In today’s world, the criminal justice system faces numerous challenges, such as bias, inefficiency, and high rates of recidivism. These issues disproportionately affect the Black community, creating a cycle of injustice and inequality, and we must address this issue if we are to move forward as a society. AI, if used correctly, could potentially be a solution to some of the problems that we seek to solve. 

 AI can play a critical role in identifying and mitigating biases. By analyzing mass amounts of historical data, AI tools can recognize patterns in policing and sentencing. AI algorithms can detect racial discrepancies in arrest rates and sentencing lengths, providing insights to facilitate policy change.

For example, In New York, an AI-driven initiative was launched to address the underlying racial biases within the stop-and-frisk program (refers to the brief, non-intrusive police stop of a suspect). The AI analyzed thousands of records from the program, which showed the disproportionate targeting of Black and Latino individuals. These findings were pivotal in advocating for policy reforms, which spurred a significant reduction in the use of these tactics.

AI could also prove helpful in rehabilitation efforts and the reduction of recidivism. If given a file, AI can develop personalized rehabilitation programs tailored to the specific needs of offenders. For example, AI tools can identify and assess an individual’s risk factors and recommend targeted interventions, such as counseling or job training programs. This could be very useful for organizations such as Homeboy Industries, which works with former offenders by offering services to help them get back on their feet.

Moreover, AI can monitor individuals on parole or probation, providing real-time support and reducing the likelihood of reoffending. AI systems can analyze data from electronic monitoring devices, social media activity, and other sources to identify early warning signs of potential violations or criminal activity. This could allow parole officers to intervene proactively before the situation could potentially escalate. 

Programs that use AI to predict recidivism rates have shown promising results. In Pennsylvania, the State’s Department of Corrections implemented an AI-based system to evaluate the risk of recidivism among parolees. It used data such as criminal history, behavior during incarceration, and social factors to generate risk scores. These scores were then used to make informed decisions about parole supervision levels and intervention strategies resulting in a reduction of recidivism rates.

However, it can have the opposite effect of lessening these issues if not utilized appropriately. Specifically, Predictive Policing involves using AI algorithms to forecast crime hotspots, allowing law enforcement to allocate resources more effectively. While this could enhance public safety, It could also reinforce existing biases and result in over-policing these “crime hotspot” areas, especially if these algorithms are trained on already biased historical data. 

AI can be utilized for so much good, but that is only if we train it to do so. As time passes, these algorithms will get more and more advanced. It is our job to see that they not only create a more equitable justice system but a more equitable society in general.