Abstract
Who is to blame when autonomous vehicles are involved in accidents? We report findings from an online study in which the attribution of blame and trust were measured from 206 participants who studied 18 hypothetical vignettes portraying traffic incidents under different driving environments. The focal vehicle involved in the incident was either controlled by a human driver or autonomous system. The accident severity also varied from near miss, minor accident to major accident. Participants applied double standards when assigning blame to humans and autonomous systems: an autonomous system was usually blamed more than a human driver for executing the same actions under the same circumstances with the same consequences. These findings not only have important implications to AI-related legislation, but also highlight the necessity to promote the design of robots and other automation systems which can help calibrate public perceptions and expectations of their characteristics and capabilities.
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Acknowledgments
The research was funded through the ESRC Project ES/T007079/1 Rule of Law in the Age of AI: Principles of Distributive Liability for Multi-Agent Societies and is part of a larger project on the same topic supported by ESRC (ES/T007079/1) and JST with collaborators at the Universities of Kyoto, Osaka and Doshisha. We would like to thank our collaborators Prof. Tatsu Inatani and Prof. Minoru Asada for their contribution to this work.
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Zhang, Q., Wallbridge, C.D., Jones, D.M., Morgan, P. (2021). The Blame Game: Double Standards Apply to Autonomous Vehicle Accidents. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2021. Lecture Notes in Networks and Systems, vol 270. Springer, Cham. https://doi.org/10.1007/978-3-030-80012-3_36
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DOI: https://doi.org/10.1007/978-3-030-80012-3_36
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