A support device for creating documents for new projects.

Abstract

To support the efficient creation and improvement of the quality of new project materials through co-creation between humans and AI. [Solution] The support device 1 for creating materials for a new project according to the present invention comprises an input screen display unit 112 that commands the display of an input screen E for inputting study result data related to the new project, a study result acquisition unit 113 that acquires study result data input via the input screen E, a study result candidate generation unit 114 that causes a large-scale language model to generate candidate study results (study result candidates), and a material generation unit 117 that causes a large-scale language model to generate materials for the new project. The input screen display unit 112 is configured to provide an operation on the input screen E to include part or all of the study result candidates in the input of the study result data when study result candidates have been generated.

Description

Technical Field

[0001] The present invention relates to a device for assisting in the creation of materials for a new plan.

Background Art

[0002] In the business field, the creation of materials for new plans, such as new business plans, is carried out. However, it is not easy to create such materials so that they are evaluated as business documents. Therefore, there is a need for a technology that supports the creation of materials evaluated as business documents.

[0003] In conventional services and prior arts, regarding technologies for assisting in the creation of materials evaluated as business documents, Patent Document 1 discloses a creation support device that receives a new quotation containing requirement specification information for bidding in projects such as plant design and construction, and supports the creation of a proposal containing bid specification information corresponding to the new quotation. The device includes an arithmetic unit that determines the similarity between the content included in the new quotation and the content included in past quotations or past proposals, and extracts content useful for creating a proposal from the history data associated with the past quotations using the similarity; and a providing unit that generates and provides auxiliary data for use in creating a proposal using the result of the arithmetic unit.

[0004] The technology described in Patent Document 1 can efficiently grasp the specification presented at the time of invitation to bid and support the creation of an accurate proposal based on the specification by the bidder.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Incidentally, in bidding for plant design and construction projects, it is expected that specifications similar to those of past projects will be submitted. Therefore, proposals in such bidding processes are expected to be more likely to succeed and will be more highly regarded as business documents the more similar their content is to reference documents for similar past specifications.

[0007] In contrast, new projects are required to be different from past projects. Therefore, if the materials for a new project are similar to those for past projects, it is unlikely that they will be evaluated as business documents.

[0008] The technology described in Patent Document 1 extracts content useful for creating proposals from historical data associated with past reference documents, using similarity. Therefore, the technology described in Patent Document 1 is only capable of assisting in the creation of proposals for bidding in projects such as plant design and construction, and it is presumed that there is room for further improvement in terms of assisting in the creation of materials for new projects.

[0009] The objective of this invention is to support the creation of materials for new projects through co-creation between humans and artificial intelligence (AI). [Means for solving the problem]

[0010] As a result of diligent research to solve the above problems, the inventors of the present invention have found that the above objectives can be achieved by providing an operation in the input screen for inputting the results of a new project, which includes candidate study results generated by a large-scale language model based on the basic data of the new project and the previously entered study result data. Thus, the inventors of the present invention have completed the present invention.

[0011] One aspect of the present invention provides a support device for creating materials for a new project, comprising: a basic data acquisition unit for acquiring basic data for a new project; an input screen display unit for commanding the display of an input screen for inputting review result data related to the new project; a review result acquisition unit for acquiring the review result data input via the input screen; a review result candidate generation unit for inputting a prompt including the basic data, or a prompt including the basic data and the review result data, into a large-scale language model to generate candidate review results (candidate review results); and a material generation unit for inputting a prompt including the basic data and the review result data into a large-scale language model to generate materials for the new project, wherein the input screen display unit is configured to provide an operation on the input screen to include part or all of the candidate review results in the input of the review result data when candidate review results have been generated.

[0012] The input screen display unit in this embodiment displays an input screen for entering the results of the consideration of the new project. The support device in this embodiment uses a document generation unit to generate documents for the new project using a large-scale language model based on the basic data of the new project acquired by the basic data acquisition unit and the consideration result data entered from this input screen. However, for users unfamiliar with creating documents for new projects, it is not easy to appropriately list the necessary consideration items and input them.

[0013] In this embodiment, the input screen display unit displays an input screen that provides an operation to include some or all of the candidate review results generated by the candidate review result generation unit, which inputs prompts including basic data and the aforementioned review result data into the large-scale language model, into the review result data. In other words, the support device in this embodiment shows the candidate review results generated by the large-scale language model to the user, enabling the user to add some or all of them to their own review results. This allows the user to combine the AI's review results with their own, enabling co-creation between humans and AI. The support device in this embodiment then generates new project materials through this co-creation. If the AI ​​alone were to generate the materials, there would be concerns that they would be similar to new project materials created in the past. However, by enabling co-creation between humans and AI, the support device in this embodiment can provide materials that reflect different review results from past materials input by humans.

[0014] Based on the above, this embodiment can support the efficient creation and improvement of the quality of materials for new projects through co-creation between humans and AI.

