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Towards Explainable and Trustworthy Autonomous Physical Systems
University of Oxford, Oxford, United Kingdom.
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0002-1232-346x
University of Oxford, Oxford, United Kingdom.
University of Oxford and the Alan Turing Institute, United Kingdom.
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2021 (English)In: CHI Conference on Human Factors in Computing Systems Extended Abstracts (CHI '21 Extended Abstracts) / [ed] Yoshifumi Kitamura, Aaron Quigley, Katherine Isbister, Takeo Igarashi, Association for Computing Machinery (ACM), 2021, article id 88Conference paper, Published paper (Refereed)
Abstract [en]

The safe deployment of autonomous physical systems in real-world scenarios requires them to be explainable and trustworthy, especially in critical domains. In contrast with g€black-box' systems, explainable and trustworthy autonomous physical systems will lend themselves to easy assessments by system designers and regulators. This promises to pave ways for easy improvements that can lead to enhanced performance, and as well, increased public trust. In this one-day virtual workshop, we aim to gather a globally distributed group of researchers and practitioners to discuss the opportunities and social challenges in the design, implementation, and deployment of explainable and trustworthy autonomous physical systems, especially in a post-pandemic era. Interactions will be fostered through panel discussions and a series of spotlight talks. To ensure lasting impact of the workshop, we will conduct a pre-workshop survey which will examine the public perception of the trustworthiness of autonomous physical systems. Further, we will publish a summary report providing details about the survey as well as the identified challenges resulting from the workshop's panel discussions.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2021. article id 88
Keywords [en]
collaboration, Explainability, human-machine interaction, trust
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:umu:diva-183629DOI: 10.1145/3411763.3441338ISI: 000759178500029Scopus ID: 2-s2.0-85105807078ISBN: 978-1-4503-8095-9 (electronic)OAI: oai:DiVA.org:umu-183629DiVA, id: diva2:1557901
Conference
CHI '21: CHI Conference on Human Factors in Computing Systems, Yokohama, Japan, 8-13 May, 2021
Available from: 2021-05-27 Created: 2021-05-27 Last updated: 2023-09-05Bibliographically approved

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Anjomshoae, SuleFrämling, Kary

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Citation style
  • apa
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  • ieee
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