Information processing device, method, program and system

Abstract

An object of the present disclosure is to enable the level of skills to be properly evaluated even when the skills required differ from organization to organization. [Solution] A program that causes a processor to execute the following steps: inputting a first prompt including an instruction to converse with a member of an organization into a generation AI; inputting a statement by the member into the generation AI and having the generation AI output a response to the statement; presenting the response to the member; storing the content of the conversation including the statement and the response; inputting a second prompt including the content of the conversation and an instruction to output, based on the content of the conversation, core skills related to the member's mindset that is valued in the organization and parameter values ​​that represent the member's proficiency in those core skills, into the generation AI, and having the generation AI output the member's core skills and parameter values ​​based on the content of the conversation; and presenting the output core skills and parameter values.

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, a method, a program, and a system. [Background technology]

[0002] In Patent Document 1, conversational AI processing is provided to a user terminal used by the user, allowing the user to interact with AI in a dialogue format, and conversation data regarding the user's work report is obtained through a conversation regarding the work report using the conversational AI processing.Based on the conversation data, a personality analysis is performed, including at least one of a personality aptitude diagnosis, a character diagnosis, and an emotional intelligence (EQ) diagnosis.

[0003] [Patent Document 1] Patent No. 7649586 Summary of the Invention [Problem to be solved by the invention]

[0004] The skills to be evaluated vary from organization to organization, and the level of evaluation may also depend on the evaluator. It is important for an organization to fairly evaluate its members. Note that the technology in Patent Document 1 does not determine the skills and levels of members.

[0005] The purpose of this disclosure is to properly evaluate the level of skills required, even if the skills required differ from organization to organization. [Means for solving the problem]

[0006] A program for operating a computer having a processor and a memory, the program causing the processor to execute the following steps: inputting a first prompt including an instruction to converse with a member of an organization to a generation AI; inputting a statement by the member to the generation AI and having the generation AI output a response to the statement; presenting the response to the member; storing the content of the conversation including the statement and the response; inputting a second prompt including the content of the conversation and an instruction to output, based on the content of the conversation, core skills related to the member's mindset that is emphasized in the organization and parameter values ​​that represent the member's proficiency in those core skills, to the generation AI, and having the generation AI output the member's core skills and parameter values ​​based on the content of the conversation; and presenting the output core skills and parameter values. [Effects of the Invention]

[0007] According to the present disclosure, even if the skills required differ from organization to organization, the level can be properly evaluated. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing the overall configuration of a system 1. FIG. [Figure 2] 2 is a block diagram showing an example of the functional configuration of a terminal device 10. FIG. [Figure 3] 2 is a block diagram showing an example of the functional configuration of a server 20. FIG. [Figure 4] FIG. 2 is a diagram illustrating a data structure of a table. [Figure 5] FIG. 2 is a diagram illustrating a data structure of a table. [Figure 6] FIG. 2 is a diagram illustrating a data structure of a table. [Figure 7] FIG. 2 is a diagram illustrating a data structure of a table. [Figure 8] FIG. 2 is a diagram illustrating an example of the flow of operations in the system 1. [Figure 9] FIG. 2 is a diagram illustrating an example of the flow of operations in the system 1. [Figure 10]FIG. 10 is a diagram illustrating an example screen of the present disclosure. [Figure 11] FIG. 10 is a diagram illustrating an example screen of the present disclosure. [Figure 12] FIG. 9 is a block diagram showing the basic hardware configuration of a computer 90. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. In all drawings describing the embodiments, common components are designated by the same reference numerals, and repeated description will be omitted. Note that the following embodiments do not unduly limit the content of the present disclosure described in the claims. Furthermore, not all components shown in the embodiments are necessarily essential components of the present disclosure. Furthermore, each drawing is a schematic diagram and is not necessarily a precise illustration.

[0010] In the following description, a "processor" refers to one or more processors. The at least one processor is typically a microprocessor such as a CPU (Central Processing Unit), but may also be another type of processor such as a GPU (Graphics Processing Unit). The at least one processor may be single-core or multi-core.

[0011] Furthermore, the at least one processor may be a processor in the broad sense, such as a hardware circuit (for example, a field-programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) that performs part or all of the processing.

[0012] In the following explanation, information that produces an output for an input may be described using expressions such as "xxx table," but this information may be data of any structure, or may be a learning model such as a neural network that produces an output for an input. Therefore, an "xxx table" may be referred to as "xxx information."

[0013] Furthermore, in the following description, the configuration of each table is an example, and one table may be divided into two or more tables, or all or part of two or more tables may be one table.

[0014] In addition, in the following explanation, processing may be described using the "program" as the subject, but since a program is executed by a processor to perform specified processing while appropriately using a memory unit and / or an interface unit, etc., the subject of the processing may also be the processor (or a device such as a controller that has that processor).

[0015] The program may be installed in a device such as a computer, or may be stored in, for example, a program distribution server or a computer-readable (e.g., non-transitory) recording medium. Also, in the following description, two or more programs may be realized as one program, or one program may be realized as two or more programs.

[0016] Furthermore, in the following description, identification numbers are used as identification information for various objects, but other types of identification information (for example, identifiers including alphabetic characters or symbols) may also be used.

[0017] In addition, in the following description, when describing elements of the same type without distinguishing between them, reference symbols (or common symbols among the reference symbols) may be used, and when describing elements of the same type with distinction between them, the identification numbers (or reference symbols) of the elements may be used.

[0018] In the following description, the control lines and information lines are those that are considered necessary for the description, and do not necessarily represent all the control lines and information lines in the product. All components may be interconnected.

[0019] Each information processing device is configured by a computer equipped with an arithmetic unit and a storage device. The basic hardware configuration of the computer and the basic functional configuration of the computer realized by the hardware configuration will be described later. For each of the server 20 and the terminal device 10, descriptions that overlap with the basic hardware configuration and basic functional configuration of the computer will be omitted.

[0020] <Summary> The system according to this embodiment determines the skills and levels of organizational members from conversations between the members and an AI avatar. The skills determined in this embodiment are core skills related to mindsets that are emphasized in the organization. In this embodiment, core skills are, for example, unique skills that are uniquely evaluated within the organization. In this embodiment, the level of a core skill is expressed, for example, by a parameter that indicates the degree of skill proficiency. The level of a core skill is expressed, for example, by a number, a letter, a symbol, or the like. Core skills and their levels can be taken into consideration in personnel decisions such as promotion, salary increase, hiring, training, and performance evaluation.

