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Course Details

Course Information
  • smart_display Format

    On-Demand

  • signal_cellular_alt Difficulty Level

  • work Practice Area

    Personal Injury and Med Mal

Date & Time
  • event Date

    Wednesday, April 27, 2022

  • schedule Time

    1:00 p.m. ET./10:00 a.m. PT

  • timer Program Length

    90 minutes

Credit Information

  • This 90-minute webinar is eligible in most states for 1.5 CLE credits.

$197.00
CLE
ALL

This CLE course will discuss the increasing importance in civil cases of ascertaining, proving, and challenging the admissibility of evidence derived from artificial intelligence (AI) applications. The program will discuss what AI is and how it works, what kinds of AI application are being used, issues implicated by AI, and how the rules of evidence affect and apply to admissibility, including the need for expert witnesses, and hurdles that must be overcome before such applications or the resulting data can or should be admitted in a case.

Faculty

Maura R. Grossman
Research Professor
David R. Cheriton School of Computer Science at the University of Waterloo

Ms. Grossman, J.D., Ph.D., is a Research Professor in the David R. Cheriton School of Computer Science at the University of Waterloo, an Adjunct Professor at Osgoode Hall Law School of York University, and an affiliate faculty member at the Vector Institute of Artificial Intelligence, all in Ontario, Canada. She also is Principal at Maura Grossman Law, an eDiscovery law and consulting firm in Buffalo, New York. Ms. Grossman is most well known for her scholarly work on technology-assisted review (“TAR”), which has been widely cited in the case law, both in the U.S. and abroad. She is also known for her appointments as a special master and/or as an expert in multiple, high-profile federal and state court cases. In addition to her J.D. from the Georgetown University Law Center, Ms. Grossman also holds M.A. and Ph.D. degrees in Psychology from the Derner Institute of Adelphi University.   

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Paul W. Grimm
District Judge
United States District Court for the District of Maryland

Judge Grimm graduated with an A.B. (with highest honors) from the University of California, Davis in 1973. He received his J.D., magna cum laude and Order of the Coif, from the University of New Mexico in 1976, and an LL.M. from Duke University in 2016.  Jude Grimm is an Adjunct Professor at the University of Maryland Carey School of Law, where he currently teaches Advanced Evidence. He is a member (emeritus) of the Civil Rules Advisory Committee, from 2009-2015, and was Chair of its Discovery Subcommittee, which crafted, in part, the 2015 amendments to the Federal Rules of Civil Procedure. He also is a member of American Law Institute.

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Description

AI applications are growing increasingly ubiquitous. Thus, counsel have no choice but to understand how to admit AI evidence--or object to its admission--in the courtroom. Counsel must comprehend AI fundamentals, including what AI is and how it works, and what issues AI raises. Counsel ignore AI evidence at their own and their clients' peril.

As insurance companies, medical providers, and other companies more frequently rely on data from AI-based processes to make decisions, plaintiffs' counsel must understand how to challenge the validity, reliability, and therefore, admissibility of this data.

Both plaintiff and defense counsel must fully appreciate which rules of evidence apply to AI evidence, and what proofs are necessary. With renewed emphasis on the court's gatekeeping function, choosing the right expert(s) can make or break the case.

Listen as this experienced panel addresses what AI is, how it works, how AI is used by lawyers, what judges need to know, admissibility issues when introducing AI evidence, and a discussion of applicable rules of evidence.

Outline

  1. AI fundamentals
  2. Current uses of AI in the law
  3. Issues implicated by AI
  4. Application of the evidence rules to AI

Benefits

The panel will discuss these and other pivotal issues:

  • A plain-English explanation of what AI is, how it works, and what it can do
  • A description in how AI is being used in litigation
  • An understanding of what factors determine the validity and reliability of AI applications, and what rules of evidence govern its admissibility
  • Knowledge of the kind of experts and testimony that will be necessary when seeking to admit AI evidence