TY  - CPAPER
U1  - Konferenzveröffentlichung
A1  - Stodt, Jan
A1  - Reich, Christoph
A1  - Knahl, Martin
T1  - Demystifying XAI : Requirements for Understandable XAI Explanations
T2  - Digital Health and Informatics : Innovations for Sustainable Health Care Systems; Proceedings of MIE 2024, 25–29 August 2024, Athens, Greece
N2  - This paper establishes requirements for assessing the usability of Explainable Artificial Intelligence (XAI) methods, focusing on non-AI experts like healthcare professionals. Through a synthesis of literature and empirical findings, it emphasizes achieving optimal cognitive load, task performance, and task time in XAI explanations. Key components include tailoring explanations to user expertise, integrating domain knowledge, and using non-propositional representations for comprehension. The paper highlights the critical role of relevance, accuracy, and truthfulness in fostering user trust. Practical guidelines are provided for designing transparent and user-friendly XAI explanations, especially in high-stakes contexts like healthcare. Overall, the paper's primary contribution lies in delineating clear requirements for effective XAI explanations, facilitating human-AI collaboration across diverse domains.
KW  - Peer-reviewed conference
Y1  - 2024
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:fn1-opus4-108055
SN  - 978-1-64368-533-5
SB  - 978-1-64368-533-5
U6  - https://doi.org/10.3233/SHTI240477
DO  - https://doi.org/10.3233/SHTI240477
SP  - 565
EP  - 569
PB  - IOS Press
ER  -