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Legal Issues in Computational Research Using Images and Audio-Visual Works


Dave Hansen

Computational research using large numbers of images and audio-visual works holds incredible potential, yielding new insights and enabling new technologies. Unfortunately, legal uncertainty associated with text and data-mining of images and audio-visual works can stifle this research. Recent lawsuits, such as the high-profile cases brought against Micrsoft, Github, StabiltyAI only underscore this uncertainty, causing researchers to either avoid this work or to bias their work by relying only on works thought to be "safe" from copyright problems. This workshop will survey the existing law and policy and highlight pathways forward for researchers under existing law, including fair use and TDM specific exemptions to copyright, with a specific focus on creating and using datasets of images and audio-visual works.. We will offer a hybrid attendance option, but the workshop will be hands-on, so we encourage in-person participation. We are also offering a workshop on March 23 on legal issues with TDM for textual materials. This workshop is led by Dave Hansen, Executive Director of Authors Alliance (, a nonprofit that exists to support authors who research and write for the public benefit. Dave is a copyright expert who has worked extensively on legal barriers to research, and is a PI for the Authors Alliance Text and Data-Mining: Demonstrating Fair Use Project, which is generously supported by the Mellon Foundation. Food and coffee will be provided. Please RSVP at so we can have an accurate count. For virtual attendance, please register for the zoom webinar here: This event is organized by Duke University Libraries and the John Hope Franklin Humanities Institute.