[0015] Furthermore, the present invention can take various forms, as exemplified by: a form that promotes co-creation between humans and AI through questions to the inputter; a form that allows input of the results of consideration divided into three stages: advantages and prospects of the new project, concerns of the new project, and measures to overcome the concerns; a form that shows the AI's evaluation of the generated materials; and a form that enables co-creation with others in addition to co-creation with AI. Each of these forms, through the effects brought about by the addition of its unique configuration, contributes to supporting the efficient creation of materials for new projects and improving their quality through co-creation between humans and AI. [Effects of the Invention]

[0016] Based on the above, the present invention can support the efficient creation of materials for new projects and the improvement of their quality through co-creation between humans and AI. [Brief explanation of the drawing]

[0017] [Figure 1]FIG. 1 is a block diagram showing an example of the hardware configuration and software configuration of the system S of the present embodiment. [Figure 2] FIG. 2 is a main flowchart showing an example of a preferred flow of the support process executed by the support device 1 of the present embodiment. [Figure 3] FIG. 3 is a figure following the previous figure. [Figure 4] FIG. 4 is a flowchart of the consideration process in the main flowchart. [Figure 5] FIG. 5 is a figure following the previous figure. [Figure 6] FIG. 6 is an example of the display of the input screen E. [Figure 7] FIG. 7 is an example of the display of the evaluation screen A.

MODE FOR CARRYING OUT THE INVENTION

[0018] First, although the following disclosure, charts, and / or claims, etc. are described as being alone or in combination with one or more other aspects, the subject matter of the immediate disclosure is not intended to be so limited. That is, the immediate disclosure, charts, and claims are intended to encompass the various aspects described herein, either alone or in one or more combinations with each other. For example, even if the immediate disclosure describes and illustrates the first embodiment, the second embodiment, and the third embodiment in such a way that the first embodiment is described and illustrated particularly in relation to the second embodiment, or the second embodiment is described and illustrated only in relation to the third embodiment, the immediate disclosure and illustration are not limited in such a way, and only the first embodiment, only the second embodiment, only the third embodiment, or one or more combinations of the first, second, and / or third embodiments, for example, the first embodiment and the second embodiment, the first embodiment and the third embodiment, the second embodiment and the third embodiment, or the first, second, and third embodiments may be included.

[0019] Unless otherwise specified, the use of the phrase "or" in this document shall mean a "non-exclusive" arrangement. For example, when we say "Item x is A or B", it shall mean either of the following: (1) Item x is only one of A or B, (2) Item x is both A and B. In other words, the word "or" is not used to define an "exclusive" arrangement.

[0020] Also, when the phrases "including at least one" or "including at least one of the following" are used in this document in combination with a system or element, it shall mean that the system or element includes one or more of the elements listed after the phrase. For example, if there are three types of elements from the first element to the third element, the phrases "including at least one" or "including at least one of the following" shall be interpreted as any of the following structural arrangements: a device including the first element, a device including the second element, a device including the third element, a device including the first and second elements, a device including the first and third elements, a device including the second and third elements, or a device including the first, second, and third elements.

[0021] The same interpretation is intended when the phrase "used in at least one of the following" is used in this document. Furthermore, "and / or" used in this document is used as a linguistic conjunction to indicate that one or more of the described elements or conditions are included or occur. For example, a device including the first element, the second element, and / or the third element shall be interpreted as any of the following structural arrangements: a device including the first element, a device including the second element, a device including the third element, a device including the first and second elements, a device including the first and third elements, a device including the second and third elements, or a device including the first, second, and third elements.

[0022] Note that the use of the phrase "and / or" in this document meaning a "non-exclusive" arrangement is also specified in the "Format and Preparation Method of Specification Sheets JIS Z 8301" of the Japanese Industrial Standards (JIS).

[0023] The following describes in detail an example of an embodiment of the present invention with reference to the drawings.

[0024] <System S> Figure 1 is a block diagram showing an example of the hardware and software configuration of System S in this embodiment. The new project document creation support system (System S) according to this embodiment is configured to include a new project document creation support device 1 (hereinafter also simply referred to as "support device 1"). Support device 1 is configured to communicate with terminal T via network N.

[0025] [Materials for a new project] In this embodiment, "materials for new projects" include, for example, drafts or strategic planning materials related to new projects such as new business development or project development. In addition, "materials for new projects" may also include materials related to the consideration of future visions, problem identification, idea generation, etc.

[0026] [Support device 1] Support device 1 comprises various hardware components such as a control unit 11, a memory unit 13, and a communication unit 14. Support device 1 assists in the creation of materials for new projects through co-creation between humans and AI by providing a unique user interface and processing related to large-scale language models. The type of support device 1 is not particularly limited and may be, for example, a server device, a cloud server, etc.

[0027] [Control Unit 11] The control unit 11 includes a Central Processing Unit (CPU), Random Access Memory (RAM), and Read Only Memory (ROM), among other things.

[0028] The control unit 11 cooperates with at least one of the storage unit 13 and the communication unit 14 as needed. The control unit 11 then implements the software components of the program of this embodiment executed by the support device 1, such as the basic data acquisition unit 111, input screen display unit 112, examination result acquisition unit 113, examination result candidate generation unit 114, information provision unit 115, collaborator examination result acquisition unit 116, data generation unit 117, evaluation generation unit 118, comparison display command unit 119, etc.

