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Free keywords:
Delegation ; Decision-making for others ; Algorithm aversion ; Redistribution ; Fairness
Abstract:
As technology-assisted decision-making is becoming more widespread, it is important to understand how the algorithmic nature of the decision maker affects how decisions are perceived by those affected. We use an online experiment to study the preference for human or algorithmic decision makers in redistributive decisions. In particular, we consider whether an algorithmic decision maker will be preferred because of its impartiality. Contrary to previous findings, the majority of participants (over 60%) prefer the algorithm as a decision maker over a human—but this is not driven by concerns over biased decisions. However, despite this preference, the decisions made by humans are regarded more favorably. Subjective ratings of the decisions are mainly driven by participants’ own material interests and fairness ideals. Participants tolerate any explainable deviation between the actual decision and their ideals but react very strongly and negatively to redistribution decisions that are not consistent with any fairness principles.
