AI in Parole Decisions: Just or Unjust?
Caiden Cellak is a History, Law, and Society major, graduating in Spring 2027. She grew up in Chicago, Illinois, USA.
Artificial Intelligence (AI) has rapidly become an important tool in various industries, promising efficiency, consistency, and a reduction in human error. However, its application within the legal system brings to light profound ethical implications, particularly when it comes to accountability, fairness, and the avoidance of bias. These concepts are foundational to any legal system, as they ensure justice is not only done but seen to be done. In the context of parole decisions, where an individual’s freedom is at stake, fairness and impartiality are crucial. Imagine a world where an algorithm determines the fate of individuals seeking parole—where justice is influenced not by human discernment but by data-driven predictions. While some argue that AI can act as an unbiased mediator, there is substantial evidence suggesting the opposite. This paper delves into the ethical complexities of integrating AI into parole decisions, exploring how biased data and lack of accountability can reinforce systemic inequalities in our legal system.
AI has become a pivotal player across various industries, as seen in its integration into the legal field. AI systems perform tasks that typically require human intelligence, such as decision-making and learning. Its advanced technology allows it to provide efficiency in multiple sectors. For example, AI is used to diagnose illnesses in healthcare, detect fraud in finance, and assist in parole decisions and risk assessments within the legal field. While AI aims to reduce human bias, it can instead do the opposite by reinforcing existing inequities. As Gary Bernstein of CloudTweaks notes, “Proponents argue that these tools can help eliminate human biases and create more consistent legal outcomes. However, there is mounting evidence that these systems can perpetuate or even exacerbate existing biases, leading to unjust outcomes.” (CloudTweaks) These ethical dilemmas that arise with AI are significant, especially as its influence spreads across powerful industries controlling various aspects of economies, healthcare systems, justice systems, and more. The convenience of AI can sometimes overshadow its issues, especially when used to determine an individual’s freedom, a fundamental human right. Scrutiny is essential to eliminate any potential flaws.
One stark example of AI integration into the legal system is pre-trial detention, where ingrained biases prevail. Pre-trial detention refers to the detainment of an accused individual awaiting trial. Judges decide whether the accused may post bail or remain detained based on their potential risk to the community and likelihood of appearing at trial (Fair Trials). To expedite this decision-making, AI has been employed: “AI’s role in bail decisions is particularly contentious. In many jurisdictions, judges use risk assessment algorithms to determine whether a defendant should be released before trial.”(CloudTweaks) In using a “non-biased” algorithm to determine bail the hope is to terminate human biases. However, despite efforts to avoid racial bias by excluding race as a factor, the underlying data in AI often introduces biases, resulting in skewed outcomes. This highlights a deeper issue: human biases are so deeply embedded that they persist even in advanced algorithmic systems which are supposed to be mitigating this problem.
In the case of Mobley v. Workday, Inc., AI algorithms used in employment decisions were found to discriminate against certain groups. Similarly, the Equal Employment Opportunity Commission’s (EEOC) lawsuit against iTutorGroup highlighted how AI systems can perpetuate biases in hiring practices (Attorneys.Media). The use of AI for efficiency should never come at the expense of individual freedom. If the legal system becomes too dependent on automation without proper oversight, it could greatly weaken the social contract - the foundation of societal cohesion and governance. The social contract is built on the idea that people consent to be governed by human institutions that uphold justice and fairness. However, when AI starts making critical legal decisions, it removes the human element that is essential to this agreement. Instead of laws being enforced by individuals who understand social complexities, decisions are left to an unaccountable machine, distancing people from the justice system. This shift could erode trust in legal institutions, as people may feel they are being judged by an emotionless algorithm rather than by fellow citizens who recognize their humanity. If individuals no longer see the legal system as a fair and just entity created by and for the people, the very principles that hold society together could begin to break down.