[0029] The details of the support processing realized by the above-mentioned software components will be explained later using Figures 2 to 5.

[0030] [Storage section 13] The storage unit 13 is a device on which data and / or files are stored, and has a storage unit that stores data non-temporarily using a hard disk, semiconductor memory, recording medium, and memory card, etc. The storage unit 13 stores programs and the like that are executed by a microcomputer.

[0031] (Large-scale language models) The large-scale language model in this embodiment is not particularly limited. Examples of large-scale language models in this embodiment include GPT-4 and GPT-4o, which are used in ChatGPT®. In the following, the large-scale language model may be simply referred to as "AI".

[0032] [Communications Section 14] The communication unit 14 is not particularly limited as long as it connects the support device 1 to the network N and enables communication. Examples of the communication unit 14 include a network card compatible with the Ethernet standard and a communication device compatible with wireless LAN.

[0033] [Network N] The type of network N is not particularly limited as long as it enables communication with the support device 1, etc. Examples of network N include the internet, a mobile phone network, a wireless LAN, etc.

[0034] [Terminal T] Terminal T performs processes such as transmitting user input data to support device 1 and displaying various information based on display-related commands received from support device 1. The type of terminal T is not particularly limited and may be any type of terminal, such as a stationary terminal like a personal computer or a portable terminal like a tablet.

[0035] [Main flowchart for support processing] Figure 2 is a main flowchart showing an example of a preferred flow of support processing performed by the support device 1 of this embodiment. Figure 3 is a continuation of the previous figure. The following is an example of a preferred flow of support processing performed by the support device 1 of this embodiment, using Figures 2 to 3.

[0036] [Step S1: Obtain basic data] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the basic data acquisition unit 111. Then, the control unit 11 executes the process of acquiring basic data for a new project using the basic data acquisition unit 111 (basic data acquisition step). The control unit 11 then moves the process to step S2.

[0037] In the basic data acquisition step, the basic data acquisition unit 111 acquires basic data, for example, that has been input at terminal T. If some or all of the basic data is already stored in the storage unit 13 in order to enable pre-input or reuse of basic data, the basic data acquisition unit 111 may acquire that data. The basic data acquisition unit 111 may also acquire that data from the internet. In this case, the basic data acquisition unit 111 searches the internet using search words based on, for example, the heading of a new project input from terminal T.

[0038] (Basic data for new projects) The basic data for a new project acquired in the basic data acquisition step includes, for example, the headline, basic idea, target market, strengths of the project, and assets of the project.

[0039] After acquiring basic data, the support process executes a review process that involves various considerations related to the new project through co-creation between humans and AI. The following is an example of a case where the review process is divided into the first review process, the second review process, and the third review process. Note that the number of divisions in the review process and the content of each divided review process are not limited to the example below.

[0040] [Step S2: First Review Process] The control unit 11 works in cooperation with the memory unit 13 and the communication unit 14 to perform a first review process related to the merits and prospects of the new project (first review step). The control unit 11 then moves the process to step S3. In the first review process, co-creation between humans and AI regarding the merits and prospects of the new project is carried out by the input screen display unit 112, the review result acquisition unit 113, and the review result candidate generation unit 114, etc. Furthermore, the first review process can take the form of supporting co-creation with collaborators by the information provision unit 115 and the collaborator review result acquisition unit 116. Details of the first review process will be explained later using Figures 4 and 5.

[0041] [Step S3: Second Review Process] The control unit 11 works in cooperation with the memory unit 13 and the communication unit 14 to perform a second review process related to concerns regarding the new project (second review step). The control unit 11 then moves the process to step S4. In the second review process, co-creation between humans and AI regarding concerns about the new project is carried out by the input screen display unit 112, the review result acquisition unit 113, and the review result candidate generation unit 114, etc. Furthermore, the second review process can take the form of supporting co-creation with the further involvement of collaborators by the information provision unit 115 and the collaborator review result acquisition unit 116. Details of the second review process will be explained later using Figures 4 and 5.

[0042] [Step S4: Third Review Process] The control unit 11, in cooperation with the memory unit 13 and the communication unit 14, executes a third review process related to measures to overcome the above-mentioned concerns (third review step). The control unit 11 then moves the process to step S5. In the third review process, co-creation between humans and AI regarding measures to overcome the above-mentioned concerns is carried out by the input screen display unit 112, the review result acquisition unit 113, and the review result candidate generation unit 114, etc. Furthermore, the third review process may take the form of supporting co-creation with collaborators by the information provision unit 115 and the collaborator review result acquisition unit 116. Details of the third review process will be explained later using Figures 4 to 5.

[0043] [Step S5: Generate the document] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the data generation unit 117. The control unit 11 then uses the data generation unit 117 to input prompts containing basic data and examination result data related to the examination process into the large-scale language model and executes the process of generating data (data generation step). The control unit 11 then moves the process to step S6. The examination result data related to the examination process referred to here refers to data that summarizes the examination result data related to each of the first to third examination processes.

