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.