Models derived from random utility theory represent the workhorse methods to learn about consumer preferences from discrete choice data. However, a large body of literature documents various behavioral patterns that cannot be captured by basic random utility models and require different...

Using a representative survey with 1317 individuals and 12,815 moral decisions, we elicit Swedish citizens' preferences on how algorithms for self-driving cars should be programmed in cases of unavoidable harm to humans. Participants' choices in different dilemma situations (treatments) show...