Company rule revision device, company rule revision method, company rule revision program, and recording medium

Abstract

To obtain a company regulation revision device, a company regulation revision method, a company regulation revision program, and a recording medium that can reduce time and effort required for company regulation revision.SOLUTION: A company regulation revision device 10 includes a data acquisition section 11, and a revised company regulation generation section 12. The data acquisition section 11 acquires current company regulation data, and revision outline data. The revised company regulation generation section 12 generates revised company regulation that is company internal regulation after revision, by inputting the current company regulation data and the revision outline data acquired by the data acquisition section 11 to artificial intelligence 20.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to a company rule revising device, a company rule revising method, a company rule revising program, and a recording medium. [Background technology]

[0002] In a conventional standards information management device, when revision information indicating the revision details of a standard to be revised is input to an input unit, an update unit updates a database of revision information for the standard to be revised based on the revision information. Then, a notification unit notifies the revision information to those involved in shipped products that correspond to the standard to be revised (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-163242 Summary of the Invention [Problem to be solved by the invention]

[0004] In conventional standards information management devices such as those described above, when revision information is input, the revision information database is updated and relevant parties are notified of the revision information, but the revision content itself is created manually, and the actual revision work requires a great deal of effort.

[0005] The present disclosure has been made to solve the above-mentioned problems, and aims to provide a company rule revision device, a company rule revision method, a company rule revision program, and a recording medium that can reduce the effort required for revising company rules. [Means for solving the problem]

[0006] The company rule revision device according to the present disclosure includes a data acquisition unit that acquires current company rule data, which is data on the current company rules that are the subject of revision, and revision summary data, which is data that outlines the revisions to the current company rules, and a revised company rule generation unit that generates revised company rules, which are the company rules after revision, by inputting the current company rule data and revision summary data acquired by the data acquisition unit into artificial intelligence. The company rule revision method disclosed herein includes a data acquisition step of acquiring current company rule data, which is data on the current company rules that are to be revised, and revision summary data, which is data that shows an overview of the revisions to the current company rules, and a revised company rule generation step of generating revised company rules, which are the company rules after revision, by inputting the current company rule data and revision summary data acquired by the data acquisition step into artificial intelligence. [Effects of the Invention]

[0007] According to the present disclosure, the effort required for revising company rules can be reduced. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a block diagram showing a company rule revision system according to a first embodiment. [Figure 2] 3 is a flowchart showing a company rule revising process performed by the company rule revising device of FIG. 1. [Figure 3] FIG. 10 is a block diagram showing a modified example of the company rule revising device according to the first to seventh embodiments. [Figure 4] 1 is a configuration diagram showing a first example of a processing circuit that realizes each function of the company rule revising device and artificial intelligence according to the first to seventh embodiments. FIG. [Figure 5] FIG. 10 is a configuration diagram showing a second example of a processing circuit that realizes each function of the company rule revising device and artificial intelligence according to the first to seventh embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments will be described with reference to the drawings. Embodiment 1 1 is a block diagram showing a company rule revision system according to embodiment 1. In the figure, the company rule revision system includes a company rule revision device 10 and an artificial intelligence 20.

[0010] The company rule revising device 10 has, as functional blocks, a data acquiring unit 11 and a revised company rule generating unit 12. As the company rule revising device 10, for example, a personal computer can be used.

[0011] The data acquisition unit 11 acquires input data. The input data includes current company rule data, revision summary data, and explanatory data. The user inputs the current company rule data, revision summary data, and explanatory data into the company rule revision device 10.

[0012] Current company rules data is data on the current company rules that are subject to revision. Company rules include employee work rules, wage rules, detailed wage regulations, etc. Wage rules are attached to employee work rules. Furthermore, detailed wage regulations stipulate the details of wage rules. In this way, company rules are often divided into multiple layers.

