International Journal of Law and Information Technology Advance Access originally published online on August 13, 2007
International Journal of Law and Information Technology 2008 16(1):1-7; doi:10.1093/ijlit/eam006
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An Artificial Intelligence System Suggests Arbitrariness of Death Penalty
* Truman & Anita Arnold Chair and Professor of Computer & Information Sciences, Texas A&M University - Texarkana, P.O. Box 5518, Texarkana, TX 75505-5518, USA, +1 903 223-3188, stamos.karamouzis{at}tamut.edu
* Professor, Department of Criminal Justice, Loyola University New Orleans, Campus Box 14, 6363 St. Charles Ave., New Orleans, LA 70118, USA, + 1 504 865-2161, harper{at}loyno.edu
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Abstract |
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The arguments against the death penalty in the United States have centered on due process and fairness. Since the death penalty is so rarely rendered and subsequently applied, it appears on the surface to be arbitrary. Considering the potential utility of determining whether or not a death row inmate is actually executed along with the promising behavior of Artificial Neural Networks (ANNs) as classifiers led us into the development, training, and testing of an ANN as a tool for predicting death penalty outcomes. For our ANN we reconstructed the profiles of 1,366 death row inmates by utilizing variables that are independent of the substantive characteristics of the crime for which they have been convicted. The ANN's successful performance in predicting executions has serious implications concerning the fairness of the justice system.