Locating fault and responsibility for AI harms: A systems theory of foreseeability, reasonable care and causal responsibility in the AI value chain

Published: 21 Mar 2025, Last Modified: 15 Jan 2026Law, Innovation and TechnologyEveryoneCC BY 4.0
Abstract: This paper presents an original perspective on fault for harms caused by artificial intelligence (AI) systems. Scholarship on liability for AI harms highlights the difficulties that doctrines like negligence may encounter in attributing responsibility across complex AI value chains. Drawing on the theory of ‘system safety’, this paper argues that these difficulties can be diminished by conceptualising AI hazards as a set of socio-technical conditions (including system affordances, use context, and organisational arrangements) rather than specific aberrant outputs (‘errors’) with discrete technical causes. Animated by case studies of AI harms and near misses, the paper clarifies what is ‘reasonably foreseeable’ about AI harms, and to which value chain participants. It also identifies various kinds of ‘reasonable care’ that different actors can exercise to avert harm. This socio-technical perspective makes it easier to apply concepts that are vital not only to negligence, but to wider discussions about responsibility for AI risks.
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