits the following options: "High-end earphones that provide high-quality sound," "Wireless earphones with the best value for money," and "Waterproof sports earphones." The input option list arrives at the server and is saved in its original format.

[0747] Step 2:

[0748] The server prepares generative AI agents according to the number of options received. Each agent generates reasons for supporting a particular option. In this step, the server invokes the generative AI model and configures an agent for each option. For example, Agent A is configured to support "high-quality earphones that provide high-quality sound," and Agent B is configured to support "wireless earphones with the best cost performance."

[0749] Step 3:

[0750] The server sends a command to the generative AI agent to generate reasons for each option, including a prompt such as, "Why is this option superior?" The prompt is input to the generative AI model, which outputs reasons for support. For example, the prompt for Agent A might be, "Why are high-end earphones that provide high-quality sound superior?", and the output would be a reason such as, "The sound quality is very clear and provides a superior hearing experience compared to other products."

[0751] Step 4:

[0752] The server passes the generated support reasons to the emotion engine, which adjusts them based on the user's emotional state. In this step, the emotion engine analyzes the user's emotional data in real time and adjusts the support reasons based on that data. For example, if the user is feeling stressed, the emotion engine adjusts the support reasons to emphasize a sense of relief.

[0753] Step 5:

[0754] The server then presents the support reasons for each agent, adjusted by the emotion engine, to the user's device. In this step, the adjusted support reasons are sent to the device and displayed to the user. For example, the support reason for "luxury earphones that provide high-quality sound" is presented as "The sound quality is very clear and provides a superior hearing experience compared to other products. Don't worry, we guarantee that it is the best choice."

[0755] Step 6:

[0756] The server generates counterarguments to the other options, which are similarly adjusted by the emotion engine and then presented to the user. In this step, the generation AI agent generates a counterargument, with a prompt that includes, "Why are the other options inferior?" For example, a counterargument from Agent A might be, "The best value-for-money earphones are inferior to high-end earphones in terms of sound quality." The counterargument, adjusted by the emotion engine, is then presented to the user.

[0757] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0758] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0759] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0760] [Third embodiment]

[0761] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0762] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0763] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0764] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0765] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0766] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0767] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0768] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0769] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0770] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0771] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0772] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0773] The following describes a specific embodiment of the present invention. The present invention is a system for supporting user decision-making, and in particular, provides a method for supporting a user who is struggling between multiple options by having a generation AI agent that supports each option exchange opinions to support the user's decision-making.

[0774] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, and a means for presenting the generated reasons for supporting and counterarguments to the user.

[0775] System Operation

[0776] 1. Setting options

[0777] The server receives as input the multiple options the user is considering. These options are set in list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0778] 2. Initial setup of the generated AI agent

[0779] The server prepares a generative AI agent for each option. The generative AI agent is designed to support each option and generates text using a generative AI model.

[0780] 3. Generating reasons for support

[0781] For each option, the server sends a command to the generating AI agent to generate reasons for each option. Each agent generates text explaining the merits and validity of each option and sends it to the server.

[0782] 4. Presentation of reasons for support

[0783] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0784] 5. Generating and Presenting Counterarguments

[0785] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also presented to the user.

[0786] Specific examples

[0787] Campaign banner wording selection

[0788] The server sets the following options:

[0789] Option A: "Flash Sale - 50% OFF!"

[0790] Option B: "Limited Time Offer - Buy One, Get One Free"

[0791] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0792] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0793] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0794] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0795] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0796] The server presents these reasons to the user's device, and the user compares and considers each reason. Furthermore, counterarguments to other options are also generated and presented to the user. This allows the user to deeply understand the advantages and disadvantages of each option and make a final decision.

[0797] The present invention provides users with comprehensive support for selecting the most appropriate option from among multiple options, thereby aiming to improve the accuracy and satisfaction of decision-making.

[0798] The processing flow will be explained below.

[0799] Step 1:

[0800] The server receives multiple options from the user's terminal, which are presented in the form of a list based on a specific theme, such as selecting a campaign banner or choosing a specific product.

[0801] Step 2:

[0802] The server prepares generative AI agents according to the number of options received, each configured to support a particular option using a specified generative AI model.

[0803] Step 3:

[0804] The server sends a prompt to each agent, instructing them to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of each option.

[0805] Step 4:

[0806] The server aggregates the generated support reasons and sends them to the user's terminal, where the user can view the support reasons presented by each agent.

[0807] Step 5:

[0808] The server generates counterarguments to other options as needed, sending prompts to each agent to criticize or point out flaws in the other options, and each agent generates a counterargument.

[0809] Step 6:

[0810] The server collects the generated counterarguments and sends them to the user's terminal, where the user can view the counterarguments for each option.

[0811] Step 7:

[0812] The user compares the arguments for and against each agent presented on the device, allowing them to gain a balanced perspective on multiple options.

[0813] Step 8:

[0814] The user can decide the most appropriate option based on the information presented and provide feedback of that decision to the server.

[0815] Example 1

[0816] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0817] Conventional decision support systems often lack the information necessary to make an appropriate decision between multiple options. Furthermore, there are limited means to provide users with sufficient information to properly compare the supporting and counterargumentative arguments for each option and make the optimal choice. This can lead to problems such as users being confused and reducing the accuracy and satisfaction of their decision-making.

[0818] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0819] In this invention, the server includes means for presenting options to a user, a generation AI agent supporting each option, means for the generation AI agent to generate reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments for other options, means for presenting the generated counterarguments to the user, and means for generating reasons for supporting each option based on a prompt sentence using a generative AI model. This allows the user to easily compare the reasons for supporting and counterarguments for each option, and provides sufficient information for making an optimal decision.

[0820] A "means for presenting options to a user" is a system element that provides multiple options to a user in visual or text format, allowing the user to compare and consider the options.

[0821] A "generative AI agent" is an artificial intelligence program or algorithm that generates reasons and counterarguments in support of each option.

[0822] "Means for generating supporting reasons" is a function that allows the generative AI agent to use the generative AI model to generate reasons and advantages in favor of a given option in text format.

[0823] The "means for presenting the generated reasons for supporting each option to the user" is a system element that visualizes and displays to the user the reasons for supporting each option generated by the generating AI agent.

[0824] "Means for generating counterarguments to alternative options" refers to the ability of a generative AI agent to use a generative AI model to generate, in text form, reasons for opposing or shortcomings of alternative options.

[0825] The "means for presenting the generated counterargument to the user" is a system element that visualizes and displays the counterargument generated by the generating AI agent to the user.

[0826] A "generative AI model" is an artificial intelligence algorithm or program that automatically generates text, specifically a model trained for natural language processing.

[0827] A "prompt sentence" is an input sentence that instructs a generative AI model to generate a specific text.

[0828] This invention is a system that supports user decision-making, and provides a method for users who are struggling to decide between multiple options by having a generating AI agent that supports each option exchange opinions to support the user's decision-making. This system has the following specific configuration and functions.

[0829] System Overview

[0830] The system primarily includes the following hardware and software components:

[0831] Server: Handles data processing and manages generated AI agents.

[0832] User terminal: A device through which a user can input their choices and view the generated supporting and counterargumentative reasons.

[0833] Generative AI models: AI models for natural language processing and text generation (e.g., GPT-4).

[0834] Specific operation of the system

[0835] 1. Enter your choices

[0836] The server receives multiple options from the user as input. These options are set in a list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[0837] 2. Initial setup of the generated AI agent

[0838] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option and generates text using a generative AI model (e.g., GPT-4). The prompt text is also set at this stage.

[0839] 3. Generating reasons for support

[0840] For each option, the server sends a prompt to the generating AI agent, which generates a reason for each option and sends the generated text to the server.

[0841] 4. Presentation of reasons for support

[0842] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[0843] 5. Generating and Presenting Counterarguments

[0844] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option look more favorable. The generated counterarguments are also presented to the user.

[0845] Specific examples

[0846] Scenario for selecting campaign banner wording

[0847] 1. Setting options

[0848] The server sets the following options:

[0849] Option A: "Flash Sale - 50% OFF!"

[0850] Option B: "Limited Time Offer - Buy One, Get One Free"

[0851] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0852] 2. Initial setup of the generated AI agent

[0853] The server prepares a generating AI agent to support each option, with each prompt set as follows:

[0854] "Generate a 3-5 sentence reasoning in support of the following option: 'Flash Sale - 50% OFF!'"

[0855] "Generate 3-5 sentences supporting the following option: 'Limited Time Offer - Buy One, Get One Free'"

[0856] "Generate 3-5 sentences supporting the following option: 'Exclusive Deal - Free Shipping on Orders Over $50'"

[0857] 3. Generating reasons for support

[0858] The generating AI agent uses the prompt sentence to generate reasons for support such as:

[0859] Agent A: "Flash Sale - 50% OFF!" will motivate customers to buy and contribute to immediate sales.

[0860] Agent B: "Limited Time Offer - Buy One, Get One Free" increases sales and smooths inventory flow.

[0861] Agent C: "Exclusive Deal - Free Shipping on Orders Over $50" encourages customers to buy and reduces shipping costs, increasing their motivation to buy.

[0862] 4. Presentation of reasons for support

[0863] The server transmits these reasons for support to the user's terminal, and the user compares and considers each reason for support on the terminal.

[0864] 5. Generating and Presenting Counterarguments

[0865] The server also generates a rebuttal as follows:

[0866] Agent A argues against the "Limited Time Offer - Buy One, Get One Free" by pointing out that it would make inventory management difficult.

