Using the Double Transparency of Autonomous Vehicles to Increase Fairness and Social Welfare

Jie Xu () and Min Ding ()
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Jie Xu: Fudan University
Min Ding: The Pennsylvania State University

Customer Needs and Solutions, 2019, vol. 6, issue 1, No 3, 26-35

Abstract: Abstract Fully autonomous vehicles (AVs) create double transparency regarding human driving decisions. Opaque decision rules in the human mind have become transparent in AVs, and in turn, can be made transparent to third parties. This double transparency is creating an unprecedented opportunity to regulate driving decision rules to eliminate unreasonable selfishness and increase fairness and social welfare because AVs can be programmed to follow regulations 100% of the time. In this experimental ethics study, we performed an incentive aligned online experiment to examine humans’ willingness to sacrifice other people’s lives to protect their own in five different accident scenarios and to investigate the potential for AV regulation to curb unreasonable selfishness, thereby increasing fairness and social welfare. Our results reveal the need to regulate rules governing AV driving decisions; yet, a full transparency policy for decision algorithms may not necessarily lead to desired social effects. Thus, regulations should be tailored to different scenarios.

Keywords: Autonomous vehicles; Transparency; Fairness; Social welfare; Ethics (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1007/s40547-019-00093-2

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