[0013] Multiple internal rules are interrelated. Furthermore, each internal rule is made up of multiple articles. The number of internal rules to be revised may be one or more. Furthermore, the internal rules to be revised may be all of the articles in each internal rule, or only some of the articles contained in each internal rule.

[0014] The revision summary data is data that indicates an outline of the revisions to the current company rules. Specifically, the revision summary data includes text data that explains the outline of the revisions.

[0015] The outline of the revisions can be of various granularities. In other words, the outline of the revisions can be close to the articles of the revised company rules, or it can only indicate the direction of the revised company rules, and various patterns are possible. The revised company rules are the revised company rules obtained by revising the current company rules.

[0016] The explanatory data is data explaining the current company rules. For example, the explanatory data is data explaining each article of the current company rules. The article-by-article explanation explains the content of each article contained in the current company rules in simple language. The article-by-article explanation also explains the purpose of the current company rules, the scope of application, etc., as information necessary for applying the company rules.

[0017] The revised company rules generation unit 12 generates revised company rules by inputting the current company rules data, the revised summary data, and the explanatory data acquired by the data acquisition unit 11 into the artificial intelligence 20.

[0018] The artificial intelligence 20 is provided, for example, in a server independent from the company rule revising device 10. The company rule revising device 10 and the artificial intelligence 20 can communicate with each other.

[0019] The artificial intelligence 20 has, as functional blocks, a trained model storage unit 21 and an inference unit 22. The trained model storage unit 21 stores trained models. The trained models are models that receive current company rule data, revision summary data, and explanatory data sent from the company rule revision device 10 as inputs and output revised company rules.

[0020] The inference unit 22 inputs the current company rule data, revision summary data, and explanation data input by the company rule revision device 10 into the trained model stored in the trained model storage unit 21. The inference unit 22 also sends the revised company rule data output from the trained model to the company rule revision device 10.

[0021] The trained model may be a model trained by machine learning, for example, by supervised learning, reinforcement learning, or unsupervised learning.

[0022] Furthermore, the trained model may be a model obtained by performing learning according to, for example, deep learning, genetic programming, functional logic programming, or other known algorithms or methods.

[0023] Specifically, the trained model may be a model called a Neural Network (NN) model, a Convolutional Neural Network (CNN) model, a Recurrent Neural Network (RNN), a Variational Autoencoder (VAE), a Generative Adversarial Network (GAN), a Diffusion Model, a Transformer model, a Large Language Model (LLM), a Visual Language Model (VLM), a Bidirectional Encoder Representations from Transformers (BERT), a Generative Pre-trained Transformer (GPT), or a Contrastive Language Image Pre-training (CLIP).

[0024] The above-mentioned models are not exclusive, and for example, LLM, VLM, BERT, and GPT are included in the Transformer model. Also, for example, the Transformer model is included in the NN model.

[0025] Furthermore, multiple types of learning algorithms and models may be combined. Trained models also include models called multimodal models that are trained by combining multiple different types of data.

[0026] Fig. 2 is a flowchart showing the company rule revision process by the company rule revision device 10 of Fig. 1. When the company rule revision process starts, the company rule revision device 10 acquires current company rule data, revision summary data, and commentary data in step S101.

[0027] Next, in step S102, the company rule revision device 10 inputs the current company rule data, revision summary data, and commentary data into the artificial intelligence 20. Then, in step S103, the company rule revision device 10 acquires and stores the output from the artificial intelligence 20. Once the revised company rule has been created in this way, the company rule revision device 10 ends the processing.

[0028] The company rule revision device 10 creates a format for the revised company rules as needed. The format may include a revision history showing the revised parts, a comparison table of the company rules before and after the revision, etc. The revision history, comparison table, etc. may be included in the output from the artificial intelligence 20.

[0029] The format of the revised company rules may be created by an external device (not shown). In this case, the company rules revising device 10 outputs the data of the revised company rules acquired from the artificial intelligence 20 to the external device.