[0867] Agent B argues that the "Exclusive Deal - Free Shipping on Orders Over $50" offer is not as impressive a discount.

[0868] This allows users to deeply understand the advantages and disadvantages of each option and make optimal decisions. This system aims to improve the accuracy and satisfaction of users' decision-making.

[0869] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0870] Step 1: User inputs choices

[0871] The server provides an interface for the user to input multiple options via the terminal. The options to be input may be, for example, campaign banner text or product features, and once the user has completed the input, the server receives it. The received data is structured and stored in a database. The input data is often in the form of a list or JSON.

[0872] Specific behavior:

[0873] The user enters options such as "Flash Sale - 50% OFF!" or "Limited Time Offer - Buy One, Get One Free" into the terminal, and the server receives it and stores it in the database.

[0874] Step 2: Initializing the generated AI agent

[0875] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option, and the server sets a prompt sentence that is adapted to it. Specifically, it sets it up to generate text using a generative AI model (e.g., GPT-4).

[0876] Input and Output:

[0877] The server takes the choice data as input and generates the initial settings and prompt sentences for the generated AI agent based on it. The output is the generated AI agent with the initial settings completed.

[0878] Specific behavior:

[0879] For the option "Flash Sale - 50% OFF!", the server sets the prompt text "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'" to the generating AI agent.

[0880] Step 3: Generate supporting reasons

[0881] The server commands the generative AI agent to generate supporting reasons for each option. The generative AI model generates text explaining the merits and validity of each option based on the specified prompt. The generated supporting reasons are sent to the server.

[0882] Input and Output:

[0883] The input is the prompt sentence and option data set in Step 2. This is processed by the generative AI model, and the output is a text of the reasons for support.

[0884] Specific behavior:

[0885] In response to the prompt, "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'", the AI ​​model generates text such as "'Flash Sale - 50% OFF!' will increase customer purchasing intent and contribute to immediate sales growth."

[0886] Step 4: Present your reasons for support

[0887] The server sends the generated reasons for support to the user's device, where these reasons are visually displayed, allowing the user to compare and consider the reasons for support for each option.

[0888] Input and Output:

[0889] The input is the text of the support reasons generated by the generative AI model, and the output is the support reasons displayed on the user's device.

[0890] Specific behavior:

[0891] The server transmits the reason for support, such as "'Flash Sale - 50% OFF!' will increase customers' desire to purchase and contribute to an immediate increase in sales," to the user's terminal, which then displays the reason.

[0892] Step 5: Generate and present a counterargument

[0893] The server commands the generative AI agent to generate a counterargument against the other options. This counterargument is generated by the generative AI model and is a text that points out the shortcomings and problems of the other options. The generated counterargument is also sent to the user's device.

[0894] Input and Output:

[0895] The input is a set of alternatives and a corresponding prompt, which is processed by a generative AI model, and the output is a counterargument text.

[0896] Specific behavior:

[0897] The server inputs a prompt such as "Generate a three-sentence counterargument to the following option, 'Limited Time Offer - Buy One, Get One Free'" into the generative AI model, and the generated text, such as "Inventory management will become more difficult" or "Profit margins may decline," is sent to the user's device, where it is displayed.

[0898] Through these steps, users can compare the reasons for and counterarguments of each option and make the best decision.

[0899] (Application example 1)

[0900] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0901] Currently, when users select the optimal product from multiple product options, it is difficult for them to objectively evaluate the advantages and disadvantages of each product. In particular, e-commerce platforms are overwhelmed with a wide variety of product information, making it difficult for users to properly compare and consider this information. Furthermore, the lack of a system that effectively supports the user selection process leads to problems such as incorrect selection and time-consuming selection.

[0902] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0903] In this invention, the server includes a means for presenting options to a user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments for other options, a means for presenting the generated counterarguments to the user, and a means for generating reasons for supporting and counterarguments for different products and displaying them to the user in the product selection process, thereby enabling the user to understand the advantages and disadvantages of each product option and select the optimal option quickly and efficiently.

[0904] "Choice" refers to each item or option that a user considers to select from multiple choices.

[0905] "User" refers to an individual or corporation that makes decisions using this system.

[0906] "Means" refers to the methods or processes used to achieve a particular goal.

[0907] A "generative AI agent" is a program that uses a generative AI model to support specific options and has the ability to generate text about the advantages and disadvantages of each option.

[0908] "Generated reasons for support" refers to text generated by the generating AI agent explaining the benefits or validity of a particular option.

[0909] "Rebuttal" refers to text generated to point out the flaws or problems of an alternative.

[0910] The "product selection process" refers to a series of actions or steps a user takes to select the optimal product from multiple product options.

[0911] "Display means" refers to a method or device that allows a user to visually view information generated by the system.

[0912] This invention provides a system that helps users select the most suitable product from multiple product options. The system's main hardware configuration is a server and a user terminal. The server uses a generation AI agent to generate reasons for and counterarguments for each option and presents them to the user terminal.

[0913] System Operation

[0914] 1. Setting options

[0915] The user device receives as input multiple product options that the user wants to compare, such as product models like "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6."

[0916] 2. Initial setup of the generated AI agent

[0917] The server prepares a generative AI agent for each product option, each of which uses a specific generative AI model.

[0918] 3. Generating reasons for support

[0919] The server sends commands to each generative AI agent to generate reasons in favor of each option. For example, the generative AI model might generate reasons that the iPhone 13 has the latest processor and offers better performance to users.

[0920] 4. Presentation of reasons for support

[0921] The server transmits the generated reasons for support to the user terminal for the user to view, allowing the user to compare the merits of each product option.

[0922] 5. Generating and Presenting Counterarguments

[0923] The server instructs each generative AI agent to generate a counterargument to the other options. For example, the generative AI model generates a counterargument pointing out that a disadvantage of the Samsung Galaxy S21 is its short battery life.

[0924] These counterarguments are also sent to the user's terminal, allowing the user to weigh the drawbacks of each option.

[0925] Specific usage

[0926] For example, if a user wants to use a shopping site to choose the best smartphone, they might enter the following prompt:

[0927] I want to choose the best smartphone.

[0928] My options are the iPhone 13, the Samsung Galaxy S21, and the Google Pixel 6. What are the advantages of each?

[0929] In response, the generating AI agent generates the following reasons for support:

[0930] Reasons for choosing the iPhone 13: The iPhone 13 is equipped with the latest chipset, offering effective battery management and excellent performance, and is highly compatible with other devices thanks to the Apple ecosystem.

[0931] Reasons for choosing the Samsung Galaxy S21: The Samsung Galaxy S21 has a high-resolution display that is ideal for watching videos and playing games. It also has an excellent camera.

[0932] Reasons for choosing the Google Pixel 6: The Google Pixel 6 receives the latest Android updates early and has smooth integration with Google services. Its competitive price makes it a great value for money.

[0933] Software used and data processing

[0934] The server handles the main data processing and runs generative AI models, particularly those using OpenAI GPT-3. The user device is used to input data and display the generated reasons and counterarguments. Data processing and calculations are performed by scripts (e.g., Python scripts) running on the server.

[0935] Users can understand the advantages and disadvantages of each product option based on specific supporting and counterargumentative reasons, and make the best choice. This system makes users' decision-making quick and effective.

[0936] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0937] Step 1:

[0938] The user inputs product options. The user device receives as input the multiple product options the user wants to compare. This input includes specific product names such as "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6." The server begins processing based on this input.

[0939] Step 2:

[0940] The server presents the options to the user. The server generates a list of products received from the user and sends it to the user's terminal. This allows the user to check the options and obtain information about each option.

[0941] Step 3:

[0942] Prepare the generative AI agents. The server configures a generative AI agent for each product option. Each generative AI agent is configured to utilize a generative AI model (e.g., OpenAI GPT-3) to support a specific product.

[0943] Step 4:

[0944] Generate reasons for support. The server sends each generation AI agent an instruction to generate reasons for support for a specified product. For example, a prompt sentence such as "I want to choose the best smartphone. The options are 'iPhone 13', 'Samsung Galaxy S21', and 'Google Pixel 6'. Please tell me the advantages of each." is input into the generation AI model, which then outputs specific reasons for support. This output is text information about the advantages of each product.

[0945] Step 5:

[0946] The reasons for support are presented to the user. The server sends the generated text of the reasons for support to the user's terminal. The user's terminal displays this, allowing the user to view the reasons for support for each product. Based on this, the user can consider which option is best.

[0947] Step 6:

[0948] Generate counterarguments. The server sends each generation AI agent an instruction to generate counterarguments about other options. For example, the generation AI model receives a prompt such as "What are the disadvantages of the iPhone 13?" and generates a counterargument. This output is text information about the shortcomings and problems of other products.

[0949] Step 7:

[0950] The rebuttals are presented to the user. The server sends the generated rebuttal text to the user's terminal. The user's terminal displays it, allowing the user to view the rebuttal information for each product. Based on this, the user can make the optimal selection, taking into account the drawbacks of each product.

[0951] Step 8:

[0952] The user decides on an option. Based on the presented reasons for and counterarguments, the user selects the most suitable product. Through this process, the user can comprehensively assess the advantages and disadvantages of each product and select the most suitable option.

