About this Project
Use of artificial intelligence (“AI”) tools in eDiscovery creates new opportunities for attorneys. By extracting, analyzing, and applying information from large data sets, AI tools can provide new insights, systematize processes, speed time to resolution, and reduce costs. A notable example is technology-assisted review (“TAR”), a process that makes use of machine learning to prioritize or classify relevant material in document reviews. Legal practitioners may reduce costs, time, and mistakes by applying TAR in litigation, antitrust reviews, investigations, and other matters. However, as legal teams’ uses of these technologies evolve, ethical issues may arise, particularly with the opportunities for reusing the results of the computer learning in future matters, but for different clients.
Read the project document here:Download Professional Responsibility Considerations in AI for eDiscovery
EDRM_2023_AI_Professional-Responsibility-V312.pdf -- 520.98 KB
The project team is grateful for the comments received prior to finalization of this version, and welcomes your thoughts for future publications.
The project team (organizations noted for identification purposes only) includes:
- Ricardo Baeza-Yates, Director of Research, Institute for Experiential AI at Northeastern University, USA (San Jose, CA)
- Lilith Bat-Leah, Vice President, Data Services at Digital Prism Advisors, Inc. (New York, NY)
- Darius Bennett, Darius Emeka Bennett, P.C., CEO and Attorney, Civil Litigation, eDiscovery and Criminal Defense (Birmingham, AL)
- Tara Emory, Senior Vice President of Strategic Growth and General Counsel at Redgrave Data (Falls Church, VA)
- David D. Lewis, Chief Scientific Officer at Redgrave Data (Denver, CO) [Trustee]
- Khrhysna McKinney, Principal at K L McKinney (Sugar Land, TX) [Trustee]
- Dana Bucy Miller, Associate Director, Legal Solutions, QuisLex Inc. (Baltimore, MD)
- James A. Sherer, Partner, BakerHostetler (New York, NY)
- George Socha, Senior Vice President of Brand Awareness, Reveal (St Paul, MN)