Understanding AI liability requires fluency in three distinct vocabularies: artificial intelligence technology, legal doctrine, and regulatory frameworks. This glossary provides clear definitions of essential terms across all three domains, with cross-references and practical examples to illuminate how these concepts interact in real-world AI liability scenarios.
Introduction: The Fragmented AI Regulatory Landscape # The United States has no single AI regulatory agency. Instead, AI oversight is fragmented across dozens of federal agencies, each applying its existing statutory authority to AI systems within its jurisdiction. The Federal Trade Commission addresses AI in consumer protection and competition. The Food and Drug Administration regulates AI medical devices. The Equal Employment Opportunity Commission enforces civil rights laws against discriminatory AI. The Consumer Financial Protection Bureau oversees AI in financial services.
The Doctrine That Changes Everything # When an AI system violates a federal or state statute designed to protect a class of persons, injured plaintiffs may not need to prove that the defendant breached the standard of care. Under the doctrine of negligence per se, the statutory violation itself establishes negligence, transforming regulatory non-compliance into a powerful litigation weapon.
Liability Allocation # Who is liable when AI makes a mistake, the user, deployer, or vendor? # The short answer: it depends on the circumstances, but deployers typically bear primary responsibility.