Open Access. Powered by Scholars. Published by Universities.®

Evidence Commons

Open Access. Powered by Scholars. Published by Universities.®

Science and Technology Law

Faculty Scholarship

2021

Articles 1 - 2 of 2

Full-Text Articles in Evidence

Artificial Intelligence As Evidence, Paul W. Grimm, Maura R. Grossman, Gordon V. Cormack Jan 2021

Artificial Intelligence As Evidence, Paul W. Grimm, Maura R. Grossman, Gordon V. Cormack

Faculty Scholarship

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 …


The Easterbrook Theorem: An Application To Digital Markets, Joshua D. Wright, Murat C. Mungan Jan 2021

The Easterbrook Theorem: An Application To Digital Markets, Joshua D. Wright, Murat C. Mungan

Faculty Scholarship

The rise of large firms in the digital economy, including Amazon, Apple, Facebook, and Google, has rekindled the debate about monopolization law. There are proposals to make finding liability easier against alleged digital monopolists by relaxing substantive standards; to flip burdens of proof; and to overturn broad swaths of existing Supreme Court precedent, and even to condemn a law review article. Frank Easterbrook’s seminal 1984 article, The Limits of Antitrust, theorizes that Type I error costs are greater than Type II error costs in the antitrust context, a proposition that has been woven deeply into antitrust law by the Supreme …