[0030] As a concrete example of company rule revision, the following will explain the case where the company rule to be revised is the travel expense rule. In this example, the travel expense rule stipulates that actual expenses must be paid for accommodation during business trips. However, it also stipulates that the upper limit of accommodation expenses is 10,000 yen.

[0031] In addition, the explanation of the travel expenses regulations states that the upper limit for travel expenses is set at 10,000 yen, taking into account the average accommodation prices at accommodation facilities across the country.

[0032] In addition, the summary of the revisions to the travel expenses regulations states that, since accommodation fees vary greatly depending on the region, the upper limit on accommodation fees will be revised to a rate that takes into account the circumstances of each region.

[0033] By inputting the current company regulations data, the revised summary data, and the explanatory data containing the above-mentioned content into the artificial intelligence 20, the artificial intelligence 20 outputs revised company regulations in which the upper limit of accommodation costs has been changed for each region, for example, based on data on the average cost of accommodation suitable for business trips in each region.

[0034] In addition, travel expense regulations may also stipulate an upper limit on subsidies for food and beverage expenses during business trips. In this case, even if the summary of revisions to the travel expense regulations does not include any mention of revisions to food and beverage expenses, the AI ​​20 can suggest revisions to the provisions regarding food and beverage expenses based on data on average food and beverage expenses by region, just as with accommodation expenses.

[0035] On the other hand, if there are circumstances that make it undesirable to revise the food and beverage expenses, by stating in the summary of the revision that the provisions regarding food and beverage expenses will not be revised, the artificial intelligence 20 will output revised company rules that do not change the provisions regarding food and beverage expenses. In other words, the summary of the revision may state the items that are prohibited from being revised, which can prevent unnecessary revisions and save the effort of checking the output contents.

[0036] The company rule revising method of the first embodiment includes a data acquiring step and a revised company rule generating step.

[0037] The data acquisition step is a step of acquiring current company rules data, revised summary data, and explanatory data. The revised company rules generation step is a step of generating revised company rules by inputting the current company rules data, revised summary data, and explanatory data acquired in the data acquisition step into the artificial intelligence 20.

[0038] In such a company rule revising device 10 and company rule revising method, revised company rules are generated by acquiring current company rule data and revision summary data and inputting them into the artificial intelligence 20. Therefore, by using current company rule data that is usually prepared in-house, specific revised company rules can be created simply by preparing revision summary data, thereby reducing the effort required for revising company rules.

[0039] Furthermore, in the first embodiment, revised company rules are generated by acquiring explanatory data in addition to the current company rule data and the revision summary data and inputting it into the artificial intelligence 20. Therefore, by using explanatory data that is usually prepared in-house, more appropriate revised company rules can be created, further reducing the effort required to revise company rules.

[0040] The company rule revision program of the first embodiment is a program that causes a computer to execute the company rule revision method described above.

[0041] The recording medium of the first embodiment is a computer-readable recording medium having recorded thereon a company rule revising program that causes a computer to execute the company rule revising method of the first embodiment.

[0042] Embodiment 2 Next, a company rule revising device 10 according to embodiment 2 will be described. The configuration of the company rule revising system according to embodiment 2 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 2 is the same as that shown in Fig. 2.

[0043] The data acquisition unit 11 of the second embodiment acquires related rule data in addition to the current company rule data, the revision summary data, and the commentary data. A user inputs the current company rule data, the revision summary data, the commentary data, and the related rule data into the company rule revision device 10.

[0044] The related rule data is data on rules that are related to the current company rules that are the subject of revision, but are not the subject of revision.

[0045] The revised company rules generation unit 12 generates revised company rules by inputting the relevant rule data to the artificial intelligence 20 in addition to the current company rules data, the revision summary data, and the commentary data.

[0046] The data acquisition step of the second embodiment is a step of acquiring related rule data in addition to current company rule data, revision summary data, and commentary data.

