System

Abstract

A system is provided.SOLUTION: A system disposed between an in-house network and the Internet, the system comprising: means for monitoring usage of a generation and AI service; means for recording usage of the generation and AI service; means for detecting compliance and security violations in the usage of the generation and AI service; means for providing an alert notification for excessive usage of the generation and AI service; means for generating a report based on the usage of the generation and AI service; and means for suggesting recommended actions for excessive usage of the generation and AI service.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] As generative AI becomes more widespread, companies are facing issues with employees' inappropriate use of generative AI services and excessive reliance on them. This increases compliance and security risks and reduces productivity. It is also difficult to immediately respond to unauthorized access to generative AI services or inappropriate use. Measures to maintain employees' digital well-being and prevent reliance on generative AI are urgently needed. [Means for solving the problem]

[0005] The present invention provides a system that is located between an internal company network and the Internet and includes a means for monitoring the usage of a generating AI service and a means for recording usage data of the generating AI service. The system also includes a means for detecting compliance violations and security violations in the use of the generating AI service, a means for issuing alerts regarding excessive use of the generating AI service, and a means for generating reports based on the usage of the generating AI service. The system further includes a means for proposing recommended actions for excessive use of the generating AI service. By including a means for blocking access to unauthorized generating AI services and a means for collaborating with generating AI service providers to provide data via APIs, the system reduces corporate compliance and security risks and maintains employee productivity and digital well-being.

[0006] 1. An internal company network is a local area network (LAN) used within a company, a communications network to which computers and devices used by employees are connected.

[0007] 2. The Internet is a global network that connects computers and networks around the world to each other and exchanges information.

[0008] 3. Generative AI services are a general term for online platforms and applications that use artificial intelligence to automatically generate content such as text, images, and audio.

[0009] 4. Monitoring means refers to the technologies and methods used to monitor employees' use of AI-generated services in real time and collect necessary data.

[0010] 5. Recording Measures means the technologies and methods, including databases and log files, used to store generated AI service usage data collected through monitoring.

[0011] 6. Detective measures are methods and algorithms used to analyze collected data and identify compliance or security violations in the use of generative AI services.

[0012] 7. Alert Notification Measures are technologies and methods for sending real-time warnings to administrators and applicable users when usage of the Generative AI Service exceeds established thresholds.

[0013] 8. Report generation means are the techniques and methods used to generate weekly and monthly usage reports based on the collected data.

[0014] 9. Means for suggesting recommended actions are technologies and methods for providing appropriate countermeasures to administrators when excessive use of generative AI services is detected.

[0015] 10. Measures to block access to unauthorized generative AI services are technologies and methods used to prevent access to generative AI services that are not included in the allow list.

[0016] 11. API is an abbreviation for Application Programming Interface, which refers to the definitions and protocols for exchanging data between different software programs.

[0017] 12. Digital well-being refers to the state in which employees can use digital tools and services appropriately and healthily, and is a concept aimed at preventing excessive reliance and maintaining physical and mental health. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

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

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

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

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form 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.

[0033] 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.

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

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention is a system for appropriately managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet and monitors and records employee usage of multiple different generative AI services in real time.

[0040] The present invention is carried out as follows.

[0041] 1. Initial Setup

[0042] The user (administrator) first logs in to the server and sets up a list of allowed generative AI services. For example, the administrator adds services such as "ServiceA," "ServiceB," and "ServiceC" to the allowed list. The administrator can also set usage criteria and alert conditions (e.g., more than three hours of use per day).

[0043] 2. Traffic Monitoring

[0044] The server monitors all traffic from the company network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if an employee's device accesses "ServiceA," the traffic is allowed because it is included in the authorization list. On the other hand, access to "ServiceD," which is not authorized, is blocked.

[0045] 3. Records of usage

[0046] The server records detailed usage information for the AI ​​service (start time, end time, type of service, etc.) For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[0047] 4. Report Generation

[0048] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details such as each employee's usage time, type of usage, and the number of alerts generated.

[0049] 5. Real-time alerts

[0050] The server generates real-time alerts when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B.

[0051] 6. Recommended Action Suggestion

[0052] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0053] Specific examples

[0054] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours per day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that employee A review his or her usage time and, if necessary, retrain him or her on the usage guidelines for the generation AI service.

[0055] In this way, the system aims to monitor the appropriate use of generative AI services, maintaining compliance and security while preserving employees' digital well-being.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[0059] Step 2:

[0060] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[0061] Step 3:

[0062] User (Administrator): Sets usage criteria and alert conditions. For example, you can set "Generate an alert if usage time exceeds 3 hours per day."

[0063] Step 4:

[0064] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[0065] Step 5:

[0066] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[0067] Step 6:

[0068] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[0069] Step 7:

[0070] Server: Saves the collected data in a database. For example, data such as "Employee A, Service A, 10:00-11:00" is recorded in the database.

[0071] Step 8:

[0072] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, number of alerts, etc.

[0073] Step 9:

[0074] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[0075] Step 10:

[0076] Server: Generates alerts in real time when an employee's AI service usage exceeds a set threshold. For example, if employee B uses "Service B" for four hours in one day, an alert is generated to notify the administrator and employee B.

[0077] Step 11:

[0078] Server: If excessive use of generated AI is detected, the server will propose specific countermeasures to the administrator. For example, it will recommend that employee C undergo user training.

[0079] Step 12:

[0080] User (Administrator): Implements countermeasures based on suggestions from the server. For example, re-educating employees about usage guidelines and setting usage time limits.

[0081] Example 1

[0082] 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."

[0083] The use of generative AI services is increasing in modern corporate environments. However, excessive use of generative AI services by employees may increase compliance violations and security risks. There are also concerns that excessive use may negatively impact employees' digital well-being. Furthermore, companies must properly manage generative AI services, and effective monitoring and control measures are needed.

[0084] 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.

[0085] In this invention, the server is located between the internal network and the Internet and includes: means for monitoring usage of the generating AI service; means for recording usage data of the generating AI service; means for detecting compliance violations and security violations in the use of the generating AI service; means for issuing alerts for excessive use of the generating AI service; means for generating reports based on usage of the generating AI service; means for proposing recommended actions for excessive use of the generating AI service; means for an administrator to log in to the server and set a list of permitted services; means for the administrator to set usage criteria and alert conditions; means for monitoring all traffic from the internal network to the Internet in real time to confirm whether access to the generating AI service is permitted; and means for determining whether access to a service is permitted. This enables companies to properly manage the use of the generating AI service, maintain compliance and security, maintain employee digital well-being, and improve productivity.

[0086] An "internal network" is a computer network used within a company, and is a communications infrastructure for connecting internal computers, servers, and various devices to each other.

[0087] The "Internet" is a huge data communications network that interconnects computer networks all over the world, and is an infrastructure for exchanging information and providing services.

[0088] "Generative AI services" refer to online services that use artificial intelligence technology to generate various types of data, such as text generation, image generation, and voice synthesis.

[0089] "Usage status" refers to various log information regarding the use of the generative AI service, including, specifically, the start time of use, end time, type of service, number of uses, etc.

[0090] "Violation of compliance" refers to any act that goes against the laws, regulations, or guidelines established by a company or organization, and particularly refers to inappropriate operations in business processes or information management.

[0091] A "security breach" refers to any act that threatens the security of an information system, such as information leakage, tampering, or unauthorized access.

[0092] An "alert notification" is a warning message that the system automatically sends when set criteria or conditions are met, and is mainly notified via email or dashboard.

[0093] "Usage Data" means all recorded information relating to the use of the Generative AI Services, including data indicating which services a particular user used and to what extent.

[0094] A "report" is a document or digital file that contains aggregated results based on usage of the Generative AI Service, including details such as usage time, number of uses, and number of alerts.

[0095] "Recommended actions" are specific measures or countermeasures that the system suggests when certain conditions are met, such as strengthening usage restrictions or implementing educational programs.

[0096] An "administrator" is a user who has the authority to configure and monitor the system, check reports, etc., and primarily refers to the information systems department or security officer within a company.

[0097] "Traffic monitoring" refers to the act of observing data communications on a network in real time and detecting specific information or patterns, and is primarily used to improve network security and detect unauthorized access.

[0098] "Access determination" is the process of detecting a specific access request in network traffic and determining whether it is permitted.

[0099] This invention relates to a system for appropriately managing the use of generative AI services within a company. Specifically, it utilizes elements of servers, users (administrators), and terminals to monitor the usage of generative AI services, record data, detect compliance and security violations, issue alerts for excessive usage, generate reports, and propose recommended actions.

[0100] Initial Setup

[0101] A user (administrator) first logs in to the server, which is usually an authentication process using a username and password. The server provides a web interface, and the user accesses the administration page using a browser.

[0102] Administrators set an allow list for the AI-generated services. Specifically, administrators enter the names of the allowed services (e.g., "ServiceA," "ServiceB," and "ServiceC") through a web interface and add them to the list. Administrators also set usage criteria and alert conditions, such as generating an alert if usage exceeds three hours per day.

[0103] Traffic monitoring and access control

[0104] The server uses packet capture software (such as Wireshark or Tcpdump) to monitor all traffic from the internal network to the Internet in real time. The server detects access to the generated AI service in the traffic and checks whether the access is authorized. Access to authorized services is allowed, while access to unauthorized services is blocked.

[0105] Usage record

[0106] The server records the usage of the detected AI service in detail, including the start and end times of use, the type of service, etc. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM, that information is saved in the database. This allows data to be accumulated for later usage analysis.

[0107] Generate reports

[0108] The server generates weekly and monthly reports based on the collected data. These reports are automatically sent to administrators by email. The reports contain detailed information such as the usage time, type of usage, and number of alerts for each employee. For example, an administrator can receive a report stating that "Employee A used Service A for a total of 15 hours during this period."

[0109] Real-time alerts

[0110] The server generates a real-time alert when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B. This alert is notified via email or dashboard.

[0111] Recommended actions

[0112] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0113] Examples of specific examples and prompts

[0114] As a specific example of operation, consider the case where a user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours in a day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the standard time has been exceeded. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that they review employee A's usage time and re-educate them on the usage guidelines for the generation AI service.

[0115] Prompt Sentence Examples

[0116] "Please explain how to set up an alert to be generated if an employee uses an authorized AI generation service for more than three hours, and what action will be taken if Employee A uses the service for more than three hours."

[0117] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0118] Step 1: Initial Setup

[0119] Inputs: Administrator credentials, list of authorized AI generation services, usage criteria, alert conditions

[0120] Specific behavior:

[0121] 1. The user (administrator) logs in to the server.

[0122] The administrator enters a username and password to establish access to the server through authentication.

[0123] Output: Admin interface after successful login

[0124] 2. Administrators set a list of permitted generative AI services.

[0125] The administrator uses the web interface to enter "ServiceA", "ServiceB", and "ServiceC" into the allow list.

[0126] Output: The allow list is saved on the server.

[0127] 3. Administrators set usage criteria and alert conditions.

[0128] For example, an administrator can set up an alert to be generated if the generative AI service is used for more than three hours per day.

[0129] Output: Usage criteria and alert conditions are saved to the server

[0130] Step 2: Traffic monitoring and access control

[0131] Input: Internal network traffic data

[0132] Specific behavior:

[0133] 1. The server monitors traffic in real time.

[0134] The server uses packet capture software (e.g., Wireshark, Tcpdump) to monitor all traffic from the internal network to the Internet.

[0135] Output: Traffic data based on the watch list

[0136] 2. The server detects access to the generative AI service.

[0137] Analyze HTTP requests and API calls to the generative AI service to detect specific service access.

[0138] Output: Detected access list

[0139] 3. The server checks whether access to the service is permitted.

[0140] It checks against the permission list to determine whether access is to an authorized service or an unauthorized service.

[0141] Output: Allowed and blocked access lists

[0142] Step 3: Record usage

[0143] Input: Allowed access list, start time, end time, service type

[0144] Specific behavior:

[0145] 1. The server records the start time of use.

[0146] The server records the time of first access and stores in the database that the generative AI service has begun to be used.

[0147] Output: Recorded usage start time data

[0148] 2. The server records the end time of use.

[0149] The time when the access ended is saved in the database.

[0150] Output: Recorded end time data

[0151] 3. The server records the type of service.

[0152] The name and type of generative AI service used is recorded in a database.

[0153] Output: Recorded service type data

[0154] Step 4: Generate reports

[0155] Input: Collected usage data

[0156] Specific behavior:

[0157] 1. The server generates weekly and monthly reports.

[0158] Aggregate usage data stored in the database and generate weekly and monthly reports.

[0159] Output: Generated weekly and monthly reports

[0160] 2. The server sends the report to the administrator.

[0161] Once the report is generated, it will be automatically emailed to the administrator.

[0162] Output: Report sent to administrator's mailbox

[0163] 3. The report includes usage time and number of alerts.

[0164] Detailed information is provided on each employee's usage time, type of usage, and the number of alerts that occur when standards are exceeded.

[0165] Output: Detailed report information

[0166] Step 5: Real-time alerts

[0167] Input: Current usage time data, set criteria

[0168] Specific behavior:

[0169] 1. The server detects usage that exceeds the usage criteria.

[0170] It monitors usage time in real time and detects excessive usage if it exceeds the set standard.

[0171] Output: Excessive usage detection information

[0172] 2. The server generates and notifies alerts in real time.

[0173] Based on the detection results, an alert is immediately sent by email to administrators and relevant employees.

[0174] Output: Real-time alert notification

[0175] Step 6: Propose recommended actions

[0176] Input: Excessive usage detection information, administrator settings information

[0177] Specific behavior:

[0178] 1. The server makes recommendations when excessive usage is detected.

[0179] Analyze the data and generate recommendations to maintain compliance.

[0180] Output: Recommended action plan

[0181] 2. The server notifies the administrator of the recommended course of action.

[0182] Recommendations are sent to administrators via email and dashboard.

[0183] Output: Recommendation notification to administrator

[0184] 3. We suggest reviewing the frequency of use of generative AI services and providing user education.

[0185] As a concrete countermeasure, we will propose a review of the frequency with which employees use AI services and, if necessary, a retraining program.

[0186] Output: Notification of specific countermeasures

[0187] (Application example 1)

[0188] 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."

[0189] In recent years, the use of generative AI services within companies has been increasing, but without proper monitoring and management, there is a risk of unauthorized or excessive use, which could result in resource waste and security risks.There is also a need for a system that can monitor the usage of generative AI services in real time and promptly notify administrators.

[0190] 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.

[0191] In this invention, the server is located between the company's internal network and the Internet and includes: means for monitoring usage of the generation AI service; means for recording usage data of the generation AI service; means for detecting compliance violations and security violations in the use of the generation AI service; means for issuing alerts regarding excessive use of the generation AI service; means for generating reports based on usage of the generation AI service; means for proposing recommended actions regarding excessive use of the generation AI service; means for monitoring and managing usage of the generation AI service in real time using an application running on a smartphone; means for issuing alerts to managers and employees via email; and means for automatically generating usage reports on specific days of the week and sending them to managers. This allows for appropriate monitoring of usage of the generation AI service within a company, preventing fraudulent and excessive use, and enabling real-time problem detection and rapid response.

[0192] An "internal network" refers to a network environment within a company in which computers, servers, communication devices, etc. are interconnected.

[0193] The "Internet" refers to a huge network that interconnects computer networks all over the world.

[0194] "Generative AI services" refer to online services that use artificial intelligence technology to generate data and analyze information.

[0195] "Monitoring means" refers to the function that allows the system to check specific situations and operations in real time and check for any abnormalities.

[0196] "Recording means" refers to a function for saving specific data and log information.

[0197] "Detection means" refers to the function of automatically recognizing and determining specific situations or conditions.

[0198] "Alert notification means" refers to a function for sending notifications to administrators and relevant parties when certain conditions are met.

[0199] "Report generation means" refers to a function for periodically creating reports based on collected data.

[0200] "Recommended action suggestion means" refers to a function that presents appropriate countermeasures or actions depending on a specific situation.

[0201] "Applications running on a smartphone" refers to software programs that are installed and run on a mobile information terminal.

[0202] "Means of monitoring and management in real time" refers to the ability to instantly check the current situation and take action or respond as necessary.

[0203] "Means for notifying alerts via email" refers to a function for notifying relevant parties of alerts via email.

[0204] "Means for automatically generating reports on a specific day of the week and sending them to the administrator" refers to a function that automatically generates reports according to a schedule on a specific day of the week each week and sends them to the administrator.

[0205] overview

[0206] This invention is a system for managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet, monitors and records the use of generative AI services, and detects compliance and security violations. It also issues alerts for excessive use, periodically generates reports, and proposes recommended actions to administrators. A notable feature of this system is that it monitors and manages the use of generative AI services in real time using an application running on a smartphone.

[0207] System Configuration

[0208] The system consists of the following major hardware and software components:

[0209] 1. Server

[0210] Monitor traffic between your internal network and the internet.

[0211] A database (e.g., AWS RDS, Google Cloud SQL) for recording and managing usage data.

[0212] Performs processing for alert notifications and report generation.

[0213] It connects to smartphone applications via API.

[0214] 2. Smartphone

[0215] Devices used by IT administrators.

[0216] Run specific applications and monitor and manage the usage of generative AI services in real time.

[0217] It provides an interface for receiving alert notifications and taking necessary actions.

[0218] Processing Details

[0219] The server monitors traffic from the company's internal network to the Internet in real time, detects access to the AI ​​generation service, and records usage data for authorized AI generation services and stores the usage status in a database.

[0220] If an employee attempts to access the AI ​​generation service without authorization, the server immediately blocks that access. If usage time exceeds the set threshold, the server generates an alert in real time and notifies the administrator and the employee via email.

[0221] On a specific day of the week (e.g., every Monday), the server automatically generates a weekly usage report and sends it to the administrator, detailing the usage time of each employee, the type of AI-generating service used, the number of alerts generated, and so on.

[0222] Usage example

[0223] For example, if employee C uses "Generation AI Service A" from 9:00 AM to 1:00 PM, the server records that usage. As the usage time exceeds the set standard of three hours, the server immediately sends an alert to the administrator and employee C. In addition, every Monday, a report summarizing the previous week's usage is automatically generated and sent to the administrator. Based on this report, the administrator can review employee C's usage and take appropriate measures as necessary.

[0224] Example prompt sentence:

[0225] "Write a Python program that monitors employee usage of the Generative AI service and sends real-time alerts if it exceeds a set threshold."

[0226] In this way, the present invention is a system that properly monitors and manages the use of generative AI services, prevents fraudulent or excessive use, and enables rapid response.

[0227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0228] Step 1:

[0229] Perform initial setup. The user (administrator) logs in to the server and sets up a list of authorized generative AI services, including usage criteria and alert conditions.

[0230] Input: A list of allowed generation AI services, e.g. "ServiceA", "ServiceB", "ServiceC".

[0231] Output: Saves the configured allow list and usage criteria.

[0232] How it works: Administrators use a web interface to select permitted services and enter usage time limits and alert conditions.

[0233] Step 2:

[0234] Traffic monitoring: The server monitors all traffic from the internal network to the Internet in real time.

[0235] Input: Network traffic data.

[0236] Output: Access data to generative AI services.

[0237] Specific operation: Analyzes packet data and identifies which service is being accessed.

[0238] Step 3:

[0239] Verify access to generative AI services: The server checks whether access to the detected generative AI service is on an allow list.

[0240] Input: Access data to the generative AI service.

[0241] Output: Decision to allow or block.

[0242] Specific operation: Access data is compared against an allow list and access to unauthorized services is blocked.

