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  4. Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains
 
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2020
Conference Paper
Title

Towards Participatory Design Spaces for Explainable AI Interfaces in Expert Domains

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.
Author(s)
Mucha, Henrik  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Robert, Sebastian  
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Breitschwerdt, Rüdiger
Fellmann, Michael
Mainwork
First International Workshop on Explainable and Interpretable Machine Learning, XI-ML 2020. Proceedings. Online resource  
Conference
International Workshop on Explainable and Interpretable Machine Learning (XI-ML) 2020  
German Conference on Artificial Intelligence (KI) 2020  
Open Access
File(s)
Download (460.93 KB)
Rights
CC BY 4.0: Creative Commons Attribution
DOI
10.24406/publica-fhg-409866
Language
English
Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB  
Keyword(s)
  • Explainable AI (XAI)

  • participatory design

  • design spaces

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