Zachary Cooper, Bertin Martens, Christian Peukert, Volker Stocker
{"title":"The Law and Economics of Generative AI and Copyright: A Primer to Core Challenges for Our Digital Future.","authors":"Zachary Cooper, Bertin Martens, Christian Peukert, Volker Stocker","doi":"10.1515/rne-2025-0039","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":45659,"journal":{"name":"Review of Network Economics","volume":"24 3","pages":"161-176"},"PeriodicalIF":0.2000,"publicationDate":"2025-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12658474/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Review of Network Economics","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.1515/rne-2025-0039","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/10/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
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.
期刊介绍：
The Review of Network Economics seeks to help policy makers, academics, and practitioners keep informed of new research and policy debate in network economics and related subjects that are relevant to the study of network industries. By publishing high quality research on topical issues relevant to network industries, it is hoped readers will be able to gain a deeper understanding of the economic issues involved and that this will improve the quality of decision making by private and public organisations, and debate among researchers. The articles can cover specific network industries, or may deal with general issues that have relevance to a number of different network industries, including topics in the economics of networks, regulation, competition law, or industrial organisation. Papers that provide insights into policy debates are especially welcome, as are up-to-date surveys, book reviews, and comments.
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