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The Law and Economics of Generative AI and Copyright: A Primer to Core Challenges for Our Digital Future

Zachary Cooper et al.

The Review of Network Economics2025https://doi.org/10.1515/rne-2025-0039article
AJG 2ABDC B
Weight
0.50

What the paper says

Generative AI (GenAI) systems raise fundamental challenges for copyright law at both the input and output stages. On the input side, legal uncertainty surrounds the large-scale scraping of copyrighted data for model training, with divergent rules across jurisdictions and limited transparency on how data is sourced. On the output side, courts struggle to determine when AI-assisted creations are sufficiently human to merit protection, leading to inconsistent or unclear legal outcomes. This paper outlines the "AI copyright conundrum" and examines its impact on the incentives to create, the accessibility of high-quality datasets, and the sustainability of cultural production. We discuss policy options and open questions for research.

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Cite this paper

https://doi.org/https://doi.org/10.1515/rne-2025-0039

Or copy a formatted citation

@article{zachary2025,
  title        = {{The Law and Economics of Generative AI and Copyright: A Primer to Core Challenges for Our Digital Future}},
  author       = {Zachary Cooper et al.},
  journal      = {The Review of Network Economics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1515/rne-2025-0039},
}

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The Law and Economics of Generative AI and Copyright: A Primer to Core Challenges for Our Digital Future

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.