Explainable AI: Intrinsic, Dialogic, and Impact Measures of Success

Activity: Talk or presentationOral presentationscience to science / art to art

Description

We propose a framework that comprises three perspectives on evaluation models for explainable AI that include intrinsic measures, dialogic measures and impact measures. The paper outlines these different perspectives and looks at how the separation might be used for explanation evaluation bench marking and integration into design and development
Period2021
Event titleOperationalizing Human-Centered Perspectives in Explainable AI (HCXAI 2021)
Event typeOnline-Workshop

Keywords

  • Artificial intelligence
  • Explainable AI
  • Evaluation

Fields of Science and Technology Classification 2012

  • 102 Computer Sciences