[0021] The system according to this embodiment can be applied to various situations, such as interviews with members within an organization (work reports, career interviews, promotion interviews). In this embodiment, an example of one conversation is one daily work report, but actual conversations are not limited to this. In addition, this embodiment takes an example of an interview format in which a member converses with a generative AI model via an avatar, but the conversation may also be in the form of a chat, for example. The avatar is, for example, an interface with a human appearance and voice that can interact with members based on output data from the generative AI model. The avatar is, for example, an icon of the appearance of a workplace colleague / manager / superior, or a career counselor.

[0022] In this embodiment, an example of an organization is a company, but the organization assumed in this embodiment is not limited to a company. In this embodiment, an example of a member is an employee, but the member assumed in this embodiment is not limited to an employee.

[0023] <1. Overall system configuration> Fig. 1 is a block diagram showing an example of the overall configuration of system 1. As shown in Fig. 1, system 1 includes, for example, a terminal device 10, a server 20, and a generation AI system 30. The terminal device 10, the server 20, and the generation AI system 30 are communicatively connected via, for example, a network 80.

[0024] 1 shows an example in which the system 1 includes two terminal devices 10, but the number of terminal devices 10 included in the system 1 is not limited to two. The number of terminal devices 10 included in the system 1 may be one, or three or more.

[0025] Although FIG. 1 shows an example in which system 1 includes one generative AI system 30, the number of generative AI systems 30 included in system 1 is not limited to one. System 1 may include two or more generative AI systems 30. Also, while FIG. 1 shows an example in which generative AI system 30 is independent from server 20, server 20 may include the functions of generative AI system 30. In other words, server 20 may store a generative AI.

[0026] In this embodiment, a collection of multiple devices may be considered as one server. The allocation of multiple functions required to realize the server 20 according to this embodiment to one or more pieces of hardware can be determined appropriately in consideration of the processing capacity of each piece of hardware and / or the specifications required for the server 20.

[0027] The terminal device 10 is an information processing device used by a user who uses the personnel services provided by the server 20, i.e., an employee (member of the organization) of the company. In addition, the employee's superiors, personnel department staff, and external career counselors also use separate terminal devices 10. The terminal device 10 provides the applicant with a user interface for conducting dialogue with the generation AI provided by the generation AI system 30. The terminal device 10 is realized, for example, by a stationary PC (Personal Computer), a laptop PC, a head-mounted display, or the like. The terminal device 10 may also be a portable computer such as a smartphone or a tablet terminal.

[0028] The terminal device 10 includes a communication IF (Interface) 12, an input device 13, an output device 14, a memory 15, a storage 16, and a processor 19. The communication IF 12 is an interface for inputting and outputting signals so that the terminal device 10 can communicate with devices in the system 1, such as the server 20. The input device 13 is a device for receiving input operations from a user (e.g., a touch panel, a touchpad, a pointing device such as a mouse, a keyboard, etc.). The output device 14 is a device for presenting information to a user (e.g., a display, a speaker, etc.). The memory 15 is for temporarily storing programs and data processed by the programs, etc., and is a volatile memory such as a DRAM (Dynamic Random Access Memory). The storage 16 is for saving data, and is, for example, a flash memory or an HDD (Hard Disc Drive). The processor 19 is hardware for executing an instruction set written in a program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0029] The server 20 is an information processing device used by a business that provides personnel services according to this embodiment. The server 20 is an information processing device implemented by a computer connected to a network 80, for example.

[0030] The server 20 includes a communication IF 22, an input / output IF 23, a memory 25, a storage 26, and a processor 29. The communication IF 22 is an interface for inputting and outputting signals so that the server 20 can communicate with devices in the system 1, such as the terminal device 10. The input / output IF 23 functions as an interface with an input device for receiving input operations from a user and an output device for outputting information to the user. The memory 25 is for temporarily storing programs and data processed by the programs, etc., and is a volatile memory such as a DRAM. The storage 26 is for saving data, and is a flash memory or HDD, for example. The processor 29 is hardware for executing an instruction set written in a program, and is composed of an arithmetic unit, registers, peripheral circuits, etc.

[0031] Each information processing device is configured by a computer equipped with an arithmetic unit and a storage device. The basic hardware configuration of the computer and the basic functional configuration of the computer realized by the hardware configuration will be described later. For each of the terminal device 10 and the server 20, descriptions that overlap with the basic hardware configuration and basic functional configuration of the computer will be omitted.

[0032] The generative AI system 30 is, for example, a system in which generative AI (generative artificial intelligence) is constructed. The generative AI system 30 is, for example, a system for determining the core skills and level of employees based on the content of a conversation. The generative AI system 30 also functions as a system for realizing conversations between employees and the generative AI. In other words, the AI ​​system 30 also plays a role in generating the speech content of an AI avatar, such as making comments to employees and responding to comments made by employees.

[0033] The generative AI built in the generative AI system 30 is, for example, a large-scale language model (LLM). A large-scale language model is a natural language model designed to perform multiple tasks in natural language processing. A large-scale language model is an example of a trained model, trained using a large number of parameters (e.g., billions to hundreds of billions) and high-level computing resources. A natural language model refers to a computer program or algorithm designed to perform natural language processing tasks. For example, natural language processing involves processes such as morphological analysis, syntactic analysis, information extraction, and sentence generation, allowing a computer to analyze language used by humans (i.e., natural language) and perform predetermined processing. A large-scale language model receives a prompt (command sentence) and generates an output based on the prompt's text, image, etc. The prompt can be specified in natural language.

[0034] Examples of large-scale language models include the GPT series (Generative Pre-trained Transformer) developed by OPEN AI, BERT (Bidirectional Encoder Representations from Transformers) developed by Google, StableLM developed by StableAI, and Llama2, Palm2 (registered trademark), and LamDA2 (registered trademark) developed by Meta. Large-scale language models tend to have high training costs because they are trained using a very large number of parameters and computational resources. In this embodiment, training costs are reduced by using a trained model that is publicly available through the generative AI system 30. In this embodiment, for example, a definition is passed to GPT, which is then allowed to understand the context and generate information.

[0035] A prompt is primarily a query (including text, character strings, images, videos, audio, etc.) input to a generation AI. By inputting a prompt to the generation AI, the user of the generation AI can instruct the generation AI on information processing. The user can input a prompt to the generation AI so that the generation AI will output the desired output result. Note that a prompt does not have to be a character string, but can also be an image, video, audio, etc. For example, a user's gestures, audio instructions, etc. can also be a prompt.