[0243] Step 4:

[0244] Record usage status. The server records the start time, end time, and type of service of the AI ​​generation service in detail.

[0245] Input: Usage data of the generation AI service for which access has been granted.

[0246] Output: Saving usage data to a database.

[0247] Specific operation: Record the start and end times of use for each service and save them in a database.

[0248] Step 5:

[0249] Monitor alert conditions: The server monitors whether usage exceeds established thresholds based on usage.

[0250] Input: Usage data and configured usage criteria.

[0251] Output: Generate an alert if the criteria is exceeded.

[0252] Specific operation: Usage time is accumulated, and if it exceeds the set standard, an email notification is sent to the administrator and the relevant employee.

[0253] Step 6:

[0254] Generate reports: The server automatically generates weekly and monthly usage reports.

[0255] Input: Usage data of the generative AI service.

[0256] Output: Generate and email usage reports.

[0257] Specific operation: Usage data is collected, a report is created summarizing each employee's usage, and the report is sent to the administrator via email.

[0258] Step 7:

[0259] The server proposes recommended actions. If excessive use of the generative AI service is detected, the server will propose countermeasures to the administrator.

[0260] Input: Excessive usage data.

[0261] Output: Proposal generation and notification.

[0262] Specific actions: In the event of excessive use, the system generates a message suggesting re-education of specific users on usage guidelines or limiting usage time, and notifies the administrator.

[0263] 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.

[0264] This invention is a system that appropriately manages the usage of generative AI services and is placed between an internal company network and the Internet. It uses data from servers, terminals, and users to monitor and record the usage of generative AI services and detect compliance and security violations. Furthermore, by combining it with an emotion engine, it monitors changes in the user's emotions and provides appropriate countermeasures according to the usage situation.

[0265] 1. Initial Setup

[0266] The user (administrator) logs in to the server and configures a list of authorized generative AI services. For example, add services such as "ServiceA," "ServiceB," and "ServiceC" to the authorization list. In addition, the user configures usage criteria, alert conditions, and emotional data recording settings.

[0267] 2. Traffic Monitoring

[0268] The server monitors all traffic from the internal network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it allows the traffic because it is included in the authorization list. On the other hand, access to the unauthorized "ServiceD" is blocked.

[0269] 3. Records of usage

[0270] The server records the usage of the AI ​​service in detail (start time, end time, type of service, etc.). For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. In addition, the emotion engine analyzes the user's emotional state (e.g., stress, elation, fatigue, etc.), which is also recorded.

[0271] 4. Report Generation

[0272] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[0273] 5. Real-time alerts

[0274] The server generates alerts in real time when an employee's use of the AI-generated service exceeds a set threshold or when the user's emotions indicate a specific state (e.g., high stress level). For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[0275] 6. Recommended Action Suggestion

[0276] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0277] Specific examples

[0278] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, and configures it to generate an alert if the usage time exceeds three hours per day or if a high stress level is reached. If employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period and that the emotion data indicates high stress. The server then suggests to the administrator that employee A review his usage time and take measures to manage his stress.

[0279] In this way, the system aims to monitor the appropriate use of generative AI services, maintain compliance and security, and also take into account the emotional state of the user, thereby maintaining employees' digital well-being.

[0280] The processing flow will be explained below.

[0281] Step 1:

[0282] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[0283] Step 2:

[0284] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[0285] Step 3:

[0286] User (Administrator): Sets usage criteria and alert conditions. For example, "Generate an alert if daily usage exceeds three hours." Also, sets emotional data recording settings and alert criteria for specific emotional states.

[0287] Step 4:

[0288] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[0289] Step 5:

[0290] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[0291] Step 6:

[0292] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[0293] Step 7:

[0294] On the device: The emotion engine collects user emotion data, for example, using facial recognition and voice analysis technologies to analyze the user's stress level and other emotional states in real time.

[0295] Step 8:

[0296] Server: The collected emotion data is stored in a database along with usage data of the AI ​​generation service. For example, data such as "Employee A, Service A, 10:00-11:00, high stress level" is recorded in the database.

[0297] Step 9:

[0298] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, alert occurrences, sentiment, etc.

[0299] Step 10:

[0300] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[0301] Step 11:

[0302] Server: Generates alerts in real time when an employee's use of the AI ​​service exceeds a set threshold or indicates a specific emotional state (e.g., high stress level). For example, if employee B uses "Service B" for 4 hours a day and indicates a high stress level, an alert will be sent immediately to the manager and employee B.

[0303] Step 12:

[0304] Server: If excessive use of the AI ​​generator or specific emotional changes are detected, the server will propose specific countermeasures to the manager. For example, "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0305] Step 13:

[0306] User (Administrator): Implements countermeasures based on suggestions from the server, such as retraining employees on usage guidelines or providing emotional care support.

[0307] Example 2

[0308] 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."

[0309] Managing the appropriate use of generative AI services poses a challenging challenge: maintaining digital well-being by taking into account users' emotional states while ensuring compliance and security. Specifically, it is necessary not only to prevent excessive use of generative AI services and access to unauthorized services, but also to provide appropriate countermeasures in response to changes in users' emotions. However, an efficient system for comprehensively managing these issues is lacking.

[0310] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0311] In this invention, the server is located between the in-house network and the Internet and includes means for monitoring usage of the generated AI service, means for recording usage data of the generated AI service, means for detecting compliance violations and security violations in the use of the generated AI service, means for issuing alerts for excessive use of the generated AI service, means for generating reports based on usage of the generated AI service, means for proposing recommended actions for excessive use of the generated AI service, means for analyzing and recording the user's emotional state, and means for proposing countermeasures according to usage based on the emotional data. This makes it possible to manage appropriate use of the generated AI service, ensure compliance and security, and provide countermeasures based on the user's emotional state.

[0312] An "internal network" is a network to which computers and devices within a company or organization are connected, allowing for internal data communication and resource sharing.

[0313] The "Internet" is a huge global network that interconnects computer networks all over the world, allowing data to be sent and received and information to be shared.

[0314] A "generative AI service" is an online service that uses a generative AI model to generate content such as text, images, or audio.

[0315] "Usage monitoring means" means systems or software that have the ability to monitor the use of generative AI services in real time and track access and frequency of use.

[0316] "Means for recording usage data" refers to a function that stores information about the use of the generative AI service (such as start time, end time, and type of service) in a database or log.

[0317] "Means for detecting compliance and security violations" refers to systems and algorithms that detect when the use of the generative AI services provided violates the standards and security policies of the company or organization.

[0318] "Means for issuing alert notifications regarding excessive use" refers to a function that sends an alert when use of the generative AI service exceeds a pre-set standard.

[0319] The "means for generating usage-based reports" is a function that creates and reports weekly or monthly usage reports based on collected usage data of the generation AI service.

[0320] "Means for suggesting recommended actions" is a function that provides specific countermeasures and improvement measures based on usage data and emotional state of the generating AI service.

[0321] The "means for analyzing and recording emotional state" is a function that analyzes the user's stress level and emotional changes using sensors and input data, and stores the results in a database.

[0322] The "means for proposing countermeasures based on emotional data" is a function that provides countermeasures or improvements that are appropriate for the user's emotional state based on the analyzed emotional data.

[0323] This invention relates to a system for appropriately managing the usage of generative AI services. This system is located between an internal company network and the Internet, and has the function of monitoring and recording the usage of generative AI services using data from servers, terminals, and users, and detecting compliance violations and security violations.

[0324] Initial Setup

[0325] The user (administrator) logs in to the server and accesses the administration screen to set up a list of permitted generative AI services. For example, services such as "Service A," "Service B," and "Service C" are added to the permitted list. Next, usage criteria and alert conditions are set. The user also sets up emotional data recording, specifying the items for which data is to be collected, primarily stress, elation, and fatigue.

[0326] Traffic Monitoring

[0327] The server monitors all traffic from the internal network to the Internet. For this purpose, network traffic analysis tools (e.g., Wireshark, Suricata) are used. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it checks whether the service is on the authorized list and allows its use. Access to the unauthorized "ServiceD" is blocked.

[0328] Usage record

[0329] The server records usage information for the generated AI service—such as the start and end times, and the type of service used—in a database. For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. Additionally, an emotion engine (e.g., IBM Watson, Affectiva) is used to analyze the user's emotional state, and that data is also recorded. For example, stress levels and fatigue levels are recorded.

[0330] Report Generation

[0331] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[0332] Real-time alerts

[0333] The server generates real-time alerts when usage of the generative AI service exceeds a set threshold or when a user's emotions indicate a specific state—for example, a high stress level. For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[0334] Recommended actions

[0335] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0336] Examples of specific examples and prompts

[0337] The administrator logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list. The system is set to generate an alert if usage exceeds three hours per day or if a high stress level is reached. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A as usage that exceeds the standard. Then, at the end of the week, a report is sent to the administrator stating that employee A used "Service A" for a total of 15 hours and that the emotion data indicates high stress. The server then suggests to the administrator that they review employee A's usage time and take measures to manage stress.

[0338] Example prompt sentence:

[0339] Add "ServiceA" and "ServiceB" to the allow list and set an alert to be generated when the usage time exceeds 3 hours per day or when a high stress level is reached. Based on this, you can monitor employee usage and generate appropriate reports.

[0340] The system aims to maintain employees' digital well-being by monitoring the appropriate use of generative AI services, maintaining compliance and security, and taking into account the user's emotional state.

[0341] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0342] Step 1:

[0343] The user performs the initial setup

[0344] Input: Administrator credentials, list of allowed generative AI services, usage criteria, alert conditions, emotion data recording settings

[0345] Specific behavior:

[0346] The user (administrator) enters authentication information (user name and password) to log in to the server.

[0347] Access the admin panel and add services such as "ServiceA", "ServiceB", and "ServiceC" to the allow list.

[0348] Set usage criteria and alert conditions (if daily usage exceeds 3 hours or if high stress levels are reached).

[0349] Configure emotional data recording settings and specify the type of emotional data to collect (e.g., stress, elation, fatigue).

[0350] Output: The configured permission list, usage criteria, alert conditions, and emotion data recording settings are saved on the server.

[0351] Step 2:

[0352] The server monitors all traffic from the internal network to the Internet.

[0353] Input: Network traffic data

[0354] Specific behavior:

[0355] The server uses network traffic analysis tools (e.g., Wireshark, Suricata) to monitor communication packets in real time.

[0356] To detect access to generative AI services, filtering is performed based on specific domain names, IP addresses, and URL patterns.

[0357] Output: Access log to the generation AI service

[0358] Step 3:

[0359] The server decides whether to allow or deny the service.

[0360] Input: Allow list, access logs for generated AI services

[0361] Specific behavior:

[0362] The server checks whether the destination of the access to the generated AI service in the access log is included in the configured permission list.

[0363] For example, it detects access to "ServiceA" from an employee's device and allows that traffic if it is included in the allowed list, while blocking access to unauthorized "ServiceD."

[0364] Output: Log of allowed and blocked accesses

[0365] Step 4:

[0366] Server-generated records of AI service usage

[0367] Input: Access logs of permitted and prohibited access, start and end times of permitted AI generation services, and service types

[0368] Specific behavior:

[0369] The server records the start and end times of authorized access to the generated AI service, as well as the type of service used.

[0370] For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[0371] Output: Generated AI service usage database entries

[0372] Step 5:

[0373] The server uses an emotion engine to analyze and record the user's emotional state.

[0374] Input: User emotional data (e.g., stress level, elation, fatigue)

[0375] Specific behavior:

[0376] The server uses an emotion engine (e.g., IBM Watson, Affectiva) to analyze emotion data obtained from sensors and user input.

[0377] For example, analyze employee A's stress level and record the results in a database.

[0378] Output: A database entry of the analyzed sentiment data

[0379] Step 6:

[0380] The server generates weekly and monthly reports

[0381] Input: Usage data of the generated AI service, emotion data

[0382] Specific behavior:

[0383] The server aggregates the collected usage data and emotion data of the generative AI service and creates a report in a specified format.

[0384] For example, a report can be generated that compiles information such as usage over the course of a week, emotional state, and number of alerts.

[0385] Output: Generated weekly and monthly reports

[0386] Step 7:

[0387] Server generates real-time alerts

[0388] Input: Set criteria, usage data of the generating AI service, and emotional data

[0389] Specific behavior:

[0390] The server checks whether the usage of the generative AI service meets the criteria if it exceeds the set threshold or detects a specific emotional state, such as a high stress level.

[0391] For example, if employee B uses "Service B" for four hours and shows a high stress level, check whether the alert conditions are met.

[0392] If the alert conditions are met, an alert will be sent to the administrator and relevant employees via email or in-system notification.

[0393] Output: The generated alert notification

[0394] Step 8:

[0395] The server proposes recommended actions

[0396] Input: Usage data of the generated AI service, emotion data, and set countermeasures

[0397] Specific behavior:

[0398] The server analyzes excessive use of generative AI services and specific emotional states, and generates specific countermeasures and improvement measures.

[0399] For example, suggestions may be made such as "Suggest that employee C review the frequency of use of the generative AI service" or "Recommend that employee D take a break to relieve stress."

[0400] The administrator will be notified of the suggestions via email or dashboard.

[0401] Output: Sending a recommended action notification

[0402] (Application example 2)

[0403] 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."

[0404] As the use of generative AI services rapidly expands, companies are required to properly manage their use of generative AI services and prevent compliance and security violations. It is also important to monitor employee stress and fatigue caused by excessive use of generative AI services and help them manage their health. The present invention provides a system to solve these problems.

[0405] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0406] In this invention, the server is located between the internal network and the Internet and includes means for monitoring usage of the generating AI service, means for recording usage data of the generating AI service, means for detecting compliance violations and security violations in the use of the generating AI service, means for issuing alerts for excessive use of the generating AI service, means for generating reports based on usage of the generating AI service, means for proposing recommended actions for excessive use of the generating AI service, and means for monitoring the user's emotional state and issuing warnings or recommending actions based on the emotional data.This enables companies to effectively monitor and manage the use of the generating AI service, ensuring compliance and security, while taking appropriate measures that take into account the emotional state and health of employees.

[0407] An "internal network" refers to a computer network used within a company or organization, and is a closed network that is different from the Internet.

[0408] "Generative AI services" refer to services that automatically generate content or data using artificial intelligence technology.

[0409] "Means for monitoring usage" refers to a device or program that collects information about the use of generative AI services and monitors the duration and frequency of use in real time.

[0410] "Means for recording usage data" refers to a device or program that records the usage history of the generative AI service in detail and stores it in a state that can be analyzed later.

[0411] "Means for detecting compliance or security violations" means devices or programs for determining whether the use of generative AI services violates company regulations or security policies and for detecting violations.

[0412] "Means for providing alert notifications regarding excessive use" refers to a device or program that issues a warning to administrators or users when use of the generative AI service exceeds a specified threshold.

[0413] A "means for generating usage-based reports" is a device or program that periodically creates a report summarizing usage status based on collected usage data of the generation AI service.

[0414] A "means for proposing recommended actions" is a device or program that suggests appropriate measures to administrators or users in the event of excessive use of generative AI services or other concerns.

[0415] "Means for monitoring emotional states and issuing warnings or recommending actions based on emotional data" refers to a device or program that analyzes a user's emotional state in real time and provides appropriate warnings or countermeasures based on that information.

[0416] This paper describes a method for building a system that effectively manages and monitors the use of generative AI services based on this invention. It also describes the specific system configuration, hardware, and software used for this purpose.

[0417] System Configuration

[0418] The system mainly includes the following elements:

[0419] 1. A server located between the company network and the Internet

[0420] The server monitors all traffic from the internal network to the internet. If it detects access to a generative AI service, it checks whether that service is on an allow list. Access to unauthorized services is blocked.

[0421] 2. Device that records usage of the AI ​​service

[0422] The server records detailed usage data of the generated AI service (such as start time, end time, and type of service), including the duration and frequency of each service used by the user.

[0423] 3. Software that detects compliance and security violations

[0424] Software installed on the server analyzes usage data generated by AI services and automatically detects compliance and security violations.

[0425] 4. Emotion Engine

[0426] This engine is used to analyze the user's emotional state by analyzing the user's heart rate data, facial expressions, and voice tone in real time, and recording the user's stress level and fatigue level.

[0427] 5. Report generation function

[0428] The server periodically generates usage reports based on the collected data, which are emailed to administrators on a weekly and monthly basis.

[0429] 6. Real-time alert function

[0430] If usage or changes in emotional state exceeding set standards are detected, the server generates an alert in real time and notifies the administrator and the relevant user.

[0431] 7. Recommended Actions

[0432] If excessive use of generative AI services or high stress levels are detected, the server will suggest specific countermeasures to users and administrators.

[0433] Hardware and software used

[0434] Hardware

[0435] A server that monitors traffic on the company's internal network

[0436] Smartphones and wearable devices for collecting user emotion data

[0437] software

[0438] Network monitoring software (NetworkMonitor library)

[0439] Software for analyzing emotional states (EmotionEngine library)

[0440] Alert notification software (AlertService library)

[0441] Report generation software (ReportGenerator library)

[0442] Specific examples

[0443] For example, consider a situation where Employee A is using a smartphone app to monitor their use of "Service A." Employee A initiates a connection to the generative AI service using the prompt "Connect to Service A." The app is configured to send an alert if the user uses the app for more than three hours or if the user experiences high stress. An example prompt is shown below:

[0444] "Perform sentiment analysis using the following data to determine your current stress level: [heart rate data, facial expression images, voice tone]"

[0445] The system enables businesses to effectively manage the use of generative AI services, ensuring compliance and security while maintaining the digital well-being of their employees.

[0446] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0447] Step 1:

[0448] The server monitors all traffic on the company's internal network and detects access to the generative AI service. The input is network traffic data, and the output is detected access information for the generative AI service. This traffic data is analyzed to identify which users are accessing which generative AI services.

[0449] Step 2:

[0450] The server checks whether the detected generated AI service is included in the allow list. The input is the access information of the generated AI service, which is the output of step 1, and the output is an instruction to allow or block access. Access to generated AI services that are not included in the allow list is blocked.

[0451] Step 3:

[0452] The device records usage data of the generated AI service. The input is the usage information of the generated AI service identified in step 1, and the output is a detailed usage record such as the start time, end time, and type of service. This data is stored in a database.

[0453] Step 4:

[0454] The server analyzes the usage data of the generated AI service and detects compliance and security violations. The input is the usage data obtained in step 3, and the output is information on whether or not there is a violation. If a violation is detected, the administrator is notified.

[0455] Step 5:

[0456] The emotion engine monitors the user's emotional state and issues warnings or recommends actions based on the emotional data. The input is the user's heart rate data, facial expression images, and voice tone, and the output is the analysis result of the user's emotional state. If high stress or fatigue is detected, the server will suggest appropriate actions.

[0457] Step 6:

[0458] The server generates a report based on the usage of the generative AI service. The input is the data collected in Steps 3 and 5, and the output is a detailed usage report. This report is sent to the administrator on a weekly and monthly basis.

[0459] Step 7:

[0460] The real-time alert function allows the server to immediately generate an alert if it detects usage of the generative AI service exceeding set standards or a change in a specific emotional state. The input is the data from Steps 3 and 5, and the output is a warning message. This allows users and administrators to be notified in real time.

[0461] Step 8:

[0462] If the server detects excessive use of the generative AI service or a high level of stress, it will propose specific countermeasures to the user or administrator. The input is the warning data from Step 7, and the output is specific recommended actions. This allows the user to take appropriate actions such as taking appropriate breaks or reviewing the frequency of use.

[0463] 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.

[0464] 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.

