Algorithmic Decision-Making in AVs: Understanding Ethical and Technical Concerns for Smart Cities
Sustainability, 11(20), 5791, 2019
28 Pages Posted: 8 Nov 2019
Hazel Si Min Lim
National University of Singapore (NUS) - Lee Kuan Yew School of Public Policy
Araz Taeihagh
Lee Kuan Yew School of Public Policy, National University of Singapore
Date Written: October 18, 2019
Abstract
Autonomous Vehicles (AVs) are increasingly embraced around the world to advance smart mobility and more broadly, smart, and sustainable cities. Algorithms form the basis of decision-making in AVs, allowing them to perform driving tasks autonomously, efficiently, and more safely than human drivers and offering various economic, social, and environmental benefits. However, algorithmic decision-making in AVs can also introduce new issues that create new safety risks and perpetuate discrimination. We identify bias, ethics, and perverse incentives as key ethical issues in the AV algorithms’ decision-making that can create new safety risks and discriminatory outcomes. Technical issues in the AVs’ perception, decision-making and control algorithms, limitations of existing AV testing and verification methods, and cybersecurity vulnerabilities can also undermine the performance of the AV system. This article investigates the ethical and technical concerns surrounding algorithmic decision-making in AVs by exploring how driving decisions can perpetuate discrimination and create new safety risks for the public. We discuss steps taken to address these issues, highlight the existing research gaps and the need to mitigate these issues through the design of AV’s algorithms and of policies and regulations to fully realise AVs’ benefits for smart and sustainable cities.
Keywords: Algorithm, Autonomous vehicle, Driverless car, Decision-making, Ethics, Biases, Discrimination, Safety, Smart city, Sustainable city, Sustainable development, Artificial Intelligence, Machine Learning, Human-computer interaction
Suggested Citation: Suggested Citation
Hazel Si Min Lim
National University of Singapore (NUS) - Lee Kuan Yew School of Public Policy ( email )
Singapore 117591
Singapore
Araz Taeihagh (Contact Author)
Lee Kuan Yew School of Public Policy, National University of Singapore ( email )
469B Bukit Timah Road
Li Ka Shing Building, Level 2
Singapore, 259771
Singapore
+65 6601 5254 (Phone)
HOME PAGE: http://www.taeihagh.com/publications
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