Publication Type
Journal Article
Version
publishedVersion
Publication Date
2-2023
Abstract
It is conventionally argued that because an artificially-intelligent (AI) system acts autonomously, its makers cannot easily be held liable should the system's actions harm. Since the system cannot be liable on its own account either, existing laws expose victims to accountability gaps and need to be reformed. Recent legal instruments have nonetheless established obligations against AI developers and providers. Drawing on attribution theory, this paper examines how these seemingly opposing positions are shaped by the ways in which AI systems are conceptualised. Specifically, folk dispositionism underpins conventional legal discourse on AI liability, personality, publications, and inventions and leads us towards problematic legal outcomes. Examining the technology and terminology driving contemporary AI systems, the paper contends that AI systems are better conceptualised instead as situational characters whose actions remain constrained by their programming. Properly viewing AI systems as such illuminates how existing legal doctrines could be sensibly applied to AI and reinforces emerging calls for placing greater scrutiny on the broader AI ecosystem.
Keywords
artificial intelligence, autonomous systems, attribution theory, law and technology, law and psychology
Discipline
Artificial Intelligence and Robotics | Public Law and Legal Theory | Science and Technology Law
Research Areas
Innovation, Technology and the Law
Publication
Legal Studies
Volume
43
Issue
4
First Page
583
Last Page
602
ISSN
0261-3875
Identifier
10.1017/lst.2022.52
Publisher
Cambridge University Press
Citation
SOH, Jerrold.
Legal dispositionism and artificially-intelligent attributions. (2023). Legal Studies. 43, (4), 583-602.
Available at: https://ink.library.smu.edu.sg/sol_research/4136
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional URL
https://doi.org/10.1017/lst.2022.52
Included in
Artificial Intelligence and Robotics Commons, Public Law and Legal Theory Commons, Science and Technology Law Commons