Artificial Intelligence and the Future of Legal Accountability

The rapid integration of Artificial Intelligence into governance, commerce, and everyday life has introduced profound legal challenges, particularly in the realm of accountability. As AI systems increasingly perform tasks that were once exclusively within human control—ranging from decision-making in public administration to predictive analytics in criminal justice—the limitations of traditional legal frameworks have become more evident. These frameworks, historically grounded in notions of human agency, intent, and fault, are ill-equipped to address the complexities posed by autonomous and semi-autonomous technologies that operate with limited human intervention. One of the central concerns lies in the attribution of responsibility when AI systems produce harmful or unintended outcomes. The diffusion of accountability among developers, deployers, and users creates significant legal ambiguity, often referred to as the “accountability gap.” This challenge is further compounded by the opaque nature of algorithmic decision-making, which undermines principles such as transparency, causation, and foreseeability. This article examines the evolving concept of legal accountability in the age of AI by critically analyzing existing liability regimes, emerging regulatory approaches, and the growing role of ethical frameworks in shaping legal responses. It highlights comparative developments across jurisdictions and underscores the need for adaptive legal mechanisms. Ultimately, it argues for a hybrid legal framework that combines traditional doctrines with innovative regulatory tools—such as explainability requirements, shared liability models, and risk-based governance—to effectively address the multifaceted challenges of AI-driven decision-making while ensuring justice, fairness, and public trust.