[0953] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0954] The following describes a specific embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generation AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[0955] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, a means for presenting the generated supporting reasons and counterarguments to the user, and an emotion engine that recognizes the user's emotions and adjusts the information accordingly.

[0956] System Operation

[0957] 1. Setting options

[0958] The server receives multiple options from the user's device. These options are set in list format and are provided in a variety of forms depending on individual usage scenarios, such as selecting the wording for a campaign banner or choosing a Mother's Day gift.

[0959] 2. Initial setup of the generated AI agent

[0960] The server prepares generative AI agents according to the number of options received, each designed to support a specific option using a specified generative AI model.

[0961] 3. Generating reasons for support

[0962] For each option, the server sends a command to the generating AI agent to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of that option and sends it to the server.

[0963] 4. Emotional Engine Adjustment

[0964] Before presenting the generated supporting and counterargumentative arguments, the server uses an emotion engine to analyze the user's emotional state. The emotion engine collects real-time emotional data from the user and adjusts the output of each agent based on this data. For example, if the user is feeling stressed, the agent will emphasize more reassuring information.

[0965] 5. Presentation of reasons for support

[0966] The server presents the reasons for supporting each agent, adjusted by the emotion engine, to the user's terminal, where the user can view the reasons for supporting each agent through the terminal.

[0967] 6. Generating and Presenting Counterarguments

[0968] Furthermore, the server commands the AI ​​agent to create counterarguments against other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also adjusted by the emotion engine and presented to the user.

[0969] Specific examples

[0970] Example of using the emotion engine: Selecting campaign banner text

[0971] The server sets the following options:

[0972] Option A: "Flash Sale - 50% OFF!"

[0973] Option B: "Limited Time Offer - Buy One, Get One Free"

[0974] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[0975] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[0976] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[0977] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[0978] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[0979] The generated reasons for support are adjusted by the emotion engine based on the user's emotional state before being presented to the user. For example, if the user shows signs of impatience, Agent A's emphasis on "urgency" is adjusted, and other benefits that provide a sense of security are added.

[0980] Through these steps, users will have more balanced information and be able to make optimal decisions based on their emotional state.

[0981] The processing flow will be explained below.

[0982] Step 1:

[0983] The user inputs options using the terminal. For example, when selecting the banner wording for a campaign, the user inputs options such as "Flash Sale - 50% OFF," "Limited Time Offer - Buy One, Get One Free," and "Exclusive Deal - Free Shipping on Orders Over $50."

[0984] Step 2:

[0985] The server keeps a list of the choices received from the user, so that a generative AI agent can be applied to each choice in the subsequent process.

[0986] Step 3:

[0987] The server prepares generative AI agents according to the number of options. Each agent uses a specified generative AI model (e.g., GPT-3.5-turbo) and configures it to support a specific option.

[0988] Step 4:

[0989] The server sends prompts to each AI agent to generate reasons for each option. The prompts include questions such as "Why is this option better?". Each agent generates text based on the prompts.

[0990] Step 5:

[0991] The server collects and stores the generated reasons for support in order to organize the text output by each agent and use it in the next step.

[0992] Step 6:

[0993] The server invokes an emotion engine to analyze the user's emotional state, determining the user's current emotion based on, for example, facial expression recognition, voice tone analysis, and the content of the text input.

[0994] Step 7:

[0995] Based on the emotional state analyzed by the emotion engine, the server adjusts the generated support reasons. For example, if the user is feeling stressed, the server adds expressions that alleviate the stress, providing a sense of relief.

[0996] Step 8:

[0997] The server sends the support reasons adjusted by the emotion engine to the user's terminal and displays them. The user can view the support reasons for each agent through the terminal.

[0998] Step 9:

[0999] The server again sends commands to the generating AI agents to generate counterarguments against the other options. Each agent generates a counterargument by setting prompts to point out the shortcomings and problems of the other options.

[1000] Step 10:

[1001] The server collects and stores the generated counterarguments. These counterarguments are also analyzed by the emotion engine and adjusted to fit the user's emotional state.

[1002] Step 11:

[1003] The server sends the counterarguments adjusted by the emotion engine to the user's device and displays them. The user can view the counterarguments of each agent through the device.

[1004] Step 12:

[1005] The user compares the reasons for and counterarguments of each agent displayed on the terminal and decides on the option that they feel is most appropriate.

[1006] The above is the specific flow of operation of the system according to the present invention.

[1007] Example 2

[1008] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1009] Conventional decision support systems simply present options to users, and it is difficult to explain why one option is superior or to provide counterarguments to other options. Furthermore, because they provide information without taking into account the user's emotional state, they are unable to provide appropriate support when the user is feeling stressed or impatient. As a result, there is the issue of inadequate support for user decision-making.

[1010] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for presenting options to the user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments against other options, a means for presenting the generated counterarguments to the user, and an emotion engine that analyzes the user's emotional state and adjusts the reasons for support and counterarguments. This makes it possible to provide the user with the optimal option together with information based on the analysis of the emotional state.

[1011] "Means for presenting options to the user" means the technical elements that display and provide options in a list or other format so that the user can select from multiple options.

[1012] A "generative AI agent" is a software agent designed to generate reasons and counterarguments for a given option using a specific generative AI model.

[1013] The "means for generating supporting reasons" is a function that allows the generating AI agent to generate text that explains the benefits and advantages of an option using a prompt sentence.

[1014] The "means for presenting the generated reasons for supporting each option to the user" refers to a technical element for displaying the generated reasons for supporting on the user's terminal so that the user can view them.

[1015] "Means for generating counterarguments to other options" is a feature that allows the generative AI agent to generate text that points out the counterarguments or flaws of a particular option.

[1016] The "means for presenting the generated rebuttal to the user" refers to the technical elements for displaying the generated rebuttal on the user's terminal so that the user can view it.

[1017] The "emotion engine" is a software component that collects and analyzes real-time user emotion data and adjusts the output of the generative AI agent based on the results.

[1018] The following describes an embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generative AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[1019] The system includes the following main components:

[1020] 1. A means of presenting options to the user

[1021] 2. Generative AI agent supporting each option

[1022] 3. A method for presenting the generated support reasons to the user

[1023] 4. A means of generating counterarguments to alternatives

[1024] 5. A means for presenting generated rebuttals to the user

[1025] 6. Emotion engine that analyzes the user's emotional state and adjusts information accordingly

[1026] System configuration

[1027] Presenting options

[1028] The server receives multiple options from the user's device and sets these options in a list format. The options are provided in a format that corresponds to a specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[1029] Initial settings for generated AI agents

[1030] The server prepares generative AI agents according to the number of options received, with each agent designed to support a specific option using a generative AI model such as GPT-3 or ChatGPT.

[1031] Generating reasons for and counterarguments

[1032] Each agent uses a specified generative AI model to generate reasons for each option. The prompt is in the form of a question such as "Why is this option better?", for example, "Please explain why 'Flash Sale - 50% OFF!' is better."

[1033] Emotional engine regulation

[1034] The server analyzes the user's emotional state using an emotion engine before presenting the generated supporting and counterargumentative reasons. The emotion engine collects the user's emotional data in real time and adjusts the output of each agent based on this data, for example, by emphasizing reassuring information if the user is feeling stressed.

[1035] Presenting reasons for support and counterarguments

[1036] The server then presents the adjusted reasons for and counterarguments to the user's terminal. The user can then view the information provided by each agent through their terminal and use it as a reference for making the best choice.

[1037] Specific examples

[1038] Choosing campaign banner text using an emotion engine

[1039] As a concrete example, consider a scenario where you are selecting the banner text for a campaign. The server sets the following options:

[1040] Option A: "Flash Sale - 50% OFF!"

[1041] Option B: "Limited Time Offer - Buy One, Get One Free"

[1042] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[1043] The server initializes a generating AI agent that supports each option. The agent generates reasons for supporting each option. An example prompt is:

[1044] To Agent A, "Explain why 'Flash Sale - 50% OFF!' is a great offer."

[1045] To Agent B, "Explain why 'Limited Time Offer - Buy One, Get One Free' is a great option."

[1046] To Agent C, "Please explain why 'Exclusive Deal - Free Shipping on Orders Over $50' is a great offer."

[1047] Each generative AI agent generates a reason for support, and the emotion engine adjusts the output based on the user's emotional state. The server then presents the adjusted information to the user's device, allowing the user to choose the optimal option.

[1048] In this way, users can make better decisions based on balanced information that takes into account their emotional state.

[1049] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1050] Step 1: Receive your choices

[1051] The server receives multiple options from the user via the terminal.

[1052] Specifically, the user inputs a list of options into the device, for example, the following campaign banner text:

[1053] "Flash Sale - 50% OFF!"

[1054] "Limited Time Offer - Buy One, Get One Free"

[1055] "Exclusive Deal - Free Shipping on Orders Over $50"

[1056] Input: A list of choices the user has entered into the device

[1057] Output: List of options received by the server

[1058] Step 2: Initializing the generated AI agent

[1059] The server prepares generative AI agents according to the number of options received, assigning each agent to a different option and configuring them using a generative AI model (e.g., GPT-3 or ChatGPT).

[1060] Specifically, the server generates three generation AI agents and assigns them to options A, B, and C, respectively.

[1061] Input: list of options

[1062] Output: A set of generated AI agents with initial settings

[1063] Step 3: Generate supporting reasons

[1064] The server issues a command to each generating AI agent to generate supporting reasons, using a prompt phrase to ask "Why is this choice better?"