[0047] The revised company rules generation step of the second embodiment is a step of generating revised company rules by inputting relevant rule data to the artificial intelligence 20 in addition to the current company rules data, revision summary data, and commentary data.

[0048] Other configurations and methods in the second embodiment are the same as those in the first embodiment.

[0049] In such a company rule revising device 10 and company rule revising method, revised company rules are generated by acquiring related rule data and inputting it into the artificial intelligence 20. Therefore, revised company rules can be generated so that there is no contradiction between the revised company rules and rules that are not subject to revision.

[0050] For example, if the company rules to be revised are detailed wage rules, the related rule data may be data on the wage rules. Since the wage rules are higher-level rules than the detailed wage rules, the detailed wage rules are bound by the content of the wage rules. Therefore, by using the data on the wage rules as the related rule data, the detailed wage rules can be revised so as not to contradict the content of the wage rules.

[0051] The company rule revising program of the second embodiment is a program that causes a computer to execute the company rule revising method of the second embodiment.

[0052] The recording medium of the second embodiment is a computer-readable recording medium that records a company rule revising program that causes a computer to execute the company rule revising method of the second embodiment.

[0053] In the second embodiment, the rules not to be revised that are included in the related rule data are not limited to company rules, but may also be external rules such as related laws and regulations. For example, if the company rules to be revised are employee work rules, the related rule data may be laws such as the Labor Standards Act.

[0054] Furthermore, in the second embodiment, if the rule not subject to revision included in the related rule data is a statute, data on explanatory text explaining the content of the statute may be acquired in addition to the related rule data and input to the artificial intelligence 20. The explanatory texts of the statutes are easily available because they are published by the relevant government ministries and agencies. By using the data on explanatory texts of the statutes, the appropriateness of the revised company rules can be improved.

[0055] Furthermore, laws and regulations related to the company rules, their explanatory texts, etc. may be input manually or automatically into the artificial intelligence 20 in advance. In this case, when the laws and regulations, their explanatory texts, etc. are revised, the revisions may be automatically reflected in the trained model.

[0056] Embodiment 3 Next, a company rule revising device 10 according to embodiment 3 will be described. The configuration of the company rule revising system according to embodiment 3 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 3 is the same as that shown in Fig. 2.

[0057] The data acquisition unit 11 of the third embodiment acquires company information data in addition to the current company rule data, the revision summary data, and the commentary data. A user inputs the current company rule data, the revision summary data, the commentary data, and the company information data into the company rule revision device 10.

[0058] The company information data is data showing information about the company whose internal rules are to be revised. Examples of the company information include the company philosophy, management strategy, etc.

[0059] The revised company rules generation unit 12 generates revised company rules by inputting the current company rules data, the revision summary data, and the explanation data as well as the company information data into the artificial intelligence 20.

[0060] The data acquisition step of the third embodiment is a step of acquiring company information data in addition to the current company regulations data, the revision summary data, and the commentary data.

[0061] The revised company rules generation step of the third embodiment is a step of generating revised company rules by inputting company information data into the artificial intelligence 20 in addition to the current company rules data, revision summary data, and commentary data.

[0062] Other configurations and methods in the third embodiment are the same as those in the first embodiment.

[0063] In the company rule revising device 10 and company rule revising method, revised company rules are generated by acquiring company information data and inputting it into the artificial intelligence 20. This makes it possible to improve the validity of revised company rules in a company.

[0064] The company rule revising program of the third embodiment is a program that causes a computer to execute the company rule revising method of the third embodiment.

[0065] The recording medium of the third embodiment is a computer-readable recording medium that records a company rule revising program that causes a computer to execute the company rule revising method of the third embodiment.

[0066] Embodiment 4 Next, a company rule revising device 10 according to embodiment 4 will be described. The configuration of the company rule revising system according to embodiment 4 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 4 is the same as that shown in Fig. 2.

