Computational research techniques such as text and data mining (TDM) hold tremendous opportunities for researchers across the disciplines, ranging from mining scientific articles to create better systematic reviews to building a corpus of films to understand how concepts of gender, race, and identity are shared over time. Unfortunately, legal uncertainty associated with text and data mining can stifle this research. Recent copyright lawsuits, such as the high-profile cases brought against Microsoft, Github, and StabiltyAI underscore the legal complications.

This workshop will survey existing law and policy and highlight pathways forward for researchers and librarians, including fair use and TDM-specific exemptions to copyright, particularly for users of materials covered by digital rights management (DRM) and other similar technology. We will also discuss limitations of the law and explore ways in which it might be improved, as well as practical issues such as licensing of content for TDM use.

The workshop will be led by Dave Hansen and Rachel Brooke of Authors Alliance, a nonprofit that exists to support authors who research and write for public benefits. Dave and Rachel are copyright experts who have worked extensively on legal barriers to research. They have served as co-PIs for the Authors Alliance Text and Data Mining: Demonstrating Fair Use Project, which was generously supported by the Mellon Foundation.