DagRep.12.8.103.pdf
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Interactive Visualization for Fostering Trust in ML (Dagstuhl Seminar 22351)
Authors and all authors of the abstracts in this report
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Dagstuhl Reports, Volume 12, Issue 8
Volume: Dagstuhl Reports, Volume 12
Journal: Dagstuhl Reports (DagRep) - License:
Creative Commons Attribution 4.0 International license
- Publication Date: 2023-03-02
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Polo Chau, Alex Endert, Daniel A. Keim, and Daniela Oelke. Interactive Visualization for Fostering Trust in ML (Dagstuhl Seminar 22351). In Dagstuhl Reports, Volume 12, Issue 8, pp. 103-116, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)
https://doi.org/10.4230/DagRep.12.8.103
Abstract
The use of artificial intelligence continues to impact a broad variety of domains, application areas, and people. However, interpretability, understandability, responsibility, accountability, and fairness of the algorithms' results - all crucial for increasing humans' trust into the systems - are still largely missing. The purpose of this seminar is to understand how these components factor into the holistic view of trust. Further, this seminar seeks to identify design guidelines and best practices for how to build interactive visualization systems to calibrate trust.
Subject Classification
ACM Subject Classification
- Computing methodologies → Artificial intelligence
- Computing methodologies → Machine learning
- Human-centered computing → Visualization
Keywords
- accountability
- artificial intelligence
- explainability
- fairness
- interactive visualization
- machine learning
- responsibility
- trust
- understandability
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