[1065] Specifically, for example, Agent A is prompted with "Please explain why 'Flash Sale - 50% OFF!' is a good product." The generating AI agent generates supporting reasons based on this prompt and sends them to the server.

[1066] Input: prompt, initialised generated AI agents

[1067] Output: Text data of reasons for supporting each option

[1068] Step 4: Emotional Engine Adjustment

[1069] The server analyzes the user's emotional state using an emotion engine before presenting the generated support reasons and counterarguments. The emotion engine collects the user's emotional data in real time and adjusts the support reasons and counterarguments.

[1070] Specifically, the device uses a camera and microphone to analyze the user's facial expressions and voice, and sends the emotional data to the server. The server then uses this data to adjust the output of the generated AI agent. For example, if the user is feeling stressed, it adds information that emphasizes a sense of security to the output.

[1071] Input: Text data of generated support reasons, user emotion data

[1072] Output: Text data of adjusted support and counterarguments

[1073] Step 5: Present your reasons for support

[1074] The server presents the adjusted reasons for support to the user's terminal, and the user can view the reasons for support provided by each agent through the terminal.

[1075] Specifically, the server sends the adjusted reasons for support to the terminal, and the terminal displays them on the screen, for example, displaying the benefits of "Flash Sale - 50% OFF!", such as the immediate customer attraction effect.

[1076] Input: Text data of adjusted reasons for support

[1077] Output: The reason for support displayed on the user's terminal

[1078] Step 6: Generate and present a counterargument

[1079] The server commands the generator AI agent to create counterarguments against the other options, which point out the shortcomings and problems of the other options.

[1080] Specifically, the server generates a counterargument for Agent A explaining why 'Limited Time Offer - Buy One, Get One Free' is inferior. This information is also adjusted by the emotion engine and then presented to the user.

[1081] Input: Rebuttal prompt, emotion data

[1082] Output: Text data of the adjusted rebuttal, and the rebuttal displayed on the user's device

[1083] This system allows users to make better decisions by receiving information that corresponds to their emotional state.

[1084] (Application example 2)

[1085] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1086] Conventional decision support systems do not take into account the user's emotional state when selecting the optimal option from multiple options, resulting in insufficient support for the user. Furthermore, the generated reasons and counterarguments are not adjusted to reflect the user's emotions, making it difficult for the user to make a decision with confidence. To solve these problems, a system that provides information based on the user's emotional state and supports more appropriate decision-making is needed.

[1087] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting options to the user, a generating AI agent that supports each option and the generating AI agent generates reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments against other options, means for presenting the generated counterarguments to the user, and means including an emotion engine that recognizes the user's emotional state and adjusts information. This makes it possible to provide information according to the user's emotional state, allowing the user to make the optimal choice with greater confidence.

[1088] A "means for presenting options to a user" is a system or method that clearly displays and presents to a user multiple options that the user is considering.

[1089] A "generative AI agent" is an entity or software that uses artificial intelligence techniques to generate reasons in support of a particular choice.

[1090] A "means for generating reasons for support" is a system or method that uses a generative AI agent to automatically generate reasons for support in order to present the advantages and merits of options to a user.

[1091] "Means for presenting the generated reasons for supporting each option to the user" refers to a system or method that displays and presents the reasons for supporting each option generated by the generating AI agent in an easy-to-understand manner to the user.

[1092] A "means for generating arguments against alternatives" is a system or method for generating arguments that point out the shortcomings or problems of alternatives in order to support a particular alternative.

[1093] "Means for presenting generated counterarguments to the user" refers to a system or method for displaying and presenting the counterarguments generated by the generating AI agent in an easy-to-understand manner to the user.

[1094] An "emotion engine" is software or a system for recognizing a user's emotional state in real time and adjusting information based on this data.

[1095] "User's emotional state" refers to the user's current mental and emotional state, including, for example, feelings such as stress, joy, relief, etc.

[1096] This invention is an interactive system that supports decision-making by providing reasons for and counterarguments to options while taking into account the user's emotional state. The system consists of a user terminal and a server that includes an emotion engine and a generative AI agent.

[1097] First, a user inputs multiple options using a terminal. For example, imagine a situation where a user must choose from multiple products on an online shopping website. These options are sent to the server, and the system prepares a generative AI agent that supports each option. The generative AI agent uses a generative AI model to generate reasons for supporting each option.

[1098] The server uses an emotion engine to generate support reasons before presenting them to the user's device. The emotion engine collects real-time emotional data from the user and adjusts the generated support reasons based on this data. For example, if the user is feeling stressed, it will emphasize reassuring information in the support reasons. Counterarguments against other options are also generated by the generative AI agent, adjusted by the emotion engine, and presented to the user.

[1099] As a concrete example, consider a situation where a user has to choose between the following options:

[1100] Option A: Premium earphones that offer high-quality sound

[1101] Option B: The best value wireless earphones

[1102] Option C: Waterproof sports earphones

[1103] In this case, an example prompt would be:

[1104] "Help the user choose from the following options:

[1105] Product A: High-quality earphones that provide high-quality sound

[1106] Product B: The best value wireless earphones

[1107] Product C: Highly waterproof sports earphones

[1108] Tell users which option they should choose, why that option is better, and why based on their emotional state.”

[1109] The generated reasons and counterarguments are then adjusted by the emotion engine and optimized to provide the user with a sense of security and satisfaction, allowing the user to receive information tailored to their emotional state and make better decisions.

[1110] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1111] Step 1:

[1112] The server receives multiple options from the user's device. In this step, the user inputs their options via their device, which are then sent to the server in list form. For example, suppose the user submits the following options: "High-end earphones that provide high-quality sound," "Wireless earphones with the best value for money," and "Waterproof sports earphones." The input option list arrives at the server and is saved in its original format.

[1113] Step 2:

[1114] The server prepares generative AI agents according to the number of options received. Each agent generates reasons for supporting a particular option. In this step, the server invokes the generative AI model and configures an agent for each option. For example, Agent A is configured to support "high-quality earphones that provide high-quality sound," and Agent B is configured to support "wireless earphones with the best cost performance."

[1115] Step 3:

[1116] The server sends a command to the generative AI agent to generate reasons for each option, including a prompt such as, "Why is this option superior?" The prompt is input to the generative AI model, which outputs reasons for support. For example, the prompt for Agent A might be, "Why are high-end earphones that provide high-quality sound superior?", and the output would be a reason such as, "The sound quality is very clear and provides a superior hearing experience compared to other products."

[1117] Step 4:

[1118] The server passes the generated support reasons to the emotion engine, which adjusts them based on the user's emotional state. In this step, the emotion engine analyzes the user's emotional data in real time and adjusts the support reasons based on that data. For example, if the user is feeling stressed, the emotion engine adjusts the support reasons to emphasize a sense of relief.

[1119] Step 5:

[1120] The server then presents the support reasons for each agent, adjusted by the emotion engine, to the user's device. In this step, the adjusted support reasons are sent to the device and displayed to the user. For example, the support reason for "luxury earphones that provide high-quality sound" is presented as "The sound quality is very clear and provides a superior hearing experience compared to other products. Don't worry, we guarantee that it is the best choice."

[1121] Step 6:

[1122] The server generates counterarguments to the other options, which are similarly adjusted by the emotion engine and then presented to the user. In this step, the generation AI agent generates a counterargument, with a prompt that includes, "Why are the other options inferior?" For example, a counterargument from Agent A might be, "The best value-for-money earphones are inferior to high-end earphones in terms of sound quality." The counterargument, adjusted by the emotion engine, is then presented to the user.

[1123] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1124] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1125] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1126] [Fourth embodiment]

[1127] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1128] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1129] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1130] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1131] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1132] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1133] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1134] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1135] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1136] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1137] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1138] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1139] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1140] The following describes a specific embodiment of the present invention. The present invention is a system for supporting user decision-making, and in particular, provides a method for supporting a user who is struggling between multiple options by having a generation AI agent that supports each option exchange opinions to support the user's decision-making.

[1141] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, and a means for presenting the generated reasons for supporting and counterarguments to the user.

[1142] System Operation

[1143] 1. Setting options

[1144] The server receives as input the multiple options the user is considering. These options are set in list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[1145] 2. Initial setup of the generated AI agent

[1146] The server prepares a generative AI agent for each option. The generative AI agent is designed to support each option and generates text using a generative AI model.

[1147] 3. Generating reasons for support

[1148] For each option, the server sends a command to the generating AI agent to generate reasons for each option. Each agent generates text explaining the merits and validity of each option and sends it to the server.

[1149] 4. Presentation of reasons for support

[1150] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[1151] 5. Generating and Presenting Counterarguments

[1152] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also presented to the user.

[1153] Specific examples

[1154] Campaign banner wording selection

[1155] The server sets the following options:

[1156] Option A: "Flash Sale - 50% OFF!"

[1157] Option B: "Limited Time Offer - Buy One, Get One Free"

[1158] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[1159] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[1160] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[1161] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[1162] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[1163] The server presents these reasons to the user's device, and the user compares and considers each reason. Furthermore, counterarguments to other options are also generated and presented to the user. This allows the user to deeply understand the advantages and disadvantages of each option and make a final decision.

[1164] The present invention provides users with comprehensive support for selecting the most appropriate option from among multiple options, thereby aiming to improve the accuracy and satisfaction of decision-making.

[1165] The processing flow will be explained below.

