Paper ID: 2411.08583 • Published Nov 13, 2024
An Empirical Examination of the Evaluative AI Framework
Jaroslaw Kornowicz
TL;DR
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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.