This paper is dedicated to the memory of David Kittrell, a long-time pioneer and contributor in the field of eDiscovery and an early member of the drafting team for this paper. David passed away in September 2020 and will be sorely missed and fondly remembered.
Mallory Acheson Nelson Mullins Derek Duarte Blackstone Discovery Maura R. Grossman University of Waterloo and Maura Grossman Law Kelly Atherton Driven, Inc. Tara Emory Driven, Inc. Angela Lindstrom Amazon David Cohen Reed Smith Jeff Gilles Relativity Wilzette Louis Hogan Lovells…
Bostrom, N. (2014). Superintelligence: Paths, dangers, strategies. Oxford, UK: Oxford University Press. Brown, T., Mann, B., et al. (2020) Language Models are Few-Shot Learners. arXiv:2005.14165v4 [cs.CL] 22 Jul 2020. Domingos, P. (2012). A few useful things to know about…
Since the beginning of the rise of AI in the legal industry, there have been concerns of computers replacing, or diminishing the need for, attorneys and other litigation support professionals. While there is not universal agreement about the potential impact…
The use of AI in eDiscovery implicates several ethical concerns. The ABA Model Rules of Professional Conduct, versions of which have been adopted by 49 of the 50 U.S. states, highlight some of these issues. Model Rule 1.1 and its…
A key consideration when selecting AI technology for use in eDiscovery is to ensure that the purpose of the AI tool matches the desired results. All artificial intelligence tools are narrowly tailored to solve specific challenges. For example, most existing…
AI can offer significant advantages over the manual execution of tasks, including cost and time savings, increased efficiency, and greater consistency. Cost and time savings can be achieved by reducing the need for time-consuming human decision making. In addition, computers…
a. Ranking, Classification, and Review of ESI In litigation, the volume and diversity of text-based data and the cost of reviewing that data manually has quickly accelerated the use of cutting-edge techniques. One common use of AI is to segregate…
a. Clustering Clustering is an example of unsupervised machine learning. The purpose of clustering is to group “similar” items together, which allows users to recognize the characteristics or topics that make them similar. This allows users to learn something about…
Artificial Intelligence, or “AI,” refers to the capability of machines to mimic aspects of human intelligence, such as problem solving, reasoning, discovering meaning, generalizing, predicting, or learning from past experience. AI includes both unsupervised and supervised machine learning, but it…
This paper is dedicated to the memory of David Kittrell, a long-time pioneer and contributor in the field of eDiscovery and an early member of the drafting team for this paper. David passed away in September 2020 and will be…