[0036] Prompts can be input by inputting data into a user's terminal. Document files, images, videos, audio, etc. can also be uploaded and input as prompts. A user can create a prompt by combining an instruction entered into the user terminal with other instructions, data, etc. In this case, the prompt may include one or more instructions, data, etc. A prompt may also include only one or more instructions or one or more data. A prompt can be created by including a portion of a predetermined instruction, data, etc. with another instruction, data, etc. A prompt can be created by inserting a portion of a predetermined instruction, data, etc. with another instruction, data, etc. A prompt can be created by combining a predetermined instruction, data, etc. with another instruction, data, etc. A prompt can be created by adding a predetermined instruction, data, etc. to another instruction, data, etc.

[0037] In this disclosure, expressions such as "include," "insert," "combine," "combine," and "append," which are used when creating a prompt from a predetermined instruction, data, etc., are used as terms that refer to the same information processing process. In other words, these can be treated as the same information processing process in that the same prompt is created based on one or more instruction, data, etc. For example, the term "include" includes information processing such as "insert," "combine," "combine," and "append." Similarly, "insert," "combine," "combine," and "append" also include information processing such as "include," "insert," "combine," "combine," and "append," respectively.

[0038] <2. Terminal device configuration> Fig. 2 is a block diagram showing an example of the functional configuration of the terminal device 10. As shown in Fig. 2, the terminal device 10 includes a communication unit 120, an input device 13, an output device 14, an audio processing unit 17, a microphone 171, a speaker 172, a camera 160, a position information sensor 150, a storage unit 180, and a control unit 190. The blocks included in the terminal device 10 are electrically connected by, for example, a bus or the like.

[0039] The communication unit 120 performs processing such as modulation and demodulation for the terminal device 10 to communicate with other devices. The communication unit 120 performs transmission processing on the signal generated by the control unit 190 and transmits it to the outside (for example, the server 20). The communication unit 120 performs reception processing on the signal received from the outside and outputs it to the control unit 190.

[0040] The input device 13 is a device for inputting instructions or information by a user operating the terminal device 10. The input device 13 is realized, for example, by a touch-sensitive device 131 or the like, which inputs instructions by touching an operation surface. When the terminal device 10 is a PC or the like, the input device 13 may be realized by a reader, keyboard, mouse, or the like. The input device 13 converts instructions input by the user into electrical signals and outputs the electrical signals to the control unit 190. The input device 13 may include, for example, a receiving port that receives electrical signals input from an external input device.

[0041] The output device 14 is a device for presenting information to a user operating the terminal device 10. The output device 14 is realized, for example, by a display 141 or the like. The display 141 displays data according to the control of the control unit 190. The display 141 is realized, for example, by an LCD (Liquid Crystal Display) or an organic EL (Electro-Luminescence) display or the like.

[0042] The audio processing unit 17 performs, for example, digital-to-analog conversion processing of an audio signal. The audio processing unit 17 converts a signal provided from the microphone 171 into a digital signal and provides the converted signal to the control unit 190. The audio processing unit 17 also provides the audio signal to the speaker 172. The audio processing unit 17 is realized, for example, by a processor for audio processing. The microphone 171 receives audio input and provides an audio signal corresponding to the audio input to the audio processing unit 17. The speaker 172 converts the audio signal provided from the audio processing unit 17 into audio and outputs the audio to the outside of the terminal device 10.

[0043] The camera 160 is a device that receives light with a light receiving element and outputs the light as an image capturing signal.

[0044] The position information sensor 150 is a sensor that detects the position of the terminal device 10, and is, for example, a GPS (Global Positioning System) module. The GPS module is a receiving device used in a satellite positioning system. In the satellite positioning system, signals are received from at least three or four satellites, and the current position of the terminal device 10 equipped with the GPS module is detected based on the received signals. The position information sensor 150 may detect the current position of the terminal device 10 from the position of the wireless base station to which the terminal device 10 is connected.

[0045] The storage unit 180 is realized by, for example, the memory 15, the storage 16, etc., and stores data and programs used by the terminal device 10. The storage unit 180 stores, for example, user information 181.

[0046] The user information 181 includes, for example, information about the user who uses the terminal device 10. The information about the user includes, for example, the user's name, age, address, date of birth, contact information, and the like.

[0047] The control unit 190 is realized by the processor 19 reading a program stored in the storage unit 180 and executing instructions included in the program. The control unit 190 controls the operation of the terminal device 10. The control unit 190 functions as an operation reception unit 191, a transmission / reception unit 192, and a presentation control unit 193 by operating in accordance with the program.

[0048] The operation reception unit 191 performs processing for receiving instructions or information input from the input device 13. Specifically, for example, the operation reception unit 191 receives instructions or information input from the touch-sensitive device 131 or the like.

[0049] Furthermore, the operation reception unit 191 receives voice instructions input from the microphone 171. Specifically, for example, the operation reception unit 191 receives a voice signal that is input from the microphone 171 and converted into a digital signal by the voice processing unit 17. For example, the operation reception unit 191 analyzes the received voice signal and extracts a predetermined noun, thereby acquiring an instruction from the user.

[0050] The transmitting / receiving unit 192 performs processing for the terminal device 10 to transmit and receive data to and from an external device such as the server 20 in accordance with a communication protocol. Specifically, for example, the transmitting / receiving unit 192 transmits information input by a user or instructions from a user to the server 20. In addition, the transmitting / receiving unit 192 receives information provided by the server 20.

[0051] The presentation control unit 193 controls the output device 14 to present information provided from the server 20 to the user. Specifically, for example, the presentation control unit 193 causes the information transmitted from the server 20 to be displayed on the display 141. As an example, the presentation control unit 193 causes an AI avatar to be displayed on the browser of the terminal device 10. In addition, the presentation control unit 193 causes the information transmitted from the server 20 to be output from the speaker 172.

[0052] <3. Functional configuration of the server> 3 is a diagram showing an example of the functional configuration of the server 20. As shown in FIG.

[0053] The communication unit 201 performs processing for the server 20 to communicate with external devices.

[0054] The storage unit 202 includes, for example, an employee table 2021, a conversation table 2022, a skill management table 2023, a training table 2024, etc. The tables stored in the storage unit 202 are not limited to these.

[0055] The employee table 2021 is a table that stores information related to employees.

[0056] The conversation table 2022 is a table that stores information related to conversations between employees and the generation AI.

[0057] The skill management table 2023 is a table that stores information related to the core skills of employees.

[0058] The training table 2024 is a table that stores information related to training.

[0059] The control unit 203 functions as a module that controls all processes related to personnel services by operating according to a program. Specifically, the control unit 203, for example, causes the generative AI system 30 to determine the core skills and levels of employees. Also, specifically, the control unit 203 controls the generative AI system 30 to learn about core skills.

[0060] The control unit 203 controls, for example, a conversation between the generation AI and an employee. The control unit 203 controls, for example, the speech and actions of an avatar displayed on the display 141 via the presentation control unit 193. The speech and actions of the avatar are directly controlled by the presentation control unit 193.

