Three Liability Regimes for Artificial Intelligence: Algorithmic Actants, Hybrids, Crowds

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). It develops a threefold typology of machine behavior and specifies the socio-digital institutions related to this typology, identifying the social risks that emerge when algorithms operate within these institutions. The book demonstrates that the law needs to respond to these specific risks by recognizing personified algorithms as vicarious agents, human-machine associations as collective enterprises, and interconnected systems as risk pools, and developing corresponding liability rules.

Format: Hardback
Length: 208 pages
Publication date: 27 January 2022
Publisher: Bloomsbury Publishing PLC

This book presents three liability regimes to address the significant responsibility gaps arising from AI systems. Firstly, it introduces the concept of vicarious liability for autonomous software agents (actants), holding them accountable for their actions. Secondly, it proposes enterprise liability for inseparable human-AI interactions (hybrids), recognizing the responsibilities of organizations in managing these interactions. Lastly, it suggests collective fund liability for interconnected AI systems (crowds), acknowledging the collective risks associated with these systems.

Drawing from information technology studies, the book develops a comprehensive typology that distinguishes between individual, hybrid, and collective machine behavior. This typology serves as a foundation for the subsequent social science analysis, which identifies the socio-digital institutions associated with each behavior type. By examining these institutions, the book identifies the social risks that emerge when algorithms operate within these contexts. Actants, for instance, pose the risk of digital autonomy, hybrids the risk of double contingency in human-algorithm encounters, and crowds the risk of opaque interconnections.

Recognizing the unique challenges posed by these risks, the book advocates for a responsive legal framework. It proposes recognizing personified algorithms as vicarious agents, human-machine associations as collective enterprises, and interconnected systems as risk pools. Accordingly, it develops corresponding liability rules to address these specific risks.

This book's approach is distinctive in its combination of information technology studies, sociological institution analysis, and risk analysis. By integrating these disciplines, it uncovers recursive relations between different types of machine behavior, emergent socio-digital institutions, their associated risks, legal conditions for liability rules, and the ascription of legal status to the algorithms involved. This holistic approach provides a comprehensive framework for understanding and addressing the liability challenges posed by AI systems.

In conclusion, this book offers valuable insights into the liability regimes needed to address the growing responsibility gaps associated with AI systems. By proposing innovative liability frameworks and analyzing the interrelationships between machine behavior, socio-digital institutions, and legal conditions, it contributes to the development of a more robust and accountable AI ecosystem.

Weight: 458g
Dimension: 208 x 381 x 19 (mm)
ISBN-13: 9781509949335