Restructuring Tort and Contract Law in the Era of Autonomous Decision Infrastructures

Abstract

The rise of autonomous decision infrastructures introduces profound challenges to traditional tort and contract law. As artificial intelligence systems increasingly execute actions independently of human oversight, long-standing doctrines based on human intent, foreseeability, and voluntariness face fundamental limitations. These systems generate decisions that are often opaque, probabilistic, and influenced by dynamic learning processes, making classical legal attributions of fault insufficient. This paper explores how tort and contract law must adapt to account for machine-driven agency, distributed accountability, and algorithmic unpredictability. It evaluates the shortcomings of existing doctrines and proposes conceptual pathways for reconfiguring liability, consent, and enforceability in environments where autonomous systems mediate or even independently determine outcomes. Ultimately, the study argues for a hybrid legal model capable of addressing emerging risks without undermining established legal protections.