Police used AI facial recognition to arrest a Tennessee woman for crimes committed in a state she says she’s never visited - CNN
<a href="https://news.google.com/rss/articles/CBMid0FVX3lxTE1YTmlPZzU5S3RCZElOWGZ2aXpGSjItTDBvUVJLNDRzWmhyUHR6TXIyWjBVRzJaWk5CUVNrTzUwMjU0MzJXVlFCQTVmNGl4OTUzRnFHRk96RUdjQ3hNQ2hTUE5TbDUtdko4dVZ3T09WMmszRzN5Uy1J?oc=5" target="_blank">Police used AI facial recognition to arrest a Tennessee woman for crimes committed in a state she says she’s never visited</a> <font color="#6f6f6f">CNN</font>
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Uncertainty Gating for Cost-Aware Explainable Artificial Intelligence
arXiv:2603.29915v1 Announce Type: new Abstract: Post-hoc explanation methods are widely used to interpret black-box predictions, but their generation is often computationally expensive and their reliability is not guaranteed. We propose epistemic uncertainty as a low-cost proxy for explanation reliability: high epistemic uncertainty identifies regions where the decision boundary is poorly defined and where explanations become unstable and unfaithful. This insight enables two complementary use cases: `improving worst-case explanations' (routing samples to cheap or expensive XAI methods based on expected explanation reliability), and `recalling high-quality explanations' (deferring explanation generation for uncertain samples under constrained budget). Across four tabular datasets, five dive
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