Abstract

The proliferation of autonomous systems across critical domains—such as transportation, healthcare, finance, and defense—poses unprecedented legal and ethical challenges, particularly in assigning liability for harm. These systems, capable of independent decision-making, disrupt traditional legal doctrines built on human intent and foreseeability. This paper critically examines the inadequacies of current legal frameworks—civil, tortious, and criminal—in addressing the complex liability questions raised by autonomous technologies. Key concerns include fault attribution in ethically ambiguous scenarios, such as self-driving car accidents, algorithmic trading disruptions, and AI-driven misinformation. Through real-world examples, including the role of Facebook’s algorithm in the Myanmar crisis, the paper illustrates the growing societal impact of unregulated autonomy. Comparative analysis of regulatory approaches in the European Union, Canada, Singapore, and India highlights varied strategies in adapting to these challenges, from strict liability models to soft law frameworks. The paper evaluates controversial proposals like AI personhood and recommends a hybrid model of legal accountability—combining strict liability, fault-based principles, and mandatory insurance—to reconcile innovation with justice. It also advocates for transparency mandates and judicial mechanisms to lift the “technological veil” shielding human responsibility. The study concludes that legal systems must evolve to maintain public trust and uphold moral and legal accountability in the face of rapidly advancing autonomous technologies. Without such reforms, victims may remain uncompensated, and societal harms may proliferate unchecked.

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