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.


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: 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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