Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles

20 Colorado Technology Law Journal 249 (2022)

29 Pages Posted: 6 Aug 2022

See all articles by A. Feder Cooper

A. Feder Cooper

Stanford University; Microsoft Research; Yale University

Karen Levy

Cornell University

Date Written: August 3, 2022

Abstract

The tremendous excitement around the deployment of autonomous vehicles (AVs) comes from their purported promise. In addition to decreasing accidents, AVs are projected to usher in a new era of equity in human autonomy by providing affordable, accessible, and widespread mobility for disabled, elderly, and low-income populations. However, to realize this promise, it is necessary to ensure that AVs are safe for deployment, and to contend with the risks AV technology poses, which threaten to eclipse its benefits. In this Article, we focus on an aspect of AV engineering currently unexamined in the legal literature, but with critical implications for safety, accountability, liability, and power. Specifically, we explain how understanding the fundamental engineering trade-off between accuracy and speed in AVs is critical for policymakers to regulate the uncertainty and risk inherent in AV systems. We discuss how understanding the trade-off will help create tools that will enable policymakers to assess how the trade-off is being implemented. Such tools will facilitate opportunities for developing concrete, ex ante AV safety standards and conclusive mechanisms for ex post determination of accountability after accidents occur. This will shift the balance of power from manufacturers to the public by facilitating effective regulation, reducing barriers to tort recovery, and ensuring that public values like safety and accountability are appropriately balanced.

Keywords: automation, efficiency, autonomous vehicles, speed, governance, artificial intelligence, AI, regulation

JEL Classification: R4, R41, K20

Suggested Citation

Cooper, A. Feder and Levy, Karen, Fast or Accurate? Governing Conflicting Goals in Highly Autonomous Vehicles (August 3, 2022). 20 Colorado Technology Law Journal 249 (2022), Available at SSRN: https://ssrn.com/abstract=4180473

A. Feder Cooper

Stanford University ( email )

269 Campus Dr.

Microsoft Research ( email )

New York, NY

Yale University ( email )

493 College St
New Haven, CT CT 06520
United States

Karen Levy (Contact Author)

Cornell University ( email )

Ithaca, NY 14853
United States

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