[0044] [Editing Steps] To facilitate the finalization of the document by human hands, the support process preferably further includes an editing step that edits the document generated based on the user's input. In this case, the support device 1 preferably includes a display that visualizes the degree of AI's contribution to the edited document. This allows the support device 1 to enhance the reliability of the generated and edited document and further encourage the user to adopt a workflow that does not rely solely on AI generation.

[0045] [Work time display step] To make the review process transparent, it is preferable that the support process displays the time spent by the user for each of the following stages: the first review process, the second review process, the third review process, and the process related to the generation and editing of materials. This allows the user to refer to how much time they spent reviewing at each stage and to refine the review process.

[0046] [Adding explanatory text step] To demonstrate the logical nature of the AI-driven review process, it is preferable that the support process displays text explaining the data sources the AI ​​relied on and the logic it employed for each of the following stages: the first review process, the second review process, the third review process, and the process related to the generation and editing of materials. This allows users to refer to how the AI ​​reviewed the material at each stage and refine the review process.

[0047] The support process preferably includes a series of processes for displaying an evaluation of the generated material. Steps S6 to S9 are an example of such processes.

[0048] [Step S6: Determine whether to evaluate] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the evaluation generation unit 118. The control unit 11 then performs a process to determine whether to evaluate the material generated by the evaluation generation unit 118 (evaluation determination step). If the control unit 11 determines that it should evaluate the material, it moves the process to step S7; otherwise, it moves the process to step S9.

[0049] The evaluation generation unit 118 achieves the above-mentioned determination by, for example, determining whether to perform an evaluation if data requesting an evaluation is received from terminal T.

[0050] [Step S7: Generate evaluation] The control unit 11 inputs a prompt containing the data and evaluation indicators generated by the data generation unit 117 into the large-scale language model via the evaluation generation unit 118, and executes a process to generate an evaluation for the data (evaluation generation step). The control unit 11 then moves the process to step S8.

[0051] (Evaluation metrics) The evaluation indicators related to the evaluation generation step include, for example, text indicating the items to be evaluated and the score range. To ensure stable evaluations, it is preferable that the indicators include text indicating the correspondence between the content described in the document and the scores. To obtain evaluations from various perspectives, it is preferable that the evaluation indicators can be selected from multiple sets.

[0052] [Step S8: Show rating] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the comparison display command unit 119. The control unit 11 then executes a process to instruct the comparison display command unit 119 to display an evaluation of the material (display command step). The control unit 11 then moves the process to step S9.

[0053] (Regarding comparative displays) The comparative display command unit 119 preferably commands the system to display a comparative evaluation of the multiple generated documents. This allows the user to consider which documents would receive a higher evaluation based on the displayed comparative evaluations.

[0054] It is preferable that multiple documents include a history of documents generated by the same user. This allows the user to consider what kind of document would receive a higher rating based on differences in input in past generation or differences in input between past generation, and their respective ratings.

[0055] It is preferable that the multiple materials include materials used by different users. This allows users to incorporate the insights of other users whose background knowledge or perspectives are expected to differ. Furthermore, this can foster a sense of competition among users, which can serve as motivation. A specific example of comparative display will be explained later using Figure 7.

[0056] [Step S9: Determine whether to return to the first review] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to perform a process to determine whether to return to the first review (first review continuation determination step). If the control unit 11 determines to return, it moves the process to step S2; otherwise, it moves the process to step S10.

[0057] The control unit 11 achieves the above determination by, for example, determining whether to return if data is received from terminal T requesting to continue or restart the first examination.

[0058] [Step S10: Determine whether to return to the second review] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to perform a process to determine whether to return to the second review (second review continuation determination step). If the control unit 11 determines to return, it moves the process to step S3; otherwise, it moves the process to step S11.

[0059] The control unit 11 achieves the above determination by, for example, determining whether to return if data is received from terminal T requesting to continue or restart the second examination.

[0060] [Step S11: Determine whether to return to the third consideration] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to perform a process to determine whether to return to the third review (third review continuation determination step). If the control unit 11 determines to return, it moves the process to step S4; otherwise, it returns the process to step S1 and repeats the process from step S1 to step S11.

[0061] The control unit 11 achieves the above determination by, for example, determining to return if data is received from terminal T requesting to continue or restart the third review.

[0062] [Flowchart of the review process] Figure 4 is a flowchart of the review process in the main flowchart. Figure 5 is a continuation of the previous figure. The following is an example of a preferred flow of the review process using Figures 4 and 5. The review process described below corresponds to various review processes such as the first review process (step S2), the second review process (step S3), and the third review process (step S4). Therefore, in the explanation of each step below, the common parts of the first review process (step S2), the second review process (step S3), and the third review process (step S4) will be explained first, followed by the parts that differ in each process.

[0063] [Step S21: Command to display the input screen] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the input screen display unit 112. The control unit 11 then executes a process to instruct the input screen display unit 112 to display an input screen for inputting the review result data related to the new project (input screen display command step). The control unit 11 then moves the process to step S22.

