Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy

Donald R. Honeycutt, Mahsan Nourani, Eric D. Ragan. Soliciting Human-in-the-Loop User Feedback for Interactive Machine Learning Reduces User Trust and Impressions of Model Accuracy. In Lora Aroyo, Elena Simperl, editors, Proceedings of the Eighth AAAI Conference on Human Computation and Crowdsourcing, HCOMP 2020, Hilversum, The Netherlands (virtual), October 25-29, 2020. pages 63-72, AAAI Press, 2020. [doi]

Abstract

Abstract is missing.