Maura R. Grossman
Appointment
Solution Network Co-Director
Canadian AI Safety Institute Research Program
Safeguarding Courts from Synthetic AI Content
About
Maura R. Grossman’s principal research involves the legal, ethical, and policy implications of artificial intelligence, with an emphasis on acknowledged and unacknowledged AI as evidence in the court system. Previously, she studied high-recall information retrieval (HRIR), which falls at the intersection of technology and other disciplines, including the law, government archives, and healthcare. In particular, she investigated the application and evaluation of supervised machine learning technologies for use in electronic discovery in litigation, in the curation of government records, and for systematic reviews in evidence-based medicine.
Awards
- Number 1 Commercial Litigation – E-Discovery Lawyer in Canada, The Lexology Index: 2026 Client Choice Report (2025)
- Shira Scheindlin Lifetime Achievement Award, Zapproved Corporate E-Discovery Hero Awards (2021)
- Faculty Teaching Award, Osgoode Hall Law School (2020)
- Named to the Fastcase50 List, Fastcase (2017)
- Legal Rebel, American Bar Association (“ABA”) (2016)
Relevant Publications
- Grossman, M.R. and Grimm, P.W. (2025). “Judicial Approaches to Acknowledged and Unacknowledged AI-Generated Evidence.” Columbia Sci. & Tech. L. Rev., 26:2, pp. 110-155.
- Grimm, P.W., Grossman, M.R., and Cormack, G.V. (2021). “Artificial Intelligence as Evidence.” Nw. J. Tech. & Intell. Prop. 19, pp. 9-106.
- Cormack, G.V. and Grossman, M.R. (2014). Evaluation of Machine-Learning Protocols for Technology-Assisted Review in Electronic Discovery.” Proceedings of the 37th Int’l ACM SIGIR Conference on Research & Dev. in Info. Retrieval, pp. 253-262.
- Grossman, M.R. and Cormack, G.V., The Grossman-Cormack Glossary of Technology-Assisted Review.” (2013). Fed. Cts. L. Rev. 7, pp. 1-34.
- Grossman, M.R. and Cormack, G.V., “Technology-Assisted Review in E-Discovery Can Be More Effective and More Efficient Than Exhaustive Manual Review.” (2011). Rich. J. L. & Tech. 17, pp. 1-48.