AI as Evidence

‘AI as Evidence’ Published in Northwestern Law Journal

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ACEDS Advisory Board member Maura Grossman, an attorney and professor at the Cheriton School of Computer Science at the University of Waterloo, The Honorable Paul W. Grimm, United States District Judge for the District of Maryland, and Gordon V. Cormack, professor at the Cheriton School of Computer Science at the University of Waterloo, have published in the Northwestern Pritzker School of Law Journal of Technology & Intellectual Property, their article Artificial Intelligence as Evidence.

This article explores issues that govern the admissibility of Artificial Intelligence (“AI”) applications in civil and criminal cases from the perspective of a federal trial judge and two computer scientists, one of whom also is an experienced attorney. It provides a detailed, yet intelligible discussion of what AI is and how it works, a history of its development, and a description of the wide variety of functions that it is designed to accomplish, stressing that AI applications are ubiquitous, both in the private and public sectors. Applications today include health care, education, employment-related decision-making, finance, law enforcement, and the legal profession.

The article underscores the importance of determining the validity of an AI application. In other words, how accurately the AI measures, classifies, or predicts what it is designed to measure, classify or predict. It also examines the reliability of AI and the consistency with which the AI produces accurate results when applied to the same or similar circumstances. The objective of course is to decide whether AI should be admitted into evidence in civil and criminal cases. The article further discusses factors that can affect the validity and reliability of AI evidence, including bias of various types, “function creep,” lack of transparency and explainability, and the sufficiency of the objective testing of AI applications before they are released for public use.

The article also includes an in-depth discussion of the evidentiary principles that govern whether AI evidence should be admitted in court cases, a topic which, at present, is not the subject of comprehensive analysis in decisional law. The focus of this discussion is on providing a step-by-step analysis of the most important issues, and the factors that affect decisions on whether to admit AI evidence.

Finally, the article concludes with a discussion of practical suggestions intended to assist lawyers and judges as they are called upon to introduce, object to, or decide on whether to admit AI evidence.

Join us in congratulating our friend and colleague, Professor Grossman, and her co-authors, for their continued contributions to advancing a unifying influence in the use of technology in the practice of law and fulfilling one of ACEDS primary missions.

Artificial Intelligence as Evidence is available free to download here:


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