[0067] The revised company rules generation unit 12 of the fourth embodiment generates revised company rules and revised explanations by inputting the current company rules data, revision summary data, and explanation data into the artificial intelligence 20. The revised explanations are explanations of the company rules after the revision.

[0068] The revised company regulations generation step of embodiment 4 is a step of generating revised company regulations and revised explanations by inputting the current company regulations data, revised summary data, and explanatory data acquired in the data acquisition step into artificial intelligence 20.

[0069] Other configurations and methods in the fourth embodiment are the same as those in the first embodiment.

[0070] In such a company rule revision device 10 and company rule revision method, revision explanations are generated, so that the data of the revision explanations can be used as explanation data when revising the company rules next time, thereby reducing the effort required for the next company rule revision.

[0071] The company rule revising program of the fourth embodiment is a program that causes a computer to execute the company rule revising method of the fourth embodiment.

[0072] The recording medium of the fourth embodiment is a computer-readable recording medium having recorded thereon a company rule revising program that causes a computer to execute the company rule revising method of the fourth embodiment.

[0073] Embodiment 5 Next, a company rule revising device 10 according to embodiment 5 will be described. The configuration of the company rule revising system according to embodiment 5 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 5 is the same as that shown in Fig. 2.

[0074] The revised company rules generation unit 12 of the fifth embodiment generates the revised company rules and related department information by inputting the current company rules data, the revision summary data, and the explanation data into the artificial intelligence 20. The related department information is information about the internal departments related to the revised company rules.

[0075] The revised company regulations generation step of embodiment 5 is a step in which the revised company regulations and related department information are generated by inputting the current company regulations data, revised summary data, and explanatory data acquired in the data acquisition step into artificial intelligence 20.

[0076] Other configurations and methods in the fifth embodiment are the same as those in the first embodiment.

[0077] In the company rule revising device 10 and company rule revising method, the relevant department information is generated, so that the revised company rules can be more reliably disseminated to all relevant departments within the company.

[0078] For example, the department in charge of travel expense regulations is primarily the general affairs department, but it is also considered that the accounting department is also involved. In this case, information indicating that the departments involved in the revised company regulations are the general affairs department and the accounting department is generated as the related department information.

[0079] The company rule revising program of the fifth embodiment is a program that causes a computer to execute the company rule revising method of the fifth embodiment.

[0080] The recording medium of the fifth embodiment is a computer-readable recording medium that records a company rule revising program that causes a computer to execute the company rule revising method of the fifth embodiment.

[0081] Embodiment 6 Next, a company rule revising device 10 according to embodiment 6 will be described. The configuration of the company rule revising system according to embodiment 6 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 6 is the same as that shown in Fig. 2.

[0082] The revised company rules generation unit 12 of the sixth embodiment inputs the current company rules data, the revision summary data, and the explanation data into the artificial intelligence 20, thereby generating a plurality of different company rules revision proposals as revised company rules.

[0083] The revised company regulations generation step of embodiment 6 is a step in which the current company regulations data, revision summary data, and explanatory data acquired in the data acquisition step are input into artificial intelligence 20 to generate multiple different proposed company regulations as revised company regulations.

[0084] Other configurations and methods in the sixth embodiment are the same as those in the first embodiment.

[0085] In the company rule revision device 10 and company rule revision method, multiple company rule revision proposals are generated, and the person in charge can select the most appropriate company rule revision proposal and use it as the final revised company rule. This allows the appropriateness of revised company rules in a company to be improved simply by selecting one of the multiple company rule revision proposals.

[0086] The company rule revising program of the sixth embodiment is a program that causes a computer to execute the company rule revising method of the sixth embodiment.

[0087] The recording medium of the sixth embodiment is a computer-readable recording medium that records a company rule revising program that causes a computer to execute the company rule revising method of the sixth embodiment.

