Evaluation of artificial intelligence-enhanced critical infrastructure systems

A conceptual framework

Datos Bibliográficos

ID6423923
AutoresSteven Pudney (0000-0001-8015-0030, Southern Cross University), David E Mills (0000-0002-5521-2479, Queensland University of Technology), Alireza Alaei (0000-0003-1669-2606, Southern Cross University), Sarah Seller, Sarah Sellers (Southern Cross University), Sam Sellers (0009-0003-7992-781X, Southern Cross University), Jaroslav Dvorak (0000-0003-1052-8741, Klaipeda University, Lithuania), Oto Potluka (0000-0002-9558-9473, University of Basel)
Año2025
Volumen31
Número3
Páginas412-443
Fecha de publicación2025-07-01
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaEvaluation (JOURNAL)
Identificadores de la revistaISSN: 1356-3890 • E-ISSN: 1461-7153
EditorialSAGE Publishing (PUBLISHER • US)
DOI10.1177/13563890251350677
OpenAlexW4413194470
IdiomaEN
Citas recibidas1
Referencias citadas72

The use of artificial intelligence in Critical Infrastructure Systems has increased substantially, having evolved to become both technically possible and financially beneficial. Yet there is an emerging consensus that the consideration and management of artificial intelligence-related risks in Critical Infrastructure Systems have not been commensurate with its rapid growth. Our surveys have identified that generalised artificial intelligence principles such as those promoted by the Organisation for Economic Co-operation and Development are alone not fit for purpose in guiding use of artificial intelligence in Critical Infrastructure Systems. Evaluation is an important aspect of that, and we argue for the development of a foundational approach suited to evaluation of artificial intelligence-enhanced Critical Infrastructure Systems as a base to further research and improve practice. This study develops a novel conceptual framework for evaluation of artificial intelligence-enhanced Critical Infrastructure Systems, based on theory adaptation of Value-Focused Thinking. The framework offers simplicity and additional functionality over the default principles-based framework

Conceptual framework · Knowledge management · Management science · Process management · Social science · Sociology · Adversarial Robustness in Machine Learning · Computer Science · Engineering · Ethics and Social Impacts of AI · Smart Grid Security and Resilience · Artificial Intelligence