USA – NEW YORK Trends and Developments Contributed by: Nancy E Wolff, Scott J Sholder and Elizabeth Safran, Cowan DeBaets Abrahams & Sheppard LLP
licence image and video datasets, and a deal between Reddit and Google for access to Reddit’s API for AI training. An agreement between the New York Times (NYT) and Amazon, meanwhile, will allow Amazon products, including Alexa speakers, to excerpt from NYT stories or use stories and recipes from the publi - cation, employing this content, additionally, for train - ing. AP and Google’s content licensing deal allows AP’s real-time news information to appear in Google’s Gemini chatbot. Such undertakings speak to the value in licensing from trusted and curated datasets. AI models trained from datasets without such oversight pose greater risk of AI platform failure. Such systems may often, for example, propagate harmful biases in their training data as to race, gender, socioeconomic status and other sensi - tive cultural factors, as well as lead to poor model per - formance, unreliable outputs, and privacy violations including unauthorised data and personal information exposure. Contractually licensing for curated content mitigates such risks, as companies with aggregated original content may serve as trusted sources, cor - recting issues in current commercially available mod - els. Additionally, licensing ensures fair compensation for rights-holders that avoids their resorting to bring - ing infringement claims in court, mitigating risk and leaving developers free to focus on their product. Licensing aggregated content for AI contexts is a natural evolution in content licensing, as companies have been licensing mass quantities of content well prior to the advent and proliferation of generative AI. The Copyright Clearance Center (CCC), for exam - ple, follows a voluntary “collective licensing” model to facilitate large-scale licensing for corporate and academic users of copyrighted materials, including books, newspapers, magazines, television shows, images and blogs. Collective licensing refers to a sys - tem whereby a Collective Management Organisation (CMO) represents rights-holders to license their works to third parties, via a collective, or blanket licence. This is an effective way to manage the reuse of small portions of published copyrighted works, balancing the needs of rights-holders with those who wish to use their content.
In addition to CMOs, the music, fine art, photogra - phy, news media, book publishing and motion pic - ture industries all also have a history of facilitating aggregated licensing deals. In the United States, most aggregate licensing frameworks are voluntary, with these industries independently setting licensing norms and standard practices in relation to economic considerations. Though the government has imposed compulsory licensing systems in rare instances, such as for regulating musical works, these are “exception - al cases”, as noted by former Register of Copyrights Marybeth Peters, reserved for “when the marketplace is incapable of working”; of course, it is “difficult to say that the marketplace is incapable of working... when the marketplace has” not been given enough chance to succeed, so compulsory licences may not be an immediately necessary solution in the case of gen - erative AI platforms. See Regan Smith, Licensing of Text or Generative AI: Learnings from Non-AI Licens- ing Practices , 48 Colum. J.L. & Arts 450, 454 (2025) (quoting Music Licensing Reform: Hearing Before the Subcomm. on Intellectual Property of the Comm. on the Judiciary, 109th Cong. 13 (2005) (statement of Marybeth Peters, Register of Copyrights, U.S. Copy - right Office)). Indeed, compulsory licences may also risk depressing technological and market develop - ment by imposing mandatory, less flexible licensing terms on an industry. Recognising the need for voluntary collective AI licens - ing, the CCC currently facilitates various systems, including AI re-use rights within its Annual Copyright Licences (ACL), a content licensing system that offers rights for millions of works to subscribing companies. Pioneered by CCC in mid-2024, the ACL re-use rights marked the first collective licensing solution for inter - nal use of copyrighted materials in AI systems. Noting the need for “[r]esponsible AI”, CCC President and CEO Tracey Armstrong advised that “[i]t is possible to be pro-AI and pro-copyright, and to couple AI with respect for creators”. CCC Pioneers Collective Licens- ing Solution for Content Usage in Internal AI Systems , CCC (16 July 2024). The CCC also maintains an AI Systems Training Licence, a voluntary non-exclusive collective licence to aid organisations wishing to com - ply with copyright laws to use third-party content to train AI systems. A growing number of other volun - tary collective rights organisations and similar services
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