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Intellectual Property and Creative Machines

Author

Listed:
  • Gaétan de Rassenfosse

    (Ecole polytechnique federale de Lausanne)

  • Adam Jaffe

    (Brandeis University)

  • Joal Waldfogel

    (University of Minnesota)

Abstract

The arrival of creative machines—software capable of producing human-like creative content—has triggered a series of legal challenges about intellectual property. The outcome of these legal challenges will shape the future of the creative industry in ways that could enhance or jeopardize welfare. Policymakers are already tasked with creating regulations for a post-generative AI creative industry. Economics may offer valuable insights, and this paper is our attempt to contribute to the discussion. We identify the main economic issues and propose a framework and some tools for thinking about them.

Suggested Citation

  • Gaétan de Rassenfosse & Adam Jaffe & Joal Waldfogel, 2024. "Intellectual Property and Creative Machines," Working Papers 27, Chair of Science, Technology, and Innovation Policy.
    • Handle: RePEc:iip:wpaper:27
    as

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    References listed on IDEAS

    as
    1. Nicholas Bloom & Charles I. Jones & John Van Reenen & Michael Webb, 2020. "Are Ideas Getting Harder to Find?," American Economic Review, American Economic Association, vol. 110(4), pages 1104-1144, April.
    2. Pierre Azoulay & Joshua Krieger & Abhishek Nagaraj, 2024. "Old Moats for New Models: Openness, Control, and Competition in Generative AI," NBER Chapters, in: Entrepreneurship and Innovation Policy and the Economy, volume 4, National Bureau of Economic Research, Inc.
    3. Joshua S. Gans, 2024. "Copyright Policy Options for Generative Artificial Intelligence," NBER Working Papers 32106, National Bureau of Economic Research, Inc.
    4. Bruno Van Pottelsberghe & Dominique Guellec, 2008. "Patents and academic research: a state of the art," ULB Institutional Repository 2013/6187, ULB -- Universite Libre de Bruxelles.
    5. Christian Peukert & Florian Abeillon & Jérémie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," CESifo Working Paper Series 11099, CESifo.
    6. Silverberg, Gerald & Verspagen, Bart, 2007. "The size distribution of innovations revisited: An application of extreme value statistics to citation and value measures of patent significance," Journal of Econometrics, Elsevier, vol. 139(2), pages 318-339, August.
    7. Luis Aguiar & Joel Waldfogel, 2018. "Quality Predictability and the Welfare Benefits from New Products: Evidence from the Digitization of Recorded Music," Journal of Political Economy, University of Chicago Press, vol. 126(2), pages 492-524.
    8. Christian Peukert & Florian Abeillon & J'er'emie Haese & Franziska Kaiser & Alexander Staub, 2024. "Strategic Behavior and AI Training Data," Papers 2404.18445, arXiv.org.
    9. Luis Aguiar & Joel Waldfogel, 2021. "Platforms, Power, and Promotion: Evidence from Spotify Playlists," Journal of Industrial Economics, Wiley Blackwell, vol. 69(3), pages 653-691, September.
    10. Erik Brynjolfsson & Danielle Li & Lindsey Raymond, 2023. "Generative AI at Work," Papers 2304.11771, arXiv.org.
    11. Ashish Arora & Andrea Fosfuri & Alfonso Gambardella, 2004. "Markets for Technology: The Economics of Innovation and Corporate Strategy," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262511819, April.
    12. Eric Budish & Benjamin N. Roin & Heidi Williams, 2016. "Patents and Research Investments: Assessing the Empirical Evidence," American Economic Review, American Economic Association, vol. 106(5), pages 183-187, May.
    13. Feng Shi & James Evans, 2023. "Surprising combinations of research contents and contexts are related to impact and emerge with scientific outsiders from distant disciplines," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    14. de Rassenfosse, Gaétan & Palangkaraya, Alfons & Webster, Elizabeth, 2016. "Why do patents facilitate trade in technology? Testing the disclosure and appropriation effects," Research Policy, Elsevier, vol. 45(7), pages 1326-1336.
    15. Kenneth L. Sokoloff & Naomi R. Lamoreaux, 2001. "Market Trade in Patents and the Rise of a Class of Specialized Inventors in the 19th-Century United States," American Economic Review, American Economic Association, vol. 91(2), pages 39-44, May.
    16. Amil Merchant & Simon Batzner & Samuel S. Schoenholz & Muratahan Aykol & Gowoon Cheon & Ekin Dogus Cubuk, 2023. "Scaling deep learning for materials discovery," Nature, Nature, vol. 624(7990), pages 80-85, December.
    17. Mansfield, Edwin & Schwartz, Mark & Wagner, Samuel, 1981. "Imitation Costs and Patents: An Empirical Study," Economic Journal, Royal Economic Society, vol. 91(364), pages 907-918, December.
    18. Gaétan de Rassenfosse & Adam B. Jaffe, 2018. "Are patent fees effective at weeding out low‐quality patents?," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 27(1), pages 134-148, March.
    19. Liebowitz, S J, 1985. "Copying and Indirect Appropriability: Photocopying of Journals," Journal of Political Economy, University of Chicago Press, vol. 93(5), pages 945-957, October.
    20. Joshua S. Gans & David H. Hsu & Scott Stern, 2008. "The Impact of Uncertain Intellectual Property Rights on the Market for Ideas: Evidence from Patent Grant Delays," Management Science, INFORMS, vol. 54(5), pages 982-997, May.
    21. Abhishek Nagaraj & Imke Reimers, 2023. "Digitization and the Market for Physical Works: Evidence from the Google Books Project," American Economic Journal: Economic Policy, American Economic Association, vol. 15(4), pages 428-458, November.
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    More about this item

    Keywords

    generative AI; machine learning; copyright; fair use;
    All these keywords.

    JEL classification:

    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital
    • K20 - Law and Economics - - Regulation and Business Law - - - General

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