[0465] 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.

[0466] [Second embodiment]

[0467] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0468] 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.

[0469] 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).

[0470] 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.

[0471] 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.

[0472] 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).

[0473] 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.

[0474] 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.

[0475] 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.

[0476] 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.

[0477] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0478] 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."

[0479] The present invention is a system for appropriately managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet and monitors and records employee usage of multiple different generative AI services in real time.

[0480] The present invention is carried out as follows.

[0481] 1. Initial Setup

[0482] The user (administrator) first logs in to the server and sets up a list of allowed generative AI services. For example, the administrator adds services such as "ServiceA," "ServiceB," and "ServiceC" to the allowed list. The administrator can also set usage criteria and alert conditions (e.g., more than three hours of use per day).

[0483] 2. Traffic Monitoring

[0484] The server monitors all traffic from the company network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if an employee's device accesses "ServiceA," the traffic is allowed because it is included in the authorization list. On the other hand, access to "ServiceD," which is not authorized, is blocked.

[0485] 3. Records of usage

[0486] The server records detailed usage information for the AI ​​service (start time, end time, type of service, etc.) For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[0487] 4. Report Generation

[0488] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details such as each employee's usage time, type of usage, and the number of alerts generated.

[0489] 5. Real-time alerts

[0490] The server generates real-time alerts when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B.

[0491] 6. Recommended Action Suggestion

[0492] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0493] Specific examples

[0494] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours per day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that employee A review his or her usage time and, if necessary, retrain him or her on the usage guidelines for the generation AI service.

[0495] In this way, the system aims to monitor the appropriate use of generative AI services, maintaining compliance and security while preserving employees' digital well-being.

[0496] The processing flow will be explained below.

[0497] Step 1:

[0498] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[0499] Step 2:

[0500] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[0501] Step 3:

[0502] User (Administrator): Sets usage criteria and alert conditions. For example, you can set "Generate an alert if usage time exceeds 3 hours per day."

[0503] Step 4:

[0504] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[0505] Step 5:

[0506] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[0507] Step 6:

[0508] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[0509] Step 7:

[0510] Server: Saves the collected data in a database. For example, data such as "Employee A, Service A, 10:00-11:00" is recorded in the database.

[0511] Step 8:

[0512] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, number of alerts, etc.

[0513] Step 9:

[0514] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[0515] Step 10:

[0516] Server: Generates alerts in real time when an employee's AI service usage exceeds a set threshold. For example, if employee B uses "Service B" for four hours in one day, an alert is generated to notify the administrator and employee B.

[0517] Step 11:

[0518] Server: If excessive use of generated AI is detected, the server will propose specific countermeasures to the administrator. For example, it will recommend that employee C undergo user training.

[0519] Step 12:

[0520] User (Administrator): Implements countermeasures based on suggestions from the server. For example, re-educating employees about usage guidelines and setting usage time limits.

[0521] Example 1

[0522] 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."

[0523] The use of generative AI services is increasing in modern corporate environments. However, excessive use of generative AI services by employees may increase compliance violations and security risks. There are also concerns that excessive use may negatively impact employees' digital well-being. Furthermore, companies must properly manage generative AI services, and effective monitoring and control measures are needed.

[0524] 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.

[0525] In this invention, the server is located between the internal network and the Internet and includes: means for monitoring usage of the generating AI service; means for recording usage data of the generating AI service; means for detecting compliance violations and security violations in the use of the generating AI service; means for issuing alerts for excessive use of the generating AI service; means for generating reports based on usage of the generating AI service; means for proposing recommended actions for excessive use of the generating AI service; means for an administrator to log in to the server and set a list of permitted services; means for the administrator to set usage criteria and alert conditions; means for monitoring all traffic from the internal network to the Internet in real time to confirm whether access to the generating AI service is permitted; and means for determining whether access to a service is permitted. This enables companies to properly manage the use of the generating AI service, maintain compliance and security, maintain employee digital well-being, and improve productivity.

[0526] An "internal network" is a computer network used within a company, and is a communications infrastructure for connecting internal computers, servers, and various devices to each other.

[0527] The "Internet" is a huge data communications network that interconnects computer networks all over the world, and is an infrastructure for exchanging information and providing services.

[0528] "Generative AI services" refer to online services that use artificial intelligence technology to generate various types of data, such as text generation, image generation, and voice synthesis.

[0529] "Usage status" refers to various log information regarding the use of the generative AI service, including, specifically, the start time of use, end time, type of service, number of uses, etc.

[0530] "Violation of compliance" refers to any act that goes against the laws, regulations, or guidelines established by a company or organization, and particularly refers to inappropriate operations in business processes or information management.

[0531] A "security breach" refers to any act that threatens the security of an information system, such as information leakage, tampering, or unauthorized access.

[0532] An "alert notification" is a warning message that the system automatically sends when set criteria or conditions are met, and is mainly notified via email or dashboard.

[0533] "Usage Data" means all recorded information relating to the use of the Generative AI Services, including data indicating which services a particular user used and to what extent.

[0534] A "report" is a document or digital file that contains aggregated results based on usage of the Generative AI Service, including details such as usage time, number of uses, and number of alerts.

[0535] "Recommended actions" are specific measures or countermeasures that the system suggests when certain conditions are met, such as strengthening usage restrictions or implementing educational programs.

[0536] An "administrator" is a user who has the authority to configure and monitor the system, check reports, etc., and primarily refers to the information systems department or security officer within a company.

[0537] "Traffic monitoring" refers to the act of observing data communications on a network in real time and detecting specific information or patterns, and is primarily used to improve network security and detect unauthorized access.

[0538] "Access determination" is the process of detecting a specific access request in network traffic and determining whether it is permitted.

[0539] This invention relates to a system for appropriately managing the use of generative AI services within a company. Specifically, it utilizes elements of servers, users (administrators), and terminals to monitor the usage of generative AI services, record data, detect compliance and security violations, issue alerts for excessive usage, generate reports, and propose recommended actions.

[0540] Initial Setup

[0541] A user (administrator) first logs in to the server, which is usually an authentication process using a username and password. The server provides a web interface, and the user accesses the administration page using a browser.

[0542] Administrators set an allow list for the AI-generated services. Specifically, administrators enter the names of the allowed services (e.g., "ServiceA," "ServiceB," and "ServiceC") through a web interface and add them to the list. Administrators also set usage criteria and alert conditions, such as generating an alert if usage exceeds three hours per day.

[0543] Traffic monitoring and access control

[0544] The server uses packet capture software (such as Wireshark or Tcpdump) to monitor all traffic from the internal network to the Internet in real time. The server detects access to the generated AI service in the traffic and checks whether the access is authorized. Access to authorized services is allowed, while access to unauthorized services is blocked.

[0545] Usage record

[0546] The server records the usage of the detected AI service in detail, including the start and end times of use, the type of service, etc. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM, that information is saved in the database. This allows data to be accumulated for later usage analysis.

[0547] Generate reports

[0548] The server generates weekly and monthly reports based on the collected data. These reports are automatically sent to administrators by email. The reports contain detailed information such as the usage time, type of usage, and number of alerts for each employee. For example, an administrator can receive a report stating that "Employee A used Service A for a total of 15 hours during this period."

[0549] Real-time alerts

[0550] The server generates a real-time alert when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B. This alert is notified via email or dashboard.

[0551] Recommended actions

[0552] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0553] Examples of specific examples and prompts

[0554] As a specific example of operation, consider the case where a user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours in a day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the standard time has been exceeded. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that they review employee A's usage time and re-educate them on the usage guidelines for the generation AI service.

[0555] Prompt Sentence Examples

[0556] "Please explain how to set up an alert to be generated if an employee uses an authorized AI generation service for more than three hours, and what action will be taken if Employee A uses the service for more than three hours."

[0557] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0558] Step 1: Initial Setup

[0559] Inputs: Administrator credentials, list of authorized AI generation services, usage criteria, alert conditions

[0560] Specific behavior:

[0561] 1. The user (administrator) logs in to the server.

[0562] The administrator enters a username and password to establish access to the server through authentication.

[0563] Output: Admin interface after successful login

[0564] 2. Administrators set a list of permitted generative AI services.

[0565] The administrator uses the web interface to enter "ServiceA", "ServiceB", and "ServiceC" into the allow list.

[0566] Output: The allow list is saved on the server.

[0567] 3. Administrators set usage criteria and alert conditions.

[0568] For example, an administrator can set up an alert to be generated if the generative AI service is used for more than three hours per day.

[0569] Output: Usage criteria and alert conditions are saved to the server

[0570] Step 2: Traffic monitoring and access control

[0571] Input: Internal network traffic data

[0572] Specific behavior:

[0573] 1. The server monitors traffic in real time.

[0574] The server uses packet capture software (e.g., Wireshark, Tcpdump) to monitor all traffic from the internal network to the Internet.

[0575] Output: Traffic data based on the watch list

[0576] 2. The server detects access to the generative AI service.

[0577] Analyze HTTP requests and API calls to the generative AI service to detect specific service access.

[0578] Output: Detected access list

[0579] 3. The server checks whether access to the service is permitted.

[0580] It checks against the permission list to determine whether access is to an authorized service or an unauthorized service.

[0581] Output: Allowed and blocked access lists

[0582] Step 3: Record usage

[0583] Input: Allowed access list, start time, end time, service type

[0584] Specific behavior:

[0585] 1. The server records the start time of use.

[0586] The server records the time of first access and stores in the database that the generative AI service has begun to be used.

[0587] Output: Recorded usage start time data

[0588] 2. The server records the end time of use.

[0589] The time when the access ended is saved in the database.

[0590] Output: Recorded end time data

[0591] 3. The server records the type of service.

[0592] The name and type of generative AI service used is recorded in a database.

[0593] Output: Recorded service type data

[0594] Step 4: Generate reports

[0595] Input: Collected usage data

[0596] Specific behavior:

[0597] 1. The server generates weekly and monthly reports.

[0598] Aggregate usage data stored in the database and generate weekly and monthly reports.

[0599] Output: Generated weekly and monthly reports

[0600] 2. The server sends the report to the administrator.

[0601] Once the report is generated, it will be automatically emailed to the administrator.

[0602] Output: Report sent to administrator's mailbox

[0603] 3. The report includes usage time and number of alerts.

[0604] Detailed information is provided on each employee's usage time, type of usage, and the number of alerts that occur when standards are exceeded.

[0605] Output: Detailed report information

[0606] Step 5: Real-time alerts

[0607] Input: Current usage time data, set criteria

[0608] Specific behavior:

[0609] 1. The server detects usage that exceeds the usage criteria.

[0610] It monitors usage time in real time and detects excessive usage if it exceeds the set standard.

[0611] Output: Excessive usage detection information

[0612] 2. The server generates and notifies alerts in real time.

[0613] Based on the detection results, an alert is immediately sent by email to administrators and relevant employees.

[0614] Output: Real-time alert notification

[0615] Step 6: Propose recommended actions

[0616] Input: Excessive usage detection information, administrator settings information

[0617] Specific behavior:

[0618] 1. The server makes recommendations when excessive usage is detected.

[0619] Analyze the data and generate recommendations to maintain compliance.

[0620] Output: Recommended action plan

[0621] 2. The server notifies the administrator of the recommended course of action.

[0622] Recommendations are sent to administrators via email and dashboard.

[0623] Output: Recommendation notification to administrator

[0624] 3. We suggest reviewing the frequency of use of generative AI services and providing user education.

[0625] As a concrete countermeasure, we will propose a review of the frequency with which employees use AI services and, if necessary, a retraining program.

[0626] Output: Notification of specific countermeasures

[0627] (Application example 1)

[0628] 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."

[0629] In recent years, the use of generative AI services within companies has been increasing, but without proper monitoring and management, there is a risk of unauthorized or excessive use, which could result in resource waste and security risks.There is also a need for a system that can monitor the usage of generative AI services in real time and promptly notify administrators.

[0630] 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.

[0631] In this invention, the server is located between the company's internal network and the Internet and includes: means for monitoring usage of the generation AI service; means for recording usage data of the generation AI service; means for detecting compliance violations and security violations in the use of the generation AI service; means for issuing alerts regarding excessive use of the generation AI service; means for generating reports based on usage of the generation AI service; means for proposing recommended actions regarding excessive use of the generation AI service; means for monitoring and managing usage of the generation AI service in real time using an application running on a smartphone; means for issuing alerts to managers and employees via email; and means for automatically generating usage reports on specific days of the week and sending them to managers. This allows for appropriate monitoring of usage of the generation AI service within a company, preventing fraudulent and excessive use, and enabling real-time problem detection and rapid response.

[0632] An "internal network" refers to a network environment within a company in which computers, servers, communication devices, etc. are interconnected.

[0633] The "Internet" refers to a huge network that interconnects computer networks all over the world.

[0634] "Generative AI services" refer to online services that use artificial intelligence technology to generate data and analyze information.

[0635] "Monitoring means" refers to the function that allows the system to check specific situations and operations in real time and check for any abnormalities.

[0636] "Recording means" refers to a function for saving specific data and log information.

[0637] "Detection means" refers to the function of automatically recognizing and determining specific situations or conditions.

[0638] "Alert notification means" refers to a function for sending notifications to administrators and relevant parties when certain conditions are met.

[0639] "Report generation means" refers to a function for periodically creating reports based on collected data.

[0640] "Recommended action suggestion means" refers to a function that presents appropriate countermeasures or actions depending on a specific situation.

[0641] "Applications running on a smartphone" refers to software programs that are installed and run on a mobile information terminal.

[0642] "Means of monitoring and management in real time" refers to the ability to instantly check the current situation and take action or respond as necessary.

[0643] "Means for notifying alerts via email" refers to a function for notifying relevant parties of alerts via email.

[0644] "Means for automatically generating reports on a specific day of the week and sending them to the administrator" refers to a function that automatically generates reports according to a schedule on a specific day of the week each week and sends them to the administrator.

[0645] overview

[0646] This invention is a system for managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet, monitors and records the use of generative AI services, and detects compliance and security violations. It also issues alerts for excessive use, periodically generates reports, and proposes recommended actions to administrators. A notable feature of this system is that it monitors and manages the use of generative AI services in real time using an application running on a smartphone.

[0647] System Configuration

[0648] The system consists of the following major hardware and software components:

[0649] 1. Server

[0650] Monitor traffic between your internal network and the internet.

[0651] A database (e.g., AWS RDS, Google Cloud SQL) for recording and managing usage data.

[0652] Performs processing for alert notifications and report generation.

[0653] It connects to smartphone applications via API.

[0654] 2. Smartphone

[0655] Devices used by IT administrators.

[0656] Run specific applications and monitor and manage the usage of generative AI services in real time.

[0657] It provides an interface for receiving alert notifications and taking necessary actions.

[0658] Processing Details

[0659] The server monitors traffic from the company's internal network to the Internet in real time, detects access to the AI ​​generation service, and records usage data for authorized AI generation services and stores the usage status in a database.

[0660] If an employee attempts to access the AI ​​generation service without authorization, the server immediately blocks that access. If usage time exceeds the set threshold, the server generates an alert in real time and notifies the administrator and the employee via email.

[0661] On a specific day of the week (e.g., every Monday), the server automatically generates a weekly usage report and sends it to the administrator, detailing the usage time of each employee, the type of AI-generating service used, the number of alerts generated, and so on.

[0662] Usage example

[0663] For example, if employee C uses "Generation AI Service A" from 9:00 AM to 1:00 PM, the server records that usage. As the usage time exceeds the set standard of three hours, the server immediately sends an alert to the administrator and employee C. In addition, every Monday, a report summarizing the previous week's usage is automatically generated and sent to the administrator. Based on this report, the administrator can review employee C's usage and take appropriate measures as necessary.

[0664] Example prompt sentence:

[0665] "Write a Python program that monitors employee usage of the Generative AI service and sends real-time alerts if it exceeds a set threshold."

[0666] In this way, the present invention is a system that properly monitors and manages the use of generative AI services, prevents fraudulent or excessive use, and enables rapid response.

[0667] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0668] Step 1:

[0669] Perform initial setup. The user (administrator) logs in to the server and sets up a list of authorized generative AI services, including usage criteria and alert conditions.

[0670] Input: A list of allowed generation AI services, e.g. "ServiceA", "ServiceB", "ServiceC".

[0671] Output: Saves the configured allow list and usage criteria.

[0672] How it works: Administrators use a web interface to select permitted services and enter usage time limits and alert conditions.

[0673] Step 2:

[0674] Traffic monitoring: The server monitors all traffic from the internal network to the Internet in real time.

[0675] Input: Network traffic data.

[0676] Output: Access data to generative AI services.

[0677] Specific operation: Analyzes packet data and identifies which service is being accessed.

[0678] Step 3:

[0679] Verify access to generative AI services: The server checks whether access to the detected generative AI service is on an allow list.

[0680] Input: Access data to the generative AI service.

[0681] Output: Decision to allow or block.

[0682] Specific operation: Access data is compared against an allow list and access to unauthorized services is blocked.

[0683] Step 4:

[0684] Record usage status. The server records the start time, end time, and type of service of the AI ​​generation service in detail.

[0685] Input: Usage data of the generation AI service for which access has been granted.

[0686] Output: Saving usage data to a database.

[0687] Specific operation: Record the start and end times of use for each service and save them in a database.

[0688] Step 5:

[0689] Monitor alert conditions: The server monitors whether usage exceeds established thresholds based on usage.

[0690] Input: Usage data and configured usage criteria.

[0691] Output: Generate an alert if the criteria is exceeded.

[0692] Specific operation: Usage time is accumulated, and if it exceeds the set standard, an email notification is sent to the administrator and the relevant employee.

[0693] Step 6:

[0694] Generate reports: The server automatically generates weekly and monthly usage reports.

[0695] Input: Usage data of the generative AI service.

[0696] Output: Generate and email usage reports.

[0697] Specific operation: Usage data is collected, a report is created summarizing each employee's usage, and the report is sent to the administrator via email.

[0698] Step 7:

[0699] The server proposes recommended actions. If excessive use of the generative AI service is detected, the server will propose countermeasures to the administrator.

[0700] Input: Excessive usage data.

[0701] Output: Proposal generation and notification.

[0702] Specific actions: In the event of excessive use, the system generates a message suggesting re-education of specific users on usage guidelines or limiting usage time, and notifies the administrator.

[0703] 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.

[0704] This invention is a system that appropriately manages the usage of generative AI services and is placed between an internal company network and the Internet. It uses data from servers, terminals, and users to monitor and record the usage of generative AI services and detect compliance and security violations. Furthermore, by combining it with an emotion engine, it monitors changes in the user's emotions and provides appropriate countermeasures according to the usage situation.

[0705] 1. Initial Setup

[0706] The user (administrator) logs in to the server and configures a list of authorized generative AI services. For example, add services such as "ServiceA," "ServiceB," and "ServiceC" to the authorization list. In addition, the user configures usage criteria, alert conditions, and emotional data recording settings.

[0707] 2. Traffic Monitoring

[0708] The server monitors all traffic from the internal network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it allows the traffic because it is included in the authorization list. On the other hand, access to the unauthorized "ServiceD" is blocked.

[0709] 3. Records of usage

[0710] The server records the usage of the AI ​​service in detail (start time, end time, type of service, etc.). For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. In addition, the emotion engine analyzes the user's emotional state (e.g., stress, elation, fatigue, etc.), which is also recorded.