[1166] Step 1:

[1167] The server receives multiple options from the user's terminal, which are presented in the form of a list based on a specific theme, such as selecting a campaign banner or choosing a specific product.

[1168] Step 2:

[1169] The server prepares generative AI agents according to the number of options received, each configured to support a particular option using a specified generative AI model.

[1170] Step 3:

[1171] The server sends a prompt to each agent, instructing them to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of each option.

[1172] Step 4:

[1173] The server aggregates the generated support reasons and sends them to the user's terminal, where the user can view the support reasons presented by each agent.

[1174] Step 5:

[1175] The server generates counterarguments to other options as needed, sending prompts to each agent to criticize or point out flaws in the other options, and each agent generates a counterargument.

[1176] Step 6:

[1177] The server collects the generated counterarguments and sends them to the user's terminal, where the user can view the counterarguments for each option.

[1178] Step 7:

[1179] The user compares the arguments for and against each agent presented on the device, allowing them to gain a balanced perspective on multiple options.

[1180] Step 8:

[1181] The user can decide the most appropriate option based on the information presented and provide feedback of that decision to the server.

[1182] Example 1

[1183] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1184] Conventional decision support systems often lack the information necessary to make an appropriate decision between multiple options. Furthermore, there are limited means to provide users with sufficient information to properly compare the supporting and counterargumentative arguments for each option and make the optimal choice. This can lead to problems such as users being confused and reducing the accuracy and satisfaction of their decision-making.

[1185] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1186] In this invention, the server includes means for presenting options to a user, a generation AI agent supporting each option, means for the generation AI agent to generate reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments for other options, means for presenting the generated counterarguments to the user, and means for generating reasons for supporting each option based on a prompt sentence using a generative AI model. This allows the user to easily compare the reasons for supporting and counterarguments for each option, and provides sufficient information for making an optimal decision.

[1187] A "means for presenting options to a user" is a system element that provides multiple options to a user in visual or text format, allowing the user to compare and consider the options.

[1188] A "generative AI agent" is an artificial intelligence program or algorithm that generates reasons and counterarguments in support of each option.

[1189] "Means for generating supporting reasons" is a function that allows the generative AI agent to use the generative AI model to generate reasons and advantages in favor of a given option in text format.

[1190] The "means for presenting the generated reasons for supporting each option to the user" is a system element that visualizes and displays to the user the reasons for supporting each option generated by the generating AI agent.

[1191] "Means for generating counterarguments to alternative options" refers to the ability of a generative AI agent to use a generative AI model to generate, in text form, reasons for opposing or shortcomings of alternative options.

[1192] The "means for presenting the generated counterargument to the user" is a system element that visualizes and displays the counterargument generated by the generating AI agent to the user.

[1193] A "generative AI model" is an artificial intelligence algorithm or program that automatically generates text, specifically a model trained for natural language processing.

[1194] A "prompt sentence" is an input sentence that instructs a generative AI model to generate a specific text.

[1195] This invention is a system that supports user decision-making, and provides a method for users who are struggling to decide between multiple options by having a generating AI agent that supports each option exchange opinions to support the user's decision-making. This system has the following specific configuration and functions.

[1196] System Overview

[1197] The system primarily includes the following hardware and software components:

[1198] Server: Handles data processing and manages generated AI agents.

[1199] User terminal: A device through which a user can input their choices and view the generated supporting and counterargumentative reasons.

[1200] Generative AI models: AI models for natural language processing and text generation (e.g., GPT-4).

[1201] Specific operation of the system

[1202] 1. Enter your choices

[1203] The server receives multiple options from the user as input. These options are set in a list format and can be configured in a variety of ways depending on the specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[1204] 2. Initial setup of the generated AI agent

[1205] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option and generates text using a generative AI model (e.g., GPT-4). The prompt text is also set at this stage.

[1206] 3. Generating reasons for support

[1207] For each option, the server sends a prompt to the generating AI agent, which generates a reason for each option and sends the generated text to the server.

[1208] 4. Presentation of reasons for support

[1209] The server presents the generated reasons for supporting each agent to the user's terminal, where the user can view the reasons for supporting each option.

[1210] 5. Generating and Presenting Counterarguments

[1211] In addition, the server commands the AI ​​agent to create counterarguments against the other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option look more favorable. The generated counterarguments are also presented to the user.

[1212] Specific examples

[1213] Scenario for selecting campaign banner wording

[1214] 1. Setting options

[1215] The server sets the following options:

[1216] Option A: "Flash Sale - 50% OFF!"

[1217] Option B: "Limited Time Offer - Buy One, Get One Free"

[1218] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[1219] 2. Initial setup of the generated AI agent

[1220] The server prepares a generating AI agent to support each option, with each prompt set as follows:

[1221] "Generate a 3-5 sentence reasoning in support of the following option: 'Flash Sale - 50% OFF!'"

[1222] "Generate 3-5 sentences supporting the following option: 'Limited Time Offer - Buy One, Get One Free'"

[1223] "Generate 3-5 sentences supporting the following option: 'Exclusive Deal - Free Shipping on Orders Over $50'"

[1224] 3. Generating reasons for support

[1225] The generating AI agent uses the prompt sentence to generate reasons for support such as:

[1226] Agent A: "Flash Sale - 50% OFF!" will motivate customers to buy and contribute to immediate sales.

[1227] Agent B: "Limited Time Offer - Buy One, Get One Free" increases sales and smooths inventory flow.

[1228] Agent C: "Exclusive Deal - Free Shipping on Orders Over $50" encourages customers to buy and reduces shipping costs, increasing their motivation to buy.

[1229] 4. Presentation of reasons for support

[1230] The server transmits these reasons for support to the user's terminal, and the user compares and considers each reason for support on the terminal.

[1231] 5. Generating and Presenting Counterarguments

[1232] The server also generates a rebuttal as follows:

[1233] Agent A argues against the "Limited Time Offer - Buy One, Get One Free" by pointing out that it would make inventory management difficult.

[1234] Agent B argues that the "Exclusive Deal - Free Shipping on Orders Over $50" offer is not as impressive a discount.

[1235] This allows users to deeply understand the advantages and disadvantages of each option and make optimal decisions. This system aims to improve the accuracy and satisfaction of users' decision-making.

[1236] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1237] Step 1: User inputs choices

[1238] The server provides an interface for the user to input multiple options via the terminal. The options to be input may be, for example, campaign banner text or product features, and once the user has completed the input, the server receives it. The received data is structured and stored in a database. The input data is often in the form of a list or JSON.

[1239] Specific behavior:

[1240] The user enters options such as "Flash Sale - 50% OFF!" or "Limited Time Offer - Buy One, Get One Free" into the terminal, and the server receives it and stores it in the database.

[1241] Step 2: Initializing the generated AI agent

[1242] The server prepares a generative AI agent corresponding to each option. The generative AI agent is designed to support each option, and the server sets a prompt sentence that is adapted to it. Specifically, it sets it up to generate text using a generative AI model (e.g., GPT-4).

[1243] Input and Output:

[1244] The server takes the choice data as input and generates the initial settings and prompt sentences for the generated AI agent based on it. The output is the generated AI agent with the initial settings completed.

[1245] Specific behavior:

[1246] For the option "Flash Sale - 50% OFF!", the server sets the prompt text "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'" to the generating AI agent.

[1247] Step 3: Generate supporting reasons

[1248] The server commands the generative AI agent to generate supporting reasons for each option. The generative AI model generates text explaining the merits and validity of each option based on the specified prompt. The generated supporting reasons are sent to the server.

[1249] Input and Output:

[1250] The input is the prompt sentence and option data set in Step 2. This is processed by the generative AI model, and the output is a text of the reasons for support.

[1251] Specific behavior:

[1252] In response to the prompt, "Generate 3-5 sentences supporting the following option: 'Flash Sale - 50% OFF!'", the AI ​​model generates text such as "'Flash Sale - 50% OFF!' will increase customer purchasing intent and contribute to immediate sales growth."

[1253] Step 4: Present your reasons for support

[1254] The server sends the generated reasons for support to the user's device, where these reasons are visually displayed, allowing the user to compare and consider the reasons for support for each option.

[1255] Input and Output:

[1256] The input is the text of the support reasons generated by the generative AI model, and the output is the support reasons displayed on the user's device.

[1257] Specific behavior:

[1258] The server transmits the reason for support, such as "'Flash Sale - 50% OFF!' will increase customers' desire to purchase and contribute to an immediate increase in sales," to the user's terminal, which then displays the reason.

[1259] Step 5: Generate and present a counterargument

[1260] The server commands the generative AI agent to generate a counterargument against the other options. This counterargument is generated by the generative AI model and is a text that points out the shortcomings and problems of the other options. The generated counterargument is also sent to the user's device.

[1261] Input and Output:

[1262] The input is a set of alternatives and a corresponding prompt, which is processed by a generative AI model, and the output is a counterargument text.

[1263] Specific behavior:

[1264] The server inputs a prompt such as "Generate a three-sentence counterargument to the following option, 'Limited Time Offer - Buy One, Get One Free'" into the generative AI model, and the generated text, such as "Inventory management will become more difficult" or "Profit margins may decline," is sent to the user's device, where it is displayed.

[1265] Through these steps, users can compare the reasons for and counterarguments of each option and make the best decision.

