Data processing device, data processing method and data processing program

Abstract

To provide a device, a method and a program capable of preventing an unjustifiable obtainment of a profit by contents generated by a generative model.SOLUTION: A data processing device includes: a monitoring unit that monitors a command to be input to a generative model to generate contents; a detecting unit that detects, based on the command, the plagiarism of the contents generated by the generative model; and an associating unit that associates the detected result with the contents.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The technology of the present disclosure relates to a data processing apparatus, a data processing method, and a data processing program.

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In recent years, due to the remarkable progress of AI (Artificial Intelligence), various generative AIs that generate content using generative models have emerged. As a result, creators who generate content using generative AI (also referred to as "AI creators") can generate content relatively easily. On the other hand, creators who produce content without using generative AI (also referred to as "non-AI creators" or "handwritten creators") have the problem that the works they create are easily plagiarized by generative AI.

[0005] Therefore, the technology of the present disclosure aims to provide an apparatus, a method, and a program that can prevent obtaining improper benefits by content generated by a generation model.

Means for Solving the Problems

[0006] A first aspect of the technology according to the present disclosure is a data processing apparatus including a monitoring unit that monitors an instruction input to a generation model to generate content, a detection unit that detects plagiarism of the content generated by the generation model based on the instruction, and an association unit that associates the detected result with the content.

[0007] The instruction and the content may be exchanged on a blockchain.

[0008] The data processing apparatus may further include an interface unit that supplies the instruction to the generation model via an API and acquires the content from the generation model via the API.

[0009] The detection unit may detect that the content is plagiarized when one or more pre-registered prohibited words are extracted from the instruction.

[0010] The association unit may assign a flag to the content detected as being plagiarized.

[0011] The association unit may assign a score that quantifies the degree of plagiarism to the content.

[0012] The data processing apparatus may further include a determination unit that determines whether the content can be offered based on the detected result.

[0013] A second aspect of the technology according to the present disclosure is a data processing method in which a computer executes a process including monitoring instructions input to a generation model to generate content, detecting plagiarism of the content generated by the generation model based on the instructions, and associating the detected result with the content.

[0014] A third aspect of the technology according to the present disclosure is a data processing program for causing a computer to execute a process including monitoring instructions input to a generation model to generate content, detecting plagiarism of the content generated by the generation model based on the instructions, and associating the detected result with the content.

Brief Description of the Drawings

[0015]

Figure 1

Figure 2

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Figure 4

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Embodiments for Carrying Out the Invention

[0016] Hereinafter, an example of an embodiment of a data processing device, a data processing method, and a data processing program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, the labeled processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit), etc.

[0019] In the following embodiments, the labeled RAM (Random Access Memory) is a memory where information is temporarily stored and is used as a work memory by the processor.

[0020] In the following embodiments, the labeled storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, etc.

[0021] In the following embodiments, the labeled communication I / F (Interface) is an interface that includes a communication processor and an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

[0023] FIG. 1 shows an example of the configuration of a data processing system 10 according to an embodiment.

[0024] As shown in FIG. 1, the data processing system 10 includes a data processing device 12 and a user terminal 14. An example of the data processing device 12 is a server. Examples of the user terminal 14 include a personal computer, a smartphone, and the like. The data processing device 12 is an example of the "data processing device" according to the technology of the present disclosure.

[0025] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of the "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The user terminal 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. Also, the reception device 38, the output device 40, and the camera 42 are connected to the bus 52.

[0027] The reception device 38 includes a touch panel 38A, a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by contact of an indicator (for example, a pen or a finger, etc.) by detecting the contact of the indicator. The microphone 38B receives user input by voice by detecting the voice of the user. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires data indicating the user input.

[0028] The output device 40 includes a display 40A, a speaker 40B, etc., and presents data to the user by outputting the data in a form (for example, voice and / or text) that the user can perceive. The display 40A displays visible information such as text and images according to an instruction from the processor 46. The speaker 40B outputs voice according to an instruction from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, a diaphragm, and a shutter, and an imaging device such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] The communication I / F 44 is connected to the network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0030] FIG. 2 shows an example of the main functions of the data processing device 12 and the user terminal 14.