[0711] 4. Report Generation

[0712] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[0713] 5. Real-time alerts

[0714] The server generates alerts in real time when an employee's use of the AI-generated service exceeds a set threshold or when the user's emotions indicate a specific state (e.g., high stress level). For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[0715] 6. Recommended Action Suggestion

[0716] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0717] Specific examples

[0718] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, and configures it to generate an alert if the usage time exceeds three hours per day or if a high stress level is reached. If employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period and that the emotion data indicates high stress. The server then suggests to the administrator that employee A review his usage time and take measures to manage his stress.

[0719] In this way, the system aims to monitor the appropriate use of generative AI services, maintain compliance and security, and also take into account the emotional state of the user, thereby maintaining employees' digital well-being.

[0720] The processing flow will be explained below.

[0721] Step 1:

[0722] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[0723] Step 2:

[0724] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[0725] Step 3:

[0726] User (Administrator): Sets usage criteria and alert conditions. For example, "Generate an alert if daily usage exceeds three hours." Also, sets emotional data recording settings and alert criteria for specific emotional states.

[0727] Step 4:

[0728] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[0729] Step 5:

[0730] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[0731] Step 6:

[0732] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[0733] Step 7:

[0734] On the device: The emotion engine collects user emotion data, for example, using facial recognition and voice analysis technologies to analyze the user's stress level and other emotional states in real time.

[0735] Step 8:

[0736] Server: The collected emotion data is stored in a database along with usage data of the AI ​​generation service. For example, data such as "Employee A, Service A, 10:00-11:00, high stress level" is recorded in the database.

[0737] Step 9:

[0738] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, alert occurrences, sentiment, etc.

[0739] Step 10:

[0740] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[0741] Step 11:

[0742] Server: Generates alerts in real time when an employee's use of the AI ​​service exceeds a set threshold or indicates a specific emotional state (e.g., high stress level). For example, if employee B uses "Service B" for 4 hours a day and indicates a high stress level, an alert will be sent immediately to the manager and employee B.

[0743] Step 12:

[0744] Server: If excessive use of the AI ​​generator or specific emotional changes are detected, the server will propose specific countermeasures to the manager. For example, "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0745] Step 13:

[0746] User (Administrator): Implements countermeasures based on suggestions from the server, such as retraining employees on usage guidelines or providing emotional care support.

[0747] Example 2

[0748] 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."

[0749] Managing the appropriate use of generative AI services poses a challenging challenge: maintaining digital well-being by taking into account users' emotional states while ensuring compliance and security. Specifically, it is necessary not only to prevent excessive use of generative AI services and access to unauthorized services, but also to provide appropriate countermeasures in response to changes in users' emotions. However, an efficient system for comprehensively managing these issues is lacking.

[0750] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0751] In this invention, the server is located between the in-house network and the Internet and includes means for monitoring usage of the generated AI service, means for recording usage data of the generated AI service, means for detecting compliance violations and security violations in the use of the generated AI service, means for issuing alerts for excessive use of the generated AI service, means for generating reports based on usage of the generated AI service, means for proposing recommended actions for excessive use of the generated AI service, means for analyzing and recording the user's emotional state, and means for proposing countermeasures according to usage based on the emotional data. This makes it possible to manage appropriate use of the generated AI service, ensure compliance and security, and provide countermeasures based on the user's emotional state.

[0752] An "internal network" is a network to which computers and devices within a company or organization are connected, allowing for internal data communication and resource sharing.

[0753] The "Internet" is a huge global network that interconnects computer networks all over the world, allowing data to be sent and received and information to be shared.

[0754] A "generative AI service" is an online service that uses a generative AI model to generate content such as text, images, or audio.

[0755] "Usage monitoring means" means systems or software that have the ability to monitor the use of generative AI services in real time and track access and frequency of use.

[0756] "Means for recording usage data" refers to a function that stores information about the use of the generative AI service (such as start time, end time, and type of service) in a database or log.

[0757] "Means for detecting compliance and security violations" refers to systems and algorithms that detect when the use of the generative AI services provided violates the standards and security policies of the company or organization.

[0758] "Means for issuing alert notifications regarding excessive use" refers to a function that sends an alert when use of the generative AI service exceeds a pre-set standard.

[0759] The "means for generating usage-based reports" is a function that creates and reports weekly or monthly usage reports based on collected usage data of the generation AI service.

[0760] "Means for suggesting recommended actions" is a function that provides specific countermeasures and improvement measures based on usage data and emotional state of the generating AI service.

[0761] The "means for analyzing and recording emotional state" is a function that analyzes the user's stress level and emotional changes using sensors and input data, and stores the results in a database.

[0762] The "means for proposing countermeasures based on emotional data" is a function that provides countermeasures or improvements that are appropriate for the user's emotional state based on the analyzed emotional data.

[0763] This invention relates to a system for appropriately managing the usage of generative AI services. This system is located between an internal company network and the Internet, and has the function of monitoring and recording the usage of generative AI services using data from servers, terminals, and users, and detecting compliance violations and security violations.

[0764] Initial Setup

[0765] The user (administrator) logs in to the server and accesses the administration screen to set up a list of permitted generative AI services. For example, services such as "Service A," "Service B," and "Service C" are added to the permitted list. Next, usage criteria and alert conditions are set. The user also sets up emotional data recording, specifying the items for which data is to be collected, primarily stress, elation, and fatigue.

[0766] Traffic Monitoring

[0767] The server monitors all traffic from the internal network to the Internet. For this purpose, network traffic analysis tools (e.g., Wireshark, Suricata) are used. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it checks whether the service is on the authorized list and allows its use. Access to the unauthorized "ServiceD" is blocked.

[0768] Usage record

[0769] The server records usage information for the generated AI service—such as the start and end times, and the type of service used—in a database. For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. Additionally, an emotion engine (e.g., IBM Watson, Affectiva) is used to analyze the user's emotional state, and that data is also recorded. For example, stress levels and fatigue levels are recorded.

[0770] Report Generation

[0771] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[0772] Real-time alerts

[0773] The server generates real-time alerts when usage of the generative AI service exceeds a set threshold or when a user's emotions indicate a specific state—for example, a high stress level. For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[0774] Recommended actions

[0775] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[0776] Examples of specific examples and prompts

[0777] The administrator logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list. The system is set to generate an alert if usage exceeds three hours per day or if a high stress level is reached. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A as usage that exceeds the standard. Then, at the end of the week, a report is sent to the administrator stating that employee A used "Service A" for a total of 15 hours and that the emotion data indicates high stress. The server then suggests to the administrator that they review employee A's usage time and take measures to manage stress.

[0778] Example prompt sentence:

[0779] Add "ServiceA" and "ServiceB" to the allow list and set an alert to be generated when the usage time exceeds 3 hours per day or when a high stress level is reached. Based on this, you can monitor employee usage and generate appropriate reports.

[0780] The system aims to maintain employees' digital well-being by monitoring the appropriate use of generative AI services, maintaining compliance and security, and taking into account the user's emotional state.

[0781] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0782] Step 1:

[0783] The user performs the initial setup

[0784] Input: Administrator credentials, list of allowed generative AI services, usage criteria, alert conditions, emotion data recording settings

[0785] Specific behavior:

[0786] The user (administrator) enters authentication information (user name and password) to log in to the server.

[0787] Access the admin panel and add services such as "ServiceA", "ServiceB", and "ServiceC" to the allow list.

[0788] Set usage criteria and alert conditions (if daily usage exceeds 3 hours or if high stress levels are reached).

[0789] Configure emotional data recording settings and specify the type of emotional data to collect (e.g., stress, elation, fatigue).

[0790] Output: The configured permission list, usage criteria, alert conditions, and emotion data recording settings are saved on the server.

[0791] Step 2:

[0792] The server monitors all traffic from the internal network to the Internet.

[0793] Input: Network traffic data

[0794] Specific behavior:

[0795] The server uses network traffic analysis tools (e.g., Wireshark, Suricata) to monitor communication packets in real time.

[0796] To detect access to generative AI services, filtering is performed based on specific domain names, IP addresses, and URL patterns.

[0797] Output: Access log to the generation AI service

[0798] Step 3:

[0799] The server decides whether to allow or deny the service.

[0800] Input: Allow list, access logs for generated AI services

[0801] Specific behavior:

[0802] The server checks whether the destination of the access to the generated AI service in the access log is included in the configured permission list.

[0803] For example, it detects access to "ServiceA" from an employee's device and allows that traffic if it is included in the allowed list, while blocking access to unauthorized "ServiceD."

[0804] Output: Log of allowed and blocked accesses

[0805] Step 4:

[0806] Server-generated records of AI service usage

[0807] Input: Access logs of permitted and prohibited access, start and end times of permitted AI generation services, and service types

[0808] Specific behavior:

[0809] The server records the start and end times of authorized access to the generated AI service, as well as the type of service used.

[0810] For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[0811] Output: Generated AI service usage database entries

[0812] Step 5:

[0813] The server uses an emotion engine to analyze and record the user's emotional state.

[0814] Input: User emotional data (e.g., stress level, elation, fatigue)

[0815] Specific behavior:

[0816] The server uses an emotion engine (e.g., IBM Watson, Affectiva) to analyze emotion data obtained from sensors and user input.

[0817] For example, analyze employee A's stress level and record the results in a database.

[0818] Output: A database entry of the analyzed sentiment data

[0819] Step 6:

[0820] The server generates weekly and monthly reports

[0821] Input: Usage data of the generated AI service, emotion data

[0822] Specific behavior:

[0823] The server aggregates the collected usage data and emotion data of the generative AI service and creates a report in a specified format.

[0824] For example, a report can be generated that compiles information such as usage over the course of a week, emotional state, and number of alerts.

[0825] Output: Generated weekly and monthly reports

[0826] Step 7:

[0827] Server generates real-time alerts

[0828] Input: Set criteria, usage data of the generating AI service, and emotional data

[0829] Specific behavior:

[0830] The server checks whether the usage of the generative AI service meets the criteria if it exceeds the set threshold or detects a specific emotional state, such as a high stress level.

[0831] For example, if employee B uses "Service B" for four hours and shows a high stress level, check whether the alert conditions are met.

[0832] If the alert conditions are met, an alert will be sent to the administrator and relevant employees via email or in-system notification.

[0833] Output: The generated alert notification

[0834] Step 8:

[0835] The server proposes recommended actions

[0836] Input: Usage data of the generated AI service, emotion data, and set countermeasures

[0837] Specific behavior:

[0838] The server analyzes excessive use of generative AI services and specific emotional states, and generates specific countermeasures and improvement measures.

[0839] For example, suggestions may be made such as "Suggest that employee C review the frequency of use of the generative AI service" or "Recommend that employee D take a break to relieve stress."

[0840] The administrator will be notified of the suggestions via email or dashboard.

[0841] Output: Sending a recommended action notification

[0842] (Application example 2)

[0843] 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."

[0844] As the use of generative AI services rapidly expands, companies are required to properly manage their use of generative AI services and prevent compliance and security violations. It is also important to monitor employee stress and fatigue caused by excessive use of generative AI services and help them manage their health. The present invention provides a system to solve these problems.

[0845] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0846] In this invention, the server is located between the internal network and the Internet and includes means for monitoring usage of the generating AI service, means for recording usage data of the generating AI service, means for detecting compliance violations and security violations in the use of the generating AI service, means for issuing alerts for excessive use of the generating AI service, means for generating reports based on usage of the generating AI service, means for proposing recommended actions for excessive use of the generating AI service, and means for monitoring the user's emotional state and issuing warnings or recommending actions based on the emotional data.This enables companies to effectively monitor and manage the use of the generating AI service, ensuring compliance and security, while taking appropriate measures that take into account the emotional state and health of employees.

[0847] An "internal network" refers to a computer network used within a company or organization, and is a closed network that is different from the Internet.

[0848] "Generative AI services" refer to services that automatically generate content or data using artificial intelligence technology.

[0849] "Means for monitoring usage" refers to a device or program that collects information about the use of generative AI services and monitors the duration and frequency of use in real time.

[0850] "Means for recording usage data" refers to a device or program that records the usage history of the generative AI service in detail and stores it in a state that can be analyzed later.

[0851] "Means for detecting compliance or security violations" means devices or programs for determining whether the use of generative AI services violates company regulations or security policies and for detecting violations.

[0852] "Means for providing alert notifications regarding excessive use" refers to a device or program that issues a warning to administrators or users when use of the generative AI service exceeds a specified threshold.

[0853] A "means for generating usage-based reports" is a device or program that periodically creates a report summarizing usage status based on collected usage data of the generation AI service.

[0854] A "means for proposing recommended actions" is a device or program that suggests appropriate measures to administrators or users in the event of excessive use of generative AI services or other concerns.

[0855] "Means for monitoring emotional states and issuing warnings or recommending actions based on emotional data" refers to a device or program that analyzes a user's emotional state in real time and provides appropriate warnings or countermeasures based on that information.

[0856] This paper describes a method for building a system that effectively manages and monitors the use of generative AI services based on this invention. It also describes the specific system configuration, hardware, and software used for this purpose.

[0857] System Configuration

[0858] The system mainly includes the following elements:

[0859] 1. A server located between the company network and the Internet

[0860] The server monitors all traffic from the internal network to the internet. If it detects access to a generative AI service, it checks whether that service is on an allow list. Access to unauthorized services is blocked.

[0861] 2. Device that records usage of the AI ​​service

[0862] The server records detailed usage data of the generated AI service (such as start time, end time, and type of service), including the duration and frequency of each service used by the user.

[0863] 3. Software that detects compliance and security violations

[0864] Software installed on the server analyzes usage data generated by AI services and automatically detects compliance and security violations.

[0865] 4. Emotion Engine

[0866] This engine is used to analyze the user's emotional state by analyzing the user's heart rate data, facial expressions, and voice tone in real time, and recording the user's stress level and fatigue level.

[0867] 5. Report generation function

[0868] The server periodically generates usage reports based on the collected data, which are emailed to administrators on a weekly and monthly basis.

[0869] 6. Real-time alert function

[0870] If usage or changes in emotional state exceeding set standards are detected, the server generates an alert in real time and notifies the administrator and the relevant user.

[0871] 7. Recommended Actions

[0872] If excessive use of generative AI services or high stress levels are detected, the server will suggest specific countermeasures to users and administrators.

[0873] Hardware and software used

[0874] Hardware

[0875] A server that monitors traffic on the company's internal network

[0876] Smartphones and wearable devices for collecting user emotion data

[0877] software

[0878] Network monitoring software (NetworkMonitor library)

[0879] Software for analyzing emotional states (EmotionEngine library)

[0880] Alert notification software (AlertService library)

[0881] Report generation software (ReportGenerator library)

[0882] Specific examples

[0883] For example, consider a situation where Employee A is using a smartphone app to monitor their use of "Service A." Employee A initiates a connection to the generative AI service using the prompt "Connect to Service A." The app is configured to send an alert if the user uses the app for more than three hours or if the user experiences high stress. An example prompt is shown below:

[0884] "Perform sentiment analysis using the following data to determine your current stress level: [heart rate data, facial expression images, voice tone]"

[0885] The system enables businesses to effectively manage the use of generative AI services, ensuring compliance and security while maintaining the digital well-being of their employees.

[0886] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0887] Step 1:

[0888] The server monitors all traffic on the company's internal network and detects access to the generative AI service. The input is network traffic data, and the output is detected access information for the generative AI service. This traffic data is analyzed to identify which users are accessing which generative AI services.

[0889] Step 2:

[0890] The server checks whether the detected generated AI service is included in the allow list. The input is the access information of the generated AI service, which is the output of step 1, and the output is an instruction to allow or block access. Access to generated AI services that are not included in the allow list is blocked.

[0891] Step 3:

[0892] The device records usage data of the generated AI service. The input is the usage information of the generated AI service identified in step 1, and the output is a detailed usage record such as the start time, end time, and type of service. This data is stored in a database.

[0893] Step 4:

[0894] The server analyzes the usage data of the generated AI service and detects compliance and security violations. The input is the usage data obtained in step 3, and the output is information on whether or not there is a violation. If a violation is detected, the administrator is notified.

[0895] Step 5:

[0896] The emotion engine monitors the user's emotional state and issues warnings or recommends actions based on the emotional data. The input is the user's heart rate data, facial expression images, and voice tone, and the output is the analysis result of the user's emotional state. If high stress or fatigue is detected, the server will suggest appropriate actions.

[0897] Step 6:

[0898] The server generates a report based on the usage of the generative AI service. The input is the data collected in Steps 3 and 5, and the output is a detailed usage report. This report is sent to the administrator on a weekly and monthly basis.

[0899] Step 7:

[0900] The real-time alert function allows the server to immediately generate an alert if it detects usage of the generative AI service exceeding set standards or a change in a specific emotional state. The input is the data from Steps 3 and 5, and the output is a warning message. This allows users and administrators to be notified in real time.

[0901] Step 8:

[0902] If the server detects excessive use of the generative AI service or a high level of stress, it will propose specific countermeasures to the user or administrator. The input is the warning data from Step 7, and the output is specific recommended actions. This allows the user to take appropriate actions such as taking appropriate breaks or reviewing the frequency of use.

[0903] 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.

[0904] 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.

[0905] 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.

[0906] [Third embodiment]

[0907] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0908] 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.

[0909] 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).

[0910] 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.

[0911] 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.

[0912] 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).

[0913] 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.

[0914] 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.

[0915] 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.

[0916] 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.

[0917] 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.

[0918] 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."

[0919] The present invention is a system for appropriately managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet and monitors and records employee usage of multiple different generative AI services in real time.

[0920] The present invention is carried out as follows.

[0921] 1. Initial Setup

[0922] The user (administrator) first logs in to the server and sets up a list of allowed generative AI services. For example, the administrator adds services such as "ServiceA," "ServiceB," and "ServiceC" to the allowed list. The administrator can also set usage criteria and alert conditions (e.g., more than three hours of use per day).

[0923] 2. Traffic Monitoring

[0924] The server monitors all traffic from the company network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if an employee's device accesses "ServiceA," the traffic is allowed because it is included in the authorization list. On the other hand, access to "ServiceD," which is not authorized, is blocked.

[0925] 3. Records of usage

[0926] The server records detailed usage information for the AI ​​service (start time, end time, type of service, etc.) For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[0927] 4. Report Generation

[0928] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details such as each employee's usage time, type of usage, and the number of alerts generated.

[0929] 5. Real-time alerts

[0930] The server generates real-time alerts when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B.

[0931] 6. Recommended Action Suggestion

[0932] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0933] Specific examples

[0934] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours per day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that employee A review his or her usage time and, if necessary, retrain him or her on the usage guidelines for the generation AI service.

[0935] In this way, the system aims to monitor the appropriate use of generative AI services, maintaining compliance and security while preserving employees' digital well-being.

[0936] The processing flow will be explained below.

[0937] Step 1:

[0938] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[0939] Step 2:

[0940] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[0941] Step 3:

[0942] User (Administrator): Sets usage criteria and alert conditions. For example, you can set "Generate an alert if usage time exceeds 3 hours per day."

[0943] Step 4:

[0944] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[0945] Step 5:

[0946] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[0947] Step 6:

[0948] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[0949] Step 7:

[0950] Server: Saves the collected data in a database. For example, data such as "Employee A, Service A, 10:00-11:00" is recorded in the database.

[0951] Step 8:

[0952] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, number of alerts, etc.

[0953] Step 9:

[0954] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[0955] Step 10:

[0956] Server: Generates alerts in real time when an employee's AI service usage exceeds a set threshold. For example, if employee B uses "Service B" for four hours in one day, an alert is generated to notify the administrator and employee B.

[0957] Step 11:

[0958] Server: If excessive use of generated AI is detected, the server will propose specific countermeasures to the administrator. For example, it will recommend that employee C undergo user training.