[0064] (If the step for generating candidate review results has already been performed) If the candidate analysis result generation step (described later) has been completed, the input screen display unit 112 commands the display of an input screen that provides an operation to include some or all of the candidate analysis results generated in that step in the input of the analysis result data. Such an input screen is implemented, for example, by displaying a list of candidate analysis results and by user interface elements such as copy buttons and paste buttons that allow some or all of the candidates to be pasted into the field where the analysis results are entered. If candidate analysis results that include questions for the inputter have been generated, it is preferable that the input screen be configured to allow the input of analysis result data that includes answers to those questions.

[0065] The input screen preferably includes an operation to exclude some or all of the candidate results from the input of the result data. Furthermore, in order to reduce the effort required of users involved in co-creation, the operation to include some or all of the candidate results from the input of the result data preferably completes in a single basic operation procedure, such as a single click. This allows users to switch between data to be handed over to the AI ​​and data not to be handed over in a single operation.

[0066] In order to incorporate AI suggestions for each cohesive candidate, if the candidate results are divided into multiple groups, it is preferable for the input screen display unit 112 to instruct the display of an input screen that provides an operation to select one of the divided candidates and include part or all of it in the input of the candidate results data.

[0067] (In the case of the first review process) In the first review process, the input screen display unit 112 commands the display of the first input screen for inputting the first review result data, including the advantages and prospects of the new project. This allows the support device 1 to support co-creation between humans and AI regarding the advantages and prospects of the new project.

[0068] (In the case of the second review process) In the second review process, the input screen display unit 112 commands the display of the second input screen for inputting the second review result data, which includes concerns about the new project. This allows the support device 1 to support co-creation between humans and AI regarding concerns about the new project.

[0069] (In the case of the third review process) In the third review process, the input screen display unit 112 commands the display of the third input screen for inputting the third review result data, which includes measures to overcome the concerns. This allows the support device 1 to support co-creation between humans and AI regarding measures to overcome the concerns of the new project.

[0070] [Step S22: Obtain the results of the review] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the examination result acquisition unit 113. The control unit 11 then executes the process of acquiring the examination result data entered via the input screen described above by the examination result acquisition unit 113 (examination result acquisition step). The control unit 11 then moves the process to step S23.

[0071] (In the case of the first review process) In the first review process, the review result acquisition unit 113 acquires the first review result data described above.

[0072] (In the case of the second review process) In the second review process, the review result acquisition unit 113 acquires the second review result data described above.

[0073] (In the case of the third review process) In the third review process, the review result acquisition unit 113 acquires the above-mentioned third review result data.

[0074] [Step S23: Determine whether to generate candidate results for consideration] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the candidate analysis result generation unit 114. The control unit 11 then performs a process to determine whether to generate candidate analysis results, which are candidates for the aforementioned analysis results, using the candidate analysis result generation unit 114 (candidate analysis result generation determination step). If the control unit 11 determines that it should generate candidates, it moves the process to step S24; otherwise, it moves the process to step S25.

[0075] [Step S24: Generate candidate results] The control unit 11 uses the candidate analysis result generation unit 114 to input a prompt containing the above-mentioned basic data, or a prompt containing the above-mentioned basic data and the above-mentioned analysis result data, into the large-scale language model and executes a process to generate the above-mentioned candidate analysis result (candidate analysis result) (candidate analysis result generation step). The control unit 11 then moves the process to step S25.

[0076] In the candidate analysis result generation step, the candidate analysis result generation unit 114 inputs, for example, prompts containing already entered data from the basic data and various analysis result data into the large-scale language model.

[0077] (Questions for the person who entered the information) In the step of generating candidate review results, it is preferable that the candidate review result generation unit 114 generates candidate review results that include questions to the inputter regarding the data, including basic data or review result data. This allows the support device 1 to promote co-creation between humans and AI through questions to the inputter.

[0078] (In the case of the first review process) In the first review process, the candidate review result generation unit 114 inputs a prompt containing basic data into the large-scale language model to generate the above-mentioned candidate first review result (first review result candidate). This allows the candidate review result generation unit 114 to generate candidate review results related to the merits and prospects of the new project based on the basic data. If first review result data has already been input, the candidate review result generation unit 114 may input a prompt further containing the input first review result data into the large-scale language model. This allows the candidate review result generation unit 114 to generate candidate review results for the merits and prospects of the new project by utilizing the input first review result data.

[0079] (In the case of the second review process) In the second review process, the candidate review result generation unit 114 inputs a prompt containing basic data and first review result data into the large-scale language model to generate the above-mentioned candidate for the second review result (second review result candidate). As a result, the candidate review result generation unit 114 can generate candidate review results related to concerns of the new project based on the basic data and first review result data. If second review result data has already been input, the candidate review result generation unit 114 may input a prompt further containing the input second review result data into the large-scale language model. As a result, the candidate review result generation unit 114 can generate candidate review results related to concerns of the new project by utilizing the input second review result data.