[0088] The revised company rules generation unit 12 may generate multiple company rule revision proposals and difference explanation information by inputting the current company rules data, revision summary data, and commentary data into the artificial intelligence 20. The difference explanation information is information that explains the differences between the multiple company rule revision proposals. The differences between the multiple company rule revision proposals may include, for example, at least one of the advantages and disadvantages of each company rule revision proposal.

[0089] Embodiment 7 Next, a company rule revising device 10 according to embodiment 7 will be described. The configuration of the company rule revising system according to embodiment 7 is the same as that shown in Fig. 1. The basic flow of the company rule revising process according to embodiment 7 is the same as that shown in Fig. 2.

[0090] The revised company rules generation unit 12 of the seventh embodiment generates revised company rules and revision explanation information by inputting the current company rules data, revision summary data, and explanation data into the artificial intelligence 20. The revision explanation information is information explaining the revised company rules to a person in charge within the company who is related to the revised company rules. The person in charge may be, for example, a person in a managerial position.

[0091] The revised company regulations generation step of embodiment 7 is a step of generating revised company regulations and revised explanatory information by inputting the current company regulations data, revised summary data, and explanatory data acquired in the data acquisition step into artificial intelligence 20.

[0092] Other configurations and methods in the seventh embodiment are the same as those in the first embodiment.

[0093] In the company rule revising device 10 and the company rule revising method, revision explanation information is generated, so that the person in charge can easily understand the content of the revised company rules. As a result, for example, if the person in charge is a manager, the manager's approval for the revised company rules can be quickly obtained.

[0094] The company rule revising program of the seventh embodiment is a program that causes a computer to execute the company rule revising method of the seventh embodiment.

[0095] The recording medium of the seventh embodiment is a computer-readable recording medium having recorded thereon a company rule revising program that causes a computer to execute the company rule revising method of the seventh embodiment.

[0096] The above first to seventh embodiments may be implemented in combination as appropriate.

[0097] For example, in the third to seventh embodiments, the same association rule data as in the second embodiment may be acquired and input to the artificial intelligence 20.

[0098] In addition, in the second and fourth to seventh embodiments, the same company information data as in the third embodiment may be acquired and input to the artificial intelligence 20.

[0099] In addition, in the second, third, fifth to seventh embodiments, a revised commentary may be generated in the same manner as in the fourth embodiment.

[0100] In addition, in the second, third, fourth, sixth, and seventh embodiments, related department information may be generated in the same manner as in the fifth embodiment.

[0101] In addition, in the first to third and fifth to seventh embodiments, the acquisition and input of guidance data may be omitted.

[0102] In the first to seventh embodiments, the current company rule data acquired by the data acquisition unit 11 and the data acquisition step may include data on multiple company rules that do not have a hierarchical relationship. In this case, only the revision summary data on some of the multiple company rules may be acquired.

[0103] An example of multiple internal company rules that do not have a hierarchical relationship is travel expense rules and housing allowance rules. In this case, only the summary data of the revisions to the travel expense rules may be acquired and input to the artificial intelligence 20. In this case, for the housing allowance rules, a revision to the upper limit of the housing allowance subsidy can be proposed based on data on the average rent of rental housing by region, similar to the revision of food and beverage expenses described in the first embodiment.

[0104] In addition, in the first to seventh embodiments, the current company rules data acquired by the data acquisition unit 11 and the data acquisition step may be all current company rules. In this case, the revised company rules generation unit 12 and the revised company rules generation step may generate revised company rules and relationship explanation information. The relationship explanation information is information that explains the relationship between the revised company rules and other company rules.

[0105] 3 is a block diagram showing a modification of the company rule revising device 10 according to the first to seventh embodiments. In this modification, an artificial intelligence 20 is provided in the company rule revising device 10. As shown in FIG.

[0106] In this way, in the first to seventh embodiments, the artificial intelligence 20 may be provided in the company rule revision device 10, and the same effects as those of the first to seventh embodiments can be obtained.