Moreover, this reinforcement of systemic inequalities is alarming. Biased data can lead to unfair decisions that disproportionately affect marginalized communities. For instance, in predictive policing, AI tools often predict higher crime rates in areas with historically high arrest rates, which are frequently minority neighborhoods. This can lead to increased police presence and a cycle of over-policing and arrests in these communities, exacerbating existing inequalities rather than alleviating them (Heaven). As mentioned before, risk assessment algorithms used in courts can perpetuate biases present in historical data, affecting parole decisions and sentencing. If these algorithms are not carefully monitored and audited for fairness, they can undermine efforts toward an equitable justice system.
Accountability is another major concern when integrating AI into the legal system. Traditional decision-making processes involve human judges who can be held accountable for their judgments. However, when AI systems are used, it becomes challenging to pinpoint responsibility when biases or errors occur. This lack of accountability can lead to mistrust and resistance towards AI in legal settings. Ensuring transparency in AI decision-making is crucial to maintaining public trust and accountability. Clear guidelines and monitoring protocols are necessary to ensure these systems operate fairly and justly. Without this trust, however, skepticism and distrust may grow toward judicial decisions, ultimately undermining the authority of the law. As Aristotle said in the Nicomachean Ethics, "The law is reason, free from passion.”(Chapter 1) However, AI systems bring in their own biases and prejudices, which can lead to unjust outcomes. These biases are not always evident and can be deeply ingrained within the data used to train AI algorithms. When these systems are deployed without proper oversight, the consequences can be severe, impacting the lives of individuals who are already marginalized within society.
For example, researchers at Georgetown Law School found that an estimated 117 million American adults are in facial recognition networks used by law enforcement, and that African Americans were more likely to be singled out primarily because of their over-representation in mug-shot databases(Lee, et al.). This highlights the systemic issues within law enforcement practices that are further exemplified by AI systems.
Historical context is vital in understanding the depth of AI's impact on parole decisions. Historically marginalized communities have faced systemic biases within the legal system for decades. The introduction of AI, rather than alleviating these biases, often compounds them by embedding historical prejudices within data-driven algorithms. This historical perpetuation of inequality is a significant concern, as it reinforces discriminatory practices that have long been criticized. The whole of society, especially in recent years, has woken up to the reality of ingrained prejudice within large institutions governing nations. Due to this awakening, an increasing number of people have been demanding systemic equality and reform, leading to genuine change. However, with the integration of AI into the legal system, society could reverse progress made in addressing systemic biases if these systems are not properly monitored and evaluated.
Possible solutions to the problems posed by AI in the legal system include incorporating more diverse and representative data sets into AI systems and providing education and training for those who implement and interact with these systems. Additionally, involving experts from various fields—including ethicists, sociologists, and legal professionals—in the development and oversight of AI systems can help identify and address potential biases. Judges, parole officers, and other legal professionals must be adequately trained to identify and prevent biased AI decisions from influencing legal outcomes. This knowledge can empower them to critically assess AI recommendations and make more informed decisions that uphold the core ideas of law: justice and fairness.
Adding on, the role of public engagement and societal discourse in shaping AI policies cannot be understated. Engaging the public in conversations about the implications of AI in legal contexts can foster greater understanding and trust which will allow for a continual upholding of the legal system and social cohesion. Public input can provide valuable insights into societal values and expectations, which should be reflected in the development and implementation of AI systems to ensure the legal system reflects the needs and perspectives of the people it serves. Allowing the public to have a say can build confidence within communities, giving them a platform to voice their concerns on issues that impact them and their loved ones daily. In general, when making changes to the legal system, one of grave importance to the lives of those under it, public opinion should always be taken into consideration to have a system that accurately reflects those it governs.
The European Union recently released “Ethics Guidelines for Trustworthy AI,” which delineates seven governance principles: (1) human agency and oversight, (2) technical robustness and safety, (3) privacy and data governance, (4) transparency, (5) diversity, nondiscrimination, and fairness, (6) environmental and societal well-being, and (7) accountability (European Commission). These principles aim to guide the development and deployment of AI systems to ensure they are used ethically and responsibly. Adhering to these guidelines can help mitigate some of the ethical concerns associated with AI in legal decisions.
