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    How to program autonomous vehicle (AV) crash algorithms: an Islamic ethical perspective

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    Date
    2023-11-07
    Author
    Elmahjub, Ezieddin
    Qadir, Junaid
    Metadata
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    Abstract
    Purpose: Fully autonomous self-driving cars not only hold the potential for significant economic and environmental advantages but also introduce complex ethical dilemmas. One of the highly debated issues, known as the “trolley problems,” revolves around determining the appropriate actions for a self-driving car when faced with an unavoidable crash. Currently, the discourse on autonomous vehicle (AV) crash algorithms is primarily shaped by Western ethical traditions, resulting in a Eurocentric bias due to the dominant economic and political influence of the West. However, considering that AV technology will be deployed across diverse cultural and religious contexts, this paper aims to contribute to the discourse by providing an Islamic perspective on programming the response of AVs in the event of an imminent crash. Design/methodology/approach: This study proposes a novel methodology based on the Islamic concept of maṣlaḥa for the normative assessment of ethical decisions related to AV programming. Findings: Drawing upon the works of classic Islamic jurists, this study highlights two distinct normative visions within Islamic traditions (akin to deontology and consequentialism) concerning the preservation of human lives in the context of AVs. This study explores the shared and divergent elements between Islamic and Western ethical approaches proposed for AVs. Originality/value: This pioneering work examines AV crash algorithms from an Islamic perspective, filling a void in the global ethical discourse. This work will also serve an important role to bridge the gap between the theoretical Islamic ethical principles and their practical application in the realm of AVs.
    URI
    https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85166753977&origin=inward
    DOI/handle
    http://dx.doi.org/10.1108/JICES-02-2023-0015
    http://hdl.handle.net/10576/50926
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    • Computer Science & Engineering [‎2428‎ items ]
    • Law Research [‎294‎ items ]

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