Law Commons^™

Computationally Assessing Suspicion, Wesley M. Oliver, Morgan A. Gray, Jaromir Savelka, Kevin D. Ashley

University of Cincinnati Law Review

Law enforcement officers performing drug interdiction on interstate highways have to decide nearly every day whether there is reasonable suspicion to detain motorists until a trained dog can sniff for the presence of drugs. The officers’ assessments are often wrong, however, and lead to unnecessary detentions of innocent persons and the suppression of drugs found on guilty ones. We propose a computational method of evaluating suspicion in these encounters and offer experimental results from early efforts demonstrating its feasibility. With the assistance of large language and predictive machine learning models, it appears that judges, advocates, and even police officers could …

Protecting The Promise To The Families Of Tuskegee: Banning The Use Of Persuasive Ai In Obtaining Informed Consent For Commercial Drug Trials, Jennifer S. Bard

San Diego Law Review

This is the first article to call for a ban on the use of AI technology designed to influence human decision-making, “Persuasive AI,” for the purpose of recruiting or enrolling human participants in drug trials sponsored by commercial entities. It does so from a perspective of precaution, not fear. Advances in Artificial Technology that can assist human decision-making have tremendous potential for good. It makes the case for doing so based on both the substantial risk of harm to the decision-making process and the ineffectiveness of intermediate regulatory measures. This Article looks directly at Persuasive AI, a type of AI …

Challenging The Criminalization Of Undocumented Drivers Through A Health-Justice Framework, Jason A. Cade

Scholarly Works

States increasingly use driver’s license laws to further policy objectives unrelated to road safety. This symposium contribution employs a health justice lens to focus on one manifestation of this trend—state schemes that prohibit noncitizen residents from accessing driver’s licenses and then impose criminal sanctions for driving without authorization. Status-based no-license laws not only facilitate legally questionable enforcement of local immigration priorities but also impose structural inequities with long-term health consequences for immigrants and their family members, including US citizen children. Safe, reliable transportation is a significant social determinant of health for individuals, families, and communities. Applying a health justice lens …

Automated Stategraft: Electronic Enforcement Technology And The Economic Predation Of Black Communities, Sonia Gipson Rankin, Melanie E. Moses, Kathy Powers

Faculty Scholarship

Automated traffic enforcement systems disproportionately impact Black communities in the United States. This Essay uncovers a troubling reality: while technologies such as speed cameras and red light cameras are often touted as tools for public safety by the National Highway Safety Transportation Administration, they disproportionately burden Black and Hispanic neighborhoods. The authors coin the term “automated stategraft” to describe this phenomenon—an insidious process that siphons financial resources from already vulnerable groups under the guise of law enforcement. In doing so, it exacerbates economic disparities and erodes trust in legal and governmental institutions.

This Essay delves into the biases inherent in …

Teaching And Learning About Implicit Bias In The Legal Practice Classroom: The Lesson Of Sandy Jordan, Anupama C. Connor

Saint Louis University Law Journal

“Implicit bias” describes the unconscious stereotypes and attitudes that all humans have hard wired in their brains. It can go awry when we have implicit biases based on race or ethnicity that are unrealized and unfair. Gen Z students are famously diverse, and they are proud of their diversity, but they are also uncomfortable talking about sensitive topics, including implicit bias. Legal Practice professors are in a unique position to work with their Gen Z students to identify and eliminate implicit bias because of our year-long course and the interactive nature of our class. This article discusses how implicit bias …

Mandatory Anti-Bias Cle: A Serious Problem Deserves A More Meaningful Response, Rima Sirota

Georgetown Law Faculty Publications and Other Works

This essay addresses the problematic convergence of two recent trends: (1) the expansion of jurisdictions requiring anti-bias training (ABT) as part of mandatory continuing legal education (CLE), and (2) the growing recognition among social scientists that such training, at least as currently practiced, is of limited effectiveness.

Forty-six American states require continuing legal education (CLE), and eleven of these states now require lawyer ABT as one facet of CLE requirements. I have previously criticized the mandatory CLE system because so little evidence supports the conclusion that it results in more competent lawyers. The central question tackled by this essay is …