Responding to Challenges in the Design of Moral Autonomous Vehicles
Zhao, Helen (Johns Hopkins University) | Dimovitz, Kirsten (The George Washington University) | Staveland, Brooke (The Geroge Washington University) | Medsker, Larry (The George Washington University)
One major example of promising ‘smart’ technology in the public sector is the autonomous vehicle (AV). AVs are expected to yield numerous social benefits, such as increasing traffic efficiency, decreasing pollution, and decreasing traffic accidents by 90%. However, a recent 2016 study published by Bonnefon et al. argued that manufacturers and regulators face a major design challenge of balancing competing public preferences: a moral preference for “utilitarian” algorithms; a consumer preference for vehicles that prioritize passenger safety; and a policy preference for minimum government regulation of vehicle algorithm design. Our paper responds to the 2016 study, calling into question the importance of explicitly moral algorithms and the seriousness of the challenge identified by Bonnefon et al. We conclude that the ‘social dilemma’ is probably overstated. Given that attempts to resolve the ‘social dilemma’ are likely to delay the rollout of socially beneficial AVs, we implore the need for further research validating Bonnefon et al.’s conclusions and encourage manufacturers and regulators to commercialize AVs as soon as possible. We discuss the implications of this example for AV’s for the larger context of Cognitive Assistance in other application areas and the government and public policies that are being discussed.