A new paper examines the evaluation of explainable AI (XAI) methods, specifically Shapley value variants, in high-stakes scenarios like fraud detection. Researchers found that standard quantitative metrics for XAI do not align with human understanding or decision utility. While the tested XAI formulations did not improve analyst performance, they did increase decision confidence, raising concerns about automation bias. AI
影响 Current XAI evaluation metrics may not reflect real-world human utility, potentially leading to overconfidence and automation bias in critical decision-making.
排序理由 Academic paper on XAI evaluation methods.
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