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ABSTRACT. This research investigates the relationship between machine ethics, artificial driving intelligence, and crash algorithms. Building my argument by drawing on data collected from AUVSI, Ipsos, Nature, Pew Research Center, Perkins Coie, Statista, and YouGov, I performed analyses and made estimates regarding U.S. adults who say they would/would not want to ride in a driverless vehicle (%), statements closest to international drivers’ opinion (I am in favor of self-driving cars and cannot wait to use them/I am unsure about self-driving cars, but I find the idea interesting/I am against self-driving cars and would never use them), U.S. adults that would feel (un)safe as a pedestrian in a city with self-driving cars (%), countries that are most prepared for autonomous vehicles (policy and legislation, technology and innovation, infrastructure, and consumer acceptance), and the top data infrastructure requirements in smart cities to facilitate autonomous vehicle testing (wireless connectivity to other cars, parking meters, traffic lights and other smart infrastructure, wireless connectivity to nearby towers/antennas, and data centers to perform analytics on large volumes of data received from vehicles). The data for this research were gathered via an online survey questionnaire and were analyzed through structural equation modeling on a sample of 5,400 respondents.

Keywords: autonomous vehicle; moral decision; artificial driving intelligence; crash algorithm

How to cite: Rowthorn, Michael (2019). “How Should Autonomous Vehicles Make Moral Decisions? Machine Ethics, Artificial Driving Intelligence, and Crash Algorithms,” Contemporary Readings in Law and Social Justice 11(1): 9–14. doi:10.22381/CRLSJ11120191

Received 2 March 2019 • Received in revised form 10 July 2019
Accepted 12 July 2019 • Available online 15 July 2019

Michael Rowthorn
This email address is being protected from spambots. You need JavaScript enabled to view it.
The Center for Labor Research and Education
at AAER, Chicago, IL, USA

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