The EU AI Act (Regulation (EU) 2024/1689) is the world’s first comprehensive AI law, and it applies to companies worldwide. If your AI system is used in the European Union, you’re subject to EU jurisdiction regardless of where your headquarters is located. For US companies serving European markets, this creates significant compliance obligations and liability exposure that cannot be ignored.
While federal AI legislation remains in development, US states have moved aggressively to regulate artificial intelligence. From Colorado’s comprehensive AI discrimination law to Illinois’ biometric privacy statute generating hundreds of lawsuits annually, state-level AI regulation creates a complex patchwork of compliance obligations that varies dramatically by jurisdiction, industry, and use case.
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.
AI Liability Legal Timeline A chronological guide to landmark cases, regulations, and developments shaping the legal landscape for AI liability. Key Developments in AI Liability Law # 2018 Epic Sepsis Model Deployed Epic Systems deploys sepsis prediction algorithm to hundreds of hospitals. Later studies will reveal significant performance gaps between clinical validation and real-world deployment, raising questions about hospital liability for algorithm selection. March 2018 Uber AV Fatality - Tempe, AZ First pedestrian fatality involving a fully autonomous vehicle (Uber ATG). Raises fundamental questions about manufacturer vs. operator liability for autonomous systems. Criminal charges filed against safety driver; civil settlements reached. 2019 FDA De Novo Clearance for IDx-DR First FDA clearance for autonomous AI diagnostic device - diabetic retinopathy screening that operates without physician oversight. Establishes precedent for AI systems that can diagnose without human intermediary. 2020 EEOC Begins AI Hiring Investigations Equal Employment Opportunity Commission begins investigating AI-powered hiring tools for potential discrimination under Title VII. Signals increased regulatory scrutiny of employment algorithms. February 2021 Mobley v. Workday Filed Landmark class action alleging Workday’s AI hiring tools discriminate against Black, disabled, and older applicants. First major federal court test of AI hiring discrimination theories. 2022 Illinois BIPA Settlements Surge Biometric Information Privacy Act litigation accelerates, with Facebook ($650M), Google ($100M), and TikTok ($92M) settlements. Establishes significant liability exposure for facial recognition and biometric AI. June 2023 Mata v. Avianca - AI Hallucination Sanctions New York federal judge sanctions attorneys for submitting ChatGPT-generated brief with fabricated case citations. Becomes defining case for attorney competence obligations when using generative AI. November 2023 California State Bar AI Guidance California becomes first state bar to issue practical guidance on attorney AI use, addressing competence, confidentiality, and verification duties. Sets template for other jurisdictions. January 2024 Florida Ethics Opinion 24-1 Florida Bar issues comprehensive ethics opinion on AI, emphasizing verification requirements and establishing “reasonable attorney” standard for AI tool competence. April 2024 New York State Bar AI Report NYSBA Task Force releases comprehensive report suggesting that refusing to use AI may itself raise competence concerns in some circumstances - a significant shift in the standard of care discussion. July 2024 ABA Formal Opinion 512 American Bar Association issues national guidance on AI in legal practice, establishing baseline ethical obligations applicable across all jurisdictions. August 2024 EU AI Act Enters Force European Union’s comprehensive AI regulation takes effect, with extraterritorial reach affecting US companies. Establishes risk-based framework and mandatory requirements for high-risk AI systems. February 2025 Texas Ethics Opinion 705 Texas State Bar joins states with formal AI ethics guidance, emphasizing practical verification workflows and client disclosure requirements. Emerging Trends # The “Failure to Use AI” Question # Perhaps the most significant emerging question: When does failure to use available AI tools constitute malpractice? The NYSBA’s suggestion that AI refusal may raise competence concerns signals a potential inversion of traditional liability analysis.
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.
Introduction: Why AI Contracts Are Different # Artificial intelligence systems challenge traditional contract frameworks in fundamental ways. A standard software license assumes the software will behave predictably and consistently, the same inputs will produce the same outputs. AI systems, by contrast, may behave unpredictably, evolve over time, produce different results from identical inputs, and cause harms that neither party anticipated.
Introduction: Discovery in the Age of AI # Discovery in AI litigation presents challenges unlike any the legal system has previously faced. Traditional e-discovery concerns, email preservation, document production, metadata integrity, seem quaint compared to the complexities of preserving a machine learning model, obtaining training data that may encompass billions of data points, or compelling production of algorithms that companies claim as their most valuable trade secrets.
Introduction: The Critical Role of AI Experts # As artificial intelligence systems proliferate across industries, from healthcare diagnostics to autonomous vehicles to financial underwriting, litigation involving AI has exploded. In virtually every AI-related case, expert testimony is not just helpful but essential. Judges and juries lack the technical background to evaluate whether an AI system was properly designed, tested, deployed, or monitored. Expert witnesses bridge that knowledge gap.
The Doctrine That Once Shielded Medical Manufacturers # For decades, the learned intermediary doctrine provided pharmaceutical and medical device manufacturers with a powerful liability shield. The principle was elegant: manufacturers need not warn patients directly because physicians, as “learned intermediaries”, stand between manufacturer and patient. Warn the doctor adequately, and the duty to warn is satisfied.
The Doctrine That Solves AI’s Black Box Problem # Artificial intelligence systems are often described as “black boxes”, systems where inputs go in and outputs emerge, but the internal reasoning remains opaque even to their creators. This opacity creates a fundamental litigation problem: how can an injured plaintiff prove what went wrong inside a system that nobody can fully explain?
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.
When AI Systems Fail # Every organization deploying AI will eventually face an AI incident. It’s not a question of if, but when. The difference between a manageable incident and an existential crisis often comes down to preparation and response.