The Electronic Discovery Reference Model (EDRM) is pleased to announce a white paper addressing “Professional Responsibility Considerations in AI for eDiscovery: Competence, Confidentiality, Privacy and Ownership.” Comments from the public are welcomed until February 20, 2023.
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.
Attorneys who authorize the use of machine learning on their client data add protection for themselves and their clients by first learning what, if any, of their client’s information informs the software application beyond the initial matter.
Khrys McKinney, Principal, K L McKinney
The white paper addressing “Professional Responsibility Considerations in AI for eDiscovery: Competence, Confidentiality, Privacy and Ownership” is offered by EDRM’s Analytics and Machine Learning’s subgroup on AI Ethics and Bias, led by Project Trustees, Khrys McKinney, Principal, K L McKinney and Dave Lewis, Chief Scientific Officer, Redgrave Data.
“Attorneys who authorize the use of machine learning on their client data add protection for themselves and their clients by first learning what, if any, of their client’s information informs the software application beyond the initial matter,” said Khrys McKinney.
AI programs like ChatGPT say the darndest things. So do machine learning systems that attorneys might train on client data, and it behooves them to be aware of the risks to confidentiality, privacy, and intellectual property. We hope this white paper will provide helpful guidance.
Dave Lewis, Chief Scientific Officer, Redgrave Data
“AI programs like ChatGPT say the darndest things. So do machine learning systems that attorneys might train on client data, and it behooves them to be aware of the risks to confidentiality, privacy, and intellectual property,” asserted Dave Lewis. “We hope this white paper will provide helpful guidance.”
“EDRM and our whole legal community are fortunate that top e-discovery data scientists, and other experts, led and contributed to preparation of this cutting-edge paper,” commented David R. Cohen, Reed Smith partner and Chair of the EDRM Project Trustees. “It highlights important issues that arise from the use of AI models across multiple matters– issues that most attorneys may not have previously considered, but must consider– to ensure that we are fulfilling our ethical duties, including protecting client confidences.”
EDRM is grateful to the project team (organizations noted for identification purposes only):
• 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)
Among the EDRM opportunities and resources available are the ability to connect, network and contribute via EDRM projects and events, share their expertise with our global community. The EDRM community of knowledgeable, multidisciplinary professionals is building resources to enhance e-discovery, privacy, security and information governance frameworks, processes and standards.
The EDRM community is comprised of 33% corporations, 30% law firms and 23% software and service providers, 12% governments with the remaining 2% being a mix of educators, students, judges and media in 145 countries spanning six continents.
Empowering the global leaders of e-discovery, the Electronic Discovery Reference Model (EDRM) creates practical resources to improve e-discovery, privacy, security and information governance. Since 2005, EDRM has delivered leadership, standards, tools and guides to improve best practices throughout the world. EDRM has an international presence in 145 countries spanning six continents and growing has an innovative support infrastructure for individuals, law firms, corporations and government organizations seeking to improve the practice and provision of data and legal discovery. Learn more about the EDRM today at EDRM.net.
About EDRM’s Analytics and Machine Learning Project’s subgroup on AI Ethics and Bias
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. The initial whitepaper, “Professional Responsibility Considerations in AI for eDiscovery: Competence, Confidentiality, Privacy and Ownership,” can be downloaded here. Comments from the public are welcomed until February 20, 2023.
Contact info@edrm.net for more information on how to get involved in our global project community.
