Activity: Talk or presentation › Oral presentation › science 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
Period
2021
Event title
Operationalizing Human-Centered Perspectives in Explainable AI (HCXAI 2021)
Event type
Online-Workshop
Keywords
Artificial intelligence
Explainable AI
Evaluation
Fields of Science and Technology Classification 2012