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Can Licensing Mitigate the Negative Implications of Commercial Web Scraping?

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Publication date14/10/2023
Host publicationCSCW 2023 Companion - Conference Companion Publication of the 2023 Computer Supported Cooperative Work and Social Computing
EditorsMorgan Ames, Susan Fussell, Eric Gilbert, Vera Liao, Xiaojuan Ma, Xinru Page, Mark Rouncefield, Vivek Singh, Pamela Wisniewski
Place of PublicationNew York
PublisherACM
Pages553-555
Number of pages3
ISBN (electronic)9798400701290
<mark>Original language</mark>English

Publication series

NameProceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW

Abstract

The rise of prominent AI models such as ChatGPT and Stable Diffusion has brought the scale of commercial web scraping to the forefront attention of content creators and researchers. Billions of webpages and images are used to train these models without content creators’ knowledge, sparking extensive criticism and even lawsuits against AI firms. Amidst such debates, licensing is proposed by researchers and legal experts to be a potential approach to mitigate content creators’ concerns and promote more responsible data reuse. However, it remains unclear what specific licensing terms will be effective to mitigate content creators’ concerns and what sociotechnical environments are necessary to facilitate the use of licensing at scale. This workshop will provide a venue for researchers, content creators, and legal experts to answer these questions.