Abstract
Modern scraping practices—the automated extraction of data from online websites—by companies employing generative AI models threatens the foundational and essential openness of the internet. There are calls for regulating the use of scraping in generative AI models, but lawmakers, concerned about its impact on US global AI leadership, have failed to act. This article presents two legal frameworks aimed at regulating generative AI scraping. The adverse possession framework addresses property rights and allows for the use of copyrighted works where the author abandons or fails to claim their works. The public records framework addresses privacy rights and treats personal information made publicly available by the subject as a public record with context-based privacy exemptions. These frameworks seek to strike a balance between private interests in development and the public’s interest in safeguarding its property and privacy rights.
Last Page
589
Recommended Citation
Melany Amarikwa,
Internet Openness at Risk: Generative AI's Impact on Data Scraping,
30
Rich. J.L. & Tech
533
(2025).
Available at:
https://scholarship.richmond.edu/jolt/vol30/iss3/3
Included in
Intellectual Property Law Commons, Internet Law Commons, Privacy Law Commons, Science and Technology Law Commons
