Ethical issues in focus by the autonomous vehicles industry

ABSTRACT

The onset of autonomous driving has provided fertile ground for discussions about ethics in recent years. These discussions are heavily documented in the scientific literature and have mainly revolved around extreme traffic situations depicted as moral dilemmas, i.e. situations in which the autonomous vehicle (AV) is required to make a difficult moral choice. Quite surprisingly, little is known about the ethical issues in focus by the AV industry. General claims have been made about the struggles of companies regarding the ethical issues of AVs but these lack proper substantiation. As private companies are highly influential on the development and acceptance of AV technologies, a meaningful debate about the ethics of AVs should take into account the ethical issues prioritised by industry. In order to assess the awareness and engagement of industry on the ethics of AVs, we inspected the narratives in the official business and technical reports of companies with an AV testing permit in California. The findings of our literature and industry review suggest that: (i) given the plethora of ethical issues addressed in the reports, autonomous driving companies seem to be aware of and engaged in the ethics of autonomous driving technology; (ii) scientific literature and industry reports prioritise safety and cybersecurity; (iii) scientific and industry communities agree that AVs will not eliminate the risk of accidents; (iv) scientific literature on AV technology ethics is dominated by discussions about the trolley problem; (v) moral dilemmas resembling trolley cases are not addressed in industry reports but there are nuanced allusions that unravel underlying concerns about these extreme traffic situations; (vi) autonomous driving companies have different approaches with respect to the authority of remote operators; and (vii) companies seem invested in a lowest liability risk design strategy relying on rules and regulations, expedite investigations, and crash/collision avoidance algorithms.

KEYWORDS:

• Autonomous vehicles
• ethics
• moral dilemma
• trolley
• industry
• companies

Acknowledgments

The authors acknowledge Nicolas Cointe for his assistance in the linguistic-based text data analytics, the three anonymous reviewers for providing helpful comments on earlier versions of the manuscript, and the European Research Council for financial support of this research (ERC Consolidator grant BEHAVE – 724431).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Different nomenclatures are used for highly automated vehicles such as autonomous vehicles, automated vehicles, self-driving cars, or driverless cars (Gandia et al., 2019). Here we adopt autonomous vehicles when referring to automated driving systems-equipped vehicles (levels 3, 4, or 5 driving automation systems according to the Society of Automotive Engineers International Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles Committee, 2014) for reasons of consistency with the nomenclature favoured by the industry. In this context autonomy is associated with the ability of a vehicle to determine its operational environment, thus modulating its behaviour according to relevant norms, needs or constraints (Danks & London, 2017).

2 Information regarding the companies with a testing permit in California, the reports used in this study, and the lexicons is available in the dataset stored in the 4TU. Center for Research Data in doi:10.4121/13348535 (Martins Martinho Bessa, Chorus, Kroesen, & Herber, 2020).

3 Waymo LLC; Tesla Motors; Nissan; BMW; Ford; Valeo North America Inc.; AutoX Technologies Inc.; Nuro Inc.; Apple Inc.; TuSimple; Aurora Innovation; Toyota Research Institute; Intel Corp; TORC Robotics Inc.; EasyMile; Ridecell; Mercedes Benz; Bosch; GM Cruise LLC; Honda; Zoox Inc.; NVIDIA Corporation; Navya Inc.; Udelv; Pony.AI; Continental Automotive Systems; Mando America Corporation; Uber Advanced Technologies Group; and AImotive Inc.

4 RSS stands for Responsibility-Sensitive Safety and NHTSA stands for National Highway Traffic Safety Administration.

Additional information

Funding

This research has received funding from the European Research Council: Consolidator Grant BEHAVE (grant agreement 724431).