The pace of development of new technological products is reportedly faster than their social adoption and ethico-legal assessment. This creates a risk that the beneficial potential of technologies, including those centering on automation, remains far below its potential if social, ethical and legal implications remain unaddressed1-7.
With the advent of automated and autonomous vehicles and other transport robots, much media attention and research has focused on the question of how these cars and other smart modes of transport should make decisions. Particular attention has been given to decisions that affect who lives, dies and is injured in crash and other accident scenarios. Those who tried to establish general ethical codes for intelligent machines, such as the Asilomar AI Principles8, have suggested that machine ethics should be aligned with human values. Following this, some have recommended that cars should mimic intuitive human responses, or reflect societal preferences on who should be prioritized in such incidents. In addition to the plethora of papers on how to engineer algorithms for crash handling in smart vehicles, the groundbreaking Moral Machine project has mapped millions of people’s responses to crash dilemma situations2. The study found significant cultural differences between three main clusters of countries (the Western cluster, composed of Northern America and many European countries, the Eastern cluster, mainly Asian countries, and the Southern cluster, composed in particular of South America). The authors conclude that “manufacturers and policymakers should be, if not responsive, at least cognizant of moral preferences in the countries in which they design artificial intelligence systems and policies. Whereas the ethical preferences of the public should not necessarily be the primary arbiter of ethical policy, the people’s willingness to buy autonomous vehicles and tolerate them on the roads will depend on the palatability of the ethical rules that are adopted”