[0107] Each function of the company rule revising device 10 and the artificial intelligence 20 in the first to seventh embodiments is realized by a processing circuit. Fig. 4 is a configuration diagram showing a first example of a processing circuit that realizes each function of the company rule revising device 10 and the artificial intelligence 20 in the first to seventh embodiments. The processing circuit 100 in the first example is dedicated hardware.

[0108] The processing circuit 100 may be, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or a combination thereof. Each function of the company rule revision device 10 and the artificial intelligence 20 may be realized by a separate processing circuit 100, or all functions may be realized by the processing circuit 100.

[0109] 5 is a configuration diagram showing a second example of a processing circuit that realizes each function of the company rule revising device 10 and the artificial intelligence 20 according to the first to seventh embodiments. The processing circuit 200 of the second example includes a processor 201 and a memory 202.

[0110] The processor 201 may be, for example, a central processing unit (CPU), a graphics processing unit (GPU), a microprocessor, a microcontroller, or a digital signal processor (DSP).

[0111] In the processing circuit 200, each function of the company rule revision device 10 and the artificial intelligence 20 is realized by software, firmware, or a combination of software and firmware. The software and firmware are written as programs and stored in the memory 202. The processor 201 realizes each function by reading and executing the programs stored in the memory 202.

[0112] It can also be said that the programs stored in memory 202 cause the computer to execute the procedures or methods of the above-mentioned sections. Here, memory 202 refers to non-volatile or volatile semiconductor memory, such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable and Programmable Read Only Memory). Magnetic disks, flexible disks, optical disks, compact disks, minidisks, DVDs, and the like also fall under memory 202.

[0113] It should be noted that some of the functions of the above-described units may be realized by dedicated hardware, and other parts may be realized by software or firmware.

[0114] In this way, the processing circuit can realize the functions of each of the above-mentioned units by hardware, software, firmware, or a combination of these.

[0115] The above describes in detail preferred embodiments, but the present invention is not limited to the above-described embodiments, and various modifications and substitutions can be made to the above-described embodiments without departing from the scope of the claims.

[0116] Various aspects of the present disclosure are summarized below as appendices.

[0117] (Appendix 1) a data acquisition unit that acquires current company rule data, which is data on the current company rule to be revised, and revision summary data, which is data showing an outline of the revision content of the current company rule; a revised company rules generation unit that generates revised company rules, which are company rules after the revision, by inputting the current company rules data and the revision summary data acquired by the data acquisition unit into an artificial intelligence; A company rule revision device equipped with the above. (Appendix 2) The data acquisition unit further acquires commentary data that is data explaining the current company rules, The company rules revision device described in Appendix 1, wherein the revised company rules generation unit generates the revised company rules by further inputting the explanatory data into the artificial intelligence. (Appendix 3) The company rule revision device described in Appendix 2, wherein the commentary data is data of article-by-article commentary for each article of the current company rules. (Appendix 4) The company rules revision device described in Appendix 2 or Appendix 3, wherein the revised company rules generation unit further generates a revised commentary, which is a commentary of the revised company rules, by further inputting the commentary data into the artificial intelligence. (Appendix 5) The data acquisition unit further acquires related rule data, which is data on rules that are not subject to revision and are related to the current company rules; A company rule revision device described in any one of Appendix 1 to Appendix 4, wherein the revised company rule generation unit generates the revised company rule by further inputting the related rule data into the artificial intelligence. (Appendix 6) The data acquisition unit further acquires company information data, which is data on information of a company that has the current company rules; A company rules revision device described in any one of Appendix 1 to Appendix 5, wherein the revised company rules generation unit generates the revised company rules by further inputting the company information data into the artificial intelligence. (Appendix 7) A company rules revision device described in any one of Appendix 1 to Appendix 6, wherein the revised company rules generation unit further generates related department information, which is information about internal departments related to the revised company rules, by inputting the current company rules data and the revision summary data into artificial intelligence. (Appendix 8) The revised company rules generation unit inputs the current company rules data and the revision summary data into artificial intelligence, thereby generating a plurality of different company rules revision proposals as the revised company rules. (Appendix 9) A company rules revision device as described in any one of Appendix 1 to Appendix 8, wherein the revised company rules generation unit further generates revision explanation information, which is information explaining the revised company rules to internal personnel related to the revised company rules, by inputting the current company rules data and the revision summary data into artificial intelligence. (Appendix 10) A data acquisition step of acquiring current company rules data, which is data on the current company rules to be revised, and revision summary data, which is data showing an outline of the revision content of the current company rules; a revised company rules generation step of generating revised company rules that are company rules after the revision by inputting the current company rules data and the revision summary data acquired in the data acquisition step into an artificial intelligence; How to revise company rules, including: (Appendix 11) A company rule revision program that causes a computer to execute the company rule revision method described in Appendix 10. (Appendix 12) A computer-readable recording medium having recorded thereon a company rule revision program that causes a computer to execute the company rule revision method described in Appendix 10. [Explanation of symbols]