[0080] (In the case of the third review process) In the third review process, the candidate review result generation unit 114 inputs a prompt containing basic data, first review result data, and second review result data into the large-scale language model to generate the above-mentioned candidate for the third review result (third review result candidate). This allows the candidate review result generation unit 114 to generate candidate review results related to measures to overcome concerns regarding the new project, based on the basic data, first review result data, and second review result data. If third review result data has already been input, the candidate review result generation unit 114 may input a prompt further containing the already inputted third review result data into the large-scale language model. This allows the candidate review result generation unit 114 to generate candidate review results related to measures to overcome concerns regarding the new project, utilizing the already inputted third review result data.

[0081] The review process preferably includes a series of processes related to co-creation with collaborators other than the data inputters, such as basic data and review result data. Steps S25 to S28 are an example of such a process.

[0082] [Step S25: Determine whether to provide information to the collaborator] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the information provision unit 115. The control unit 11 then performs a process to determine whether to provide the information to a collaborator different from the person who input the data (information provision determination step). If the control unit 11 determines that it should provide the information, it moves the process to step S26; otherwise, it moves the process to step S28.

[0083] The control unit 11 achieves the above determination by, for example, determining whether to provide the service if a collaborator has been specified from terminal T.

[0084] [Step S26: Provide to collaborators] The control unit 11 performs the process of providing data including basic data or the aforementioned study result data to a collaborator different from the person who input the data, via the information provision unit 115 (information provision step). The control unit 11 then moves the process to step S27.

[0085] [Step S27: Obtain the results of the collaborator review] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to execute the collaborator review result acquisition unit 116. The control unit 11 then executes the process of acquiring the collaborator review results from the collaborators using the collaborator review result acquisition unit 116 (collaborator review result acquisition step). The control unit 11 then moves the process to step S28.

[0086] (Regarding the provision of collaborator review results on the input screen) In the input screen, it is preferable that the results of the collaborator review are provided in a manner that allows for the inclusion of some or all of the results in the input of the review result data, similar to the candidate review results.

[0087] [Step S28: Determine whether to continue the investigation] The control unit 11 works in cooperation with the storage unit 13 and the communication unit 14 to perform a process to determine whether to continue the review (review continuation determination step). If the control unit 11 determines to continue, it returns to step S21; otherwise, it moves the process to the step following the step that transitioned to the review process.

[0088] (In the case of the first review process) In the case of the first review process, if it is not determined to continue, the next step is step S3.

[0089] (In the case of the second review process) In the case of the second review process, if it is not determined to continue, the next step is step S4.

[0090] (In the case of the third review process) In the case of the third review process, if it is not determined to continue, the next step is step S5.

[0091] [Effects of support processing] In the support process, the basic data acquisition unit 111 acquires basic data for the new project (step S1). The input screen display unit 112 also commands the display of the input screen E for inputting the results of the consideration of the new project (step S21).

[0092] However, for users who are not sufficiently proficient in creating materials for new projects, it is not easy to appropriately list the various points that need to be considered and input the results of their considerations for those points. On the other hand, AI can output a large amount of consideration results in a short time compared to humans. Furthermore, AI has a broader range of knowledge than humans. Therefore, if human ideas and selections can be effectively combined with the consideration results of AI, excellent materials for new projects can be created in a short time through co-creation between humans and AI.

[0093] To achieve this co-creation, the candidate result generation unit 114 inputs prompts containing basic data and result data into a large-scale language model to generate candidate results (steps S23 to S24). Then, the input screen display unit 112 displays an input screen that provides an operation to include some or all of these candidate results in the result data (step S21).

[0094] Then, the review result acquisition unit 113 acquires the review result data entered from the input screen (step S22). The support device 1, using the material generation unit 117, generates materials for the new project using a large-scale language model based on the basic data of the new project acquired by the basic data acquisition unit 111 and the review result data entered from this input screen (step S5).

[0095] In other words, support device 1 presents the user with candidate results for consideration generated by the large-scale language model, allowing the user to add some or all of these results to their own considerations. This enables co-creation between humans and AI, where the user combines the AI's considerations with their own. Through this co-creation, support device 1 generates materials for new projects.

[0096] If the materials were generated solely by AI, there would be concerns that they would be similar to those created for new projects in the past. However, the support device 1, which performs the aforementioned support processing, facilitates co-creation between humans and AI, enabling it to provide materials that reflect different considerations than those previously created by humans, and in a shorter time than if created solely by humans. Therefore, the support device 1, which performs the support processing, can support the efficient creation of materials for new projects and improve their quality through co-creation between humans and AI.

[0097] In other words, the support device 1 of this embodiment can realize Human in the Loop (HITL), an approach in which humans and AI cooperate to solve problems. In this approach, the AI ​​makes judgments and analyses, and humans evaluate and correct the results. As a result, more accurate and efficient results can be obtained.

[0098] Furthermore, the support process may take the form of providing candidate review results that include questions to the inputter (step S24). This allows the inputter to determine what should be entered as review result data through the questions. Thus, the support device 1 in this form can promote co-creation between humans and AI through questions to the inputter.

[0099] In addition, the support process can be configured to input the results of the examination in three stages: the advantages and prospects of the new project, the concerns of the new project, and measures to overcome the concerns (steps S2 to S4). This allows the support device 1 to sequentially assist in co-creating the examination results related to these important points in the new project materials.