[0959] Step 12:

[0960] User (Administrator): Implements countermeasures based on suggestions from the server. For example, re-educating employees about usage guidelines and setting usage time limits.

[0961] Example 1

[0962] 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."

[0963] The use of generative AI services is increasing in modern corporate environments. However, excessive use of generative AI services by employees may increase compliance violations and security risks. There are also concerns that excessive use may negatively impact employees' digital well-being. Furthermore, companies must properly manage generative AI services, and effective monitoring and control measures are needed.

[0964] 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.

[0965] In this invention, the server is located between the internal network and the Internet and includes: means for monitoring usage of the generating AI service; means for recording usage data of the generating AI service; means for detecting compliance violations and security violations in the use of the generating AI service; means for issuing alerts for excessive use of the generating AI service; means for generating reports based on usage of the generating AI service; means for proposing recommended actions for excessive use of the generating AI service; means for an administrator to log in to the server and set a list of permitted services; means for the administrator to set usage criteria and alert conditions; means for monitoring all traffic from the internal network to the Internet in real time to confirm whether access to the generating AI service is permitted; and means for determining whether access to a service is permitted. This enables companies to properly manage the use of the generating AI service, maintain compliance and security, maintain employee digital well-being, and improve productivity.

[0966] An "internal network" is a computer network used within a company, and is a communications infrastructure for connecting internal computers, servers, and various devices to each other.

[0967] The "Internet" is a huge data communications network that interconnects computer networks all over the world, and is an infrastructure for exchanging information and providing services.

[0968] "Generative AI services" refer to online services that use artificial intelligence technology to generate various types of data, such as text generation, image generation, and voice synthesis.

[0969] "Usage status" refers to various log information regarding the use of the generative AI service, including, specifically, the start time of use, end time, type of service, number of uses, etc.

[0970] "Violation of compliance" refers to any act that goes against the laws, regulations, or guidelines established by a company or organization, and particularly refers to inappropriate operations in business processes or information management.

[0971] A "security breach" refers to any act that threatens the security of an information system, such as information leakage, tampering, or unauthorized access.

[0972] An "alert notification" is a warning message that the system automatically sends when set criteria or conditions are met, and is mainly notified via email or dashboard.

[0973] "Usage Data" means all recorded information relating to the use of the Generative AI Services, including data indicating which services a particular user used and to what extent.

[0974] A "report" is a document or digital file that contains aggregated results based on usage of the Generative AI Service, including details such as usage time, number of uses, and number of alerts.

[0975] "Recommended actions" are specific measures or countermeasures that the system suggests when certain conditions are met, such as strengthening usage restrictions or implementing educational programs.

[0976] An "administrator" is a user who has the authority to configure and monitor the system, check reports, etc., and primarily refers to the information systems department or security officer within a company.

[0977] "Traffic monitoring" refers to the act of observing data communications on a network in real time and detecting specific information or patterns, and is primarily used to improve network security and detect unauthorized access.

[0978] "Access determination" is the process of detecting a specific access request in network traffic and determining whether it is permitted.

[0979] This invention relates to a system for appropriately managing the use of generative AI services within a company. Specifically, it utilizes elements of servers, users (administrators), and terminals to monitor the usage of generative AI services, record data, detect compliance and security violations, issue alerts for excessive usage, generate reports, and propose recommended actions.

[0980] Initial Setup

[0981] A user (administrator) first logs in to the server, which is usually an authentication process using a username and password. The server provides a web interface, and the user accesses the administration page using a browser.

[0982] Administrators set an allow list for the AI-generated services. Specifically, administrators enter the names of the allowed services (e.g., "ServiceA," "ServiceB," and "ServiceC") through a web interface and add them to the list. Administrators also set usage criteria and alert conditions, such as generating an alert if usage exceeds three hours per day.

[0983] Traffic monitoring and access control

[0984] The server uses packet capture software (such as Wireshark or Tcpdump) to monitor all traffic from the internal network to the Internet in real time. The server detects access to the generated AI service in the traffic and checks whether the access is authorized. Access to authorized services is allowed, while access to unauthorized services is blocked.

[0985] Usage record

[0986] The server records the usage of the detected AI service in detail, including the start and end times of use, the type of service, etc. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM, that information is saved in the database. This allows data to be accumulated for later usage analysis.

[0987] Generate reports

[0988] The server generates weekly and monthly reports based on the collected data. These reports are automatically sent to administrators by email. The reports contain detailed information such as the usage time, type of usage, and number of alerts for each employee. For example, an administrator can receive a report stating that "Employee A used Service A for a total of 15 hours during this period."

[0989] Real-time alerts

[0990] The server generates a real-time alert when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B. This alert is notified via email or dashboard.

[0991] Recommended actions

[0992] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[0993] Examples of specific examples and prompts

[0994] As a specific example of operation, consider the case where a user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours in a day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the standard time has been exceeded. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that they review employee A's usage time and re-educate them on the usage guidelines for the generation AI service.

[0995] Prompt Sentence Examples

[0996] "Please explain how to set up an alert to be generated if an employee uses an authorized AI generation service for more than three hours, and what action will be taken if Employee A uses the service for more than three hours."

[0997] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0998] Step 1: Initial Setup

[0999] Inputs: Administrator credentials, list of authorized AI generation services, usage criteria, alert conditions

[1000] Specific behavior:

[1001] 1. The user (administrator) logs in to the server.

[1002] The administrator enters a username and password to establish access to the server through authentication.

[1003] Output: Admin interface after successful login

[1004] 2. Administrators set a list of permitted generative AI services.

[1005] The administrator uses the web interface to enter "ServiceA", "ServiceB", and "ServiceC" into the allow list.

[1006] Output: The allow list is saved on the server.

[1007] 3. Administrators set usage criteria and alert conditions.

[1008] For example, an administrator can set up an alert to be generated if the generative AI service is used for more than three hours per day.

[1009] Output: Usage criteria and alert conditions are saved to the server

[1010] Step 2: Traffic monitoring and access control

[1011] Input: Internal network traffic data

[1012] Specific behavior:

[1013] 1. The server monitors traffic in real time.

[1014] The server uses packet capture software (e.g., Wireshark, Tcpdump) to monitor all traffic from the internal network to the Internet.

[1015] Output: Traffic data based on the watch list

[1016] 2. The server detects access to the generative AI service.

[1017] Analyze HTTP requests and API calls to the generative AI service to detect specific service access.

[1018] Output: Detected access list

[1019] 3. The server checks whether access to the service is permitted.

[1020] It checks against the permission list to determine whether access is to an authorized service or an unauthorized service.

[1021] Output: Allowed and blocked access lists

[1022] Step 3: Record usage

[1023] Input: Allowed access list, start time, end time, service type

[1024] Specific behavior:

[1025] 1. The server records the start time of use.

[1026] The server records the time of first access and stores in the database that the generative AI service has begun to be used.

[1027] Output: Recorded usage start time data

[1028] 2. The server records the end time of use.

[1029] The time when the access ended is saved in the database.

[1030] Output: Recorded end time data

[1031] 3. The server records the type of service.

[1032] The name and type of generative AI service used is recorded in a database.

[1033] Output: Recorded service type data

[1034] Step 4: Generate reports

[1035] Input: Collected usage data

[1036] Specific behavior:

[1037] 1. The server generates weekly and monthly reports.

[1038] Aggregate usage data stored in the database and generate weekly and monthly reports.

[1039] Output: Generated weekly and monthly reports

[1040] 2. The server sends the report to the administrator.

[1041] Once the report is generated, it will be automatically emailed to the administrator.

[1042] Output: Report sent to administrator's mailbox

[1043] 3. The report includes usage time and number of alerts.

[1044] Detailed information is provided on each employee's usage time, type of usage, and the number of alerts that occur when standards are exceeded.

[1045] Output: Detailed report information

[1046] Step 5: Real-time alerts

[1047] Input: Current usage time data, set criteria

[1048] Specific behavior:

[1049] 1. The server detects usage that exceeds the usage criteria.

[1050] It monitors usage time in real time and detects excessive usage if it exceeds the set standard.

[1051] Output: Excessive usage detection information

[1052] 2. The server generates and notifies alerts in real time.

[1053] Based on the detection results, an alert is immediately sent by email to administrators and relevant employees.

[1054] Output: Real-time alert notification

[1055] Step 6: Propose recommended actions

[1056] Input: Excessive usage detection information, administrator settings information

[1057] Specific behavior:

[1058] 1. The server makes recommendations when excessive usage is detected.

[1059] Analyze the data and generate recommendations to maintain compliance.

[1060] Output: Recommended action plan

[1061] 2. The server notifies the administrator of the recommended course of action.

[1062] Recommendations are sent to administrators via email and dashboard.

[1063] Output: Recommendation notification to administrator

[1064] 3. We suggest reviewing the frequency of use of generative AI services and providing user education.

[1065] As a concrete countermeasure, we will propose a review of the frequency with which employees use AI services and, if necessary, a retraining program.

[1066] Output: Notification of specific countermeasures

[1067] (Application example 1)

[1068] 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."

[1069] In recent years, the use of generative AI services within companies has been increasing, but without proper monitoring and management, there is a risk of unauthorized or excessive use, which could result in resource waste and security risks.There is also a need for a system that can monitor the usage of generative AI services in real time and promptly notify administrators.

[1070] 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.

[1071] In this invention, the server is located between the company's internal network and the Internet and includes: means for monitoring usage of the generation AI service; means for recording usage data of the generation AI service; means for detecting compliance violations and security violations in the use of the generation AI service; means for issuing alerts regarding excessive use of the generation AI service; means for generating reports based on usage of the generation AI service; means for proposing recommended actions regarding excessive use of the generation AI service; means for monitoring and managing usage of the generation AI service in real time using an application running on a smartphone; means for issuing alerts to managers and employees via email; and means for automatically generating usage reports on specific days of the week and sending them to managers. This allows for appropriate monitoring of usage of the generation AI service within a company, preventing fraudulent and excessive use, and enabling real-time problem detection and rapid response.

[1072] An "internal network" refers to a network environment within a company in which computers, servers, communication devices, etc. are interconnected.

[1073] The "Internet" refers to a huge network that interconnects computer networks all over the world.

[1074] "Generative AI services" refer to online services that use artificial intelligence technology to generate data and analyze information.

[1075] "Monitoring means" refers to the function that allows the system to check specific situations and operations in real time and check for any abnormalities.

[1076] "Recording means" refers to a function for saving specific data and log information.

[1077] "Detection means" refers to the function of automatically recognizing and determining specific situations or conditions.

[1078] "Alert notification means" refers to a function for sending notifications to administrators and relevant parties when certain conditions are met.

[1079] "Report generation means" refers to a function for periodically creating reports based on collected data.

[1080] "Recommended action suggestion means" refers to a function that presents appropriate countermeasures or actions depending on a specific situation.

[1081] "Applications running on a smartphone" refers to software programs that are installed and run on a mobile information terminal.

[1082] "Means of monitoring and management in real time" refers to the ability to instantly check the current situation and take action or respond as necessary.

[1083] "Means for notifying alerts via email" refers to a function for notifying relevant parties of alerts via email.

[1084] "Means for automatically generating reports on a specific day of the week and sending them to the administrator" refers to a function that automatically generates reports according to a schedule on a specific day of the week each week and sends them to the administrator.

[1085] overview

[1086] This invention is a system for managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet, monitors and records the use of generative AI services, and detects compliance and security violations. It also issues alerts for excessive use, periodically generates reports, and proposes recommended actions to administrators. A notable feature of this system is that it monitors and manages the use of generative AI services in real time using an application running on a smartphone.

[1087] System Configuration

[1088] The system consists of the following major hardware and software components:

[1089] 1. Server

[1090] Monitor traffic between your internal network and the internet.

[1091] A database (e.g., AWS RDS, Google Cloud SQL) for recording and managing usage data.

[1092] Performs processing for alert notifications and report generation.

[1093] It connects to smartphone applications via API.

[1094] 2. Smartphone

[1095] Devices used by IT administrators.

[1096] Run specific applications and monitor and manage the usage of generative AI services in real time.

[1097] It provides an interface for receiving alert notifications and taking necessary actions.

[1098] Processing Details

[1099] The server monitors traffic from the company's internal network to the Internet in real time, detects access to the AI ​​generation service, and records usage data for authorized AI generation services and stores the usage status in a database.

[1100] If an employee attempts to access the AI ​​generation service without authorization, the server immediately blocks that access. If usage time exceeds the set threshold, the server generates an alert in real time and notifies the administrator and the employee via email.

[1101] On a specific day of the week (e.g., every Monday), the server automatically generates a weekly usage report and sends it to the administrator, detailing the usage time of each employee, the type of AI-generating service used, the number of alerts generated, and so on.

[1102] Usage example

[1103] For example, if employee C uses "Generation AI Service A" from 9:00 AM to 1:00 PM, the server records that usage. As the usage time exceeds the set standard of three hours, the server immediately sends an alert to the administrator and employee C. In addition, every Monday, a report summarizing the previous week's usage is automatically generated and sent to the administrator. Based on this report, the administrator can review employee C's usage and take appropriate measures as necessary.

[1104] Example prompt sentence:

[1105] "Write a Python program that monitors employee usage of the Generative AI service and sends real-time alerts if it exceeds a set threshold."

[1106] In this way, the present invention is a system that properly monitors and manages the use of generative AI services, prevents fraudulent or excessive use, and enables rapid response.

[1107] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1108] Step 1:

[1109] Perform initial setup. The user (administrator) logs in to the server and sets up a list of authorized generative AI services, including usage criteria and alert conditions.

[1110] Input: A list of allowed generation AI services, e.g. "ServiceA", "ServiceB", "ServiceC".

[1111] Output: Saves the configured allow list and usage criteria.

[1112] How it works: Administrators use a web interface to select permitted services and enter usage time limits and alert conditions.

[1113] Step 2:

[1114] Traffic monitoring: The server monitors all traffic from the internal network to the Internet in real time.

[1115] Input: Network traffic data.

[1116] Output: Access data to generative AI services.

[1117] Specific operation: Analyzes packet data and identifies which service is being accessed.

[1118] Step 3:

[1119] Verify access to generative AI services: The server checks whether access to the detected generative AI service is on an allow list.

[1120] Input: Access data to the generative AI service.

[1121] Output: Decision to allow or block.

[1122] Specific operation: Access data is compared against an allow list and access to unauthorized services is blocked.

[1123] Step 4:

[1124] Record usage status. The server records the start time, end time, and type of service of the AI ​​generation service in detail.

[1125] Input: Usage data of the generation AI service for which access has been granted.

[1126] Output: Saving usage data to a database.

[1127] Specific operation: Record the start and end times of use for each service and save them in a database.

[1128] Step 5:

[1129] Monitor alert conditions: The server monitors whether usage exceeds established thresholds based on usage.

[1130] Input: Usage data and configured usage criteria.

[1131] Output: Generate an alert if the criteria is exceeded.

[1132] Specific operation: Usage time is accumulated, and if it exceeds the set standard, an email notification is sent to the administrator and the relevant employee.

[1133] Step 6:

[1134] Generate reports: The server automatically generates weekly and monthly usage reports.

[1135] Input: Usage data of the generative AI service.

[1136] Output: Generate and email usage reports.

[1137] Specific operation: Usage data is collected, a report is created summarizing each employee's usage, and the report is sent to the administrator via email.

[1138] Step 7:

[1139] The server proposes recommended actions. If excessive use of the generative AI service is detected, the server will propose countermeasures to the administrator.

[1140] Input: Excessive usage data.

[1141] Output: Proposal generation and notification.

[1142] Specific actions: In the event of excessive use, the system generates a message suggesting re-education of specific users on usage guidelines or limiting usage time, and notifies the administrator.

[1143] 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.

[1144] This invention is a system that appropriately manages the usage of generative AI services and is placed between an internal company network and the Internet. It uses data from servers, terminals, and users to monitor and record the usage of generative AI services and detect compliance and security violations. Furthermore, by combining it with an emotion engine, it monitors changes in the user's emotions and provides appropriate countermeasures according to the usage situation.

[1145] 1. Initial Setup

[1146] The user (administrator) logs in to the server and configures a list of authorized generative AI services. For example, add services such as "ServiceA," "ServiceB," and "ServiceC" to the authorization list. In addition, the user configures usage criteria, alert conditions, and emotional data recording settings.

[1147] 2. Traffic Monitoring

[1148] The server monitors all traffic from the internal network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it allows the traffic because it is included in the authorization list. On the other hand, access to the unauthorized "ServiceD" is blocked.

[1149] 3. Records of usage

[1150] The server records the usage of the AI ​​service in detail (start time, end time, type of service, etc.). For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. In addition, the emotion engine analyzes the user's emotional state (e.g., stress, elation, fatigue, etc.), which is also recorded.

[1151] 4. Report Generation

[1152] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[1153] 5. Real-time alerts

[1154] The server generates alerts in real time when an employee's use of the AI-generated service exceeds a set threshold or when the user's emotions indicate a specific state (e.g., high stress level). For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[1155] 6. Recommended Action Suggestion

[1156] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1157] Specific examples

[1158] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, and configures it to generate an alert if the usage time exceeds three hours per day or if a high stress level is reached. If employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period and that the emotion data indicates high stress. The server then suggests to the administrator that employee A review his usage time and take measures to manage his stress.

[1159] In this way, the system aims to monitor the appropriate use of generative AI services, maintain compliance and security, and also take into account the emotional state of the user, thereby maintaining employees' digital well-being.

[1160] The processing flow will be explained below.

[1161] Step 1:

[1162] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[1163] Step 2:

[1164] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[1165] Step 3:

[1166] User (Administrator): Sets usage criteria and alert conditions. For example, "Generate an alert if daily usage exceeds three hours." Also, sets emotional data recording settings and alert criteria for specific emotional states.

[1167] Step 4:

[1168] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[1169] Step 5:

[1170] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[1171] Step 6:

[1172] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[1173] Step 7:

[1174] On the device: The emotion engine collects user emotion data, for example, using facial recognition and voice analysis technologies to analyze the user's stress level and other emotional states in real time.

[1175] Step 8:

[1176] Server: The collected emotion data is stored in a database along with usage data of the AI ​​generation service. For example, data such as "Employee A, Service A, 10:00-11:00, high stress level" is recorded in the database.

[1177] Step 9:

[1178] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, alert occurrences, sentiment, etc.

[1179] Step 10:

[1180] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[1181] Step 11:

[1182] Server: Generates alerts in real time when an employee's use of the AI ​​service exceeds a set threshold or indicates a specific emotional state (e.g., high stress level). For example, if employee B uses "Service B" for 4 hours a day and indicates a high stress level, an alert will be sent immediately to the manager and employee B.

[1183] Step 12:

[1184] Server: If excessive use of the AI ​​generator or specific emotional changes are detected, the server will propose specific countermeasures to the manager. For example, "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1185] Step 13:

[1186] User (Administrator): Implements countermeasures based on suggestions from the server, such as retraining employees on usage guidelines or providing emotional care support.

[1187] Example 2

[1188] 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."

[1189] Managing the appropriate use of generative AI services poses a challenging challenge: maintaining digital well-being by taking into account users' emotional states while ensuring compliance and security. Specifically, it is necessary not only to prevent excessive use of generative AI services and access to unauthorized services, but also to provide appropriate countermeasures in response to changes in users' emotions. However, an efficient system for comprehensively managing these issues is lacking.