[0031] As shown in FIG. 2, in the data processing apparatus 12, specific processing is performed by the processor 28. The storage 32 stores a specific processing program 56. The specific processing program 56 is an example of the "data processing program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] In the user terminal 14, input / output processing for reception is performed by the processor 46. The storage 50 stores a reception input / output program 62. The reception input / output program 62 is used in combination with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception input / output program 62 from the storage 50 and executes the read reception input / output program 62 on the RAM 48. The input / output processing for reception is realized by the processor 46 operating as a control unit 46A according to the reception input / output program 62 executed on the RAM 48.

[0033] Next, the processing of the specific processing unit 290 when the data processing apparatus 12 performs specific processing for detecting the piracy of content will be described. Here, the "content" referred to herein indicates so-called "digital content" configured in a digital format. Hereinafter, the case where the content is an image will be described as an example, but it is not limited thereto. The content may be various contents such as videos, music, e-books, and games.

[0034] FIG. 3 shows an overview of specific processing for detecting the piracy of content. Generally, a transaction is performed in which (1) a creator generates content, (2) the creator offers the content for sale, and (3) a purchasing user purchases the content. In such a transaction, a model in which the content is traded as an NFT (Non-Fungible Token) on an NFT platform (also referred to as an "NFT marketplace") is known.

[0035] NFT is non-fungible digital data created based on the blockchain. Until now, digital content has been easily copied and tampered with, making it difficult to give it asset value. In contrast, NFT, which utilizes the blockchain, is attracting attention because it makes it possible for digital content to have unique asset value just like analog content.

[0036] In recent years, due to remarkable progress in AI, various generation tools 16 that generate such content using AI have appeared. In the generation tool 16, various contents are generated using a generation model 58. The generation model 58 is an example of a "generative model" according to the technology of the present disclosure.

[0037] When the content is an image, an example of a generative model 58 is Stable Diffusion (Internet search<URL: https: / / stablediffusionweb.com / > ), DALL-E2 (Internet search<URL: https: / / openai.com / dall-e-2> ), Midjourney (Internet search<URL:https: / / www.midjourney.com / > In such a generative AI, when a command called a prompt is input to the generative model 58, the generative model 58 generates content according to the command and outputs it.

[0038] The identification process in this embodiment aims to prevent unfair profits from being gained from the content generated by the generative model 58 by monitoring the commands input to the generative model 58 in this manner and detecting plagiarism of the content generated by the generative model 58.

[0039] To achieve this, the NFT platform may have the generation tool 16 connected to the API. API (Application Programming Interface) connection means connecting external applications or systems for data communication using the API.

[0040] In this case, the AI creator can use the generation AI as if directly accessing it by connecting the wallet to the NFT platform (so-called login) and selecting the generation tool 16 that is data-connected as an extension function. On the other hand, since all interactions between the AI creator and the generation model 58 go through the API, the data processing device 12 implemented on the NFT platform can monitor such interactions. Therefore, the data processing device 12 according to this embodiment detects plagiarism of the generated content by tracking the generation route of the content by the generation model 58. This will be described in detail below.

[0041] FIG. 4 schematically shows the functional configuration of the specific processing unit of the data processing device. The specific processing unit 290 includes an interface unit 291, a monitoring unit 292, a detection unit 293, a correlation unit 294, and a determination unit 295.

[0042] The interface unit 291 supplies commands for generating content to the generation model 58 via the API and acquires the content from the generation model 58 via the API.

[0043] The monitoring unit 292 monitors the commands input to the generation model 58 for generating content.

[0044] The detection unit 293 detects plagiarism of the content generated by the generation model 58 based on the commands.

[0045] The correlation unit 294 correlates the detected result with the content.

[0046] The determination unit 295 determines whether the content can be listed based on the detected result.

[0047] Next, the operation of the data processing system 10 will be described.

[0048] FIG. 5 schematically shows an example of the operation flow of a specific process by the data processing device. The flow of the specific process will be described with reference to this figure. Note that the flow of the specific process shown in this figure is an example of the "data processing method" according to the technology of the present disclosure.

[0049] This operation flow may be started when the AI creator connects the wallet to the NFT platform and selects the generation tool 16.

[0050] In step S301, the computer 22 supplies, as the interface unit 291, an instruction for generating content to the generation model 58 via the API. In response to this, the generation model 58 generates and outputs content corresponding to the input instruction. Then, the computer 22 acquires the content from the generation model 58 via the API as the interface unit 291.

[0051] Here, when the content is an image, the instruction may be, for example, the following prompts. <Prompt 1> "Please create an image that A (the original author) would create." <Prompt 2> "Please create an image imitating X (the name of the work)." <Prompt 3> "Please create an image of a 3-year-old child playing in the snow with their parents in the yard using the deformed touch style."