[0061] The control unit 203 is realized by the processor 29 reading a program stored in the storage unit 202 and executing instructions included in the program. The program includes an application such as a web browser application. The program includes a programming language such as JavaScript (registered trademark) that is executed on a web browser application stored in the terminal device 10. In the process of executing the program, the control unit 203 may realize the functions according to this embodiment by linking with an external system or service using an API (Application Programming Interface) as necessary. That is, the control unit 203 may, for example, call a program stored in an external system using the API.

[0062] <4. Data Structure> The data structure of the tables stored in the server 20 will be described. Note that the data structure described is an example and does not exclude data that is not described. Furthermore, even data that is described in the same table may be stored in separate storage areas in the storage unit 202. Each table may have columns other than the columns described in that table. Each table may not have any of the columns described in that table.

[0063] Fig. 4 is a diagram showing the data structure of the employee table 2021. As shown in Fig. 4, the employee table 2021 has columns such as name, date of birth, email address, department, rank, and position, with the employee ID as a key, for example.

[0064] Employee ID is a column that stores an identifier to uniquely identify an employee.

[0065] Name is a column that stores the name of the employee.

[0066] Date of Birth is a column that stores the employee's date of birth.

[0067] The email address is a column that stores the email address of the terminal device 10 that the employee has.

[0068] The affiliation is a column that stores the organization to which the employee belongs. The affiliation is composed of, for example, a company, a base, a department, etc.

[0069] The position is a column that stores the employee's grade and position. Examples of grade and position include person in charge, chief, section chief, department manager, and executive.

[0070] Fig. 5 is a diagram showing the data structure of the conversation table 2022. As shown in Fig. 5, the conversation table 2022 has columns such as date and time, conversation content, etc., with an employee ID as a key. An example of one conversation is one daily business report.

[0071] Employee ID is a column that stores the employee ID (same as Figure 4) of the employee who conversed with the generation AI.

[0072] The conversation ID is a column that stores an identifier for uniquely identifying each conversation session. The control unit 203 assigns one conversation ID to each conversation session.

[0073] The date and time is a column that stores the date and time when the conversation took place.

[0074] The conversation content is a column that stores the content of the conversation between the employee and the generation AI. The conversation content, for example, stores the employee's statements and the generation AI's responses alternately as text, following the flow of the actual conversation. Each statement and response may be timestamped with the time at which the statement and response were made. The conversation content may store, for example, the audio of the conversation, the video of the conversation, or both.

[0075] Fig. 6 is a diagram showing the data structure of the skill management table 2023. As shown in Fig. 6, the skill management table 2023 has columns such as a core skill ID, a core skill name, a level, and an update date and time, with an employee ID as a key, for example.

[0076] The employee ID is a column that stores the employee ID (same as in Figure 4) of the employee whose core skills have been judged.

[0077] The core skill ID is a column that stores an identifier for uniquely identifying the determined core skill.

[0078] The core skill name is a column that stores the name of the determined core skill. In this embodiment, core skills include, for example, the "ability to involve" to motivate others and create collaboration, the "ability to create" to explore new values ​​and ideas without being bound by existing frameworks, and the "ability to accomplish" to persevere until a goal is achieved without succumbing to difficulties. However, core skills are not limited to these. For example, a human resources staff member of a company can set any core skill to be determined in a skill master (not shown) on the server 20 via the terminal device 10.

[0079] The level is a column that stores the determined level of a core skill. The level is, for example, a five-point rating from 1 to 5. In this embodiment, the skill level is determined on a five-point scale, but this is merely an example of a parameter value that represents the skill level. The parameter value that represents the skill level may be, for example, a rating on a ten-point scale or a score out of 100 points.

[0080] The date and time is a column for storing the date and time when the core skill and level were determined.

[0081] 7 is a diagram showing the data structure of the training table 2024. As shown in FIG. 7, the training table 2024 has columns such as a training name and a URL, with a training ID as a key. The server 20 may include the training table 2024, or an external server 20A (not shown; for example, an external server that provides personnel services such as a server that builds a training system or a server that builds an onboarding system) that is communicatively connected to the server 20 via the network 80 may have the training table 2024 built in.

[0082] The training ID is a column that stores an identifier for uniquely identifying the training.

[0083] The training name is a column that stores the name of the training.

[0084] The URL is a column for storing the URL of a website that introduces an overview of the training or the URL of a website where the training is taken as online training.

[0085] <5. Operation> The following describes an example of the flow of operations in the system 1. Note that, although the explanation is given taking an example of operations for one skill, processing for multiple skills may be performed in one operation.

[0086] <5.1. Learning before operation>

[0087] The generative AI system 30 is trained in advance on core skills before the actions 1 and 2.

[0088] The server 20 receives learning data from the terminal device 10A of the administrator of the generative AI system 30. Specifically, the control unit 203 receives text information about a model employee via the terminal device 10A, and receives the name of the model member's core skill and the level of that core skill. A model employee is a person who possesses a core skill that serves as a standard for the level of a core skill. A model employee is, for example, a person in a higher position, an ace employee, etc. The text information about a model employee is a document used to identify the standard for the level. The text information about a model employee may be in the form of complete sentences, such as transcripts, meeting minutes, diaries, memoirs, or emails, or in the form of incomplete sentences (bullet points, lists, or enumerations of numbers and nouns), such as resumes, qualification certificates, work schedules, and training history. The name of the model member's core skill and the level of that core skill are, for example, "Involvement Ability Level 5." Specifically, the control unit 203 then inputs text information about the model member as input data and the names of the core skills of the model member to be output and the levels of those core skills as correct answer data into the generative AI system 30, causing it to learn about the core skills. The generative AI system 30 determines the core skills and levels based on the model member by repeating learning. The generative AI system 30 builds a predictive model that determines the core skills and levels while adjusting coefficients that indicate the degree of influence each element of the text information has on the core skills and levels. For example, the generative AI system 30 determines the level of skill implied by a level 5 in the ability to engage employees based on the linguistic expressions and behavioral patterns of the model employee that can be read from the text information.

[0089] Note that a prompt tuning technique may be used in the generative AI system 30. Specifically, the control unit 203 receives, via the terminal device 10A, an instruction such as "Learn core skills and levels based on the information below. Input text information about a model employee. The model employee has an engagement ability level of 5. Specify engagement ability level 5," along with text information about the model member. The control unit 203 inputs the instruction and the text information about the model member into the generative AI system 30, causing it to learn about core skills.

[0090] <5.2. Operation 1>

[0091] FIG. 8 is a flowchart showing an example of the operation of the system 1 when a member (employee) of an organization and the generation AI have a conversation.