[1266] (Application example 1)

[1267] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1268] Currently, when users select the optimal product from multiple product options, it is difficult for them to objectively evaluate the advantages and disadvantages of each product. In particular, e-commerce platforms are overwhelmed with a wide variety of product information, making it difficult for users to properly compare and consider this information. Furthermore, the lack of a system that effectively supports the user selection process leads to problems such as incorrect selection and time-consuming selection.

[1269] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1270] In this invention, the server includes a means for presenting options to a user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments for other options, a means for presenting the generated counterarguments to the user, and a means for generating reasons for supporting and counterarguments for different products and displaying them to the user in the product selection process, thereby enabling the user to understand the advantages and disadvantages of each product option and select the optimal option quickly and efficiently.

[1271] "Choice" refers to each item or option that a user considers to select from multiple choices.

[1272] "User" refers to an individual or corporation that makes decisions using this system.

[1273] "Means" refers to the methods or processes used to achieve a particular goal.

[1274] A "generative AI agent" is a program that uses a generative AI model to support specific options and has the ability to generate text about the advantages and disadvantages of each option.

[1275] "Generated reasons for support" refers to text generated by the generating AI agent explaining the benefits or validity of a particular option.

[1276] "Rebuttal" refers to text generated to point out the flaws or problems of an alternative.

[1277] The "product selection process" refers to a series of actions or steps a user takes to select the optimal product from multiple product options.

[1278] "Display means" refers to a method or device that allows a user to visually view information generated by the system.

[1279] This invention provides a system that helps users select the most suitable product from multiple product options. The system's main hardware configuration is a server and a user terminal. The server uses a generation AI agent to generate reasons for and counterarguments for each option and presents them to the user terminal.

[1280] System Operation

[1281] 1. Setting options

[1282] The user device receives as input multiple product options that the user wants to compare, such as product models like "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6."

[1283] 2. Initial setup of the generated AI agent

[1284] The server prepares a generative AI agent for each product option, each of which uses a specific generative AI model.

[1285] 3. Generating reasons for support

[1286] The server sends commands to each generative AI agent to generate reasons in favor of each option. For example, the generative AI model might generate reasons that the iPhone 13 has the latest processor and offers better performance to users.

[1287] 4. Presentation of reasons for support

[1288] The server transmits the generated reasons for support to the user terminal for the user to view, allowing the user to compare the merits of each product option.

[1289] 5. Generating and Presenting Counterarguments

[1290] The server instructs each generative AI agent to generate a counterargument to the other options. For example, the generative AI model generates a counterargument pointing out that a disadvantage of the Samsung Galaxy S21 is its short battery life.

[1291] These counterarguments are also sent to the user's terminal, allowing the user to weigh the drawbacks of each option.

[1292] Specific usage

[1293] For example, if a user wants to use a shopping site to choose the best smartphone, they might enter the following prompt:

[1294] I want to choose the best smartphone.

[1295] My options are the iPhone 13, the Samsung Galaxy S21, and the Google Pixel 6. What are the advantages of each?

[1296] In response, the generating AI agent generates the following reasons for support:

[1297] Reasons for choosing the iPhone 13: The iPhone 13 is equipped with the latest chipset, offering effective battery management and excellent performance, and is highly compatible with other devices thanks to the Apple ecosystem.

[1298] Reasons for choosing the Samsung Galaxy S21: The Samsung Galaxy S21 has a high-resolution display that is ideal for watching videos and playing games. It also has an excellent camera.

[1299] Reasons for choosing the Google Pixel 6: The Google Pixel 6 receives the latest Android updates early and has smooth integration with Google services. Its competitive price makes it a great value for money.

[1300] Software used and data processing

[1301] The server handles the main data processing and runs generative AI models, particularly those using OpenAI GPT-3. The user device is used to input data and display the generated reasons and counterarguments. Data processing and calculations are performed by scripts (e.g., Python scripts) running on the server.

[1302] Users can understand the advantages and disadvantages of each product option based on specific supporting and counterargumentative reasons, and make the best choice. This system makes users' decision-making quick and effective.

[1303] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1304] Step 1:

[1305] The user inputs product options. The user device receives as input the multiple product options the user wants to compare. This input includes specific product names such as "iPhone 13," "Samsung Galaxy S21," and "Google Pixel 6." The server begins processing based on this input.

[1306] Step 2:

[1307] The server presents the options to the user. The server generates a list of products received from the user and sends it to the user's terminal. This allows the user to check the options and obtain information about each option.

[1308] Step 3:

[1309] Prepare the generative AI agents. The server configures a generative AI agent for each product option. Each generative AI agent is configured to utilize a generative AI model (e.g., OpenAI GPT-3) to support a specific product.

[1310] Step 4:

[1311] Generate reasons for support. The server sends each generation AI agent an instruction to generate reasons for support for a specified product. For example, a prompt sentence such as "I want to choose the best smartphone. The options are 'iPhone 13', 'Samsung Galaxy S21', and 'Google Pixel 6'. Please tell me the advantages of each." is input into the generation AI model, which then outputs specific reasons for support. This output is text information about the advantages of each product.

[1312] Step 5:

[1313] The reasons for support are presented to the user. The server sends the generated text of the reasons for support to the user's terminal. The user's terminal displays this, allowing the user to view the reasons for support for each product. Based on this, the user can consider which option is best.

[1314] Step 6:

[1315] Generate counterarguments. The server sends each generation AI agent an instruction to generate counterarguments about other options. For example, the generation AI model receives a prompt such as "What are the disadvantages of the iPhone 13?" and generates a counterargument. This output is text information about the shortcomings and problems of other products.

[1316] Step 7:

[1317] The rebuttals are presented to the user. The server sends the generated rebuttal text to the user's terminal. The user's terminal displays it, allowing the user to view the rebuttal information for each product. Based on this, the user can make the optimal selection, taking into account the drawbacks of each product.

[1318] Step 8:

[1319] The user decides on an option. Based on the presented reasons for and counterarguments, the user selects the most suitable product. Through this process, the user can comprehensively assess the advantages and disadvantages of each product and select the most suitable option.

[1320] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1321] The following describes a specific embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generation AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[1322] The main components of the system are a means for presenting options to the user, a generating AI agent that supports each option, a means for presenting the generated supporting reasons and counterarguments to the user, and an emotion engine that recognizes the user's emotions and adjusts the information accordingly.

[1323] System Operation

[1324] 1. Setting options

[1325] The server receives multiple options from the user's device. These options are set in list format and are provided in a variety of forms depending on individual usage scenarios, such as selecting the wording for a campaign banner or choosing a Mother's Day gift.

[1326] 2. Initial setup of the generated AI agent

[1327] The server prepares generative AI agents according to the number of options received, each designed to support a specific option using a specified generative AI model.

[1328] 3. Generating reasons for support

[1329] For each option, the server sends a command to the generating AI agent to generate reasons in support of each option. The prompt is in the form of "Why is this option better?". Each agent generates text explaining the advantages of that option and sends it to the server.

[1330] 4. Emotional Engine Adjustment

[1331] Before presenting the generated supporting and counterargumentative arguments, the server uses an emotion engine to analyze the user's emotional state. The emotion engine collects real-time emotional data from the user and adjusts the output of each agent based on this data. For example, if the user is feeling stressed, the agent will emphasize more reassuring information.

[1332] 5. Presentation of reasons for support

[1333] The server presents the reasons for supporting each agent, adjusted by the emotion engine, to the user's terminal, where the user can view the reasons for supporting each agent through the terminal.

[1334] 6. Generating and Presenting Counterarguments

[1335] Furthermore, the server commands the AI ​​agent to create counterarguments against other options. These counterarguments point out the shortcomings and problems of the other options, and are used by each agent to make their preferred option appear more favorable. The generated counterarguments are also adjusted by the emotion engine and presented to the user.

[1336] Specific examples

[1337] Example of using the emotion engine: Selecting campaign banner text

[1338] The server sets the following options:

[1339] Option A: "Flash Sale - 50% OFF!"

[1340] Option B: "Limited Time Offer - Buy One, Get One Free"

[1341] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[1342] The server prepares a generating AI agent to support each option and generates reasons for supporting each option. For example,

[1343] Agent A generates a reason for support that "Flash Sale - 50% OFF!" has an immediate customer attraction effect and creates a sense of urgency.

[1344] Agent B generates a reason for supporting "Limited Time Offer - Buy One, Get One Free" as it will increase sales and smooth the process of inventory.

[1345] Agent C generates a supporting reason that "Exclusive Deal - Free Shipping on Orders Over $50" will encourage customers to make purchases and increase their motivation to buy because it reduces shipping costs.

[1346] The generated reasons for support are adjusted by the emotion engine based on the user's emotional state before being presented to the user. For example, if the user shows signs of impatience, Agent A's emphasis on "urgency" is adjusted, and other benefits that provide a sense of security are added.

[1347] Through these steps, users will have more balanced information and be able to make optimal decisions based on their emotional state.

[1348] The processing flow will be explained below.

[1349] Step 1:

[1350] The user inputs options using the terminal. For example, when selecting the banner wording for a campaign, the user inputs options such as "Flash Sale - 50% OFF," "Limited Time Offer - Buy One, Get One Free," and "Exclusive Deal - Free Shipping on Orders Over $50."

[1351] Step 2:

[1352] The server keeps a list of the choices received from the user, so that a generative AI agent can be applied to each choice in the subsequent process.

