The Ethics of Accident-Algorithms for Self-Driving Cars: an Applied Trolley Problem?
By Sven Nyholm, Jilles Smids. Ethical Theory and Moral Practice, 2016
312 citations recorded by the source corpus.
Self-driving cars hold out the promise of being safer than manually driven cars. Yet they cannot be a 100 % safe. Collisions are sometimes unavoidable. So self-driving cars need to be programmed for how they should respond to scenarios where collisions are highly likely or unavoidable. The accident-scenarios self-driving cars might face have recently been likened to the key examples and dilemmas associated with the trolley problem. In this article, we critically examine this tempting analogy. We identify three important ways in which the ethics of accident-algorithms for self-driving cars and the philosophy of the trolley problem differ from each other. These concern: (i) the basic decision-making situation faced by those who decide how self-driving cars should be programmed to deal with accidents; (ii) moral and legal responsibility; and (iii) decision-making in the face of risks and uncertainty. In discussing these three areas of disanalogy, we isolate and identify a number of basic issues and complexities that arise within the ethics of the programming of self-driving cars.
Subfields: Cognitive Neuroscience, Safety Research
View Paper: https://www.semanticscholar.org/paper/61a5d46b606b599ed12d590daa0b393ba02ed727
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In Cognitive Neuroscience
In Safety Research
Citations in the corpus
- Governing autonomous vehicles: emerging responses for safety, liability, privacy, cybersecurity, and industry risks (2018, background): “Concerns also arise regarding how AVs should be programmed by “ crash algorithms ” to respond during unavoidable accidents (Coca-Vila, 2018; de Sio, 2017; Nyholm & Smids, 2016).”
- Impossibility and Uncertainty Theorems in AI Value Alignment (or why your AGI should not have a utility function) (2018, background): “Conversations about the safety of self-driving cars often turn into discussion of “trolley problems”, where the vehicle must make a decision between several differently disastrous outcomes [19, 35, 6, 31, 8, 29].”