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Towards a Comprehensive Human-Centred Evaluation Framework for Explainable AI
While research on explainable AI (XAI) is booming and explanation techniques
have proven promising in many application domains, standardised human-centred
evaluation procedures are still missing. In addition, current evaluation
procedures do not assess XAI methods holistically in the sense that they do not
treat explanations' effects on humans as a complex user experience. To tackle
this challenge, we propose to adapt the User-Centric Evaluation Framework used
in recommender systems: we integrate explanation aspects, summarise explanation
properties, indicate relations between them, and categorise metrics that
measure these properties. With this comprehensive evaluation framework, we hope
to contribute to the human-centred standardisation of XAI evaluation.Comment: This preprint has not undergone any post-submission improvements or
corrections. This work was an accepted contribution at the XAI world
Conference 202