Trust, trustworthiness and AI governance

An emerging issue in AI alignment is the use of artificial intelligence (AI) by public authorities, and specifically the integration of algorithmic decision-making (ADM) into core state functions. In this context, the alignment of AI with the values related to the notions of trust and trustworthines...

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Bibliographic Details
Published in:Scientific reports Vol. 14; no. 1; pp. 20752 - 10
Main Authors: Lahusen, Christian, Maggetti, Martino, Slavkovik, Marija
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 05.09.2024
Nature Publishing Group
Nature Portfolio
Subjects:
639/705/1042
639/705/117
Artificial intelligence
Decision making
Humanities and Social Sciences
Interdisciplinary aspects
multidisciplinary
Political science
Science
Science (multidisciplinary)
Trust
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:An emerging issue in AI alignment is the use of artificial intelligence (AI) by public authorities, and specifically the integration of algorithmic decision-making (ADM) into core state functions. In this context, the alignment of AI with the values related to the notions of trust and trustworthiness constitutes a particularly sensitive problem from a theoretical, empirical, and normative perspective. In this paper, we offer an interdisciplinary overview of the scholarship on trust in sociology, political science, and computer science anchored in artificial intelligence. On this basis, we argue that only a coherent and comprehensive interdisciplinary approach making sense of the different properties attributed to trust and trustworthiness can convey a proper understanding of complex watchful trust dynamics in a socio-technical context. Ensuring the trustworthiness of AI-Governance ultimately requires an understanding of how to combine trust-related values while addressing machines, humans and institutions at the same time. We offer a road-map of the steps that could be taken to address the challenges identified.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-024-71761-0