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Regulatory and Governance Mechanisms for Self-Driving Cars: Social Equity Benefits and Machine Learning-based Ethical Judgments

Regulatory and Governance Mechanisms for Self-Driving Cars: Social Equity Benefits and Machine Learning-based Ethical Judgments

ABSTRACT. The aim of this paper is to synthesize and analyze existing evidence on regulatory and governance mechanisms for self-driving cars. Using and replicating data from AUDI AG, Axios, BikePGH, Deloitte, Ipsos, Kennedys, McKinsey, and Statista, we performed analyses and made estimates regarding social equity benefits and machine learning-based ethical judgments. Data were analyzed using structural equation modeling.

Keywords: regulatory; governance; self-driving; car; machine learning; ethics

How to cite: Poliak, M., Baker, A., Konecny, V., and Nica, E. (2020). “Regulatory and Governance Mechanisms for Self-Driving Cars: Social Equity Benefits and Machine Learning-based Ethical Judgments,” Contemporary Readings in Law and Social Justice 12(1): 58–64. doi:10.22381/CRLSJ12120208

Received 17 February 2020 • Received in revised form 8 July 2020
Accepted 9 July 2020 • Available online 10 July 2020

Milos Poliak
milos.poliak@fpedas.uniza.sk
Faculty of Operation and Economics
of Transport and Communications,
Department of Road and Urban Transport,
University of Zilina, Zilina, Slovak Republic
Andrew Baker
a.baker@aa-er.org
The Cyber-Physical Production Networks
Research Unit at AAER, Wellington, New Zealand
(corresponding author)
Vladimir Konecny
vladimir.konecny@fpedas.uniza.sk
Faculty of Operation and Economics
of Transport and Communications,
Department of Road and Urban Transport,
University of Zilina, Zilina, Slovak Republic
Elvira Nica
popescu_elvira@yahoo.com
Faculty of Administration and Public Management,
The Bucharest University of Economic Studies, Romania