[0118] 10. Company rules revision device, 11. Data acquisition unit, 12. Revised company rules generation unit, 20. Artificial intelligence.

Claims

1. a data acquisition unit that acquires current company rule data, which is data on the current company rule to be revised, and revision summary data, which is data showing an outline of the revision content of the current company rule; a revised company rules generation unit that generates revised company rules, which are company rules after the revision, by inputting the current company rules data and the revision summary data acquired by the data acquisition unit into an artificial intelligence; Equipped with The data acquisition unit further acquires commentary data that is data explaining the current company rules, The revised company rules generation unit is a company rules revision device that generates the revised company rules by further inputting the explanatory data into the artificial intelligence.

2. 2. The company rule revision device according to claim 1, wherein the commentary data is data of article-by-article commentary on each article of the current company rules.

3. The company rule revision device according to claim 1 or claim 2, wherein the revised company rule generation unit further generates a revised commentary that is a commentary of the revised company rule by further inputting the commentary data into the artificial intelligence.

4. The data acquisition unit further acquires related rule data, which is data on rules that are not subject to revision and are related to the current company rules; 3. The company rule revising device according to claim 1, wherein the revised company rule generating unit generates the revised company rule by further inputting the related rule data into the artificial intelligence.

5. The data acquisition unit further acquires company information data, which is data on information of a company that has the current company rules; 3. The company rule revising device according to claim 1, wherein the revised company rule generating unit generates the revised company rule by further inputting the company information data into the artificial intelligence.

6. The company rules revision device described in claim 1 or claim 2, wherein the revised company rules generation unit further generates related department information, which is information regarding internal departments related to the revised company rules, by inputting the current company rules data and the revision summary data into artificial intelligence.

7. The company rule revision device described in claim 1 or claim 2, wherein the revised company rule generation unit generates multiple different company rule revision proposals as the revised company rules by inputting the current company rule data and the revision summary data into artificial intelligence.

8. The company rules revision device described in claim 1 or claim 2, wherein the revised company rules generation unit further generates revision explanation information, which is information explaining the revised company rules to internal personnel related to the revised company rules, by inputting the current company rules data and the revision summary data into artificial intelligence.

9. A data acquisition step in which a data acquisition unit in the company rule revision device acquires current company rule data, which is data on the current company rule to be revised, revision summary data, which is data showing an outline of the revision content of the current company rule, and commentary data, which is data on the commentary of the current company rule; A revised company rules generation step in which the current company rules data, the revision summary data, and the commentary data acquired by the data acquisition step are input to an artificial intelligence by a revised company rules generation unit in the company rules revision device, thereby generating revised company rules that are internal company rules after revision. How to revise company rules, including:

10. A company rule revision program that causes a computer to execute the company rule revision method according to claim 9.

11. A computer-readable recording medium having recorded thereon a company rule revising program for causing a computer to execute the company rule revising method according to claim 9.

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