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, 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. This interactive, in-person workshop will take place from 11am-1pm. Boxed lunches will be provided. All are welcome to attend but registration is required for space and planning purposes.

The workshop will be led by Dave Hansen, Executive Director of Authors Alliance, and Rachel Brooke, Authors Alliance Senior Staff Attorney. Authors Alliance is a nonprofit that exists to support authors who research and write for the public benefit. Both Dave and Rachel have worked extensively on legal barriers to research, and are PIs for the Authors Alliance Text and Data Mining: Demonstrating Fair Use Project, which is generously supported by the Mellon Foundation.

This event is governed by the Engelberg Center’s Code of Conduct and NYU’s COVID policies.