https://www.dagstuhl.de/22351

28. August – 02. September 2022, Dagstuhl-Seminar 22351

Interactive Visualization for Fostering Trust in ML

Organisatoren

Polo Chau (Georgia Institute of Technology – Atlanta, US)
Alex Endert (Georgia Institute of Technology – Atlanta, US)
Daniel A. Keim (Universität Konstanz, DE)
Daniela Oelke (Hochschule Offenburg, DE)

Auskunft zu diesem Dagstuhl-Seminar erteilen

Jutka Gasiorowski zu administrativen Fragen

Michael Gerke zu wissenschaftlichen Fragen

Dokumente

Programm des Dagstuhl-Seminars (Hochladen)

(Zum Einloggen bitte persönliche DOOR-Zugangsdaten verwenden)

Motivation

Artificial intelligence, and in particular machine learning algorithms, are of increasing importance in many application areas. However, interpretability, understandability, responsibility, accountability, and fairness of the algorithms' results - all crucial for increasing humans' trust into the systems - are still largely missing. All major industrial players, including Google, Microsoft, and Apple, have become aware of this gap and recently published some form of Guidelines for the Use of AI.

While it is clear that the level of trust in AI systems does not only depend on technical but many other factors, including sociological and psychological factors, interactive visualization is one of the technologies that has strong potential to increase trust into AI systems. In our Dagstuhl Seminar, we want to comprehensively discuss the requirements for trustworthy AI systems including sociological and psychological aspects as well as the technological possibilities provided by interactive visualizations to increase human trust in AI. As a first step, we will identify the factors influencing the organizational and sociological as well as psychological aspects of AI. Next, the role that visualizations play in increasing trust in AI system will be illuminated. This includes questions such as: Which mechanisms exist to make AI systems trustworthy? How can interactive visualizations contribute? Under which circumstances are interactive visualizations the decisive factor for enabling responsible AI? And what are the research challenges that still have to be solved – in the area of machine learning or interactive visualization – to leverage this potential in real world applications?

The planned outcome of this seminar is a better understanding of how interactive visualizations can help to foster trust in artificial intelligence systems by making them more understandable and responsible. This should encourage innovative research and help to start joint research projects tackling the issue. Concrete outcomes may be a position paper describing the research challenges identified in the seminar or a special issue featuring interactive visualizations for fostering trust in AI.

Motivation text license
  Creative Commons BY 3.0 DE
  Polo Chau, Alex Endert, Daniel A. Keim, and Daniela Oelke

Related Dagstuhl-Seminar

Classification

  • Artificial Intelligence
  • Computers And Society
  • Human-Computer Interaction

Keywords

  • Interactive visualization
  • Artificial intelligence
  • Machine learning
  • Trust
  • Responsibility
  • Understandability
  • Accountability
  • Explainability
  • Fairness

Dokumentation

In der Reihe Dagstuhl Reports werden alle Dagstuhl-Seminare und Dagstuhl-Perspektiven-Workshops dokumentiert. Die Organisatoren stellen zusammen mit dem Collector des Seminars einen Bericht zusammen, der die Beiträge der Autoren zusammenfasst und um eine Zusammenfassung ergänzt.

 

Download Übersichtsflyer (PDF).

Dagstuhl's Impact

Bitte informieren Sie uns, wenn eine Veröffentlichung ausgehend von Ihrem Seminar entsteht. Derartige Veröffentlichungen werden von uns in der Rubrik Dagstuhl's Impact separat aufgelistet  und im Erdgeschoss der Bibliothek präsentiert.

Publikationen

Es besteht weiterhin die Möglichkeit, eine umfassende Kollektion begutachteter Arbeiten in der Reihe Dagstuhl Follow-Ups zu publizieren.