alert fatigue 1algorithm-assisted decision making 1automation bias 1effect estimands 1experimental design 1human behavior adaptation 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.ME2026
Evaluating Algorithm-Assisted Human Decision-Making Over Repeated Algorithm Exposure: Recommendations for Effect Estimands and Experimental Design
Maggie Wang, Michael Baiocchi
The paper examines how humans adapt to repeated algorithmic recommendations in high‑stakes decision contexts and introduces new effect estimands and a minimax stepped double‑wedge…
cs.LG2026
A Practical Upper Bound on Selection Bias Effects in Medical Prediction Models
Kara Liu, Maggie Wang, Russ B. Altman
Selection bias is a common and often unavoidable aspect of real-world data that challenges the generalizability of machine learning models. When models trained on biased data are d…
stat.ME2025
Inspection-Guided Randomization: A Flexible and Transparent Restricted Randomization Framework for Better Experimental Design
Maggie Wang, René F. Kizilcec, Michael Baiocchi
Randomized experiments are considered the gold standard for estimating causal effects. However, out of the set of possible randomized assignments, some may be likely to produce poo…