[0100] However, for users like those described above, it is not easy to judge the quality of the generated materials. The support process provides the user with evaluation criteria for the generated materials by showing the AI's evaluation of the generated materials (steps S6 to S8).

[0101] It is expected that by collaborating with multiple people and AI, materials reflecting a broader range of knowledge will be created. The support process can take the form of providing various data to collaborators different from the data inputter and obtaining the collaborators' review results (steps S25 to S27). This allows the support device 1 to perform not only co-creation with AI but also co-creation involving other people.

[0102] <Usage example> The following is an example of using System S of this embodiment.

[0103] [Entering basic data] The user inputs basic data related to the creation of materials for a new project into terminal T. Terminal T transmits this data to support device 1. Support device 1 receives this data.

[0104] [Input of First Review Results] Support device 1 instructs terminal T to display input screen E, which prompts the user to input the results of the first review. Terminal T displays input screen E. The user inputs a draft of the first review results, including the advantages and prospects of the new project.

[0105] The user instructs the support device 1 to perform an AI-driven analysis via terminal T. The support device 1 instructs the display of input screen E, which includes candidate analysis results. Terminal T displays the input screen E.

[0106] Figure 6 shows an example of the display of input screen E. At the top of this example, there is a display indicating the flow of the process, which involves sequentially performing "Preparation" for inputting basic data, "Advantages and Outlook" for inputting the first set of study results data, "Concerns" for inputting the second set of study results data, "Measures to overcome" for inputting the third set of study results data, and "Draft proposal" for generating materials, as well as indicating that the current step is "Advantages and Outlook".

[0107] Below the display showing the flow, there is an input field with the heading "Highlight the advantages." The input field contains a draft written by the user: "Economic value: Efficiency will increase significantly, saving human resources and reducing costs. Functional value: High-quality proposals can be created in a short time, so work The initial review results data shows that "the process will become smoother..."

[0108] Further down, there is a heading that reads "AI Review Results List." Below that, two candidate review results are displayed, along with buttons to copy the candidate results to the input field mentioned above, to edit the candidate results, to print the candidate results or output them as a PDF file, and to hide the candidate results.

[0109] The first candidate for the review results begins with: "Social value: By promoting efficient work processes, it will contribute to increased productivity and strengthen the overall competitiveness of the company. Organizational culture transformation: By increasing work efficiency, more time will be freed up..."

[0110] The second one begins with the following points: "• Time saving • User-friendly UI • Output tailored to needs..."

[0111] Further down, there is a heading that reads "List of other users' ideas." Below that, the results of two collaborative discussions are displayed, along with buttons to copy them to the input field mentioned above, to edit them, to print or output them as a PDF file, and to hide them.

[0112] The first result of the collaborator consideration, under the heading "User 1," presents the result of the collaborator consideration, stating, "Why not just have AI evaluate the project proposal as well, and then collaboratively refine it by repeatedly rewriting it while looking at the AI's evaluation?"

[0113] The second point is that, along with a headline identifying the collaborator with "User 2," it presents the results of the collaborator consideration, stating, "Wouldn't readers feel more at ease if we visualized the degree of AI's contribution? I think there was a study on this at Duke University's Department of Psychiatry and Neurology."

[0114] In this example, the user can refine the initial evaluation result data by incorporating standardized evaluation result candidates based on broad knowledge generated by AI, as well as evaluation results from collaborators that offer perspectives not available to the AI.

[0115] [Input of the results of the second review] Support device 1 instructs terminal T to display input screen E, which prompts the user to input the second review results. Terminal T displays input screen E. The user inputs a draft of the second review results, including concerns about the new project. In addition, similar to the input of the first review results, the user refines the second review result data by incorporating standardized review result candidates based on broad knowledge generated by the AI, and collaborator review results presented from perspectives not available to the AI.

[0116] [Input of the results of the third review] Support device 1 instructs terminal T to display input screen E, which prompts the input of the third review results. Terminal T displays input screen E. The user inputs a draft of the third review results, which includes measures to overcome concerns regarding the new project. In addition, similar to the input of the first review results, the user refines the third review result data by incorporating standardized review result candidates based on broad knowledge generated by the AI, and collaborator review results presented from perspectives not available to the AI.

[0117] [Generating documents] The user, via terminal T, instructs support device 1 to generate materials for a new project based on the input described above. Support device 1 generates the materials and displays them on terminal T.

[0118] [Refinement using evaluation] The user instructs the support device 1 to evaluate the generated materials via terminal T. The support device 1 instructs terminal T to display a comparison of evaluations for multiple materials. Terminal T displays evaluation screen A.

[0119] Figure 7 shows an example of the display of evaluation screen A. In this example, following the heading "AI Evaluation," the scores and reasons for the evaluation for items 1 through 7 are shown. Further below, it is shown that the total score is 25 out of 35 points.

[0120] Further down, there are overall comments beginning with "This proposal utilizes new technology..." and advice for improving the score beginning with "The customer's problems...". Users can refer to these to refine their documents.

