Algorithmic decision-making in AVs: Understanding ethical and technical concerns for smart cities
Hazel Si Min Lim, and Araz Taeihagh

TL;DR
This paper explores ethical and technical challenges in autonomous vehicle decision-making, emphasizing bias, safety risks, and discrimination, and discusses strategies to address these issues for smarter, sustainable cities.
Contribution
It provides a comprehensive analysis of ethical and technical concerns in AV algorithms and highlights research gaps and policy needs for safer, fairer autonomous mobility.
Findings
Bias and discrimination can be embedded in AV decision algorithms.
Technical limitations affect AV safety and reliability.
Policy and algorithm design are crucial for ethical AV deployment.
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.…
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Taxonomy
TopicsEthics and Social Impacts of AI · Autonomous Vehicle Technology and Safety · Privacy-Preserving Technologies in Data