[1190] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1191] In this invention, the server is located between the in-house network and the Internet and includes means for monitoring usage of the generated AI service, means for recording usage data of the generated AI service, means for detecting compliance violations and security violations in the use of the generated AI service, means for issuing alerts for excessive use of the generated AI service, means for generating reports based on usage of the generated AI service, means for proposing recommended actions for excessive use of the generated AI service, means for analyzing and recording the user's emotional state, and means for proposing countermeasures according to usage based on the emotional data. This makes it possible to manage appropriate use of the generated AI service, ensure compliance and security, and provide countermeasures based on the user's emotional state.

[1192] An "internal network" is a network to which computers and devices within a company or organization are connected, allowing for internal data communication and resource sharing.

[1193] The "Internet" is a huge global network that interconnects computer networks all over the world, allowing data to be sent and received and information to be shared.

[1194] A "generative AI service" is an online service that uses a generative AI model to generate content such as text, images, or audio.

[1195] "Usage monitoring means" means systems or software that have the ability to monitor the use of generative AI services in real time and track access and frequency of use.

[1196] "Means for recording usage data" refers to a function that stores information about the use of the generative AI service (such as start time, end time, and type of service) in a database or log.

[1197] "Means for detecting compliance and security violations" refers to systems and algorithms that detect when the use of the generative AI services provided violates the standards and security policies of the company or organization.

[1198] "Means for issuing alert notifications regarding excessive use" refers to a function that sends an alert when use of the generative AI service exceeds a pre-set standard.

[1199] The "means for generating usage-based reports" is a function that creates and reports weekly or monthly usage reports based on collected usage data of the generation AI service.

[1200] "Means for suggesting recommended actions" is a function that provides specific countermeasures and improvement measures based on usage data and emotional state of the generating AI service.

[1201] The "means for analyzing and recording emotional state" is a function that analyzes the user's stress level and emotional changes using sensors and input data, and stores the results in a database.

[1202] The "means for proposing countermeasures based on emotional data" is a function that provides countermeasures or improvements that are appropriate for the user's emotional state based on the analyzed emotional data.

[1203] This invention relates to a system for appropriately managing the usage of generative AI services. This system is located between an internal company network and the Internet, and has the function of monitoring and recording the usage of generative AI services using data from servers, terminals, and users, and detecting compliance violations and security violations.

[1204] Initial Setup

[1205] The user (administrator) logs in to the server and accesses the administration screen to set up a list of permitted generative AI services. For example, services such as "Service A," "Service B," and "Service C" are added to the permitted list. Next, usage criteria and alert conditions are set. The user also sets up emotional data recording, specifying the items for which data is to be collected, primarily stress, elation, and fatigue.

[1206] Traffic Monitoring

[1207] The server monitors all traffic from the internal network to the Internet. For this purpose, network traffic analysis tools (e.g., Wireshark, Suricata) are used. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it checks whether the service is on the authorized list and allows its use. Access to the unauthorized "ServiceD" is blocked.

[1208] Usage record

[1209] The server records usage information for the generated AI service—such as the start and end times, and the type of service used—in a database. For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. Additionally, an emotion engine (e.g., IBM Watson, Affectiva) is used to analyze the user's emotional state, and that data is also recorded. For example, stress levels and fatigue levels are recorded.

[1210] Report Generation

[1211] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[1212] Real-time alerts

[1213] The server generates real-time alerts when usage of the generative AI service exceeds a set threshold or when a user's emotions indicate a specific state—for example, a high stress level. For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[1214] Recommended actions

[1215] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1216] Examples of specific examples and prompts

[1217] The administrator logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list. The system is set to generate an alert if usage exceeds three hours per day or if a high stress level is reached. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A as usage that exceeds the standard. Then, at the end of the week, a report is sent to the administrator stating that employee A used "Service A" for a total of 15 hours and that the emotion data indicates high stress. The server then suggests to the administrator that they review employee A's usage time and take measures to manage stress.

[1218] Example prompt sentence:

[1219] Add "ServiceA" and "ServiceB" to the allow list and set an alert to be generated when the usage time exceeds 3 hours per day or when a high stress level is reached. Based on this, you can monitor employee usage and generate appropriate reports.

[1220] The system aims to maintain employees' digital well-being by monitoring the appropriate use of generative AI services, maintaining compliance and security, and taking into account the user's emotional state.

[1221] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1222] Step 1:

[1223] The user performs the initial setup

[1224] Input: Administrator credentials, list of allowed generative AI services, usage criteria, alert conditions, emotion data recording settings

[1225] Specific behavior:

[1226] The user (administrator) enters authentication information (user name and password) to log in to the server.

[1227] Access the admin panel and add services such as "ServiceA", "ServiceB", and "ServiceC" to the allow list.

[1228] Set usage criteria and alert conditions (if daily usage exceeds 3 hours or if high stress levels are reached).

[1229] Configure emotional data recording settings and specify the type of emotional data to collect (e.g., stress, elation, fatigue).

[1230] Output: The configured permission list, usage criteria, alert conditions, and emotion data recording settings are saved on the server.

[1231] Step 2:

[1232] The server monitors all traffic from the internal network to the Internet.

[1233] Input: Network traffic data

[1234] Specific behavior:

[1235] The server uses network traffic analysis tools (e.g., Wireshark, Suricata) to monitor communication packets in real time.

[1236] To detect access to generative AI services, filtering is performed based on specific domain names, IP addresses, and URL patterns.

[1237] Output: Access log to the generation AI service

[1238] Step 3:

[1239] The server decides whether to allow or deny the service.

[1240] Input: Allow list, access logs for generated AI services

[1241] Specific behavior:

[1242] The server checks whether the destination of the access to the generated AI service in the access log is included in the configured permission list.

[1243] For example, it detects access to "ServiceA" from an employee's device and allows that traffic if it is included in the allowed list, while blocking access to unauthorized "ServiceD."

[1244] Output: Log of allowed and blocked accesses

[1245] Step 4:

[1246] Server-generated records of AI service usage

[1247] Input: Access logs of permitted and prohibited access, start and end times of permitted AI generation services, and service types

[1248] Specific behavior:

[1249] The server records the start and end times of authorized access to the generated AI service, as well as the type of service used.

[1250] For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[1251] Output: Generated AI service usage database entries

[1252] Step 5:

[1253] The server uses an emotion engine to analyze and record the user's emotional state.

[1254] Input: User emotional data (e.g., stress level, elation, fatigue)

[1255] Specific behavior:

[1256] The server uses an emotion engine (e.g., IBM Watson, Affectiva) to analyze emotion data obtained from sensors and user input.

[1257] For example, analyze employee A's stress level and record the results in a database.

[1258] Output: A database entry of the analyzed sentiment data

[1259] Step 6:

[1260] The server generates weekly and monthly reports

[1261] Input: Usage data of the generated AI service, emotion data

[1262] Specific behavior:

[1263] The server aggregates the collected usage data and emotion data of the generative AI service and creates a report in a specified format.

[1264] For example, a report can be generated that compiles information such as usage over the course of a week, emotional state, and number of alerts.

[1265] Output: Generated weekly and monthly reports

[1266] Step 7:

[1267] Server generates real-time alerts

[1268] Input: Set criteria, usage data of the generating AI service, and emotional data

[1269] Specific behavior:

[1270] The server checks whether the usage of the generative AI service meets the criteria if it exceeds the set threshold or detects a specific emotional state, such as a high stress level.

[1271] For example, if employee B uses "Service B" for four hours and shows a high stress level, check whether the alert conditions are met.

[1272] If the alert conditions are met, an alert will be sent to the administrator and relevant employees via email or in-system notification.

[1273] Output: The generated alert notification

[1274] Step 8:

[1275] The server proposes recommended actions

[1276] Input: Usage data of the generated AI service, emotion data, and set countermeasures

[1277] Specific behavior:

[1278] The server analyzes excessive use of generative AI services and specific emotional states, and generates specific countermeasures and improvement measures.

[1279] For example, suggestions may be made such as "Suggest that employee C review the frequency of use of the generative AI service" or "Recommend that employee D take a break to relieve stress."

[1280] The administrator will be notified of the suggestions via email or dashboard.

[1281] Output: Sending a recommended action notification

[1282] (Application example 2)

[1283] 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."

[1284] As the use of generative AI services rapidly expands, companies are required to properly manage their use of generative AI services and prevent compliance and security violations. It is also important to monitor employee stress and fatigue caused by excessive use of generative AI services and help them manage their health. The present invention provides a system to solve these problems.

[1285] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1286] In this invention, the server is located between the internal network and the Internet and includes means for monitoring usage of the generating AI service, means for recording usage data of the generating AI service, means for detecting compliance violations and security violations in the use of the generating AI service, means for issuing alerts for excessive use of the generating AI service, means for generating reports based on usage of the generating AI service, means for proposing recommended actions for excessive use of the generating AI service, and means for monitoring the user's emotional state and issuing warnings or recommending actions based on the emotional data.This enables companies to effectively monitor and manage the use of the generating AI service, ensuring compliance and security, while taking appropriate measures that take into account the emotional state and health of employees.

[1287] An "internal network" refers to a computer network used within a company or organization, and is a closed network that is different from the Internet.

[1288] "Generative AI services" refer to services that automatically generate content or data using artificial intelligence technology.

[1289] "Means for monitoring usage" refers to a device or program that collects information about the use of generative AI services and monitors the duration and frequency of use in real time.

[1290] "Means for recording usage data" refers to a device or program that records the usage history of the generative AI service in detail and stores it in a state that can be analyzed later.

[1291] "Means for detecting compliance or security violations" means devices or programs for determining whether the use of generative AI services violates company regulations or security policies and for detecting violations.

[1292] "Means for providing alert notifications regarding excessive use" refers to a device or program that issues a warning to administrators or users when use of the generative AI service exceeds a specified threshold.

[1293] A "means for generating usage-based reports" is a device or program that periodically creates a report summarizing usage status based on collected usage data of the generation AI service.

[1294] A "means for proposing recommended actions" is a device or program that suggests appropriate measures to administrators or users in the event of excessive use of generative AI services or other concerns.

[1295] "Means for monitoring emotional states and issuing warnings or recommending actions based on emotional data" refers to a device or program that analyzes a user's emotional state in real time and provides appropriate warnings or countermeasures based on that information.

[1296] This paper describes a method for building a system that effectively manages and monitors the use of generative AI services based on this invention. It also describes the specific system configuration, hardware, and software used for this purpose.

[1297] System Configuration

[1298] The system mainly includes the following elements:

[1299] 1. A server located between the company network and the Internet

[1300] The server monitors all traffic from the internal network to the internet. If it detects access to a generative AI service, it checks whether that service is on an allow list. Access to unauthorized services is blocked.

[1301] 2. Device that records usage of the AI ​​service

[1302] The server records detailed usage data of the generated AI service (such as start time, end time, and type of service), including the duration and frequency of each service used by the user.

[1303] 3. Software that detects compliance and security violations

[1304] Software installed on the server analyzes usage data generated by AI services and automatically detects compliance and security violations.

[1305] 4. Emotion Engine

[1306] This engine is used to analyze the user's emotional state by analyzing the user's heart rate data, facial expressions, and voice tone in real time, and recording the user's stress level and fatigue level.

[1307] 5. Report generation function

[1308] The server periodically generates usage reports based on the collected data, which are emailed to administrators on a weekly and monthly basis.

[1309] 6. Real-time alert function

[1310] If usage or changes in emotional state exceeding set standards are detected, the server generates an alert in real time and notifies the administrator and the relevant user.

[1311] 7. Recommended Actions

[1312] If excessive use of generative AI services or high stress levels are detected, the server will suggest specific countermeasures to users and administrators.

[1313] Hardware and software used

[1314] Hardware

[1315] A server that monitors traffic on the company's internal network

[1316] Smartphones and wearable devices for collecting user emotion data

[1317] software

[1318] Network monitoring software (NetworkMonitor library)

[1319] Software for analyzing emotional states (EmotionEngine library)

[1320] Alert notification software (AlertService library)

[1321] Report generation software (ReportGenerator library)

[1322] Specific examples

[1323] For example, consider a situation where Employee A is using a smartphone app to monitor their use of "Service A." Employee A initiates a connection to the generative AI service using the prompt "Connect to Service A." The app is configured to send an alert if the user uses the app for more than three hours or if the user experiences high stress. An example prompt is shown below:

[1324] "Perform sentiment analysis using the following data to determine your current stress level: [heart rate data, facial expression images, voice tone]"

[1325] The system enables businesses to effectively manage the use of generative AI services, ensuring compliance and security while maintaining the digital well-being of their employees.

[1326] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1327] Step 1:

[1328] The server monitors all traffic on the company's internal network and detects access to the generative AI service. The input is network traffic data, and the output is detected access information for the generative AI service. This traffic data is analyzed to identify which users are accessing which generative AI services.

[1329] Step 2:

[1330] The server checks whether the detected generated AI service is included in the allow list. The input is the access information of the generated AI service, which is the output of step 1, and the output is an instruction to allow or block access. Access to generated AI services that are not included in the allow list is blocked.

[1331] Step 3:

[1332] The device records usage data of the generated AI service. The input is the usage information of the generated AI service identified in step 1, and the output is a detailed usage record such as the start time, end time, and type of service. This data is stored in a database.

[1333] Step 4:

[1334] The server analyzes the usage data of the generated AI service and detects compliance and security violations. The input is the usage data obtained in step 3, and the output is information on whether or not there is a violation. If a violation is detected, the administrator is notified.

[1335] Step 5:

[1336] The emotion engine monitors the user's emotional state and issues warnings or recommends actions based on the emotional data. The input is the user's heart rate data, facial expression images, and voice tone, and the output is the analysis result of the user's emotional state. If high stress or fatigue is detected, the server will suggest appropriate actions.

[1337] Step 6:

[1338] The server generates a report based on the usage of the generative AI service. The input is the data collected in Steps 3 and 5, and the output is a detailed usage report. This report is sent to the administrator on a weekly and monthly basis.

[1339] Step 7:

[1340] The real-time alert function allows the server to immediately generate an alert if it detects usage of the generative AI service exceeding set standards or a change in a specific emotional state. The input is the data from Steps 3 and 5, and the output is a warning message. This allows users and administrators to be notified in real time.

[1341] Step 8:

[1342] If the server detects excessive use of the generative AI service or a high level of stress, it will propose specific countermeasures to the user or administrator. The input is the warning data from Step 7, and the output is specific recommended actions. This allows the user to take appropriate actions such as taking appropriate breaks or reviewing the frequency of use.

[1343] 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.

[1344] 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.

[1345] 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.

[1346] [Fourth embodiment]

[1347] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1348] 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.

[1349] 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).

[1350] 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.

[1351] 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.

[1352] 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).

[1353] 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.

[1354] 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.

[1355] 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.

[1356] 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.

[1357] 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.

[1358] 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.

[1359] 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."

[1360] The present invention is a system for appropriately managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet and monitors and records employee usage of multiple different generative AI services in real time.

[1361] The present invention is carried out as follows.

[1362] 1. Initial Setup

[1363] The user (administrator) first logs in to the server and sets up a list of allowed generative AI services. For example, the administrator adds services such as "ServiceA," "ServiceB," and "ServiceC" to the allowed list. The administrator can also set usage criteria and alert conditions (e.g., more than three hours of use per day).

[1364] 2. Traffic Monitoring

[1365] The server monitors all traffic from the company network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if an employee's device accesses "ServiceA," the traffic is allowed because it is included in the authorization list. On the other hand, access to "ServiceD," which is not authorized, is blocked.

[1366] 3. Records of usage

[1367] The server records detailed usage information for the AI ​​service (start time, end time, type of service, etc.) For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[1368] 4. Report Generation

[1369] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details such as each employee's usage time, type of usage, and the number of alerts generated.

[1370] 5. Real-time alerts

[1371] The server generates real-time alerts when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B.

[1372] 6. Recommended Action Suggestion

[1373] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[1374] Specific examples

[1375] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours per day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that employee A review his or her usage time and, if necessary, retrain him or her on the usage guidelines for the generation AI service.

[1376] In this way, the system aims to monitor the appropriate use of generative AI services, maintaining compliance and security while preserving employees' digital well-being.

[1377] The processing flow will be explained below.

[1378] Step 1:

[1379] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[1380] Step 2:

[1381] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[1382] Step 3:

[1383] User (Administrator): Sets usage criteria and alert conditions. For example, you can set "Generate an alert if usage time exceeds 3 hours per day."

[1384] Step 4:

[1385] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[1386] Step 5:

[1387] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[1388] Step 6:

[1389] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[1390] Step 7:

[1391] Server: Saves the collected data in a database. For example, data such as "Employee A, Service A, 10:00-11:00" is recorded in the database.

[1392] Step 8:

[1393] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, number of alerts, etc.

[1394] Step 9:

[1395] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[1396] Step 10:

[1397] Server: Generates alerts in real time when an employee's AI service usage exceeds a set threshold. For example, if employee B uses "Service B" for four hours in one day, an alert is generated to notify the administrator and employee B.

[1398] Step 11:

[1399] Server: If excessive use of generated AI is detected, the server will propose specific countermeasures to the administrator. For example, it will recommend that employee C undergo user training.

[1400] Step 12:

[1401] User (Administrator): Implements countermeasures based on suggestions from the server. For example, re-educating employees about usage guidelines and setting usage time limits.

[1402] Example 1

[1403] 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."

[1404] The use of generative AI services is increasing in modern corporate environments. However, excessive use of generative AI services by employees may increase compliance violations and security risks. There are also concerns that excessive use may negatively impact employees' digital well-being. Furthermore, companies must properly manage generative AI services, and effective monitoring and control measures are needed.

[1405] 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.

[1406] In this invention, the server is located between the internal network and the Internet and includes: means for monitoring usage of the generating AI service; means for recording usage data of the generating AI service; means for detecting compliance violations and security violations in the use of the generating AI service; means for issuing alerts for excessive use of the generating AI service; means for generating reports based on usage of the generating AI service; means for proposing recommended actions for excessive use of the generating AI service; means for an administrator to log in to the server and set a list of permitted services; means for the administrator to set usage criteria and alert conditions; means for monitoring all traffic from the internal network to the Internet in real time to confirm whether access to the generating AI service is permitted; and means for determining whether access to a service is permitted. This enables companies to properly manage the use of the generating AI service, maintain compliance and security, maintain employee digital well-being, and improve productivity.

[1407] An "internal network" is a computer network used within a company, and is a communications infrastructure for connecting internal computers, servers, and various devices to each other.

[1408] The "Internet" is a huge data communications network that interconnects computer networks all over the world, and is an infrastructure for exchanging information and providing services.

[1409] "Generative AI services" refer to online services that use artificial intelligence technology to generate various types of data, such as text generation, image generation, and voice synthesis.

[1410] "Usage status" refers to various log information regarding the use of the generative AI service, including, specifically, the start time of use, end time, type of service, number of uses, etc.

[1411] "Violation of compliance" refers to any act that goes against the laws, regulations, or guidelines established by a company or organization, and particularly refers to inappropriate operations in business processes or information management.

[1412] A "security breach" refers to any act that threatens the security of an information system, such as information leakage, tampering, or unauthorized access.

[1413] An "alert notification" is a warning message that the system automatically sends when set criteria or conditions are met, and is mainly notified via email or dashboard.

[1414] "Usage Data" means all recorded information relating to the use of the Generative AI Services, including data indicating which services a particular user used and to what extent.

[1415] A "report" is a document or digital file that contains aggregated results based on usage of the Generative AI Service, including details such as usage time, number of uses, and number of alerts.

[1416] "Recommended actions" are specific measures or countermeasures that the system suggests when certain conditions are met, such as strengthening usage restrictions or implementing educational programs.