[0121] At the bottom of evaluation screen A, under the heading "Draft History," a summary of previously generated documents is displayed. The first entry in the history shows a heading indicating a document generated on "2024 / 10 / 01 12:00:00" with a "Total Score of 26 / 35," along with a button to view that document. The second entry in the history shows a heading indicating a document generated on "2024 / 10 / 01 11:50:00" with a "Total Score of 20 / 35," along with a button to view that document. Users can refer to these to refine their documents and achieve a higher score.

[0122] Further down, under the heading "Other Users' Proposals," a list of documents generated by other users is displayed. The first item in the list is a document created by a user identified as "User 3," titled "Iterative Processing Using AI," with a "Total Score of 27 / 35," and is indicated by a heading and a button to view the document. The second item in the list is a document created by a user identified as "User 4," with no title, also with a "Total Score of 27 / 35," and is indicated by a heading and a button to view the document. Users can refer to these documents to improve their own and achieve higher scores.

[0123] Within the scope of the concept of this invention, those skilled in the art can conceive of various modifications and alterations. Therefore, such modifications and alterations are understood to fall within the scope of this invention. For example, any addition, deletion, or design change of components, or addition, omission, or modification of processes, made by a person skilled in the art to the above-described embodiments, is also included within the scope of this invention, as long as it retains the essence of this invention. [Explanation of symbols]

[0124] S System 1 Support equipment 11 Control Unit 111 Basic Data Acquisition Unit 112 Input screen display section 113 Department for obtaining examination results 114 Candidate Generation Unit for Review Results 115 Information Provision Department 116 Department for Obtaining Results of Collaborator Review 117 Material generation department 118 Evaluation Generation Unit 119 Comparison display command section 13 Storage section 14 Communications Department N Network T terminal E Input screen A. Evaluation screen

Claims

1. The basic data acquisition unit acquires basic data for new projects, An input screen display unit that commands the display of an input screen for inputting the data of the results of the consideration related to the aforementioned new project, A unit for acquiring the examination result data that is entered via the input screen, A candidate analysis result generation unit inputs a prompt containing the aforementioned basic data, or a prompt containing the aforementioned basic data and the aforementioned analysis result data, into a large-scale language model and generates candidate analysis results (candidate analysis results), A document generation unit that inputs prompts including the aforementioned basic data and the aforementioned examination result data into a large-scale language model and generates documents for the new project, Equipped with, The input screen display unit is configured to provide an operation on the input screen to include some or all of the candidate examination results in the input of the examination result data when the candidate examination results have been generated. A support device for creating documents for new projects.

2. The aforementioned candidate analysis result generation unit is configured to generate candidate analysis results that include questions to the inputter regarding the data, including the basic data or the analysis result data. The input screen display unit is configured to display the questions and to allow input of review result data including answers to the questions. The support device according to claim 1.

3. The aforementioned input screen display unit is A command to display the first input screen for inputting the first review result data, including the advantages and prospects of the aforementioned new project, A command to display the second input screen for inputting the second review result data, which includes concerns regarding the aforementioned new project, A command to display the third input screen for inputting the data of the third review results, which includes measures to overcome the aforementioned concerns, It is configured to do the following: The aforementioned examination result acquisition unit is configured to acquire the first examination result data, the second examination result data, and the third examination result data, respectively. The aforementioned candidate result generation unit is: The prompt containing the aforementioned basic data is input to a large-scale language model to generate a candidate for the first examination result (candidate for the first examination result), A prompt including the aforementioned basic data and the first examination result data is input to a large-scale language model to generate a candidate for the second examination result (candidate for the second examination result). A prompt including the aforementioned basic data, the first examination result data, and the second examination result data is input into a large-scale language model to generate a candidate for the third examination result (candidate for the third examination result). It is configured to do the following: The aforementioned input screen display unit is When the first candidate for the examination result has been generated, the first input screen provides an operation to include part or all of the first candidate for the examination result in the input of the first examination result data. When the second candidate for the examination result has been generated, the second input screen provides an operation to include part or all of the second candidate for the examination result in the input of the second examination result data. If the third candidate for the examination result has been generated, the third input screen will provide an operation to include part or all of the third candidate for the examination result in the input of the third examination result data. It is configured to do the following: The document generation unit inputs prompts, including the basic data, the first examination result data, the second examination result data, and the third examination result data, into a large-scale language model to generate the documents for the new project. The support device according to claim 1.

4. An evaluation generation unit inputs prompts, including the materials and evaluation indicators generated by the aforementioned materials generation unit, into a large-scale language model and generates an evaluation for the materials; A comparative display command unit that commands the unit to display comparative evaluations of multiple aforementioned documents, The support device according to claim 1, further comprising:

5. An information provision unit provides data including the aforementioned basic data or the aforementioned study result data to a collaborator different from the person who entered the data, A collaborator review result acquisition unit that acquires the results of the collaborator review by the aforementioned collaborator, Furthermore, The input screen display unit is configured to provide an operation on the input screen to include part or all of the collaborator review results in the input of the review result data when the collaborator review results have been obtained. The support device according to claim 1.

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