본문 바로가기
KERD
논문KCI 등재

인공지능(AI) 생성물과 저작권 문제

Artificial intelligence (AI) outputs and copyright issues

김경숙
IT와 법연구소 (IT & Law Research Institute)|2023.08|IT와 법연구 (IT&LAW REVIEW)|제27호|pp. 33-72|DOI 10.37877/itnlaw.2023..27.002

0

조회

0

다운로드

20

인용

0

참고문헌

키워드

공정이용크레딧생성형 인공지능ChatGPT챗지피티Generative AI독창성OriginalityFair Use저작인접권인공지능 플랫폼저작물성Credit기여자미드저니Neighboring RightMidjourneyAI platform앤디워홀인공지능 생성물CopyrightabilityContributor데이터베이스지침독자적 권리지적창작물어도비스톡디지털싱글마켓지침보호기간지침게티이미지Sui Generis rightIntellectual CreationAdobestockDSM DirectiveTerm DirectiveDatabase DirectiveAI outputsGetty ImagesAndy Worhol

초록

The development of "generative AI" technologies has significantly stimulated academic research in recent years, especially in the area of legal implications. In particular, copyright issues have been discussed more than other intellectual property rights, largely due to the widespread use of pre-existing works to train these advanced AI models. The primary copyright issues related to generative AI include whether an AI-generated output can be copyrighted, what rights can be granted if copyrightability is denied, who the rights holder might be in such circumstances, and issues of copyright infringement and liability. This article delves into these three issues across separate chapters. First, in terms of authorship, Korean copyright law defines a "copyrighted work" as "a creative expression of human thought or feeling. This implies that authorship is not extended to non-human creators. Second, it was confirmed that this position is consistent with international law and case law. Furthermore, if authorship is denied, the discussion explored whether AI-generated output should remain in the public domain or be protected by rights other than copyright. However, if any rights are not granted to AI-generated outputs, it would be challenging to address the unauthorized use of these outputs in the secondary market. Moreover, the absence of rights could reduce the incentive to create and use such outputs. From this perspective, I argue that AI-generated outputs should be afforded legal protection through intellectual property rights. Accordingly, I have suggested that it is appropriate to grant neighboring rights. This is consistent with the legislative intent behind neighboring rights, which is to protect the act of making works available to the public. Moreover, because neighboring rights are less exclusive than copyright and have a limited scope, they are proposed as the appropriate rights to grant. This approach could facilitate the use of AI-generated works. The third issue concerns copyright infringement and liability with respect to AI-generated outputs. This article has identified two primary types of copyright infringement in generative AI: 'input-phase infringement,' which occurs during the process of feeding and training an AI model, and 'output-phase infringement,' which occurs during the creation and secondary use of outputs that bear substantial similarity to the original work. A key question is who is liable for infringement at each phase, so this article has also examined this issue.

Abstract

The development of "generative AI" technologies has significantly stimulated academic research in recent years, especially in the area of legal implications. In particular, copyright issues have been discussed more than other intellectual property rights, largely due to the widespread use of pre-existing works to train these advanced AI models. The primary copyright issues related to generative AI include whether an AI-generated output can be copyrighted, what rights can be granted if copyrightability is denied, who the rights holder might be in such circumstances, and issues of copyright infringement and liability. This article delves into these three issues across separate chapters. First, in terms of authorship, Korean copyright law defines a "copyrighted work" as "a creative expression of human thought or feeling. This implies that authorship is not extended to non-human creators. Second, it was confirmed that this position is consistent with international law and case law. Furthermore, if authorship is denied, the discussion explored whether AI-generated output should remain in the public domain or be protected by rights other than copyright. However, if any rights are not granted to AI-generated outputs, it would be challenging to address the unauthorized use of these outputs in the secondary market. Moreover, the absence of rights could reduce the incentive to create and use such outputs. From this perspective, I argue that AI-generated outputs should be afforded legal protection through intellectual property rights. Accordingly, I have suggested that it is appropriate to grant neighboring rights. This is consistent with the legislative intent behind neighboring rights, which is to protect the act of making works available to the public. Moreover, because neighboring rights are less exclusive than copyright and have a limited scope, they are proposed as the appropriate rights to grant. This approach could facilitate the use of AI-generated works. The third issue concerns copyright infringement and liability with respect to AI-generated outputs. This article has identified two primary types of copyright infringement in generative AI: 'input-phase infringement,' which occurs during the process of feeding and training an AI model, and 'output-phase infringement,' which occurs during the creation and secondary use of outputs that bear substantial similarity to the original work. A key question is who is liable for infringement at each phase, so this article has also examined this issue.