[0052] When Prompt 1 is input by an AI creator, computer 22 may supply this to generation model 58 via an API. Then, computer 22 may obtain Image 1 generated by generation model 58 in response to Prompt 1 via the API. Similarly, when Prompt 2 is input by an AI creator, computer 22 may supply this to generation model 58 via an API. Then, computer 22 may obtain Image 2 generated by generation model 58 in response to Prompt 2 via the API. Similarly, when Prompt 3 is input by an AI creator, computer 22 may supply this to generation model 58 via an API. Then, computer 22 may obtain Image 3 generated by generation model 58 in response to Prompt 3 via the API.

[0053] As described above, since generation tool 16 is API - linked to an NFT platform utilizing a blockchain, all instructions and content exchanged between the AI creator and generation model 58 will be exchanged on the blockchain. Thus, when generating content under a blockchain, it is virtually impossible to tamper with how the content was generated by what instructions.

[0054] In step S302, computer 22, acting as monitoring unit 292, monitors the instructions input to generation model 58 for generating content.

[0055] In step S303, computer 22, acting as monitoring unit 292, determines whether one or more pre - registered prohibited words have been extracted from the instructions. And, computer 22, acting as detection unit 293, may detect that the content is plagiarized if it is determined that one or more pre - registered prohibited words have been extracted (Yes) from the instructions. If it is detected that the content is plagiarized, computer 22 proceeds with the process to step S304. On the other hand, if it is determined that no prohibited word has been extracted (No), computer 22 proceeds with the process to step S305.

[0056] At this time, the prohibited words may include the names of the original authors of the content (including personal names and group names), such as "Mr. A" and "Group B", and artist names. Also, the prohibited words may include the names of the works of the content, such as "X" and "Y". Further, the prohibited words may include terms that suggest plagiarism, such as "imitation" and "mimicry". The computer 22 may extract prohibited words from the instructions by searching (including fuzzy search) for instructions using such prohibited words, for example.

[0057] Here, assume that as a result of a fuzzy search of Prompt 1, the prohibited word "Mr. A" is extracted. In this case, the computer 22 may detect that Image 1 is plagiarized. Similarly, assume that as a result of a fuzzy search of Prompt 2, the prohibited words "X" and "imitation" are extracted. In this case, the computer 22 may detect that Image 2 is plagiarized. The computer 22 may detect that the content is plagiarized when one or more pre-registered prohibited words are extracted from the instructions in this way.

[0058] And in step S304, the computer 22 assigns a flag indicating plagiarism to Image 1 and Image 2 as the related part 294. The computer 22 may assign a flag to the content detected as plagiarized in this way, for example. Thereby, the computer 22 can associate the detected result with the content.

[0059] On the other hand, assume that as a result of a fuzzy search of Prompt 3, no prohibited words are extracted. In this case, the computer 22 omits the process of step S304.

[0060] In step S305, the computer 22 stores the content. For example, the computer 22 stores Image 1 and Image 2 with flags and Image 3 without a flag in the collection box of the NFT platform.

[0061] Then, the AI creator can select the content it wishes to list from the content stored in the collection box. In other words, content not stored in the collection box cannot be listed. Therefore, the content traded on the NFT platform will be limited to the content generated using the generative AI under the condition that the data processing device 12 is tracking the generation route.

[0062] In step S306, the computer 22 receives a listing instruction from the user terminal 14. Here, it is assumed that the computer 22 has received an instruction to list Image 1, Image 2, and Image 3 stored in the collection box of the NFT platform.

[0063] In step S307, the computer 22, as the determination unit 295, determines whether a flag is attached to the content for which listing is desired. For example, since flags are attached to Image 1 and Image 2, the computer 22 determines that Image 1 and Image 2 cannot be listed. If it is determined that listing is not possible, the computer 22 proceeds to step S308. On the other hand, since no flag is attached to Image 3, the computer 22 determines that Image 3 can be listed. If it is determined that listing is possible, the computer 22 proceeds to step S309. In this way, the computer 22 can determine whether the content can be listed based on the detected results.

[0064] In step S308, the computer 22 rejects the listing of the content. Here, the computer 22 rejects the listing of Image 1 and Image 2 and sends a message to the user terminal 14 indicating that the listing of Image 1 and Image 2 has been rejected.