[0092] First, when it is time for the employee to submit their daily business report, they access the interview-style conversation platform, which allows them to converse with the generated AI model via an avatar, through a web browser or app on the terminal device 10, by performing a predetermined operation. The predetermined operation is, for example, logging in.

[0093] In step S1001, the server 20 generates a first prompt including an instruction for a conversation with an employee and inputs it to the generative AI system 30. Specifically, for example, when an employee operates the terminal device 10 to launch the conversation platform, the transceiver 192 transmits a conversation start request to the server 20 via the communication unit 120. The control unit 203 receives the conversation start request via the communication unit 201, for example. The control unit 203 instructs the generative AI system 30 to start a conversation via the communication unit 201, for example. An example of the instruction for a conversation with an employee is, "Please talk to the employee about your daily work." This instruction becomes, for example, the first prompt. The instruction for a conversation with an employee may include instructions regarding the conversation time, theme, content, questions, tone, and turn allocation between the employee and the generative AI, depending on the purpose and situation of the conversation. The generative AI system 30 may be pre-trained and tuned to the conversation time, theme, content, questions, tone, and turn allocation between the employee and the generative AI, corresponding to the purpose and situation of the conversation. Conversation topics include, for example, recent work, future prospects, career outlook, educational background, work history (including previous jobs), company history, training history, hobbies, etc.

[0094] In step S1002, the server 20 inputs the employee's utterance to the generative AI system 30. Specifically, for example, the operation reception unit 191 receives the employee's utterance as voice via the input device 13. The transmission / reception unit 192 transmits the voice data of the utterance to the server 20 via the communication unit 120, for example. The control unit 203 receives the voice data of the utterance via the communication unit 201, for example. The control unit 203 converts the voice data of the utterance into text data, for example. The control unit 203 transmits the text data of the utterance to the generative AI system 30 via the communication unit 201, for example.

[0095] In step S1003, the server 20 causes the generation AI system 30 to output a response to the employee's utterance. Specifically, the generation AI system 30 outputs text data as a response to the employee's utterance, such as an answer to the employee's question, further digging into the employee's utterance, advice for the employee, encouragement for the employee, a question, a greeting, a hooter, small talk, a break from the conversation, etc. The generation AI system 30 transmits the response text data to the server 20, for example.

[0096] In step S1004, the server 20 presents the employee with a response to the employee's utterance. Specifically, the control unit 203, for example, converts the text data of the response into voice data. The conversion process from text data to voice data may be performed by, for example, the voice processing unit 17. The control unit 203, for example, transmits the text data and voice data of the response to the terminal device 10 via the communication unit 201.

[0097] The control unit 203, for example, controls the speech and actions of an avatar displayed on the display 141 via the presentation control unit 193, causing the avatar to speak response data as voice. The control unit 203 may, for example, control the presentation control unit 193 to display response text data on the display 141. In this case, the avatar may or may not be displayed. In this way, the server 20 presents the employee with a response to the employee's utterance.

[0098] During one conversation, the processes from step S1002 to step S1004 are repeated.

[0099] The conversation platform may be in the form of a chat rather than a face-to-face meeting. In this case, in step S1002, for example, the operation reception unit 191 may receive a utterance input by an employee as text via the input device 13. In this case, in step S1004, for example, the control unit 203 may transmit only the text data of the response to the terminal device 10 and display the text data of the response on the display 141 without converting the text data of the response into voice data.

[0100] In step S1005, the server 20 stores the conversation content including the employee's comments and the employee's responses to those comments. Specifically, the control unit 203 adds a record to the conversation table 2022 each time a conversation ends, and stores both the text data of the comment and the text data of the response (hereinafter referred to as "conversation content") in columns of employee ID, conversation ID, date and time, and conversation content as necessary. The "conversation content" may be both the voice data of the comment and the voice data of the response.

[0101] <5.3. Operation 2>

[0102] 9 is a flowchart showing an example of the operation of determining the core skills and levels of employees in the system 1. The server 20 performs the following operation periodically (for example, at 11:59 p.m. every day) or on an ad hoc basis (for example, every time a new conversation is stored in the conversation table 2022).

[0103] In step S1101, the server 20 inputs a second prompt to the generation AI system 30, the second prompt including the conversation content and an instruction statement for outputting the employee's condition information based on the conversation content. Specifically, the control unit 203 creates a second prompt including the conversation content stored in the conversation table 2022 and an instruction statement for outputting the employee's core skills and level based on the conversation content. The control unit 203 inputs the created second prompt to the generation AI system 30. For example, the control unit 203 inputs the conversation content of the latest conversation to the generation AI system 30. The instruction statement is, for example, "Based on the conversation content with the employee, please determine the employee's core skills and level while comparing them with a model employee. If the employee's strength is equivalent to that of the model employee, please determine the level as 5. If the employee's strength is slightly inferior to that of the model employee, please determine the level as 4. If the employee's strength is inferior to that of the model employee, please determine the level as 3. If the employee's strength is significantly inferior to that of the model employee, please determine the level as 2. If the employee's strength is significantly inferior to that of the model employee, please determine the level as 1." The instruction may include, for example, "Please do not determine core skills and levels that cannot be determined from the content of this conversation."

[0104] In step S1102, the server 20 causes the generative AI system 30 to output the employee's core skills and level based on the content of the conversation. Specifically, the generative AI system 30 outputs the employee's core skills and level (e.g., "ability to involve others, level 4") in accordance with the instruction. Specifically, the generative AI system 30 transmits the employee's core skills and level to the server 20.

[0105] The conversation topics may be, for example, recent work, future prospects, career outlook, educational background, work history (including previous job), company history, training history, hobbies, etc. The instruction may include, "Please determine the employee's core skills and level based on the conversation topics (recent work, future prospects, career outlook, educational background, work history (including previous job), company history, training history, hobbies) included in the conversation content with the employee." Therefore, the generative AI system 30 may output the employee's core skills and level based on themes included in the conversation content, such as recent work, future prospects, career outlook, educational background, work history (including previous job), company history, training history, hobbies, etc. For example, if the conversation topic is work history (including previous job) and the conversation content includes information about developing a groundbreaking new product in a previous job that required high creativity, the generative AI system 30 may output "creative ability level 5" as the employee's core skills and level based on the conversation content. For example, if the topic of the conversation is training history and the conversation content includes that the employee completed resilience training with excellent results and also accomplished a specific project in their previous job, the generative AI system 30 will output "ability to accomplish level 5" as the employee's core skill and level based on the conversation content.