참고문헌 (54)

  1. 박성호, "저작권법" (2017), 박영사
  2. 오승종, "저작권법" (2014), 박영사
  3. 이해완, "저작권법" (2019), 박영사
  4. 김경숙, "TDM 관련 저작권법 개정안의 비판적 고찰 — 기술적보호조치 관점에서의 비교법적 검토 —", 경영법률, 31(3), pp.111~141 (2021), 한국경영법률학회
  5. 김경숙, "Data mining and Copyright", The International Journal of Internet, Broadcasting and Communication, 14(4), pp.11~19 (2022), 한국인터넷방송통신학회[DOI]
  6. 김용주, "인공지능(AI; Artificial Intelligence) 창작물에 대한 저작물로서의 보호가능성", 법학연구, 27(3), pp.267~297 (2016), 법학연구소
  7. 김원오, "AI 자동 생성작품에 대한 저작권 부여 한계와 대안적 보호방법론", 계간 저작권, 36(2), pp.33~76 (2023), 한국저작권위원회[DOI]
  8. 김윤명, "데이터 공정이용", 계간 저작권, 36(1), pp.5~53 (2023), 한국저작권위원회[DOI]
  9. 김창화, "데이터 마이닝과 저작권 면책의 범위 및 한계", 계간 저작권, 34(2), pp.5~31 (2021), 한국저작권위원회[DOI]
  10. 김현경, "저작권 귀속법리와 인공지능 창작물에 대한 고찰", 성균관법학, 29(1), pp.331~374 (2017), 법학연구원[DOI]
  11. 류시원, "저작권법상 텍스트·데이터 마이닝(TDM) 면책규정 도입 방향의 검토", 선진상사법률연구, (101), pp.347~390 (2023), 법무부
  12. 손승우, "인공지능 창작물의 저작권 보호", 정보법학, 20(3), pp.83~110 (2016), 한국정보법학회
  13. 이주연, "저작권법과 연구윤리관점에서 본 학술논문과 인공지능의 저자성 —최근 ChatGPT를 둘러싼 논의를 중심으로—", 경영법률학회 2023년 하계공동 학술대회 발제문
  14. 임효성, "인공지능을 활용한 음악창작과 저작물성", 계간 저작권, 32(2), pp.37~73 (2019), 한국저작권위원회
  15. 정원준, "인공지능 창작물의 보호에 관한 법적 쟁점과 정책적 과제", 정보통신방송정책, 31(6)통권 : 689 (2019), 정보통신정책연구원
  16. 정충원, "인공지능(Artificial Intelligence:AI)시스템에 대한 저작권보호에 관한 연구", 법학연구, 31(2), pp.179~202 (2023), 법학연구소
  17. 조연하, "인공지능 창작물의 저작권 쟁점 — 저작물성과 저작자 판단을 중심으로 —", 언론과 법, 19(3), pp.71~113 (2020), (사)한국언론법학회
  18. 차상육, "인공지능 창작물의 저작권법상 보호 쟁점에 대한 개정방안에 관한 연구", 계간 저작권, 33(1), pp.5~69 (2020), 한국저작권위원회
  19. 차상육, "저작권법상 인공지능 학습용 데이터셋의 보호와 쟁점 ―텍스트·데이터마이닝(TDM) 면책규정을 중심으로―", 경영법률, 32(1), pp.1~55 (2021), 한국경영법률학회
  20. 최상필, "빅데이터의 분석과 활용을 위한 TDM의 저작권적 쟁점과 입법론", 계간 저작권, 35(1), pp.59~91 (2022), 한국저작권위원회[DOI]
  21. 한지영, "인공지능 창작물의 보호에 관한 저작권법 체계의 패러다임 전환에 관한 고찰", 경영법률, 31(3), pp.27~64 (2021), 한국경영법률학회
  22. Cornish, William, "Intellectual Property: Patents, Copyright, Trade Marks and Allied Rights" (2019), Sweet & Maxwell
  23. Flint, Michael, "A User’s Guide to Copyright" (2006), Tottel
  24. Goldstein, Paul, "International copyright: principles, law, and practice" (2019)
  25. Bond, Toby, "Artificial Intelligence and Copyright: Section 9(3) or Authorship without an Author", JIPLP, 14, pp.423~ (2019)
  26. Bridy, Annemarie, "The Evolution of Authorship: Work Made by Code", Columbia Law Journal & Arts, 39, pp.395~ (2016)
  27. Bridy, Annemarie, "Coding Creativity: Copyright and the Artificially Intelligent Author", Stan. Tech. L. Rev., 5, pp.1~ (2012)
  28. Buning, M. de Cock, "Autonomous Intelligent Systems as Creative Agents under the EU Framework for Intellectual Property", European Journal of Risk Regulation, 7, pp.310~ (2016)
  29. Cowan, David, "Robot ART! The UK Copyright Implications of Artificial Intelligence Generated Art", Robotics Journal (2019)
  30. Dickenson, Julia, "Creative Machines: Ownership of Copyright in Content Created by Artificial Intelligence Applications", EIPR, 39, pp.457~ (2017)
  31. Gendreau, Ysolde, "Copyright Ownership of Photographs in Anglo-American Law", EIPR, 15(6), pp.207~ (1993)
  32. Gervais, Daniel. J., "The machine as author", Iowa L. Rev., 105(5), pp.2053~ (2020)
  33. Gervais, Daniel J., "Is intellectual property law ready for artificial intelligence?", GRUR Int, 69(2), pp.117~ (2020)
  34. Ginsburg Jane, "People not machines: authorship and what it means in the Berne Convention", IIC Int Rev Intellect Prop Compet Law, 49, pp.131~ (2018)
  35. Ginsburg, Jane, "The concept of authorship in comparative copyright law", DePaul Law Rev, 52, pp.1063~ (2003)
  36. Gray, Earl, "Works for hire when software is commissioned, who owns the copyright", Copyright World (2003)
  37. Hristov Kalin, "Artificial intelligence and the copyright dilemma", IDEA: The IP L. Rev., 57(3), pp.431~ (2017)
  38. Hugenholtz, P. Bernt, "Copyright and Artificial Creation: Does EU Copyright Law Protect AI-Assisted Output?", IIC, 52, pp.1190~1216 (2021)
  39. Kalyatin Vitaly, "Rights to Intellectual Works Generated with Artificial Intelligence: A Russian View in the Global Context", Legal Issues in the Digital Age, 1, pp.42~ (2021)
  40. Netanel, Neil Weinstock, "Copyright and a Democratic Civil Society", The Yale Law Journal, 106(2), pp.283~ (1996)
  41. Oord, Aaron van den, "WaveNet: A Generative Model for Raw Audio", arXiv:1609.03499v2, ~
  42. Rahmatian, Andreas, "Originality in UK Copyright Law: The Old ‘Skill and Labour’ Doctrine Under Pressure", IIC, 44, pp.4~ (2013)
  43. Ralston, William.T., "Copyright in Computer-Composed Music: HAL Meets Handel", J. Copyright Society U.S.A, 52, pp.281~ (2004)
  44. Ramalho, Ana Quintela Ribeiro Neves, "Originality redux: an analysis of the originality requirement in AI-generated works", AIDA, pp.2~ (2019)
  45. Ricketson, Sam, "The 1992 Horace S. Manges lecture – people or machines: the Bern Convention and the changing concept of authorship", Columbia VLA J Law Arts, 16, pp.1~ (1991)
  46. Samuelson, Pamela, "Allocating Ownership Rights in Computer-Generated Works", U. PITT. L. REV, 47(4), pp.1185~ (1986)
  47. Senftleben Martin, "New Rights or New Business Models? An Inquiry Into the Future of Publishing in the Digital Era", IIC, 48, pp.538~ (2017)
  48. Senftleben, Martin, "Robot Creativity: An Incentive-Based Neighboring Rights Approach", Eur Intellect Prop Rev, 42(12), pp.717~ (2020)
  49. Shiffrin, Seana Valentine, "Intellectual Property and Theories of Justice" (2008), Palgrave
  50. Yanisky-Ravid, Shlomit, "Generating Rembrandt: Artificial Intelligence, Copyright and Accountability in the 3A Era-The Human-Like Authors are already here-A New Model", Michigan State Law Review, pp.659~ (2017)
  51. "Not even NYT bestsellers are safe from AI cover art" (2023)[URL]
  52. WIPO, "GUIDE to the BERNE CONVENTION for the Protection of Literary and Artistic Works", ~ (1971)
  53. WIPO, "Guide To The Copyright and Related Rights Treaties Administered By WIPO and Glossary of Copyright and Related Rights Terms", ~
  54. 차세대지재시스템검토위원회보고서(次世代知財システム 検討 委員会 報告書), "知的財産戦略本部", 知的財産戦略本部検証･評価･ 企画委員会次世代知財システム検討委員会, ~ (2016)

