Law Commons^™

Driverless Cars And The Much Delayed Tort Law Revolution, Andrzej Rapaczynski

Faculty Scholarship

The most striking development in the American tort law of the last century was the quick rise and fall of strict manufacturers’ liability for the huge social losses associated with the use of industrial products. The most important factor in this process has been the inability of the courts and academic commentators to develop a workable theory of design defects, resulting in a wholesale return of negligence as the basis of products liability jurisprudence. This article explains the reasons for this failure and argues that the development of digital technology, and the advent of self-driving cars in particular, is likely …

A Machine Learning Classifier For Corporate Opportunity Waivers, Gabriel V. Rauterberg, Eric L. Talley

Faculty Scholarship

Rauterberg & Talley (2017) develop a data set of “corporate opportunity waivers” (COWs) – significant contractual modifications of fiduciary duties – sampled from SEC filings. Part of their analysis utilizes a machine learning (ML) classifier to extend their data set beyond the hand-coded sample. Because the ML approach is likely unfamiliar to some readers, and in the light of its great potential across other areas of law and finance research, this note explains the basic components using a simple example, and it demonstrates strategies for calibrating and evaluating the classifier.

Fmri And Lie Detection, Anthony D. Wagner, Richard J. Bonnie, Bj Casey, Andre Davis, David L. Faigman, Morris B. Hoffman, Owen D. Jones, Read Montague, Stephen J. Morse, Marcus E. Raichle, Jennifer A. Richeson, Elizabeth S. Scott, Laurence Steinberg, Kim Taylor-Thompson, Gideon Yaffe

Faculty Scholarship

Some studies have reported the ability to detect lies, with a high degree of accuracy, by analyzing brain data acquired using functional magnetic resonance imaging (fMRI). But is this new technology ready for its day in court?

This consensus knowledge brief from the MacArthur Foundation Research Network on Law and Neuroscience takes a closer look at the potential and pitfalls of fMRI lie detection techniques, providing insight into the areas of the brain involved in lying, the impact of memory on deception, how countermeasures may foil our efforts to detect lies, and factors that can create cause for concern about …

G2i Knowledge Brief: A Knowledge Brief Of The Macarthur Foundation Research Network On Law And Neuroscience, David L. Faigman, Anthony Wagner, Richard J. Bonnie, Bj Casey, Andre Davis, Morris B. Hoffman, Owen D. Jones, Read Montague, Stephen J. Morse, Marcus E. Raichle, Jennifer A. Richeson, Elizabeth S. Scott, Laurence Steinberg, Kim Taylor-Thompson, Gideon Yaffe

Faculty Scholarship

Courts are daily confronted with admissibility issues – such as in cases involving neuroscientific testimony – that sometimes involve both the existence of a general phenomenon (i.e., “G”) and the question of whether a particular case represents a specific instance of that general phenomenon (i.e., “i”).

Unfortunately, courts have yet to carefully consider the implications of “G2i” for their admissibility decisions. In some areas, courts limit an expert’s testimony to the general phenomenon. They insist that whether the case at hand is an instance of that phenomenon is exclusively a jury question, and thus not an appropriate subject of expert …