An Empirical Examination of the Evaluative AI Framework

Jaroslaw Kornowicz ()
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Jaroslaw Kornowicz: Paderborn University

No 134, Working Papers Dissertations from Paderborn University, Faculty of Business Administration and Economics

Abstract: This study empirically examines the "Evaluative AI" framework, which aims to enhance the decision-making process for AI users by transitioning from a recommendation-based approach to a hypothesis-driven one. Rather than offering direct recommendations, this framework presents users pro and con evidence for hypotheses to support more informed decisions. However, findings from the current behavioral experiment reveal no significant improvement in decision-making performance and limited user engagement with the evidence provided, resulting in cognitive processes similar to those observed in traditional AI systems. Despite these results, the framework still holds promise for further exploration in future research.

Keywords: explainable AI; human-computer interaction; human-ai interaction; decision support system (search for similar items in EconPapers)
JEL-codes: C88 C91 D81 O33 (search for similar items in EconPapers)
Pages: 26
Date: 2025-03
New Economics Papers: this item is included in nep-ain
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