[1353] Step 3:

[1354] The server prepares generative AI agents according to the number of options. Each agent uses a specified generative AI model (e.g., GPT-3.5-turbo) and configures it to support a specific option.

[1355] Step 4:

[1356] The server sends prompts to each AI agent to generate reasons for each option. The prompts include questions such as "Why is this option better?". Each agent generates text based on the prompts.

[1357] Step 5:

[1358] The server collects and stores the generated reasons for support in order to organize the text output by each agent and use it in the next step.

[1359] Step 6:

[1360] The server invokes an emotion engine to analyze the user's emotional state, determining the user's current emotion based on, for example, facial expression recognition, voice tone analysis, and the content of the text input.

[1361] Step 7:

[1362] Based on the emotional state analyzed by the emotion engine, the server adjusts the generated support reasons. For example, if the user is feeling stressed, the server adds expressions that alleviate the stress, providing a sense of relief.

[1363] Step 8:

[1364] The server sends the support reasons adjusted by the emotion engine to the user's terminal and displays them. The user can view the support reasons for each agent through the terminal.

[1365] Step 9:

[1366] The server again sends commands to the generating AI agents to generate counterarguments against the other options. Each agent generates a counterargument by setting prompts to point out the shortcomings and problems of the other options.

[1367] Step 10:

[1368] The server collects and stores the generated counterarguments. These counterarguments are also analyzed by the emotion engine and adjusted to fit the user's emotional state.

[1369] Step 11:

[1370] The server sends the counterarguments adjusted by the emotion engine to the user's device and displays them. The user can view the counterarguments of each agent through the device.

[1371] Step 12:

[1372] The user compares the reasons for and counterarguments of each agent displayed on the terminal and decides on the option that they feel is most appropriate.

[1373] The above is the specific flow of operation of the system according to the present invention.

[1374] Example 2

[1375] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1376] Conventional decision support systems simply present options to users, and it is difficult to explain why one option is superior or to provide counterarguments to other options. Furthermore, because they provide information without taking into account the user's emotional state, they are unable to provide appropriate support when the user is feeling stressed or impatient. As a result, there is the issue of inadequate support for user decision-making.

[1377] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for presenting options to the user, a generating AI agent supporting each option, a means for the generating AI agent to generate reasons for supporting each option, a means for presenting the generated reasons for supporting each option to the user, a means for generating counterarguments against other options, a means for presenting the generated counterarguments to the user, and an emotion engine that analyzes the user's emotional state and adjusts the reasons for support and counterarguments. This makes it possible to provide the user with the optimal option together with information based on the analysis of the emotional state.

[1378] "Means for presenting options to the user" means the technical elements that display and provide options in a list or other format so that the user can select from multiple options.

[1379] A "generative AI agent" is a software agent designed to generate reasons and counterarguments for a given option using a specific generative AI model.

[1380] The "means for generating supporting reasons" is a function that allows the generating AI agent to generate text that explains the benefits and advantages of an option using a prompt sentence.

[1381] The "means for presenting the generated reasons for supporting each option to the user" refers to a technical element for displaying the generated reasons for supporting on the user's terminal so that the user can view them.

[1382] "Means for generating counterarguments to other options" is a feature that allows the generative AI agent to generate text that points out the counterarguments or flaws of a particular option.

[1383] The "means for presenting the generated rebuttal to the user" refers to the technical elements for displaying the generated rebuttal on the user's terminal so that the user can view it.

[1384] The "emotion engine" is a software component that collects and analyzes real-time user emotion data and adjusts the output of the generative AI agent based on the results.

[1385] The following describes an embodiment of the present invention. The present invention is an interactive system that supports user decision-making, and in particular, for a user who is struggling between multiple options, a generative AI agent that supports each option exchanges opinions and provides information based on the user's emotional state.

[1386] The system includes the following main components:

[1387] 1. A means of presenting options to the user

[1388] 2. Generative AI agent supporting each option

[1389] 3. A method for presenting the generated support reasons to the user

[1390] 4. A means of generating counterarguments to alternatives

[1391] 5. A means for presenting generated rebuttals to the user

[1392] 6. Emotion engine that analyzes the user's emotional state and adjusts information accordingly

[1393] System configuration

[1394] Presenting options

[1395] The server receives multiple options from the user's device and sets these options in a list format. The options are provided in a format that corresponds to a specific usage scenario, such as selecting the wording for a campaign banner or choosing a gift for Mother's Day.

[1396] Initial settings for generated AI agents

[1397] The server prepares generative AI agents according to the number of options received, with each agent designed to support a specific option using a generative AI model such as GPT-3 or ChatGPT.

[1398] Generating reasons for and counterarguments

[1399] Each agent uses a specified generative AI model to generate reasons for each option. The prompt is in the form of a question such as "Why is this option better?", for example, "Please explain why 'Flash Sale - 50% OFF!' is better."

[1400] Emotional engine regulation

[1401] The server analyzes the user's emotional state using an emotion engine before presenting the generated supporting and counterargumentative reasons. The emotion engine collects the user's emotional data in real time and adjusts the output of each agent based on this data, for example, by emphasizing reassuring information if the user is feeling stressed.

[1402] Presenting reasons for support and counterarguments

[1403] The server then presents the adjusted reasons for and counterarguments to the user's terminal. The user can then view the information provided by each agent through their terminal and use it as a reference for making the best choice.

[1404] Specific examples

[1405] Choosing campaign banner text using an emotion engine

[1406] As a concrete example, consider a scenario where you are selecting the banner text for a campaign. The server sets the following options:

[1407] Option A: "Flash Sale - 50% OFF!"

[1408] Option B: "Limited Time Offer - Buy One, Get One Free"

[1409] Option C: "Exclusive Deal - Free Shipping on Orders Over $50"

[1410] The server initializes a generating AI agent that supports each option. The agent generates reasons for supporting each option. An example prompt is:

[1411] To Agent A, "Explain why 'Flash Sale - 50% OFF!' is a great offer."

[1412] To Agent B, "Explain why 'Limited Time Offer - Buy One, Get One Free' is a great option."

[1413] To Agent C, "Please explain why 'Exclusive Deal - Free Shipping on Orders Over $50' is a great offer."

[1414] Each generative AI agent generates a reason for support, and the emotion engine adjusts the output based on the user's emotional state. The server then presents the adjusted information to the user's device, allowing the user to choose the optimal option.

[1415] In this way, users can make better decisions based on balanced information that takes into account their emotional state.

[1416] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1417] Step 1: Receive your choices

[1418] The server receives multiple options from the user via the terminal.

[1419] Specifically, the user inputs a list of options into the device, for example, the following campaign banner text:

[1420] "Flash Sale - 50% OFF!"

[1421] "Limited Time Offer - Buy One, Get One Free"

[1422] "Exclusive Deal - Free Shipping on Orders Over $50"

[1423] Input: A list of choices the user has entered into the device

[1424] Output: List of options received by the server

[1425] Step 2: Initializing the generated AI agent

[1426] The server prepares generative AI agents according to the number of options received, assigning each agent to a different option and configuring them using a generative AI model (e.g., GPT-3 or ChatGPT).

[1427] Specifically, the server generates three generation AI agents and assigns them to options A, B, and C, respectively.

[1428] Input: list of options

[1429] Output: A set of generated AI agents with initial settings

[1430] Step 3: Generate supporting reasons

[1431] The server issues a command to each generating AI agent to generate supporting reasons, using a prompt phrase to ask "Why is this choice better?"

[1432] Specifically, for example, Agent A is prompted with "Please explain why 'Flash Sale - 50% OFF!' is a good product." The generating AI agent generates supporting reasons based on this prompt and sends them to the server.

[1433] Input: prompt, initialised generated AI agents

[1434] Output: Text data of reasons for supporting each option

[1435] Step 4: Emotional Engine Adjustment

[1436] The server analyzes the user's emotional state using an emotion engine before presenting the generated support reasons and counterarguments. The emotion engine collects the user's emotional data in real time and adjusts the support reasons and counterarguments.

[1437] Specifically, the device uses a camera and microphone to analyze the user's facial expressions and voice, and sends the emotional data to the server. The server then uses this data to adjust the output of the generated AI agent. For example, if the user is feeling stressed, it adds information that emphasizes a sense of security to the output.

[1438] Input: Text data of generated support reasons, user emotion data

[1439] Output: Text data of adjusted support and counterarguments

[1440] Step 5: Present your reasons for support

[1441] The server presents the adjusted reasons for support to the user's terminal, and the user can view the reasons for support provided by each agent through the terminal.

[1442] Specifically, the server sends the adjusted reasons for support to the terminal, and the terminal displays them on the screen, for example, displaying the benefits of "Flash Sale - 50% OFF!", such as the immediate customer attraction effect.

[1443] Input: Text data of adjusted reasons for support

[1444] Output: The reason for support displayed on the user's terminal

[1445] Step 6: Generate and present a counterargument

[1446] The server commands the generator AI agent to create counterarguments against the other options, which point out the shortcomings and problems of the other options.

[1447] Specifically, the server generates a counterargument for Agent A explaining why 'Limited Time Offer - Buy One, Get One Free' is inferior. This information is also adjusted by the emotion engine and then presented to the user.

[1448] Input: Rebuttal prompt, emotion data

[1449] Output: Text data of the adjusted rebuttal, and the rebuttal displayed on the user's device

[1450] This system allows users to make better decisions by receiving information that corresponds to their emotional state.

