An Empirical Examination of the Evaluative AI Framework
J. Kornowicz, ArXiv (2024).
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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.
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Kornowicz J. An Empirical Examination of the Evaluative AI Framework. arXiv. Published online 2024. doi:10.48550/ARXIV.2411.08583
Kornowicz, J. (2024). An Empirical Examination of the Evaluative AI Framework. ArXiv. https://doi.org/10.48550/ARXIV.2411.08583
@article{Kornowicz_2024, title={An Empirical Examination of the Evaluative AI Framework}, DOI={10.48550/ARXIV.2411.08583}, journal={arXiv}, author={Kornowicz, Jaroslaw}, year={2024} }
Kornowicz, Jaroslaw. “An Empirical Examination of the Evaluative AI Framework.” ArXiv, 2024. https://doi.org/10.48550/ARXIV.2411.08583.
J. Kornowicz, “An Empirical Examination of the Evaluative AI Framework,” arXiv, 2024, doi: 10.48550/ARXIV.2411.08583.
Kornowicz, Jaroslaw. “An Empirical Examination of the Evaluative AI Framework.” ArXiv, 2024, doi:10.48550/ARXIV.2411.08583.
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