In conclusion, while AI has the potential to transform the legal system by providing consistent and efficient decision-making, it also poses significant ethical challenges. The biases present in the data used to train AI algorithms can perpetuate systemic inequalities, leading to unjust outcomes. Furthermore, the lack of accountability and transparency in AI decision-making processes can erode public trust in these technologies. To ensure that AI is used ethically and equitably in parole decisions, it is essential to implement strict oversight, monitoring, and governance protocols. By addressing these concerns, we can work towards a legal system that truly upholds justice and fairness for all individuals. Through continued research, collaboration, and vigilance, we can harness the potential of AI to create a more just and equitable society. By incorporating diverse data, promoting transparency, and engaging in interdisciplinary research, we can develop AI systems that support rather than undermine the principles of justice and equality. Through public engagement and the establishment of accountability mechanisms, we can ensure that AI is deployed in a manner that aligns with societal values and ethical standards.
Bibliography
AdminAI. “Ai Bias in the Courtroom: How Judges Address Algorithmic Discrimination Cases.” Attorneys.Media | Legal Issues Explained, January 2, 2025. https://attorneys.media/courts-addressing-ai-discrimination-cases/.
Artificial Intelligence in Legal Practice. Accessed February 17, 2025. https://www.dri.org/docs/default-source/dri-white-papers-and-reports/ai-legal-practice.pdf.
Aristotle, Nicomachean Ethics, Book VI, Chapter 1.
Athuraliya, Amanda. “Understanding AI in Decision-Making: What It Is, Benefits, and Practical Examples.” Creately, November 12, 2024. https://creately.com/guides/ai-in-decision-making/
Engler, Alex, Aaron Roth Michael Kearns, Solon Barocas Manish Raghavan, Jonathan Rauch, Kent E. Calder, Joshua Rovner, Tanvi Madan, Carlos Rodríguez-Castelán Luis Felipe López-Calva, and Jude Blanchette Ryan Hass. “Algorithmic Bias Detection and Mitigation: Best Practices and Policies to Reduce Consumer Harms.” Brookings, June 27, 2023. https://www.brookings.edu/articles/algorithmic-bias-detection-and-mitigation-best-practices-and-policies-to-reduce-consumer-harms/.
“Ethical Ai in Law Enforcement: Navigating the Balance between Innovation and Responsibility.” Police1, December 5, 2024. https://www.police1.com/investigations/ethical-ai-in-law-enforcement-navigating-the-balance-between-innovation-and-responsibility.
Gallo, Ryan Roth, and Amber. “Algorithms Were Supposed to Reduce Bias in Criminal Justice- Do They?” Boston University, February 23, 2023. https://www.bu.edu/articles/2023/do-algorithms-reduce-bias-in-criminal-justice/.
Heaven, Will Douglas. “Predictive Policing Algorithms Are Racist. They Need to Be Dismantled.” MIT Technology Review, June 21, 2023. https://www.technologyreview.com/2020/07/17/1005396/predictive-policing-algorithm-racist-dismantled-machine-learning-bias-criminal-justice/.
High-Level Expert Group on Artificial Intelligence. Ethics Guidelines for Trustworthy AI. European Commission, 2019.
Lee, N., Resnick, P. & Barton, G., 2019. Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms, Brookings Institution. United States of America. Retrieved from https://coilink.org/20.500.12592/k29pdg on 17 Feb 2025. COI: 20.500.12592/k29pdg.
“Pre-Trial Detention.” Fair Trials, May 8, 2024. https://www.fairtrials.org/campaigns/pre-trial-detention/.
“The Ethics of AI Decision-Making in the Criminal Justice System.” CloudTweaks, October 31, 2024. https://cloudtweaks.com/2024/09/ethics-ai-criminal-justice-system/.
Image Credits:
https://www.njordlaw.com/artificial-intelligence-part-court-proceedings-it-possible-and-necessary