[1451] (Application example 2)

[1452] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1453] Conventional decision support systems do not take into account the user's emotional state when selecting the optimal option from multiple options, resulting in insufficient support for the user. Furthermore, the generated reasons and counterarguments are not adjusted to reflect the user's emotions, making it difficult for the user to make a decision with confidence. To solve these problems, a system that provides information based on the user's emotional state and supports more appropriate decision-making is needed.

[1454] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for presenting options to the user, a generating AI agent that supports each option and the generating AI agent generates reasons for supporting each option, means for presenting the generated reasons for supporting each option to the user, means for generating counterarguments against other options, means for presenting the generated counterarguments to the user, and means including an emotion engine that recognizes the user's emotional state and adjusts information. This makes it possible to provide information according to the user's emotional state, allowing the user to make the optimal choice with greater confidence.

[1455] A "means for presenting options to a user" is a system or method that clearly displays and presents to a user multiple options that the user is considering.

[1456] A "generative AI agent" is an entity or software that uses artificial intelligence techniques to generate reasons in support of a particular choice.

[1457] A "means for generating reasons for support" is a system or method that uses a generative AI agent to automatically generate reasons for support in order to present the advantages and merits of options to a user.

[1458] "Means for presenting the generated reasons for supporting each option to the user" refers to a system or method that displays and presents the reasons for supporting each option generated by the generating AI agent in an easy-to-understand manner to the user.

[1459] A "means for generating arguments against alternatives" is a system or method for generating arguments that point out the shortcomings or problems of alternatives in order to support a particular alternative.

[1460] "Means for presenting generated counterarguments to the user" refers to a system or method for displaying and presenting the counterarguments generated by the generating AI agent in an easy-to-understand manner to the user.

[1461] An "emotion engine" is software or a system for recognizing a user's emotional state in real time and adjusting information based on this data.

[1462] "User's emotional state" refers to the user's current mental and emotional state, including, for example, feelings such as stress, joy, relief, etc.

[1463] This invention is an interactive system that supports decision-making by providing reasons for and counterarguments to options while taking into account the user's emotional state. The system consists of a user terminal and a server that includes an emotion engine and a generative AI agent.

[1464] First, a user inputs multiple options using a terminal. For example, imagine a situation where a user must choose from multiple products on an online shopping website. These options are sent to the server, and the system prepares a generative AI agent that supports each option. The generative AI agent uses a generative AI model to generate reasons for supporting each option.

[1465] The server uses an emotion engine to generate support reasons before presenting them to the user's device. The emotion engine collects real-time emotional data from the user and adjusts the generated support reasons based on this data. For example, if the user is feeling stressed, it will emphasize reassuring information in the support reasons. Counterarguments against other options are also generated by the generative AI agent, adjusted by the emotion engine, and presented to the user.

[1466] As a concrete example, consider a situation where a user has to choose between the following options:

[1467] Option A: Premium earphones that offer high-quality sound

[1468] Option B: The best value wireless earphones

[1469] Option C: Waterproof sports earphones

[1470] In this case, an example prompt would be:

[1471] "Help the user choose from the following options:

[1472] Product A: High-quality earphones that provide high-quality sound

[1473] Product B: The best value wireless earphones

[1474] Product C: Highly waterproof sports earphones

[1475] Tell users which option they should choose, why that option is better, and why based on their emotional state.”

[1476] The generated reasons and counterarguments are then adjusted by the emotion engine and optimized to provide the user with a sense of security and satisfaction, allowing the user to receive information tailored to their emotional state and make better decisions.

[1477] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1478] Step 1:

[1479] The server receives multiple options from the user's device. In this step, the user inputs their options via their device, which are then sent to the server in list form. For example, suppose the user submits the following options: "High-end earphones that provide high-quality sound," "Wireless earphones with the best value for money," and "Waterproof sports earphones." The input option list arrives at the server and is saved in its original format.

[1480] Step 2:

[1481] The server prepares generative AI agents according to the number of options received. Each agent generates reasons for supporting a particular option. In this step, the server invokes the generative AI model and configures an agent for each option. For example, Agent A is configured to support "high-quality earphones that provide high-quality sound," and Agent B is configured to support "wireless earphones with the best cost performance."

[1482] Step 3:

[1483] The server sends a command to the generative AI agent to generate reasons for each option, including a prompt such as, "Why is this option superior?" The prompt is input to the generative AI model, which outputs reasons for support. For example, the prompt for Agent A might be, "Why are high-end earphones that provide high-quality sound superior?", and the output would be a reason such as, "The sound quality is very clear and provides a superior hearing experience compared to other products."

[1484] Step 4:

[1485] The server passes the generated support reasons to the emotion engine, which adjusts them based on the user's emotional state. In this step, the emotion engine analyzes the user's emotional data in real time and adjusts the support reasons based on that data. For example, if the user is feeling stressed, the emotion engine adjusts the support reasons to emphasize a sense of relief.

[1486] Step 5:

[1487] The server then presents the support reasons for each agent, adjusted by the emotion engine, to the user's device. In this step, the adjusted support reasons are sent to the device and displayed to the user. For example, the support reason for "luxury earphones that provide high-quality sound" is presented as "The sound quality is very clear and provides a superior hearing experience compared to other products. Don't worry, we guarantee that it is the best choice."

[1488] Step 6:

[1489] The server generates counterarguments to the other options, which are similarly adjusted by the emotion engine and then presented to the user. In this step, the generation AI agent generates a counterargument, with a prompt that includes, "Why are the other options inferior?" For example, a counterargument from Agent A might be, "The best value-for-money earphones are inferior to high-end earphones in terms of sound quality." The counterargument, adjusted by the emotion engine, is then presented to the user.

[1490] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1491] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1492] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1493] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1494] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1495] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1496] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1497] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1498] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1499] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1500] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1501] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1502] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1503] 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.

[1504] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1505] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1506] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1507] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1508] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1509] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1510] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1511] The following is further disclosed regarding the above embodiment.

[1512] (Claim 1)

[1513] means for presenting options to a user;

[1514] a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option;

[1515] means for presenting to the user reasons for supporting each of the generated options;

[1516] a means of generating counterarguments to alternatives;

[1517] means for presenting the generated rebuttal to a user;

[1518] A system including:

[1519] (Claim 2)

[1520] The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

[1521] (Claim 3)

[1522] 2. The system of claim 1, wherein each generating AI agent is also capable of simultaneously generating counterarguments for each option.

[1523] "Example 1"

[1524] (Claim 1)

[1525] means for presenting options to a user;

[1526] a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option;

[1527] means for presenting to the user reasons for supporting each of the generated options;

[1528] a means of generating counterarguments to alternatives;

[1529] means for presenting the generated rebuttal to a user;

[1530] a means for generating supporting reasons for each option based on the prompt sentence using a generative AI model;

[1531] A system including:

[1532] (Claim 2)

[1533] The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

[1534] (Claim 3)

[1535] 2. The system of claim 1, wherein each generating AI agent is also capable of simultaneously generating counterarguments for each option.

[1536] "Application Example 1"

[1537] (Claim 1)

[1538] means for presenting options to a user;

[1539] a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option;

[1540] means for presenting to the user reasons for supporting each of the generated options;

[1541] a means of generating counterarguments to alternatives;

[1542] means for presenting the generated rebuttal to a user;

[1543] means for generating reasons for and counterarguments about different products and displaying them to the user during the product selection process;

[1544] A system including:

[1545] (Claim 2)

[1546] The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

[1547] (Claim 3)

[1548] 2. The system of claim 1, wherein each generating AI agent is also capable of simultaneously generating counterarguments for each option.

[1549] "Example 2: Combining Emotion Engines"

[1550] (Claim 1)

[1551] means for presenting options to a user;

[1552] a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option;

[1553] means for presenting to the user reasons for supporting each of the generated options;

[1554] a means of generating counterarguments to alternatives;

[1555] means for presenting the generated rebuttal to a user;

[1556] means including an emotion engine for analyzing the user's emotional state to adjust the reasons for and counterarguments;

[1557] A system including:

[1558] (Claim 2)

[1559] The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

[1560] (Claim 3)

[1561] 2. The system of claim 1, wherein each generating AI agent is also capable of simultaneously generating counterarguments for each option.

[1562] "Application example 2 when combining emotion engines"

[1563] (Claim 1)

[1564] means for presenting options to a user;

[1565] a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option;

[1566] means for presenting to the user reasons for supporting each of the generated options;

[1567] a means of generating counterarguments to alternatives;

[1568] means for presenting the generated rebuttal to a user;

[1569] means including an emotion engine for recognizing an emotional state of a user and adjusting the information;

[1570] A system including:

[1571] (Claim 2)

[1572] The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

[1573] (Claim 3)

[1574] 2. The system of claim 1, wherein each generating AI agent can simultaneously generate counterarguments for each option, and the generated supporting reasons and counterarguments are adjusted by an emotion engine. [Explanation of symbols]

[1575] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for presenting options to a user; a generating AI agent supporting each option, and means for the generating AI agent to generate reasons for supporting each option; means for presenting to the user reasons for supporting each of the generated options; a means of generating counterarguments to alternatives; means for presenting the generated rebuttal to a user; A system including:

2. The system according to claim 1, wherein the user can select the most suitable option based on the presented supporting reasons and counterarguments.

3. 2. The system of claim 1, wherein each generating AI agent is also capable of simultaneously generating counterarguments for each option.

Images