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Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains

 
: Mucha, Henrik; Robert, Sebastian; Breitschwerdt, Rüdiger; Fellmann, Michael

:
Fulltext urn:nbn:de:0011-n-6217587 (460 KByte PDF)
MD5 Fingerprint: 4d4e311338a643a18fc62dfcbebeea8f
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Created on: 28.1.2021


Atzmueller, Martin (Ed.):
First International Workshop on Explainable and Interpretable Machine Learning, XI-ML 2020. Proceedings. Online resource : Co-located with the 43rd German Conference on Artificial Intelligence (KI 2020), Bamberg, Germany, September 21, 2020 (Virtual Workshop)
Online im WWW, 2020 (CEUR Workshop Proceedings 2796)
http://ceur-ws.org/Vol-2796/
5 pp.
International Workshop on Explainable and Interpretable Machine Learning (XI-ML) <1, 2020, Online>
German Conference on Artificial Intelligence (KI) <43, 2020, Online>
English
Conference Paper, Electronic Publication
Fraunhofer IOSB ()
Explainable AI (XAI); participatory design; design spaces

Abstract
In this position paper, we lay out an approach to use participatory and co-design methodology to explore how users perceive and interact with explanations of artificially intelligent decision support systems. We describe how we intend to construct bottom-up participatory design spaces to systematically inform the design of interactive explanations in Human-AI interaction.

: http://publica.fraunhofer.de/documents/N-621758.html