Distinguishing the Indistinguishable: Human Expertise in Algorithmic Prediction

We introduce a novel framework for incorporating human expertise into algorithmic predictions. Our approach focuses on the use of human judgment to distinguish inputs which `look the same' to any feasible predictive algorithm. We argue that this framing clarifies the problem of human/AI collaboration in prediction tasks, as experts often have access to information -- particularly subjective information -- which is not encoded in the algorithm's training data. We use this insight to develop a set of principled algorithms for …

ai collaboration algorithm collaboration cs.ai cs.hc cs.lg expertise experts framework human inputs judgment look novel prediction predictions predictive tasks