Abstract

http://ssrn.com/abstract=1358791
 


 



An Artificial Intelligence System Suggests Arbitrariness of Death Penalty


Stamos T. Karamouzis


Texas A&M International University

Dee Wood Harper


Loyola University New Orleans

Spring 2008

International Journal of Law and Information Technology, Vol. 16, Issue 1, pp. 1-7, 2008

Abstract:     
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





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Date posted: March 13, 2009  

Suggested Citation

Karamouzis, Stamos T. and Harper, Dee Wood, An Artificial Intelligence System Suggests Arbitrariness of Death Penalty (Spring 2008). International Journal of Law and Information Technology, Vol. 16, Issue 1, pp. 1-7, 2008. Available at SSRN: http://ssrn.com/abstract=1358791 or http://dx.doi.org/10.1093/ijlit/eam006

Contact Information

Stamos T. Karamouzis (Contact Author)
Texas A&M International University ( email )
Laredo, TX 78041
United States
Dee Wood Harper
Loyola University New Orleans ( email )
526 Pine Street
New Orleans, LA 70118
United States
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