Counterfactual explanations and algorithm aversion

This dataset supports research on job applicant reactions to hiring rejection by human, AI, and hybrid (human with the support of AI) evaluators, and whether counterfactual explanations improve these reactions. The data come from two online experiments in which participants read hypothetical rejection scenarios and then reported their responses. The dataset includes measures such as fairness, trust, organisational perceptions, and behavioural intentions. It can be used to examine how evaluator type and rejection message type shape applicant reactions, and how these effects operate through cognitive and affective perceptions.