[0106] In step S1103, the server 20 presents the output core skills and levels to the employee. Specifically, for example, the control unit 203 sends a message of the core skills and levels to the employee using a personnel-related tool (for example, an employee skill management tool, a training management tool, an interview management tool, or an onboarding system). Specifically, for example, the control unit 203 sends a push notification of the core skills and levels to the employee on the employee's terminal device 10 using a personnel-related app. Specifically, for example, the control unit 203 sends the core skills and levels by email to the employee's email address.

[0107] The server 20 may present the output core skills and levels to the employee's manager (for example, the employee's superior, a human resources department member, or an external career counselor).

[0108] If the level of the output core skill is high, the server 20 may present the level together with information suggesting that the core skill is high. Information suggesting that the core skill is high, for example, is a GOOD mark, a smiley face icon, text saying "strengths," etc. A high core skill level may, for example, be level 5, or a level 0.5 or more higher than the average for employees. If an employee is provided with information suggesting that their core skill is high, the employee may be given preferential treatment in personnel decisions.

[0109] If the output core skill level is low, the server 20 may present the level together with information suggesting that the core skill is low. Information suggesting that the core skill is low may be, for example, a BAD mark, a dissatisfied face icon, or text saying "weakness." A low core skill level may be, for example, a level of 1, or a level that is 0.5 or more points lower than the employee average, etc. If an employee is provided with information suggesting that their core skill is low, the employee may be treated as a target for measures to improve the corresponding skill level.

[0110] <6. Screen Examples> An example of a screen on the display 141 of the terminal device 10 in the present disclosure will be described.

[0111] FIG. 10 shows an example of a screen displayed when an employee converses with the generated AI via an avatar on their own terminal device 10 (interview format) in steps S1002 to S1004. This screen is a user interface for a conversation between the employee and the generated AI, for example, to accept comments from the employee and present responses from the generated AI to the employee. Note that this screen example is merely an example, and various screen configurations and screen contents may be adopted. For example, only the avatar 3011 described below may be displayed on the display 141.

[0112] The avatar display area 3001 is an area where an image or animation of an avatar 3011 is displayed. The avatar 3011 is, for example, an interface that has a human appearance and voice and speaks and moves under the control of the control unit 203. When the avatar 3011 speaks, the movement of the avatar's mouth, etc. may be displayed in synchronization. The speech of the avatar 3011 is realized, for example, by audio output from the speaker 172, but may also be realized by displaying the speech content in text near the display area of ​​the avatar 3011. In this case, the avatar 3011 may function only as an icon without speaking.

[0113] The comment display area 3002 is an area where comments input by employees in voice or text are displayed in text format.

[0114] Response display area 3003 is an auxiliary display area that allows the employee to recognize the response from avatar 3011. Because avatar 3011 responds by voice, the text of the response may not be displayed in this area, or if text data is sent from server 20 together with the voice data, the text may be displayed.

[0115] Input means display area 3004 is an area that displays means by which an employee inputs a message to avatar 3011. In this example screen, for example, a microphone icon 3014 for starting voice input and a field 3024 for supplementary text input are displayed in this area. For example, when operation reception unit 191 receives an operation by an employee to press microphone icon 3014, it is assumed that reception of voice input from microphone 171 will begin.

[0116] The send button 3005 is a button for sending to the server 20 a statement (mainly a voice input or a text input) input by the employee via the input means display area 3004 .

[0117] Conversation log display area 3006 is an area where a history of a series of interactions between an employee and avatar 3011 (specifically, the generated AI) is displayed in chronological order. The employee can, for example, scroll through the contents of past conversations to check them.

[0118] Figure 11 is an example of a screen displayed when a message is sent to an employee in step S1103 containing the newly determined core skills and levels in the employee skill management tool. In the example screen shown in Figure 11, the core skills and levels are "Ability to involve others, level 5" and "Ability to create, level 1." Note that this example screen is merely an example, and various screen configurations and screen contents may be adopted.

[0119] An area 3101 is an area for displaying a message to the employee. A message indicating that the core skills and level have been newly determined is displayed in the area 3101.

[0120] Box 3102, exemplified by boxes 3102A and 3102B, is an area displaying newly determined core skills and levels. Box 3102A displays the ability to engage, level 5, and a smiling face icon as information suggesting a high level. Box 3102B displays the ability to create, level 1, and a dissatisfied face icon as information suggesting a low level.

[0121] Area 3103 is an area that displays core skills and levels that have already been registered, i.e., that are stored in the skill management table 2023. Box 3104 is a box that displays each core skill and level. Box 3104 displays the core skill, level, and a meter that represents the level. The meter expands as the level increases and contracts as the level decreases.

[0122] <7.Summary> As described above, in the above embodiment, the server 20 inputs a first prompt including an instruction for conversing with a member of an organization to the generation AI. The server 20 inputs a statement by the member to the generation AI and causes the generation AI to output a response to the statement. The server 20 presents the response to the member. The server 20 stores the conversation content, including the statement and the response. The server 20 inputs a second prompt including the conversation content and an instruction for outputting a core skill related to the member's mindset that is emphasized in the organization and a parameter value representing the member's proficiency in the core skill based on the conversation content to the generation AI, and causes the generation AI to output the member's core skill and the parameter value of the core skill based on the conversation content. The server 20 presents the output core skill and the parameter value of the core skill. The generation AI is trained in advance on core skills using text information about the model member as input data and the name of the core skill of the model member to be output and the parameter value of the core skill as correct answer data. This enables accurate evaluation of the level of skills even when the skills required for each organization differ.

[0123] Furthermore, as described above, in the above embodiment, when the parameter value of the output core skill is high, the server 20 presents the parameter value together with information suggesting that the parameter value is high. When the parameter value of the output core skill is low, the server 20 presents the parameter value together with information suggesting that the parameter value is low. This makes it easier to intuitively understand whether an employee's core skill is at a level that can be considered an advantage or a level that can be considered a disadvantage.

[0124] <8. Variations> A modification of the above embodiment will now be described.

[0125] <8.1. Variation 1> The server 20 may store the output core skills and their levels after approval by the employee or the employee's manager. Specifically, after the newly determined core skills and levels are presented in the employee skill management tool, pressing the approval button causes the control unit 203 to add a record to the skill management table 2023 and store information about the core skills and levels in the employee ID, core skill ID, core skill name, level, and date / time columns as necessary. If the core skills and levels are already stored in the skill management table 2023, the control unit 203 updates the level of the core skills. This ensures an opportunity for manual checking of the validity of the newly determined core skills and levels, while ensuring operability for smooth manual checking.