[0065] On the one hand, in step S309, computer 22 permits the submission of the content. Here, computer 22 permits the submission of Image 3 and sends a message to user terminal 14 indicating that Image 3 has been submitted. As a result, the purchasing user can purchase Image 3 on the NFT platform. Then, computer 22 ends the specific process.

[0066] Note that in the above description, the case where computer 22 executes the monitoring process after acquiring the content in step S301 is shown as an example. However, when it takes time to generate the content, computer 22 may execute the monitoring process prior to the acquisition of the content.

[0067] Also, in the above description, the case where computer 22 assigns a flag to the content detected as being plagiarized is shown as an example. However, it is not limited to this. Computer 22 may assign a score 1 indicating that one prohibited word has been extracted for Image 1. Similarly, computer 22 may assign a score 2 indicating that two prohibited words have been extracted for Image 2. Computer 22 may, for example, assign a score that quantifies the degree of plagiarism for the content in this way.

[0068] In this case, in step S307, computer 22 may determine whether the score exceeds a predetermined threshold. Then, it may be determined that the content with a score exceeding the predetermined threshold cannot be submitted, and it may be determined that the content with a score below the predetermined threshold can be submitted.

[0069] Also, in the above description, flags and scores are given only to the content detected as plagiarism, while nothing is given to the content not detected as plagiarism. That is, a case where it is implicitly shown that the content is not plagiarism was given as an example. However, by giving a flag indicating that the content is not plagiarism to the content not detected as plagiarism, or by giving a score of 0 indicating that the number of extracted prohibited words is 0, it may be explicitly shown that the content is not plagiarism.

[0070] As described above, the data processing apparatus 12 according to the present embodiment monitors an instruction input to the generation model 58 to generate content, detects plagiarism of the content generated by the generation model 58, and associates the detection result with the content. Thereby, according to the data processing apparatus 12 according to the present embodiment, since it is possible to detect plagiarism by the generation AI and associate it with the content, it is possible to prevent obtaining an improper profit by the generated content. Therefore, without stopping the evolution of AI by legal regulations, the handwritten creator can encourage the creation of works as before without worrying about the infringement of the rights of the works created by himself / herself.

[0071] Also, both the instruction input to the generation model and the content generated by the generation model may be exchanged on the blockchain. As a result, it becomes virtually impossible to falsify how the content was generated by which instruction. Therefore, according to the data processing apparatus 12, it is possible to prevent the information to be monitored for detecting plagiarism from being falsified.

[0072] In addition, the data processing device 12 may supply instructions to the generation model via the API and obtain content from the generation model via the API. As a result, according to the data processing device 12, it is possible to track the content generation route by the generation model 58, and it is possible to provide an environment in which the AI creator can use the generation AI as if directly accessing the generation tool 16. In particular, when using an existing generation AI, it is not possible to implement the existing generation AI itself on the blockchain. In contrast, according to the data processing device 12, by using API cooperation, it is possible to incorporate the existing generation AI into the blockchain without designing a new generation AI for the blockchain.

[0073] In addition, when a prohibited word is extracted from the instruction, the data processing device 12 may detect that the content is plagiarized. As a result, it is possible to detect content plagiarism by a relatively simple process of searching for prohibited words.

[0074] In addition, the data processing device 12 may flag the content detected as plagiarized. As a result, according to the data processing device 12, it is possible to identify whether the content is plagiarized only by the presence or absence of the flag.

[0075] In addition, the data processing device 12 may assign a score that quantifies the degree of plagiarism to the content. As a result, according to the data processing device 12, even when it is unclear whether the content is plagiarized or not, an objective numerical value can be associated with the content.

[0076] In addition, the data processing device 12 may determine whether the content can be listed based on the detected result. As a result, according to the data processing device 12, it is possible to provide an integrated service that links the plagiarism detection function and the listing function. Therefore, according to the data processing device 12, it is possible to prevent the risk of a lawsuit being filed, such as the content generated by the generation AI infringing on the rights of the works of handwritten creators.

[0077] Also, as described above, the content traded on the NFT platform may be limited to the content generated using the generative AI in the situation where the data processing device 12 is tracking the generation route. Thereby, according to the data processing device 12, it is possible to create an NFT platform in which only the content by the generative AI exists. Therefore, it is possible to separate the works of handwritten creators who make a living as creators and the content of AI creators using generative AI. Therefore, while the works of handwritten creators are guaranteed value as original works, it is possible to realize a world in which the content of AI creators is enjoyed as content by generative AI.

