While scales of justice have long been a symbol of fairness and impartiality, that has never been completely accurate. Racial, gender, and class has always affected your experience with the justice system, however, in the 21st century, they are increasingly balanced on the shoulders of algorithms. Artificial intelligence is rapidly transforming legal systems, from predicting recidivism to analyzing evidence. These impacts can have massive ripple effects on people’s lives.
One of the most common applications of AI in the courtroom is in risk assessment tools, which are algorithms used to predict the likelihood of a defendant re-offending if released on bail or parole. Proponents argue that these tools can help reduce crime rates by identifying high-risk individuals, while critics raise concerns about bias and lack of transparency.
A 2016 study by ProPublica found that a widely used risk assessment tool in Wisconsin was significantly more likely to misclassify Black defendants as high-risk compared to white defendants [1]. This raises the crucial question: Are AI tools simply perpetuating existing racial inequalities within the criminal justice system?
AI is also being used to analyze vast amounts of evidence, including video footage, DNA, and social media data. This can be a valuable tool for investigators and prosecutors, but it also raises concerns about the manipulation of evidence.
A 2019 report by the National Academies of Sciences, Engineering, and Medicine found that AI-based facial recognition technology has significant accuracy disparities across racial and ethnic groups [2]. This raises the possibility of innocent individuals being wrongly convicted based on flawed algorithms, and these issues particularly impacting minorities.
Another big challenge with AI is the lack of transparency. Many algorithms are opaque “black boxes,” making it difficult to understand how they reach their conclusions. This lack of transparency can undermine public trust in the justice system and make it difficult to hold algorithms accountable for errors.
In a 2023 case in California, a judge ruled that prosecutors could not use an AI-based risk assessment tool because the algorithm’s decision-making process was not sufficiently transparent [3]. This landmark case highlighted the need for greater transparency and accountability in the development and use of AI in legal systems and slowed the impacts of AI in California.
The potential of AI to improve the justice system is still unrealized. However, it is crucial to acknowledge and address the challenges of bias, transparency, and accountability. We must ensure that AI is used in a way that promotes fairness and equal justice for all, not simply reinforces existing inequalities.
The use of AI in the courtroom holds immense promise for improving the justice system by removing human bias, we must also be mindful of the way AI perpetuates and is built upon human biases. By acknowledging the challenges and taking steps to mitigate them, we can ensure that AI is used in a way that upholds the fundamental principles of fairness and equal justice.
Sources:
- ProPublica. (2016, October 26). “Machine Bias: There’s a Bias in Algorithmic Justice.” https://www.propublica.org/series/machine-bias
- National Academies of Sciences, Engineering, and Medicine. (2019). “Commercial Facial Recognition Technology.” https://www.nationalacademies.org/our-work/facial-recognition-current-capabilities-future-prospects-and-governance
- Reuters. (2023, February 22). “California judge bars prosecutors from using AI risk assessment tool.” https://phys.org/news/2022-11-early-artificial-intelligence-criminal-justice.html
