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- W4328115561 abstract "Despite the rise of decision support systems enabled by artificial intelligence (AI) in personnel selection, their impact on decision-making processes is largely unknown. Consequently, we conducted five experiments (N = 1,403) investigating how people interact with AI-generated advice in a personnel selection task. In all pre-registered experiments, we presented correct and incorrect advice. In Experiments 1a and 1b, we manipulated the source of the advice (human vs. AI). In Experiments 2a, 2b, and 2c, we further manipulated the type of explainability of AI advice (2a and 2b: heatmaps and 2c: charts) to test if explainable advice improves decision-making. The independent variables were regressed on task performance, perceived advice quality and confidence ratings. The results consistently showed that incorrect advice negatively impacted performance, as people failed to dismiss it (i.e., overreliance). Additionally, we found that the effects of source and explainability of advice on the dependent variables were limited." @default.
- W4328115561 created "2023-03-22" @default.
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- W4328115561 date "2023-03-20" @default.
- W4328115561 modified "2023-09-27" @default.
- W4328115561 title "The Effect of AI-generated Advice on Decision-Making in Personnel Selection" @default.
- W4328115561 doi "https://doi.org/10.31219/osf.io/349xe" @default.
- W4328115561 hasPublicationYear "2023" @default.
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