AINeutralarXiv – CS AI · 18h ago6/10
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UA-DCM: Uncertainty-aware Causal Decision Making via Effect Bound Decomposition
Researchers introduce UA-DCM, a framework that distinguishes between causal effect uncertainty that can be resolved with more data versus uncertainty inherent to unobserved confounding. By decomposing effect bounds through max-min optimization, the method helps practitioners determine whether additional sampling will improve decision-making or if alternative approaches like randomized trials are necessary.