2024
On the Importance of Application-Grounded Experimental Design for Evaluating Explainable ML Methods
AAAI 2024technical
Most existing evaluations of explainable machine learning (ML) methods rely on simplifying assumptions or proxies that do not reflect real-world use cases; the handful of more robust evaluations on real-world settings have shortcomings in their design, generally leading to overestimation of methods'…