An Artificial Intelligence System Suggests Arbitrariness of Death Penalty
Stamos T. Karamouzis
Texas A&M International University
Dee Wood Harper
Loyola University New Orleans
International Journal of Law and Information Technology, Vol. 16, Issue 1, pp. 1-7, 2008
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.
Accepted Paper Series
Date posted: March 13, 2009
© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo5 in 0.250 seconds