Print Email Facebook Twitter A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable Title A Two-Dimensional Explanation Framework to Classify AI as Incomprehensible, Interpretable, or Understandable Author Verhagen, R.S. Neerincx, M.A. Tielman, M.L. Contributor Calvaresi, D. (editor) Najjar, A. (editor) Winikoff, M. (editor) Främling, K. (editor) Publication year 2021 Abstract Because of recent and rapid developments in Artificial Intelligence (AI), humans and AI-systems increasingly work together in human-agent teams. However, in order to effectively leverage the capabilities of both, AI-systems need to be understandable to their human teammates. The branch of eXplainable AI (XAI) aspires to make AI-systems more understandable to humans, potentially improving human-agent teamwork. Unfortunately, XAI literature suffers from a lack of agreement regarding the definitions of and relations between the four key XAI-concepts: transparency, interpretability, explainability, and understandability. Inspired by both XAI and social sciences literature, we present a two-dimensional framework that defines and relates these concepts in a concise and coherent way, yielding a classification of three types of AI-systems: incomprehensible, interpretable, and understandable. We also discuss how the established relationships can be used to guide future research into XAI, and how the framework could be used during the development of AI-systems as part of human-AI teams. © 2021, Springer Nature Switzerland AG. Subject ExplainabilityExplainable AIHuman-agent teamingInterpretabilityTransparencyUnderstandability To reference this document use: http://resolver.tudelft.nl/uuid:92ae3ada-6a04-4e58-bd8d-a013fbe405f3 DOI https://doi.org/10.1007/978-3-030-82017-6_8 TNO identifier 958795 Publisher Springer, Cham ISBN 9783030820169 Source 3rd International Workshop on Explainable, Transparent AI and Multi-Agent Systems, EXTRAAMAS 2021, Virtual, Online, 3 May 2021 - 7 May 2021, 119-138 Series Lecture Notes in Computer ScienceLecture Notes in Computer Science Document type conference paper Files To receive the publication files, please send an e-mail request to TNO Library.