Algorithm acceptance in COVID-19-related decision making

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Description: In times of the COVID-19 pandemic, difficult decisions such as the distribution of ventilators must be made. For many of these decisions, humans could team up with algorithms; however, people often prefer human decision-makers. We examined the role of situational (morality of the scenario; perspective) and individual factors (need for leadership; conventionalism) for algorithm preference in a preregistered online experiment with German adults (n = 1,127). As expected, algorithm preference was lowest in the most moral-laden scenario. The effect of perspective (i.e., decision-makers vs. decision targets) was only significant in the most moral scenario. Need for leadership predicted a stronger algorithm preference, whereas conventionalism was related to weaker algorithm preference. Exploratory analyses revealed that attitudes and knowledge also mattered, stressing the importance of individual factors.

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In this osf project you find supplementary material for our study "Algorithm acceptance in COVID-19-related decision making". You can find the preregistration here: http://aspredicted.org/blind.php?x=am4km9. The osf project includes: (1) the paper in its current form (2) the dataset (3) explanations to deviations from the preregistration (4) the questionnaire (in German) (5) a translation of ...

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