The Library Copyright Alliance (LCA) has submitted recommendations to the White House Office of Science and Technology Policy (OSTP), advocating for the preservation of fair use rights in the development of a national AI Action Plan. LCA warns that licensing restrictions could undermine these protections, potentially limiting AI research and innovation.
Fair use is a central component of US copyright law, allowing researchers to collect and train AI models on existing content without requiring prior permission from rightsholders. LCA argues that these provisions have given the United States a competitive advantage in AI development. The organization recommends that the administration submit amicus briefs in AI-related fair use cases, asserting that the public benefits of AI outweigh potential concerns from rightsholders. If judicial decisions impose restrictions on generative AI, LCA advises that the administration seek legislative intervention from Congress to protect the field’s advancement.
LCA further urges the administration to challenge contractual clauses that attempt to override fair use in AI applications. The organization contends that such provisions should not be enforceable and suggests that, if courts fail to uphold this principle, the administration should advocate for legislation explicitly affirming that fair use and other copyright protections take precedence over conflicting licensing terms.
The recommendations were submitted in response to a request for information from the Networking and Information Technology Research and Development (NITRD) National Coordination Office, National Science Foundation (NSF), on behalf of OSTP.
Katherine Klosek, Director of Information Policy and Federal Relations at the Association of Research Libraries (ARL), noted that American research libraries invest over a billion dollars annually in licensing digital databases and journals. She emphasized that maintaining fair use protections is essential to ensuring that this investment continues to support research and innovation effectively.
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