관련 논문AI추천

인공지능 생성물의 저작권 보호 이슈와 귀속주체 연구 - 외국의 인공지능 생성물에 대한 주요 사례를 중심으로 -정세은법학연구소 · 법학논집2024 · 제28권 제4호저작물 학습자로서 생성형 AI의 저작권 침해 책임김원오, 이지연법학연구소 · IP & Data 法2024 · 제4권 제1호인공지능에 의한 저작물 사용 관련 저작권 침해 책임 면책과 저작권자에 대한 보상에 관한 연구김도경사단법인 법조협회 · 법조2024 · 제73권 제5호인공지능(Al) 창작물의 저작권법상 보호 방안정윤경법학연구소 · The Journal of Law & IP2020 · 제10권 제2호생성형 인공지능 시대에 적합한 저작물 이용허락과 저작권자에 대한 보상 체계 확립의 필요성김도경IT와 법연구소 · IT와 법연구2025 · 제30호인공지능 창작물 관련 저작권 침해 쟁점차상육한국경영법률학회 · 경영법률2022 · 제32권 제4호

이 간행물의 다른 논문 (2건)

“몸은 하나인데 많은 지체가 있고 몸의 지체가 많으나 한 몸임”을 적용한 현행 특허법상 특허권침해 판단에 관한 논의배대헌pp. 1-32법데이터학의 가능성 탐색을 위한 방법론 연구 - 토픽 모델링(Topic modeling)을 활용한 ‘법률’ 관련 경기도의 사회적 이슈 탐색을 중심으로 -박기주pp. 73-104
원문 보기