Publications on Explainable AI

Assessing Satisfaction in and Understanding of a Collaborative Explainable AI (CXAI) System through User Studies

Explaining Explanation for “Explainable AI”

Explaining Explanation, Part 1: Theoretical Foundations

Explaining Explanation, Part 2: Empirical Foundations

Modeling the Process by Which People Try to Explain Complex Things to Others

Measures for explainable AI: Explanation goodness, user satisfaction, mental models, curiosity, trust, and human-AI performance

Psychology and AI at a Crossroads: How Might Complex Systems Explain Themselves?

“Minimum Necessary Rigor” in empirically evaluating human–AI work systems

Evaluating machine-generated explanations: a “Scorecard” method for XAI measurement science

Explainable AI: roles and stakeholders, desirements and challenges

Increasing the Value of XAI for Users: A Psychological Perspective

Methods and standards for research on explainable artificial intelligence: Lessons from intelligent tutoring systems