This book provides a novel framework for adapting tort law to the challenges of artificial intelligence (AI) in all of its forms—from machine learning to generative models to autonomous and agentic systems.Centered on a liability matrix, this book maps AI systems into four zones according to their private and public risks and benefits, and it prescribes tailored liability mechanisms for each. These range from flexible, fault-based models with safe harbors for low-risk, high-benefit technologies, to strict liability, rebuttable presumptions of causation and even moratoriums for systems that pose grave public dangers without delivering corresponding public value. Combining rigorous doctrinal analysis with practical policy tools, the book addresses complex issues such as fault attribution, causation, compensable harm, evidentiary burdens and distributed responsibility.Clear, concise and globally relevant, this book provides an adaptable approach that courts, policy makers and industry leaders can apply to real-world AI governance. It will appeal to legal scholars, postgraduate students, regulators, judges and AI governance specialists seeking to understand—and shape—how tort law can both protect society and enable responsible innovation in the age of AI.
Juan Diaz-Granados is a senior lecturer at the Australian Catholic University. His research examines the legal implications of emerging technologies, and his publications include a book on the sharing economy and numerous articles in leading national and international law journals.
PrefaceAcknowledgementsCHAPTER 1: INTRODUCTION TO AI AND TORT LIABILITY CHAPTER 2: ARTIFICIAL INTELLIGENCE – PRELIMINARY NOTES A. The Historical Development of AIB. Conceptual Framework C. Taxonomy of AI CHAPTER 3: CHALLENGING FEATURES OF AI SYSTEMS A. Complexity of AI Architecture B. Duality of AI SystemsC. AI Plutocracy D. AI International and Supranational Impact CHAPTER 4: DOCTRINAL ISSUES OF TORT LAW IN AI A. Fault and Foreseeability B. Complex Causation C. Damage and Compensable Harm D. Emerging AI-Specific Risks E. Evidentiary Issues F. Distributed Liability CHAPTER 5: THEORETICAL FRAMEWORK FOR AI TORT LIABILITY A. Tort Liability and Theory B. Theoretical Dualism for AI Tort Liability CHAPTER 6: DYNAMIC FRAMEWORK OF AI TORT LIABILITY A. Green Zone B. Yellow Zone C. Orange Zone D. Red Zone CHAPTER 7: CONCLUSION
Matthias C. Kettemann, Alexander Peukert, Indra Spiecker gen. Döhmann, Austria) C. Kettemann, Matthias (University of Graz, Indra Spiecker gen. Dohmann