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Conference Paper/Proceeding/Abstract 172 views

To err is AI

Alba Bisante Orcid Logo, Alan Dix Orcid Logo, Emanuele Panizzi Orcid Logo, Stefano Zeppieri Orcid Logo

CHItaly '23: Proceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter, Pages: 1 - 11

Swansea University Author: Alan Dix Orcid Logo

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DOI (Published version): 10.1145/3605390.3605414

Abstract

In this work, we analyze the different contexts in which one chooses to integrate artificial intelligence into an interface and the implications of this choice in managing user interaction. While AI in systems can provide significant benefits, it is not infallible and can make errors that seriously...

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Published in: CHItaly '23: Proceedings of the 15th Biannual Conference of the Italian SIGCHI Chapter
ISBN: 979-8-4007-0806-0
Published: New York, NY, USA ACM 2023
Online Access: http://dx.doi.org/10.1145/3605390.3605414
URI: https://cronfa.swan.ac.uk/Record/cronfa64783
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Abstract: In this work, we analyze the different contexts in which one chooses to integrate artificial intelligence into an interface and the implications of this choice in managing user interaction. While AI in systems can provide significant benefits, it is not infallible and can make errors that seriously affect users. We aim to understand how to design more robust human-AI systems so that these initial AI errors do not lead to more catastrophic failures. To prevent failures, it is essential to detect errors as early as possible and have clear mechanisms to repair them. However, detecting errors in AI systems can be challenging. Therefore, we examine various approaches to error detection and repair, including post-hoc estimation, the use of traces and ambiguity, and multiple sensor layers.
Keywords: HCI, AI, errors, failures, error detection, error repair, user perception, interaction design
College: Faculty of Science and Engineering
Start Page: 1
End Page: 11