Ensuring AI Accountability in Judicial Proceedings: An Actor–Network Theory Perspective

Аннотация

Artificial Intelligence (AI) is increasingly being incorporated into judicial proceedings, from predictive algorithms for sentencing and risk assessment to AI-powered tools for case management. As AI continues to shape the legal landscape, questions regarding accountability in judicial proceedings become more pressing. This paper adopts an Actor–Network Theory (ANT) framework to explore the roles played by human and non-human actors— such as judges, lawyers, AI systems, and legal institutions—in establishing accountability in AI-driven legal processes. Through this lens, we examine the dynamics between these actors and the implications of AI’s role in legal decision-making. The study identifies key challenges surrounding AI accountability in judicial proceedings, highlighting the need for transparent and responsible AI development, while proposing pathways for integrating AI tools ethically and equitably into judicial processes. Keywords: AI Accountability, Judicial Proceedings, Actor–Network Theory, Legal Technology, Court Systems, AI Systems, Law and Technology, Ethics in AI, Legal Decision-Making, AI Transparency. factors. First, many AI algorithms used in the legal Introduction: The increasing adoption of Artificial system, such as those employed for risk assessments Intelligence (AI) in judicial proceedings has triggered a and predictive sentencing, are often described as significant shift in how legal decisions are made and "black boxes"—complex systems where the rationale how justice is administered. From predictive algorithms behind a given decision is not easily understood or used in sentencing to AI-driven tools for case accessible, even to those who use them. This opacity management and legal research, AI promises to challenges the principles of transparency and fairness, enhance the efficiency and accuracy of judicial systems two foundational elements of justice. When an AI worldwide. These technologies have the potential to system outputs a recommendation or decision, the reduce human biases, accelerate the adjudication individuals affected by that decision, as well as the legal process, and assist in complex decision-making tasks by professionals involved, may be unable to discern why analyzing vast amounts of data quickly and effectively. the system arrived at a particular conclusion. This lack However, as AI systems become more integrated into of transparency creates difficulties in holding AI legal processes, they also raise fundamental questions systems accountable for their outputs. about accountability. Accountability in judicial Second, AI systems in judicial settings often rely on proceedings refers to the responsibility and liability for historical data to inform their predictions. This raises actions and decisions made within the legal process. the possibility of bias in AI systems, particularly if the When AI systems play a central role in shaping data used to train these systems reflect existing social decisions, it becomes unclear who should be held or systemic inequalities. For example, in the case of accountable when an AI-driven decision leads to an predictive policing algorithms, the data might be unjust or incorrect outcome. This dilemma is especially skewed by historical biases in police practices, leading important in the context of AI’s involvement in areas AI systems to disproportionately target marginalized such as sentencing, parole decisions, risk assessments, communities. Similarly, sentencing algorithms might and predictive policing. perpetuate racial or socio-economic disparities if they AI accountability concerns are compounded by several are trained on biased historical data. Such biases in AI International Journal of Law And Criminology 1 https://theusajournals.com/index.php/ijlc International Journal of Law And Criminology (ISSN: 2771-2214) decision-making can undermine the fairness of judicial paper. processes and potentially exacerbate existing Ultimately, the goal of this research is to contribute to inequalities. the development of responsible, ethical frameworks Given these challenges, it is essential to examine the for the use of AI in judicial proceedings. As AI concept of AI accountability through a more nuanced technologies continue to advance, ensuring lens. Traditional accountability frameworks in the legal accountability will be critical to maintaining public trust system focus on human actors—judges, lawyers, and in the judicial system and ensuring that technology legal institutions—and their responsibility for ensuring serves justice rather than undermining it. just outcomes. However, AI systems complicate this The integration of Artificial Intelligence (AI) into judicial framework because they introduce non-human actors proceedings is transforming how legal decisions are into the decision-making process. As AI systems made, and it is raising significant concerns about become more autonomous and pervasive in legal accountability, fairness, and tran