[0078] As described above, the system according to the present disclosure has been mainly described in terms of the functions of the data processing device 12. However, the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program operating on a personal computer or as an application operating on a smartphone or the like. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[0079] In the above embodiment, an example form in which specific processing is performed by one computer 22 has been given. However, the technology of the present disclosure is not limited to this, and distributed processing for specific processing by a plurality of computers including the computer 22 may be performed.

[0080] In the above-described embodiment, an example has been described in which the specific processing program 56 is stored in the storage 32. However, the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable computer-readable non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0081] Further, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed in the computer 22 in response to a request from the data processing device 12.

[0082] Note that it is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32. A part of the specific processing program 56 may be stored.

[0083] As the hardware resources for executing the specific processing, the following various processors can be used. As the processor, for example, a general-purpose processor such as a CPU that functions as a hardware resource for executing specific processing by executing software, that is, a program, can be mentioned. Further, as the processor, for example, a dedicated electric circuit that is a processor having a circuit configuration designed specifically for executing specific processing such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit) can be mentioned. A memory is built in or connected to any of the processors, and any of the processors executes specific processing by using the memory.

[0084] The hardware resources for executing the specific process may be composed of one of these various processors, or may be composed of a combination of two or more processors of the same type or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resources for executing the specific process may be a single processor.

[0085] As an example of being composed of a single processor, firstly, there is a form in which one processor is composed of a combination of one or more CPUs and software, and this processor functions as the hardware resources for executing the specific process. Secondly, as represented by a SoC (System-on-a-chip), there is a form in which a processor that realizes the functions of the entire system including a plurality of hardware resources for executing the specific process is used in one IC chip. Thus, the specific process is realized as the hardware resources using one or more of the above various processors.

[0086] Furthermore, as the hardware structure of these various processors, more specifically, an electric circuit combining circuit elements such as semiconductor elements can be used. Also, the above specific process is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be changed within the scope not departing from the gist.

[0087] The description and illustration shown above are detailed descriptions of the part related to the technology of the present disclosure, and are merely examples of the technology of the present disclosure. For example, the descriptions regarding the above configurations, functions, actions, and effects are descriptions regarding examples of the configurations, functions, actions, and effects of the part related to the technology of the present disclosure. Therefore, it goes without saying that within the scope not departing from the gist of the technology of the present disclosure, the description and illustration shown above may be deleted of unnecessary parts, new elements may be added, or replacements may be made. Also, in order to avoid complication and facilitate the understanding of the part related to the technology of the present disclosure, in the description and illustration shown above, descriptions regarding common general knowledge of technology that do not particularly require explanation for implementing the technology of the present disclosure are omitted.

[0088] All documents, patent applications, and technical standards described in this specification are incorporated herein by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually stated to be incorporated by reference.

Explanation of Reference Numerals

[0089] 10 Data processing system 12 Data processing device 14 User terminal 58 Generation model 290 Specific processing unit 291 Interface unit 292 Monitoring unit 293 Detection unit 294 Related unit 295 Judgment unit

Claims

1. A monitoring unit that monitors instructions input to a generation model to generate content, a detection unit that detects plagiarism of the content generated by the generation model based on the instructions, an association unit that associates the detected result with the content, A data processing device comprising:

2. The instructions and the content are exchanged on a blockchain, The data processing device according to claim 1.

3. The data processing device according to claim 2, further comprising an interface unit that supplies the instructions to the generation model via an API and acquires the content from the generation model via the API. The data processing device according to claim 2.

4. The detection unit detects that the content is plagiarized when one or more pre-registered prohibited words are extracted from the instructions. The data processing device according to any one of claims 1 to 3.

5. The association unit assigns a flag to the content detected as being plagiarized. The data processing device according to any one of claims 1 to 3.

6. The association unit assigns a score that quantifies the degree of plagiarism to the content. The data processing device according to any one of claims 1 to 3.

7. The data processing device according to any one of claims 1 to 3, further comprising a determination unit that determines whether the content can be listed based on the detected result. The data processing device according to any one of claims 1 to 3.

8. A computer monitors instructions input to a generation model to generate content, detects plagiarism of the content generated by the generation model based on the instructions, associates the detected result with the content, A data processing method for executing a process including:

9. A data processing program for causing a computer to monitor instructions input to a generation model to generate content, detect plagiarism of the content generated by the generation model based on the instructions, associate the detected result with the content, and execute a process including:

Images