Honors Theses and Capstones

Date of Award

Spring 2024

Project Type

Senior Honors Thesis

College or School




Program or Major

Legal & Political Philosophy

Degree Name

Bachelor of Arts

First Advisor

Nicholas Smith


In this paper, I explore some of the ways in which artificial intelligence might enhance the sentencing process through recidivism prediction technology. Notably, this technology can increase the accuracy of risk predictions and the speed with which sentencing decisions are reached. I then show, however, that the recidivism prediction technology is likely to turn into what data scientist Cathy O’Neil calls a Weapon of Math Destruction. The potential harmfulness of this technology is due not to the inherent nature of the technology, but the symbiotic relationship it will have with our already harmful criminal justice system. I argue that the objective of implementing this technology is increased cost-effectiveness. It is against this metric that we will evaluate the technology’s success. Thus, if the technology makes our criminal justice system far more cost-effective—even if it proves to greatly increase harms done to society by the criminal justice system—we would be unlikely to substantially change our system once we have implemented it. Because of this, I argue that we ought to remove AI from our courtrooms now.