[0126] <8.2. Variation 2> In order to recommend training in skills relevant to the employee, the server 20 may input a third prompt to the generation AI system 30, which includes the conversation content and an instruction to output training information related to core skills relevant to the employee based on the conversation content, and cause the generation AI to output the training information based on the conversation content.

[0127] Specifically, the control unit 203 creates a third prompt that includes the conversation content stored in the conversation table 2022 and an instruction statement for outputting information about training related to core skills relevant to the employee based on the conversation content. The control unit 203 inputs the created third prompt to the generation AI system 30. The instruction statement is, for example, "Based on the conversation content, please introduce information about training related to core skills relevant to the employee. Core skills relevant to the employee include, for example, core skills related to the employee's current or future work, core skills at which the employee's current level is low, core skills in which the employee is currently struggling to improve, etc."

[0128] Specifically, the generative AI system 30 identifies core skills related to the employee and, by referring to the training table 2024, specifies training that can improve those core skills. For example, if the employee's level of involvement is low, the generative AI system 30 specifies leadership training. Specifically, the control unit 203 presents information about the specified training (training name, URL, etc.) to the employee using the employee skill management tool.

[0129] This will encourage employees to take training related to core skills that are closely related to them, thereby promoting the improvement of those skills.

[0130] <8.3. Variation 3> In the above embodiment, the server 20 causes the generative AI system 30 to determine core skills and their levels related to mindsets that are valued in an organization. The server 20 may also cause the generative AI system 30 to determine general skills related to the basics of working life that are generally valued regardless of the organization. Examples of general skills include logical reasoning, negotiation skills, stress tolerance, etc. General skills and their levels, like core skills and their levels, can be taken into consideration in personnel decisions such as promotion, salary increase, hiring, training, and performance evaluation.

[0131] <8.4. Variation 4> The directive in the above embodiment may include a statement prohibiting discriminatory treatment based on attributes unrelated to skills. For example, the directive may read, "When assessing an employee's skills and level, exclude, to the greatest extent possible, attributes unrelated to skills, such as gender, age, nationality, race, ethnicity, registered domicile, place of origin, social status, family structure, family environment, religion, ideology, creed, presence or absence of disabilities, sexual orientation, and family structure. Even if an employee voluntarily mentions information about the above attributes, do not take that information into consideration. However, while the information itself must not be taken into consideration, this does not preclude assessing skills unrelated to that information through the content of the employee's comments related to that information."

[0132] <9. Basic Computer Hardware Configuration> 12 is a block diagram showing the basic hardware configuration of a computer 90. The computer 90 includes at least a processor 901, a main memory device 902, an auxiliary memory device 903, and a communication IF 991 (interface), which are electrically connected to one another by a communication bus 921.

[0133] The processor 901 is hardware for executing an instruction set written in a program, and is composed of an arithmetic unit, registers, peripheral circuits, and the like.

[0134] The main memory device 902 is used to temporarily store programs, data to be processed by the programs, etc. For example, it is a volatile memory such as a DRAM (Dynamic Random Access Memory).

[0135] The auxiliary storage device 903 is a storage device for saving data and programs, such as a flash memory, a hard disk drive (HDD), a magneto-optical disk, a CD-ROM, a DVD-ROM, or a semiconductor memory.

[0136] The communication IF 991 is an interface for inputting and outputting signals for communicating with other computers via a network using wired or wireless communication standards. The network is composed of the Internet, a LAN, various mobile communication systems constructed by wireless base stations, etc. For example, the network includes 3G, 4G, and 5G mobile communication systems, LTE (Long Term Evolution), and wireless networks (e.g., Wi-Fi (registered trademark)) that can connect to the Internet via a predetermined access point. In the case of a wireless connection, communication protocols include, for example, Z-Wave (registered trademark), ZigBee (registered trademark), and Bluetooth (registered trademark). In the case of a wired connection, the network also includes a direct connection using a USB (Universal Serial Bus) cable, etc.

[0137] It should be noted that the computer 90 can be virtually realized by distributing all or part of each hardware configuration across multiple computers 90 and interconnecting them via a network. In this way, the computer 90 is a concept that includes not only a computer 90 housed in a single housing or case, but also a virtualized computer system.

[0138] <Basic functional configuration of computer 90> A description will now be given of the functional configuration of the computer realized by the basic hardware configuration of the computer 90. The computer comprises at least the functional units of a control unit, a storage unit, and a communication unit.

[0139] The functional units of the computer 90 can also be realized by distributing all or part of the functional units among multiple computers 90 interconnected via a network. The computer 90 is a concept that includes not only a single computer 90 but also a virtualized computer system.

[0140] The control unit is realized by the processor 901 reading out various programs stored in the auxiliary storage device 903, expanding them in the main storage device 902, and executing processing in accordance with the programs. The control unit can realize functional units that perform various types of information processing depending on the type of program. In this way, the computer is realized as an information processing device that performs information processing.

[0141] The storage unit is realized by a main storage device 902 and an auxiliary storage device 903. The storage unit stores data, various programs, and various databases. Furthermore, the processor 901 can allocate a storage area corresponding to the storage unit in the main storage device 902 or the auxiliary storage device 903 in accordance with the programs. Furthermore, the control unit can cause the processor 901 to execute processes for adding, updating, and deleting data stored in the storage unit in accordance with the various programs.

[0142] A database refers to a relational database, which manages data sets called masters and tables in a tabular format structurally defined by rows and columns, by relating them to each other. In a database, a table is called a table, a master, a column in a table is called a column, and a row in a table is called a record. In a relational database, relationships between tables and masters can be set and associated. Typically, each table and each master has a column set as a primary key to uniquely identify a record, but setting a primary key to a column is not essential. The control unit can cause the processor 901 to add, delete, or update records in specific tables and masters stored in the storage unit according to various programs. Furthermore, by storing data, various programs, and various databases in the storage unit, it can be considered that the information processing device and information processing system according to the present disclosure have been manufactured.

[0143] Note that the databases and masters in this disclosure may include any data structure in which information is structurally defined (such as a list, dictionary, associative array, or object). The data structure also includes data that can be considered as a data structure by combining data with functions, classes, methods, etc. written in any programming language.

[0144] The communication unit is realized by the communication IF 991. The communication unit realizes a function of communicating with other computers 90 via a network. The communication unit can receive information transmitted from other computers 90 and input the information to the control unit. The control unit can cause the processor 901 to execute information processing on the received information in accordance with various programs. In addition, the communication unit can transmit information output from the control unit to other computers 90.

