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

, , , and . Frontiers Comput. Sci., (2023)

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What Is Design in the Context of Human-Centered Computing?, , and . IEEE Intelligent Systems, 19 (4): 89-95 (2004)How Many Experts?, and . IEEE Intelligent Systems, 31 (6): 56-62 (2016)Metrics, Metrics, Metrics, Part 2: Universal Metrics?, , and . IEEE Intelligent Systems, 25 (6): 93-97 (2010)Human-Centered Computing: Thinking In and Out of the Box., , and . IEEE Intelligent Systems, 16 (5): 76-78 (2001)Human Total Cost of Ownership: The Penny Foolish Principle at Work., , , and . IEEE Intelligent Systems, 22 (2): 88-92 (2007)Toward a Theory of Complex and Cognitive Systems., and . IEEE Intelligent Systems, 20 (1): 76-79 (2005)Work-arounds, Make-work, and Kludges., and . IEEE Intelligent Systems, 18 (6): 70-75 (2003)Using Knowledge Libraries to Transfer Expert Knowledge., and . IEEE Intelligent Systems, 31 (2): 89-93 (2016)Explaining Explanation, Part 1: Theoretical Foundations, and . IEEE Intelligent Systems, 32 (3): 68--73 (2017)Why Expertise Matters: A Response to the Challenges., , , and . IEEE Intelligent Systems, 32 (6): 67-73 (2017)