“Quantifying disparate questioning of Black and White jurors in capital jury selection”

The title of this post is the title of this article recently published in the Journal of Empirical Legal Studies and authored by Anna Effenberger, John Blume and Martin Wells. Here is its abstract:

This article presents findings from a quantitative study of jury selection using computational natural language processing methods.  We analyzed the voir dire in a set of South Carolina capital trials cases used in previous studies to see if there was evidence of disparate questioning of potential jurors by the prosecution, defense counsel of the trial judge.  More specifically, we examined the descriptiveness and complexity of questioning.  Our results, presented here, revealed significant, but sometimes subtle, disparate questioning of Black venire persons, especially by the prosecution.

The natural language processing software used in this study could provide attorneys challenging the use of peremptory challenges on appeal as being based on race or gender discrimination with evidence relevant to the issue of disparate questioning, which is often a pretext for purposeful discrimination.  It could also potentially be used at trial since the analysis can be conducted almost instantaneously.  Using it at either stage of the proceedings could be a powerful tool in achieving the goal of having more diverse juries in criminal cases, especially where the death penalty is a potential punishment.