Author

Michael Oberst

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Jul 2026

Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness

This work presents a partial-identification approach to using prior RCT data to construct bounds on the causal effect of a new model, and leverages assumptions relating fine-grained predictive accuracy to downstream outcomes.

Jonathan Zhang, Erik Skalnes, Jacob M. Chen et al. · arXiv.org · 0 citations