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Trust Management for Artificial Intelligence: A Standardization Perspective

Um, TW, Kim, J, Lim, S and Lee, GM (2022) Trust Management for Artificial Intelligence: A Standardization Perspective. Applied Sciences, 12 (12). ISSN 2076-3417

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With the continuous increase in the development and use of artificial intelligence systems and applications, problems due to unexpected operations and errors of artificial intelligence systems have emerged. In particular, the importance of trust analysis and management technology for artificial intelligence systems is continuously growing so that users who desire to apply and use artificial intelligence systems can predict and safely use services. This study proposes trust management requirements for artificial intelligence and a trust management framework based on it. Furthermore, we present challenges for standardization so that trust management technology can be applied and spread to actual artificial intelligence systems. In this paper, we aim to stimulate related standardization activities to develop globally acceptable methodology in order to support trust management for artificial intelligence while emphasizing challenges to be addressed in the future from a standardization perspective.

Item Type: Article
Uncontrolled Keywords: trust management; trustworthiness; artificial intelligence; standardization
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science & Mathematics
Publisher: MDPI AG
SWORD Depositor: A Symplectic
Date Deposited: 14 Jun 2022 09:16
Last Modified: 21 Jun 2022 11:17
DOI or ID number: 10.3390/app12126022
URI: https://researchonline.ljmu.ac.uk/id/eprint/17070
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