[1417] An "administrator" is a user who has the authority to configure and monitor the system, check reports, etc., and primarily refers to the information systems department or security officer within a company.

[1418] "Traffic monitoring" refers to the act of observing data communications on a network in real time and detecting specific information or patterns, and is primarily used to improve network security and detect unauthorized access.

[1419] "Access determination" is the process of detecting a specific access request in network traffic and determining whether it is permitted.

[1420] This invention relates to a system for appropriately managing the use of generative AI services within a company. Specifically, it utilizes elements of servers, users (administrators), and terminals to monitor the usage of generative AI services, record data, detect compliance and security violations, issue alerts for excessive usage, generate reports, and propose recommended actions.

[1421] Initial Setup

[1422] A user (administrator) first logs in to the server, which is usually an authentication process using a username and password. The server provides a web interface, and the user accesses the administration page using a browser.

[1423] Administrators set an allow list for the AI-generated services. Specifically, administrators enter the names of the allowed services (e.g., "ServiceA," "ServiceB," and "ServiceC") through a web interface and add them to the list. Administrators also set usage criteria and alert conditions, such as generating an alert if usage exceeds three hours per day.

[1424] Traffic monitoring and access control

[1425] The server uses packet capture software (such as Wireshark or Tcpdump) to monitor all traffic from the internal network to the Internet in real time. The server detects access to the generated AI service in the traffic and checks whether the access is authorized. Access to authorized services is allowed, while access to unauthorized services is blocked.

[1426] Usage record

[1427] The server records the usage of the detected AI service in detail, including the start and end times of use, the type of service, etc. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM, that information is saved in the database. This allows data to be accumulated for later usage analysis.

[1428] Generate reports

[1429] The server generates weekly and monthly reports based on the collected data. These reports are automatically sent to administrators by email. The reports contain detailed information such as the usage time, type of usage, and number of alerts for each employee. For example, an administrator can receive a report stating that "Employee A used Service A for a total of 15 hours during this period."

[1430] Real-time alerts

[1431] The server generates a real-time alert when an employee's use of the AI-generated service exceeds the set threshold. For example, if employee B uses "Service B" for four hours in one day, this exceeds the set threshold of three hours, so the server immediately sends an alert to the administrator and employee B. This alert is notified via email or dashboard.

[1432] Recommended actions

[1433] If excessive use of AI generative services is detected, the server will propose specific countermeasures to the administrator. For example, it may suggest "reviewing the frequency of use for employee C" or "recommend user training for employee D." Such proposals are effective in maintaining digital well-being and improving productivity across the company.

[1434] Examples of specific examples and prompts

[1435] As a specific example of operation, consider the case where a user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, setting it up to generate an alert if the usage time exceeds three hours in a day. If employee A uses "Service A" from 9:00 AM to 12:00 PM, the server records this and sends an alert to the administrator and employee A because the standard time has been exceeded. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period. The server then suggests to the administrator that they review employee A's usage time and re-educate them on the usage guidelines for the generation AI service.

[1436] Prompt Sentence Examples

[1437] "Please explain how to set up an alert to be generated if an employee uses an authorized AI generation service for more than three hours, and what action will be taken if Employee A uses the service for more than three hours."

[1438] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1439] Step 1: Initial Setup

[1440] Inputs: Administrator credentials, list of authorized AI generation services, usage criteria, alert conditions

[1441] Specific behavior:

[1442] 1. The user (administrator) logs in to the server.

[1443] The administrator enters a username and password to establish access to the server through authentication.

[1444] Output: Admin interface after successful login

[1445] 2. Administrators set a list of permitted generative AI services.

[1446] The administrator uses the web interface to enter "ServiceA", "ServiceB", and "ServiceC" into the allow list.

[1447] Output: The allow list is saved on the server.

[1448] 3. Administrators set usage criteria and alert conditions.

[1449] For example, an administrator can set up an alert to be generated if the generative AI service is used for more than three hours per day.

[1450] Output: Usage criteria and alert conditions are saved to the server

[1451] Step 2: Traffic monitoring and access control

[1452] Input: Internal network traffic data

[1453] Specific behavior:

[1454] 1. The server monitors traffic in real time.

[1455] The server uses packet capture software (e.g., Wireshark, Tcpdump) to monitor all traffic from the internal network to the Internet.

[1456] Output: Traffic data based on the watch list

[1457] 2. The server detects access to the generative AI service.

[1458] Analyze HTTP requests and API calls to the generative AI service to detect specific service access.

[1459] Output: Detected access list

[1460] 3. The server checks whether access to the service is permitted.

[1461] It checks against the permission list to determine whether access is to an authorized service or an unauthorized service.

[1462] Output: Allowed and blocked access lists

[1463] Step 3: Record usage

[1464] Input: Allowed access list, start time, end time, service type

[1465] Specific behavior:

[1466] 1. The server records the start time of use.

[1467] The server records the time of first access and stores in the database that the generative AI service has begun to be used.

[1468] Output: Recorded usage start time data

[1469] 2. The server records the end time of use.

[1470] The time when the access ended is saved in the database.

[1471] Output: Recorded end time data

[1472] 3. The server records the type of service.

[1473] The name and type of generative AI service used is recorded in a database.

[1474] Output: Recorded service type data

[1475] Step 4: Generate reports

[1476] Input: Collected usage data

[1477] Specific behavior:

[1478] 1. The server generates weekly and monthly reports.

[1479] Aggregate usage data stored in the database and generate weekly and monthly reports.

[1480] Output: Generated weekly and monthly reports

[1481] 2. The server sends the report to the administrator.

[1482] Once the report is generated, it will be automatically emailed to the administrator.

[1483] Output: Report sent to administrator's mailbox

[1484] 3. The report includes usage time and number of alerts.

[1485] Detailed information is provided on each employee's usage time, type of usage, and the number of alerts that occur when standards are exceeded.

[1486] Output: Detailed report information

[1487] Step 5: Real-time alerts

[1488] Input: Current usage time data, set criteria

[1489] Specific behavior:

[1490] 1. The server detects usage that exceeds the usage criteria.

[1491] It monitors usage time in real time and detects excessive usage if it exceeds the set standard.

[1492] Output: Excessive usage detection information

[1493] 2. The server generates and notifies alerts in real time.

[1494] Based on the detection results, an alert is immediately sent by email to administrators and relevant employees.

[1495] Output: Real-time alert notification

[1496] Step 6: Propose recommended actions

[1497] Input: Excessive usage detection information, administrator settings information

[1498] Specific behavior:

[1499] 1. The server makes recommendations when excessive usage is detected.

[1500] Analyze the data and generate recommendations to maintain compliance.

[1501] Output: Recommended action plan

[1502] 2. The server notifies the administrator of the recommended course of action.

[1503] Recommendations are sent to administrators via email and dashboard.

[1504] Output: Recommendation notification to administrator

[1505] 3. We suggest reviewing the frequency of use of generative AI services and providing user education.

[1506] As a concrete countermeasure, we will propose a review of the frequency with which employees use AI services and, if necessary, a retraining program.

[1507] Output: Notification of specific countermeasures

[1508] (Application example 1)

[1509] 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."

[1510] In recent years, the use of generative AI services within companies has been increasing, but without proper monitoring and management, there is a risk of unauthorized or excessive use, which could result in resource waste and security risks.There is also a need for a system that can monitor the usage of generative AI services in real time and promptly notify administrators.

[1511] 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.

[1512] In this invention, the server is located between the company's internal network and the Internet and includes: means for monitoring usage of the generation AI service; means for recording usage data of the generation AI service; means for detecting compliance violations and security violations in the use of the generation AI service; means for issuing alerts regarding excessive use of the generation AI service; means for generating reports based on usage of the generation AI service; means for proposing recommended actions regarding excessive use of the generation AI service; means for monitoring and managing usage of the generation AI service in real time using an application running on a smartphone; means for issuing alerts to managers and employees via email; and means for automatically generating usage reports on specific days of the week and sending them to managers. This allows for appropriate monitoring of usage of the generation AI service within a company, preventing fraudulent and excessive use, and enabling real-time problem detection and rapid response.

[1513] An "internal network" refers to a network environment within a company in which computers, servers, communication devices, etc. are interconnected.

[1514] The "Internet" refers to a huge network that interconnects computer networks all over the world.

[1515] "Generative AI services" refer to online services that use artificial intelligence technology to generate data and analyze information.

[1516] "Monitoring means" refers to the function that allows the system to check specific situations and operations in real time and check for any abnormalities.

[1517] "Recording means" refers to a function for saving specific data and log information.

[1518] "Detection means" refers to the function of automatically recognizing and determining specific situations or conditions.

[1519] "Alert notification means" refers to a function for sending notifications to administrators and relevant parties when certain conditions are met.

[1520] "Report generation means" refers to a function for periodically creating reports based on collected data.

[1521] "Recommended action suggestion means" refers to a function that presents appropriate countermeasures or actions depending on a specific situation.

[1522] "Applications running on a smartphone" refers to software programs that are installed and run on a mobile information terminal.

[1523] "Means of monitoring and management in real time" refers to the ability to instantly check the current situation and take action or respond as necessary.

[1524] "Means for notifying alerts via email" refers to a function for notifying relevant parties of alerts via email.

[1525] "Means for automatically generating reports on a specific day of the week and sending them to the administrator" refers to a function that automatically generates reports according to a schedule on a specific day of the week each week and sends them to the administrator.

[1526] overview

[1527] This invention is a system for managing the use of generative AI services within a company. This system is located between the company's internal network and the Internet, monitors and records the use of generative AI services, and detects compliance and security violations. It also issues alerts for excessive use, periodically generates reports, and proposes recommended actions to administrators. A notable feature of this system is that it monitors and manages the use of generative AI services in real time using an application running on a smartphone.

[1528] System Configuration

[1529] The system consists of the following major hardware and software components:

[1530] 1. Server

[1531] Monitor traffic between your internal network and the internet.

[1532] A database (e.g., AWS RDS, Google Cloud SQL) for recording and managing usage data.

[1533] Performs processing for alert notifications and report generation.

[1534] It connects to smartphone applications via API.

[1535] 2. Smartphone

[1536] Devices used by IT administrators.

[1537] Run specific applications and monitor and manage the usage of generative AI services in real time.

[1538] It provides an interface for receiving alert notifications and taking necessary actions.

[1539] Processing Details

[1540] The server monitors traffic from the company's internal network to the Internet in real time, detects access to the AI ​​generation service, and records usage data for authorized AI generation services and stores the usage status in a database.

[1541] If an employee attempts to access the AI ​​generation service without authorization, the server immediately blocks that access. If usage time exceeds the set threshold, the server generates an alert in real time and notifies the administrator and the employee via email.

[1542] On a specific day of the week (e.g., every Monday), the server automatically generates a weekly usage report and sends it to the administrator, detailing the usage time of each employee, the type of AI-generating service used, the number of alerts generated, and so on.

[1543] Usage example

[1544] For example, if employee C uses "Generation AI Service A" from 9:00 AM to 1:00 PM, the server records that usage. As the usage time exceeds the set standard of three hours, the server immediately sends an alert to the administrator and employee C. In addition, every Monday, a report summarizing the previous week's usage is automatically generated and sent to the administrator. Based on this report, the administrator can review employee C's usage and take appropriate measures as necessary.

[1545] Example prompt sentence:

[1546] "Write a Python program that monitors employee usage of the Generative AI service and sends real-time alerts if it exceeds a set threshold."

[1547] In this way, the present invention is a system that properly monitors and manages the use of generative AI services, prevents fraudulent or excessive use, and enables rapid response.

[1548] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1549] Step 1:

[1550] Perform initial setup. The user (administrator) logs in to the server and sets up a list of authorized generative AI services, including usage criteria and alert conditions.

[1551] Input: A list of allowed generation AI services, e.g. "ServiceA", "ServiceB", "ServiceC".

[1552] Output: Saves the configured allow list and usage criteria.

[1553] How it works: Administrators use a web interface to select permitted services and enter usage time limits and alert conditions.

[1554] Step 2:

[1555] Traffic monitoring: The server monitors all traffic from the internal network to the Internet in real time.

[1556] Input: Network traffic data.

[1557] Output: Access data to generative AI services.

[1558] Specific operation: Analyzes packet data and identifies which service is being accessed.

[1559] Step 3:

[1560] Verify access to generative AI services: The server checks whether access to the detected generative AI service is on an allow list.

[1561] Input: Access data to the generative AI service.

[1562] Output: Decision to allow or block.

[1563] Specific operation: Access data is compared against an allow list and access to unauthorized services is blocked.

[1564] Step 4:

[1565] Record usage status. The server records the start time, end time, and type of service of the AI ​​generation service in detail.

[1566] Input: Usage data of the generation AI service for which access has been granted.

[1567] Output: Saving usage data to a database.

[1568] Specific operation: Record the start and end times of use for each service and save them in a database.

[1569] Step 5:

[1570] Monitor alert conditions: The server monitors whether usage exceeds established thresholds based on usage.

[1571] Input: Usage data and configured usage criteria.

[1572] Output: Generate an alert if the criteria is exceeded.

[1573] Specific operation: Usage time is accumulated, and if it exceeds the set standard, an email notification is sent to the administrator and the relevant employee.

[1574] Step 6:

[1575] Generate reports: The server automatically generates weekly and monthly usage reports.

[1576] Input: Usage data of the generative AI service.

[1577] Output: Generate and email usage reports.

[1578] Specific operation: Usage data is collected, a report is created summarizing each employee's usage, and the report is sent to the administrator via email.

[1579] Step 7:

[1580] The server proposes recommended actions. If excessive use of the generative AI service is detected, the server will propose countermeasures to the administrator.

[1581] Input: Excessive usage data.

[1582] Output: Proposal generation and notification.

[1583] Specific actions: In the event of excessive use, the system generates a message suggesting re-education of specific users on usage guidelines or limiting usage time, and notifies the administrator.

[1584] 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.

[1585] This invention is a system that appropriately manages the usage of generative AI services and is placed between an internal company network and the Internet. It uses data from servers, terminals, and users to monitor and record the usage of generative AI services and detect compliance and security violations. Furthermore, by combining it with an emotion engine, it monitors changes in the user's emotions and provides appropriate countermeasures according to the usage situation.

[1586] 1. Initial Setup

[1587] The user (administrator) logs in to the server and configures a list of authorized generative AI services. For example, add services such as "ServiceA," "ServiceB," and "ServiceC" to the authorization list. In addition, the user configures usage criteria, alert conditions, and emotional data recording settings.

[1588] 2. Traffic Monitoring

[1589] The server monitors all traffic from the internal network to the Internet. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it allows the traffic because it is included in the authorization list. On the other hand, access to the unauthorized "ServiceD" is blocked.

[1590] 3. Records of usage

[1591] The server records the usage of the AI ​​service in detail (start time, end time, type of service, etc.). For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. In addition, the emotion engine analyzes the user's emotional state (e.g., stress, elation, fatigue, etc.), which is also recorded.

[1592] 4. Report Generation

[1593] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[1594] 5. Real-time alerts

[1595] The server generates alerts in real time when an employee's use of the AI-generated service exceeds a set threshold or when the user's emotions indicate a specific state (e.g., high stress level). For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[1596] 6. Recommended Action Suggestion

[1597] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1598] Specific examples

[1599] The user (administrator) logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list, and configures it to generate an alert if the usage time exceeds three hours per day or if a high stress level is reached. If employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A because the usage has exceeded the standard. At the end of the week, a report is sent to the administrator indicating that employee A used "Service A" for a total of 15 hours during this period and that the emotion data indicates high stress. The server then suggests to the administrator that employee A review his usage time and take measures to manage his stress.

[1600] In this way, the system aims to monitor the appropriate use of generative AI services, maintain compliance and security, and also take into account the emotional state of the user, thereby maintaining employees' digital well-being.

[1601] The processing flow will be explained below.

[1602] Step 1:

[1603] User (Administrator): Logs in to the server. The administrator enters authentication information to access the server and logs in to the management interface.

[1604] Step 2:

[1605] User (Admin): Import or manually enter a list of allowed generative AI services. For example, add "ServiceA", "ServiceB", and "ServiceC" to the allowed list.

[1606] Step 3:

[1607] User (Administrator): Sets usage criteria and alert conditions. For example, "Generate an alert if daily usage exceeds three hours." Also, sets emotional data recording settings and alert criteria for specific emotional states.

[1608] Step 4:

[1609] Server: Monitors all traffic from the internal network to the Internet. The server captures network traffic in real time and detects access to the generative AI service.

[1610] Step 5:

[1611] Server: Checks whether the access is to an authorized generated AI service. If it is an authorized service, the traffic is allowed; if it is an unauthorized service, the traffic is blocked.

[1612] Step 6:

[1613] Server: Records usage of the generated AI service, specifically, detailed data such as start time, end time, and type of service.

[1614] Step 7:

[1615] On the device: The emotion engine collects user emotion data, for example, using facial recognition and voice analysis technologies to analyze the user's stress level and other emotional states in real time.

[1616] Step 8:

[1617] Server: The collected emotion data is stored in a database along with usage data of the AI ​​generation service. For example, data such as "Employee A, Service A, 10:00-11:00, high stress level" is recorded in the database.

[1618] Step 9:

[1619] Server: Generates weekly and monthly reports. Collected data is aggregated and reports are created that include usage, alert occurrences, sentiment, etc.

[1620] Step 10:

[1621] Server: Generate reports and email them to an administrator. For example, send a weekly report to admin@example.com.

[1622] Step 11:

[1623] Server: Generates alerts in real time when an employee's use of the AI ​​service exceeds a set threshold or indicates a specific emotional state (e.g., high stress level). For example, if employee B uses "Service B" for 4 hours a day and indicates a high stress level, an alert will be sent immediately to the manager and employee B.

[1624] Step 12:

[1625] Server: If excessive use of the AI ​​generator or specific emotional changes are detected, the server will propose specific countermeasures to the manager. For example, "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1626] Step 13:

[1627] User (Administrator): Implements countermeasures based on suggestions from the server, such as retraining employees on usage guidelines or providing emotional care support.

[1628] Example 2

[1629] 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."

[1630] Managing the appropriate use of generative AI services poses a challenging challenge: maintaining digital well-being by taking into account users' emotional states while ensuring compliance and security. Specifically, it is necessary not only to prevent excessive use of generative AI services and access to unauthorized services, but also to provide appropriate countermeasures in response to changes in users' emotions. However, an efficient system for comprehensively managing these issues is lacking.

[1631] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1632] In this invention, the server is located between the in-house network and the Internet and includes means for monitoring usage of the generated AI service, means for recording usage data of the generated AI service, means for detecting compliance violations and security violations in the use of the generated AI service, means for issuing alerts for excessive use of the generated AI service, means for generating reports based on usage of the generated AI service, means for proposing recommended actions for excessive use of the generated AI service, means for analyzing and recording the user's emotional state, and means for proposing countermeasures according to usage based on the emotional data. This makes it possible to manage appropriate use of the generated AI service, ensure compliance and security, and provide countermeasures based on the user's emotional state.

[1633] An "internal network" is a network to which computers and devices within a company or organization are connected, allowing for internal data communication and resource sharing.

[1634] The "Internet" is a huge global network that interconnects computer networks all over the world, allowing data to be sent and received and information to be shared.

[1635] A "generative AI service" is an online service that uses a generative AI model to generate content such as text, images, or audio.

[1636] "Usage monitoring means" means systems or software that have the ability to monitor the use of generative AI services in real time and track access and frequency of use.

