Liabilities And Modern Artificial Intelligence


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Liabilities and Modern Artificial Intelligence


Liabilities and Modern Artificial Intelligence

Author: Estelle Wallingford

language: en

Publisher: Taylor & Francis

Release Date: 2025-09-09


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This book addresses how private law liability should be assigned in contexts where modern forms of AI are deployed. AI as a technology holds the potential to radically improve global society, yet the pace of its advancement far outstrips the pace at which legal systems are responding. This book explores legal approaches to AI, how AI should be legally characterised, and proposes an overarching theoretical liability framework termed the Tri-Phase AI Liability Model. This framework is flexible in nature and considers the type of AI, the context in which it is deployed, who has the most control over the AI system and the capacity of a deployed AI. In response, this book brings greatly needed clarity to the evolving landscape of AI governance, aiding in resolving existing and emerging private law challenges. This book is a timely response to the urgent need to resolve private law liabilities and will appeal to legal professionals, policy makers, and scholars looking to understand or contribute to the current and future governance of AI within private law.

Liability for Crimes Involving Artificial Intelligence Systems


Liability for Crimes Involving Artificial Intelligence Systems

Author: Gabriel Hallevy

language: en

Publisher: Springer

Release Date: 2014-11-06


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The book develops a general legal theory concerning the liability for offenses involving artificial intelligence systems. The involvement of the artificial intelligence systems in these offenses may be as perpetrators, accomplices or mere instruments. The general legal theory proposed in this book is based on the current criminal law in most modern legal systems. In most modern countries, unmanned vehicles, sophisticated surgical systems, industrial computing systems, trading algorithms and other artificial intelligence systems are commonly used for both industrial and personal purposes. The question of legal liability arises when something goes wrong, e.g. the unmanned vehicle is involved in a car accident, the surgical system is involved in a surgical error or the trading algorithm is involved in fraud, etc. Who is to be held liable for these offenses: the manufacturer, the programmer, the user, or, perhaps, the artificial intelligence system itself? The concept of liability for crimes involving artificial intelligence systems has not yet been widely researched. Advanced technologies are forcing society to face new challenges, both technical and legal. The idea of liability in the specific context of artificial intelligence systems is one such challenge that should be thoroughly explored.

Three Liability Regimes for Artificial Intelligence


Three Liability Regimes for Artificial Intelligence

Author: Anna Beckers

language: en

Publisher: Bloomsbury Publishing

Release Date: 2021-12-02


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This book proposes three liability regimes to combat the wide responsibility gaps caused by AI systems – vicarious liability for autonomous software agents (actants); enterprise liability for inseparable human-AI interactions (hybrids); and collective fund liability for interconnected AI systems (crowds). Based on information technology studies, the book first develops a threefold typology that distinguishes individual, hybrid and collective machine behaviour. A subsequent social science analysis specifies the socio-digital institutions related to this threefold typology. Then it determines the social risks that emerge when algorithms operate within these institutions. Actants raise the risk of digital autonomy, hybrids the risk of double contingency in human-algorithm encounters, crowds the risk of opaque interconnections. The book demonstrates that the law needs to respond to these specific risks, by recognising personified algorithms as vicarious agents, human-machine associations as collective enterprises, and interconnected systems as risk pools – and by developing corresponding liability rules. The book relies on a unique combination of information technology studies, sociological institution and risk analysis, and comparative law. This approach uncovers recursive relations between types of machine behaviour, emergent socio-digital institutions, their concomitant risks, legal conditions of liability rules, and ascription of legal status to the algorithms involved.