$ECUAS_n$: A family of metrics for principled evaluation of uncertainty-augmented systems

This research proposes a new family of metrics, $ECUAS_n$, for evaluating uncertainty-augmented (UA) systems in automated decision-making. It argues that existing evaluation approaches are insufficient for assessing overall performance of UA systems, where predictive uncertainty is crucial for users to make informed decisions.