The Black Box Problem in Administering Justice: Risks of Opaque Algorithms in Legal Decision-Making
Abstract
As artificial intelligence (AI) technologies become integrated into judicial systems globally, the “black box problem” has emerged as a critical concern. This term refers to the opacity of machine learning algorithms, where the internal reasoning behind outputs is not transparent to users. This paper explores the implications of the black box problem in the administration of justice, focusing on how opaque algorithmic systems may undermine fairness, accountability, and trust in judicial processes. Drawing from global case studies, expert interviews, and legal theory, the study identifies key risks and proposes safeguards for transparent and ethical AI deployment in courts. The findings highlight the tension between technological efficiency and fundamental legal principles, suggesting that explainable AI must be prioritized to preserve judicial integrity and public confidence in legal institutions.