[0145] Furthermore, the above-described configurations, functions, processing units, processing means, etc. may be partially or entirely implemented in hardware, for example, by designing them as integrated circuits. The present invention can also be realized by software program code that implements the functions of the embodiments. In this case, a storage medium on which the program code is recorded is provided to a computer, and a processor included in the computer reads the program code stored in the storage medium. In this case, the program code itself read from the storage medium implements the functions of the above-described embodiments, and the program code itself and the storage medium on which it is stored constitute the present invention. Examples of storage media for providing such program code include flexible disks, CD-ROMs, DVD-ROMs, hard disks, SSDs, optical disks, magneto-optical disks, CD-Rs, magnetic tape, non-volatile memory cards, and ROMs.

[0146] Furthermore, the program code that realizes the functions described in this embodiment can be implemented in a wide range of program or script languages, such as assembler, C / C++, perl, Shell, PHP, and Java (registered trademark).

[0147] Furthermore, the program code of the software that realizes the functions of the embodiments may be distributed via a network and stored in a storage means such as a computer's hard disk or memory, or in a storage medium such as a CD-RW or CD-R, and the processor of the computer may read and execute the program code stored in the storage means or storage medium.

[0148] The functions performed by the components described herein may be implemented in circuitry or processing circuitry, including general-purpose processors, application-specific processors, integrated circuits, ASICs (Application Specific Integrated Circuits), a CPU (a Central Processing Unit), conventional circuits, and / or combinations thereof, programmed to perform the described functions. A processor includes transistors and other circuits and is considered to be circuitry or processing circuitry. A processor may also be a programmed processor that executes programs stored in memory. In this specification, a circuitry, unit, or means is hardware that is programmed to realize or performs the described functions, which may be any hardware disclosed herein or any hardware known to be programmed to realize or perform the described functions. If the hardware is a processor considered to be a type of circuitry, the circuitry, means, or unit is a combination of the hardware and software used to configure the hardware and / or processor.

[0149] Although several embodiments of the present disclosure have been described above, these embodiments can be embodied in various other forms, and various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. These embodiments and modifications are intended to be included in the scope of the inventions and their equivalents as defined in the claims, as well as in the scope and spirit of the inventions.

[0150] (Addendum) The matters described in the above embodiments will be supplemented below.

[0151] (Appendix 1) A program for operating a computer including a processor and a memory, the program causing the processor to: inputting a first prompt including an instruction sentence for conversing with a member of the organization to the generation AI; inputting a comment by the member into the generation AI and causing the generation AI to output a response to the comment; presenting the response to the member; storing the conversation content including the utterance and the response; inputting a second prompt to the generation AI, the second prompt including the content of the conversation and an instruction to output, based on the content of the conversation, core skills of the member related to a mindset that is emphasized in the organization and parameter values ​​representing the degree of proficiency of the core skills, and having the generation AI output the core skills of the member and the parameter values ​​of the core skills based on the content of the conversation; presenting the output core skill and the parameter value of the core skill; A program that executes the following. (Appendix 2) The generation AI is a program described in (Appendix 1), in which the generation AI is made to learn about the core skills in advance using text information about the model members as input data and the names of the core skills of the model members to be output and the parameter values ​​of the core skills as correct answer data. (Appendix 3) A program described in any of (Appendix 1) to (Appendix 2), wherein in the presentation step, if the parameter value of the output core skill is high, the parameter value is presented together with information suggesting that the parameter value is high. (Appendix 4) A program described in any of (Appendix 1) to (Appendix 3), wherein, in the presentation step, if the parameter value of the output core skill is low, the parameter value is presented together with information suggesting that the parameter value is low. (Appendix 5) the processor, a step of storing the outputted core skill and the parameter value of the core skill after approval by the member or the member's manager; A program for executing the above, the program described in any one of (Appendix 1) to (Appendix 4). (Appendix 6) the processor, inputting a third prompt to the generation AI, the third prompt including the conversation content and an instruction sentence for outputting training information related to the core skill associated with the member based on the conversation content, and causing the generation AI to output the training information based on the conversation content; A program according to any one of (Appendix 1) to (Appendix 5), which causes the program to execute the above. (Appendix 7) A method executed by a computer having a processor and a memory, wherein the processor executes all of the steps performed in any of the inventions according to (Appendix 1) to (Appendix 6). (Appendix 8) An information processing device comprising a control unit and a storage unit, wherein the control unit executes all of the steps executed in the invention according to any one of (Appendix 1) to (Appendix 6). (Appendix 9) A system comprising means for executing all steps performed in any of the inventions according to (Appendix 1) to (Appendix 6). [Explanation of symbols]

[0152] 1. System 10...Terminal device 12...Communication IF 13...Input device 14...Output device 15...Memory 16…Storage 19...Processor 20...Server 22...Communication IF 23...Input / output interface 25…Memory 26…Storage 29...Processor 80…Network

Claims

1. A program for operating a computer including a processor and a memory, the program causing the processor to: inputting a first prompt to the generating AI, the first prompt including instructions for conversing with a member of the organization; inputting a comment by the member into the generating AI and causing the generating AI to output a response to the comment; presenting the response to the member; storing the conversation content including the utterance and the response; inputting a second prompt to the generation AI, the second prompt including the content of the conversation and an instruction to output, based on the content of the conversation, core skills of the member related to a mindset that is emphasized in the organization and parameter values ​​representing the degree of proficiency of the core skills, and having the generation AI output the core skills of the member and the parameter values ​​of the core skills based on the content of the conversation; presenting the output core skill and the parameter value of the core skill; A program that executes the following.

2. The program according to claim 1, wherein the generation AI is configured to learn about the core skills in advance using text information about the model members as input data and the names of the core skills of the model members to be output and the parameter values ​​of the core skills as correct answer data.

3. The program according to claim 1 , wherein, in the presenting step, if the parameter value of the output core skill is high, the parameter value is presented together with information suggesting that the parameter value is high.

4. The program according to claim 1 , wherein, in the presenting step, if the parameter value of the output core skill is low, the parameter value is presented together with information suggesting that the parameter value is low.

5. the processor, a step of storing the output core skill and the parameter value of the core skill after approval by the member or the member's manager; 2. The program according to claim 1, wherein the program causes the program to execute the above steps.

6. the processor, A step of inputting a third prompt to the generation AI, the third prompt including the conversation content and an instruction sentence for outputting training information related to the core skill associated with the member based on the conversation content, and causing the generation AI to output the training information based on the conversation content. The program according to claim 1 ,

7. A method implemented on a computer having a processor and a memory, wherein the processor performs all of the steps performed in the invention according to any one of claims 1 to 6.

8. 10. An information processing device comprising a control unit and a storage unit, wherein the control unit executes all of the steps executed in the invention according to any one of claims 1 to 6.

9. A system comprising means for executing all steps performed in the invention according to any one of claims 1 to 6.

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