Towards a Control-Centric Account of Tort Liability for Automated Vehicles

(2021) 26 Torts Law Journal 221-243

34 Pages Posted: 5 Dec 2020 Last revised: 26 Apr 2021

See all articles by Jerrold Soh

Jerrold Soh

Singapore Management University School of Law; Singapore Management University - Centre for AI & Data Governance

Date Written: November 20, 2020

Abstract

Existing motor vehicle accident laws are generally described as ‘driver-centric’, since regulatory, liability, and insurance obligations revolve around drivers. This is sometimes taken to imply that they cannot apply to automated vehicles. This article seeks to re-centre the liability discussion around the tortious doctrine of control. It argues centrally that properly understanding legal control as influence over metaphysical risks, rather than physical objects, clarifies that automated vehicles are both legally controllable in theory, despite having no human drivers, and legally controlled in practice, despite their reliance on machine learning. Examining today’s automated driving technology and businesses, this article demonstrates how manufacturers, software developers, fleet operators, and consumers participate in vehicular risk creation. Finally, how control could illuminate courts’ analyses of automated vehicle liability is illustrated by a hypothetical application to recent automated vehicle accidents. In this light, this article concludes that existing tort principles are better-equipped to resolve liability issues arising from the use of automated vehicles than initially apparent.

Keywords: tort law, law and technology, automated vehicles

JEL Classification: K13

Suggested Citation

Soh, Jerrold, Towards a Control-Centric Account of Tort Liability for Automated Vehicles (November 20, 2020). (2021) 26 Torts Law Journal 221-243, Available at SSRN: https://ssrn.com/abstract=3735755 or http://dx.doi.org/10.2139/ssrn.3735755

Jerrold Soh (Contact Author)

Singapore Management University School of Law ( email )

55 Armenian Street
Singapore, 179943
Singapore

Singapore Management University - Centre for AI & Data Governance ( email )

55 Armenian Street
Singapore
Singapore

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