[1637] "Means for recording usage data" refers to a function that stores information about the use of the generative AI service (such as start time, end time, and type of service) in a database or log.

[1638] "Means for detecting compliance and security violations" refers to systems and algorithms that detect when the use of the generative AI services provided violates the standards and security policies of the company or organization.

[1639] "Means for issuing alert notifications regarding excessive use" refers to a function that sends an alert when use of the generative AI service exceeds a pre-set standard.

[1640] The "means for generating usage-based reports" is a function that creates and reports weekly or monthly usage reports based on collected usage data of the generation AI service.

[1641] "Means for suggesting recommended actions" is a function that provides specific countermeasures and improvement measures based on usage data and emotional state of the generating AI service.

[1642] The "means for analyzing and recording emotional state" is a function that analyzes the user's stress level and emotional changes using sensors and input data, and stores the results in a database.

[1643] The "means for proposing countermeasures based on emotional data" is a function that provides countermeasures or improvements that are appropriate for the user's emotional state based on the analyzed emotional data.

[1644] This invention relates to a system for appropriately managing the usage of generative AI services. This system is located between an internal company network and the Internet, and has the function of monitoring and recording the usage of generative AI services using data from servers, terminals, and users, and detecting compliance violations and security violations.

[1645] Initial Setup

[1646] The user (administrator) logs in to the server and accesses the administration screen to set up a list of permitted generative AI services. For example, services such as "Service A," "Service B," and "Service C" are added to the permitted list. Next, usage criteria and alert conditions are set. The user also sets up emotional data recording, specifying the items for which data is to be collected, primarily stress, elation, and fatigue.

[1647] Traffic Monitoring

[1648] The server monitors all traffic from the internal network to the Internet. For this purpose, network traffic analysis tools (e.g., Wireshark, Suricata) are used. When access to a generative AI service is detected, the server checks whether the service is authorized. For example, if it detects access to "ServiceA" from an employee's device, it checks whether the service is on the authorized list and allows its use. Access to the unauthorized "ServiceD" is blocked.

[1649] Usage record

[1650] The server records usage information for the generated AI service—such as the start and end times, and the type of service used—in a database. For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database. Additionally, an emotion engine (e.g., IBM Watson, Affectiva) is used to analyze the user's emotional state, and that data is also recorded. For example, stress levels and fatigue levels are recorded.

[1651] Report Generation

[1652] The server generates weekly and monthly reports based on the collected data. These reports are automatically emailed to administrators. For example, a weekly report might include details about each employee's usage time, type of usage, number of alerts, and mood changes.

[1653] Real-time alerts

[1654] The server generates real-time alerts when usage of the generative AI service exceeds a set threshold or when a user's emotions indicate a specific state—for example, a high stress level. For example, if employee B uses "Service B" for four hours a day and indicates a high stress level, the server immediately sends an alert to the administrator and employee B.

[1655] Recommended actions

[1656] If excessive use of the AI ​​generator or specific emotional changes are detected, the server will suggest specific countermeasures to the manager, such as "Suggest that employee C review the frequency of use of the AI ​​generator service" or "Recommend that employee D take a break to relieve stress."

[1657] Examples of specific examples and prompts

[1658] The administrator logs in to the server and adds "Service A," "Service B," and "Service C" to the allow list. The system is set to generate an alert if usage exceeds three hours per day or if a high stress level is reached. For example, if employee A uses "Service A" from 9:00 AM to 12:00 PM and the emotion engine detects a high stress level, the server records this and sends an alert to the administrator and employee A as usage that exceeds the standard. Then, at the end of the week, a report is sent to the administrator stating that employee A used "Service A" for a total of 15 hours and that the emotion data indicates high stress. The server then suggests to the administrator that they review employee A's usage time and take measures to manage stress.

[1659] Example prompt sentence:

[1660] Add "ServiceA" and "ServiceB" to the allow list and set an alert to be generated when the usage time exceeds 3 hours per day or when a high stress level is reached. Based on this, you can monitor employee usage and generate appropriate reports.

[1661] The system aims to maintain employees' digital well-being by monitoring the appropriate use of generative AI services, maintaining compliance and security, and taking into account the user's emotional state.

[1662] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1663] Step 1:

[1664] The user performs the initial setup

[1665] Input: Administrator credentials, list of allowed generative AI services, usage criteria, alert conditions, emotion data recording settings

[1666] Specific behavior:

[1667] The user (administrator) enters authentication information (user name and password) to log in to the server.

[1668] Access the admin panel and add services such as "ServiceA", "ServiceB", and "ServiceC" to the allow list.

[1669] Set usage criteria and alert conditions (if daily usage exceeds 3 hours or if high stress levels are reached).

[1670] Configure emotional data recording settings and specify the type of emotional data to collect (e.g., stress, elation, fatigue).

[1671] Output: The configured permission list, usage criteria, alert conditions, and emotion data recording settings are saved on the server.

[1672] Step 2:

[1673] The server monitors all traffic from the internal network to the Internet.

[1674] Input: Network traffic data

[1675] Specific behavior:

[1676] The server uses network traffic analysis tools (e.g., Wireshark, Suricata) to monitor communication packets in real time.

[1677] To detect access to generative AI services, filtering is performed based on specific domain names, IP addresses, and URL patterns.

[1678] Output: Access log to the generation AI service

[1679] Step 3:

[1680] The server decides whether to allow or deny the service.

[1681] Input: Allow list, access logs for generated AI services

[1682] Specific behavior:

[1683] The server checks whether the destination of the access to the generated AI service in the access log is included in the configured permission list.

[1684] For example, it detects access to "ServiceA" from an employee's device and allows that traffic if it is included in the allowed list, while blocking access to unauthorized "ServiceD."

[1685] Output: Log of allowed and blocked accesses

[1686] Step 4:

[1687] Server-generated records of AI service usage

[1688] Input: Access logs of permitted and prohibited access, start and end times of permitted AI generation services, and service types

[1689] Specific behavior:

[1690] The server records the start and end times of authorized access to the generated AI service, as well as the type of service used.

[1691] For example, if employee A uses "Service A" from 10:00 AM to 11:00 AM, that information is stored in the database.

[1692] Output: Generated AI service usage database entries

[1693] Step 5:

[1694] The server uses an emotion engine to analyze and record the user's emotional state.

[1695] Input: User emotional data (e.g., stress level, elation, fatigue)

[1696] Specific behavior:

[1697] The server uses an emotion engine (e.g., IBM Watson, Affectiva) to analyze emotion data obtained from sensors and user input.

[1698] For example, analyze employee A's stress level and record the results in a database.

[1699] Output: A database entry of the analyzed sentiment data

[1700] Step 6:

[1701] The server generates weekly and monthly reports

[1702] Input: Usage data of the generated AI service, emotion data

[1703] Specific behavior:

[1704] The server aggregates the collected usage data and emotion data of the generative AI service and creates a report in a specified format.

[1705] For example, a report can be generated that compiles information such as usage over the course of a week, emotional state, and number of alerts.

[1706] Output: Generated weekly and monthly reports

[1707] Step 7:

[1708] Server generates real-time alerts

[1709] Input: Set criteria, usage data of the generating AI service, and emotional data

[1710] Specific behavior:

[1711] The server checks whether the usage of the generative AI service meets the criteria if it exceeds the set threshold or detects a specific emotional state, such as a high stress level.

[1712] For example, if employee B uses "Service B" for four hours and shows a high stress level, check whether the alert conditions are met.

[1713] If the alert conditions are met, an alert will be sent to the administrator and relevant employees via email or in-system notification.

[1714] Output: The generated alert notification

[1715] Step 8:

[1716] The server proposes recommended actions

[1717] Input: Usage data of the generated AI service, emotion data, and set countermeasures

[1718] Specific behavior:

[1719] The server analyzes excessive use of generative AI services and specific emotional states, and generates specific countermeasures and improvement measures.

[1720] For example, suggestions may be made such as "Suggest that employee C review the frequency of use of the generative AI service" or "Recommend that employee D take a break to relieve stress."

[1721] The administrator will be notified of the suggestions via email or dashboard.

[1722] Output: Sending a recommended action notification

[1723] (Application example 2)

[1724] 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."

[1725] As the use of generative AI services rapidly expands, companies are required to properly manage their use of generative AI services and prevent compliance and security violations. It is also important to monitor employee stress and fatigue caused by excessive use of generative AI services and help them manage their health. The present invention provides a system to solve these problems.

[1726] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1727] In this invention, the server is located between the internal network and the Internet and includes means for monitoring usage of the generating AI service, means for recording usage data of the generating AI service, means for detecting compliance violations and security violations in the use of the generating AI service, means for issuing alerts for excessive use of the generating AI service, means for generating reports based on usage of the generating AI service, means for proposing recommended actions for excessive use of the generating AI service, and means for monitoring the user's emotional state and issuing warnings or recommending actions based on the emotional data.This enables companies to effectively monitor and manage the use of the generating AI service, ensuring compliance and security, while taking appropriate measures that take into account the emotional state and health of employees.

[1728] An "internal network" refers to a computer network used within a company or organization, and is a closed network that is different from the Internet.

[1729] "Generative AI services" refer to services that automatically generate content or data using artificial intelligence technology.

[1730] "Means for monitoring usage" refers to a device or program that collects information about the use of generative AI services and monitors the duration and frequency of use in real time.

[1731] "Means for recording usage data" refers to a device or program that records the usage history of the generative AI service in detail and stores it in a state that can be analyzed later.

[1732] "Means for detecting compliance or security violations" means devices or programs for determining whether the use of generative AI services violates company regulations or security policies and for detecting violations.

[1733] "Means for providing alert notifications regarding excessive use" refers to a device or program that issues a warning to administrators or users when use of the generative AI service exceeds a specified threshold.

[1734] A "means for generating usage-based reports" is a device or program that periodically creates a report summarizing usage status based on collected usage data of the generation AI service.

[1735] A "means for proposing recommended actions" is a device or program that suggests appropriate measures to administrators or users in the event of excessive use of generative AI services or other concerns.

[1736] "Means for monitoring emotional states and issuing warnings or recommending actions based on emotional data" refers to a device or program that analyzes a user's emotional state in real time and provides appropriate warnings or countermeasures based on that information.

[1737] This paper describes a method for building a system that effectively manages and monitors the use of generative AI services based on this invention. It also describes the specific system configuration, hardware, and software used for this purpose.

[1738] System Configuration

[1739] The system mainly includes the following elements:

[1740] 1. A server located between the company network and the Internet

[1741] The server monitors all traffic from the internal network to the internet. If it detects access to a generative AI service, it checks whether that service is on an allow list. Access to unauthorized services is blocked.

[1742] 2. Device that records usage of the AI ​​service

[1743] The server records detailed usage data of the generated AI service (such as start time, end time, and type of service), including the duration and frequency of each service used by the user.

[1744] 3. Software that detects compliance and security violations

[1745] Software installed on the server analyzes usage data generated by AI services and automatically detects compliance and security violations.

[1746] 4. Emotion Engine

[1747] This engine is used to analyze the user's emotional state by analyzing the user's heart rate data, facial expressions, and voice tone in real time, and recording the user's stress level and fatigue level.

[1748] 5. Report generation function

[1749] The server periodically generates usage reports based on the collected data, which are emailed to administrators on a weekly and monthly basis.

[1750] 6. Real-time alert function

[1751] If usage or changes in emotional state exceeding set standards are detected, the server generates an alert in real time and notifies the administrator and the relevant user.

[1752] 7. Recommended Actions

[1753] If excessive use of generative AI services or high stress levels are detected, the server will suggest specific countermeasures to users and administrators.

[1754] Hardware and software used

[1755] Hardware

[1756] A server that monitors traffic on the company's internal network

[1757] Smartphones and wearable devices for collecting user emotion data

[1758] software

[1759] Network monitoring software (NetworkMonitor library)

[1760] Software for analyzing emotional states (EmotionEngine library)

[1761] Alert notification software (AlertService library)

[1762] Report generation software (ReportGenerator library)

[1763] Specific examples

[1764] For example, consider a situation where Employee A is using a smartphone app to monitor their use of "Service A." Employee A initiates a connection to the generative AI service using the prompt "Connect to Service A." The app is configured to send an alert if the user uses the app for more than three hours or if the user experiences high stress. An example prompt is shown below:

[1765] "Perform sentiment analysis using the following data to determine your current stress level: [heart rate data, facial expression images, voice tone]"

[1766] The system enables businesses to effectively manage the use of generative AI services, ensuring compliance and security while maintaining the digital well-being of their employees.

[1767] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1768] Step 1:

[1769] The server monitors all traffic on the company's internal network and detects access to the generative AI service. The input is network traffic data, and the output is detected access information for the generative AI service. This traffic data is analyzed to identify which users are accessing which generative AI services.

[1770] Step 2:

[1771] The server checks whether the detected generated AI service is included in the allow list. The input is the access information of the generated AI service, which is the output of step 1, and the output is an instruction to allow or block access. Access to generated AI services that are not included in the allow list is blocked.

[1772] Step 3:

[1773] The device records usage data of the generated AI service. The input is the usage information of the generated AI service identified in step 1, and the output is a detailed usage record such as the start time, end time, and type of service. This data is stored in a database.

[1774] Step 4:

[1775] The server analyzes the usage data of the generated AI service and detects compliance and security violations. The input is the usage data obtained in step 3, and the output is information on whether or not there is a violation. If a violation is detected, the administrator is notified.

[1776] Step 5:

[1777] The emotion engine monitors the user's emotional state and issues warnings or recommends actions based on the emotional data. The input is the user's heart rate data, facial expression images, and voice tone, and the output is the analysis result of the user's emotional state. If high stress or fatigue is detected, the server will suggest appropriate actions.

[1778] Step 6:

[1779] The server generates a report based on the usage of the generative AI service. The input is the data collected in Steps 3 and 5, and the output is a detailed usage report. This report is sent to the administrator on a weekly and monthly basis.

[1780] Step 7:

[1781] The real-time alert function allows the server to immediately generate an alert if it detects usage of the generative AI service exceeding set standards or a change in a specific emotional state. The input is the data from Steps 3 and 5, and the output is a warning message. This allows users and administrators to be notified in real time.

[1782] Step 8:

[1783] If the server detects excessive use of the generative AI service or a high level of stress, it will propose specific countermeasures to the user or administrator. The input is the warning data from Step 7, and the output is specific recommended actions. This allows the user to take appropriate actions such as taking appropriate breaks or reviewing the frequency of use.

[1784] 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.

[1785] 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.

[1786] 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 robot 414.

[1787] 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.

[1788] 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.

[1789] 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.

[1790] 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).

[1791] 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.

[1792] 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."

[1793] 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.

[1794] 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).

[1795] 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.

[1796] 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.

[1797] 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.

[1798] 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.

[1799] 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.

[1800] 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.

[1801] 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.

[1802] 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.

[1803] 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.

[1804] 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.

[1805] The following is further disclosed regarding the above embodiment.

[1806] (Claim 1)

[1807] A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet;

[1808] a means for recording usage data of the Generative AI Service;

[1809] A means of detecting compliance or security violations in the use of generative AI services;

[1810] A means of alerting users to excessive use of generative AI services; and

[1811] a means for generating a report based on usage of the generating AI service;

[1812] A means to propose recommended actions for excessive use of generative AI services;

[1813] A system including:

[1814] (Claim 2)

[1815] 10. The system of claim 1, further comprising means for blocking unauthorized access to the generative AI service.

[1816] (Claim 3)

[1817] 10. The system of claim 1, further comprising means for cooperating with a generative AI service provider and providing data through an API.

[1818] "Example 1"

[1819] (Claim 1)

[1820] A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet;

[1821] a means for recording usage data of the Generative AI Service;

[1822] A means of detecting compliance or security violations in the use of generative AI services;

[1823] A means of alerting users to excessive use of generative AI services; and

[1824] a means for generating a report based on usage of the generating AI service;

[1825] A means to propose recommended actions for excessive use of generative AI services;

[1826] a means for an administrator to log in to the server and configure a list of allowed services;

[1827] A means for administrators to set usage criteria and alert conditions;

[1828] A means to monitor all traffic from the company's internal network to the Internet in real time and check whether it is access to the AI ​​generation service,

[1829] means for determining whether access to a service is permitted;

[1830] A system including:

[1831] (Claim 2)

[1832] 10. The system of claim 1, further comprising means for blocking unauthorized access to the generative AI service.

[1833] (Claim 3)

[1834] 10. The system of claim 1, further comprising means for cooperating with a generative AI service provider and providing data through an API.

[1835] "Application Example 1"

[1836] (Claim 1)

[1837] A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet;

[1838] a means for recording usage data of the Generative AI Service;

[1839] A means of detecting compliance or security violations in the use of generative AI services;

[1840] A means of alerting users to excessive use of generative AI services; and

[1841] a means for generating a report based on usage of the generating AI service;

[1842] A means to propose recommended actions for excessive use of generative AI services;

[1843] A means for monitoring and managing the usage of the generated AI service in real time through an application running on a smartphone;

[1844] A means of alerting managers and employees via email;

[1845] A means to automatically generate usage reports on specific days of the week and send them to administrators;

[1846] A system including:

[1847] (Claim 2)

[1848] 10. The system of claim 1, further comprising means for blocking unauthorized access to the generative AI service.

[1849] (Claim 3)

[1850] 10. The system of claim 1, further comprising means for cooperating with a generative AI service provider and providing data through an API.

[1851] "Example 2: Combining Emotion Engines"

[1852] (Claim 1)

[1853] A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet;

[1854] a means for recording usage data of the Generative AI Service;

[1855] A means of detecting compliance or security violations in the use of generative AI services;

[1856] A means of alerting users to excessive use of generative AI services; and

[1857] a means for generating a report based on usage of the generating AI service;

[1858] A means to propose recommended actions for excessive use of generative AI services;

[1859] means for analyzing and recording the user's emotional state;

[1860] A means for proposing countermeasures according to usage conditions based on emotion data;

[1861] A system including:

[1862] (Claim 2)

[1863] 10. The system of claim 1, further comprising means for blocking unauthorized access to the generative AI service.

[1864] (Claim 3)

[1865] 10. The system of claim 1, further comprising means for cooperating with a generative AI service provider and providing data through an API.

[1866] "Application example 2 when combining emotion engines"

[1867] (Claim 1)

[1868] A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet;

[1869] a means for recording usage data of the Generative AI Service;

[1870] A means of detecting compliance or security violations in the use of generative AI services;

[1871] A means of alerting users to excessive use of generative AI services; and

[1872] a means for generating a report based on usage of the generating AI service;

[1873] A means to propose recommended actions for excessive use of generative AI services;

[1874] A means for monitoring the user's emotional state and issuing warnings or recommending actions based on the emotional data;

[1875] A system including:

[1876] (Claim 2)

[1877] 10. The system of claim 1, further comprising means for blocking unauthorized access to the generative AI service.

[1878] (Claim 3)

[1879] 10. The system of claim 1, further comprising means for cooperating with a generative AI service provider and providing data through an API. [Explanation of symbols]

[1880] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for monitoring the usage of the generative AI service, which is placed between the company's internal network and the Internet; a means for recording usage data of the Generative AI Service; A means of detecting compliance or security violations in the use of generative AI services; A means of alerting users to excessive use of generative AI services; and a means for generating a report based on usage of the generating AI service; A means to propose recommended actions for excessive use of generative AI services; A system including:

2. The system of claim 1 , further comprising means for blocking unauthorized access to the generative AI service.

3. The system of claim 1 , further comprising means for cooperating with a generative AI service provider and providing data through an API.

Images