Allowing humans to interactively guide machines where to look does not always improve a human-AI team's classification accuracy

arXiv:2404.05238v1 Announce Type: new
Abstract: Via thousands of papers in Explainable AI (XAI), attention maps \cite{vaswani2017attention} and feature attribution maps \cite{bansal2020sam} have been established as a common means for explaining the input features that are important to AI's decisions. It is an interesting but unexplored question whether allowing users to edit the importance scores of input features at test time would improve the human-AI team's accuracy on downstream tasks. In this paper, we address this question by taking CHM-Corr, a …

accuracy arxiv classification cs.cv cs.hc guide human humans look machines team type