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Developing a framework for trustworthy AI-supported knowledge management in the governance of risk and change

Vining, Rebecca orcid logoORCID: 0000-0002-2715-8129, McDonald, Nick, McKenna, Lucy orcid logoORCID: 0000-0002-6035-7656, Ward, Marie E. orcid logoORCID: 0000-0002-6638-8461, Doyle, Brian orcid logoORCID: 0000-0002-9106-9526, Liang, Junli, Hernandez, Julio orcid logoORCID: 0000-0003-1347-9631, Guilfoyle, John, Shuhaiber, Arwa, Geary, Una, Fogarty, Mary and Brennan, Rob orcid logoORCID: 0000-0001-8236-362X (2022) Developing a framework for trustworthy AI-supported knowledge management in the governance of risk and change. In: 24th International Conference on Human-Computer Interaction (HCI'22), 26 Jun - 1 Jul 2022, Virtual. ISBN 978-3-031-17614-2

Abstract
This paper proposes a framework for developing a trustworthy artificial intelligence (AI) supported knowledge management system (KMS) by integrating existing approaches to trustworthy AI, trust in data, and trust in organisations. We argue that improvement in three core dimensions (data governance, validation of evidence, and reciprocal obligation to act) will lead to the development of trust in the three domains of the data, the AI technology, and the organisation. The framework was informed by a case study implementing the Access- Risk-Knowledge (ARK) platform for mindful risk governance across three collaborating healthcare organisations. Subsequently, the framework was applied within each organisation with the aim of measuring trust to this point and generating objectives for future ARK platform development. The resulting discussion of ARK and the framework has implications for the development of KMSs, the development of trustworthy AI, and the management of risk and change in complex socio-technical systems.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:Access-Risk-Knowledge (ARK); socio-technical systems analysis; risk governance; artificial intelligence; trust
Subjects:Computer Science > Artificial intelligence
Computer Science > Machine learning
Computer Science > Information storage and retrieval systems
Medical Sciences > Psychology
Social Sciences > Social psychology
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Institutes and Centres > ADAPT
Published in: HCI International 2022 Proceedings. Lecture Notes in Computer Science (LNCS) 13516. Springer. ISBN 978-3-031-17614-2
Publisher:Springer
Official URL:https://doi.org/10.1007/978-3-031-17615-9_22
Copyright Information:© 2022 The Authors
Funders:Science Foundation Ireland (SFI) under Grant Agreement No. 20/COV/8463 at the ADAPT SFI Research Centre at Dublin City University and Trinity CollegeDublin. The ADAPT SFI Centre for Digital Content Technology is funded by Science Foundation Ireland, Science Foundation Ireland at ADAPT, the SFI Research Centre for AI-Driven Digital Content Technology at DCU [13/RC/2106_P2]
ID Code:27118
Deposited On:20 Jun 2022 17:15 by Lucy Mckenna . Last Modified 14 Feb 2023 10:18
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