Skip to main content

Research Repository

Advanced Search

Artificial Intelligence (AI) in the Nuclear Power Plants: Who Is Liable When AI Fails to Perform

Karim, Ridoan; Muhammad Sukki, Firdaus

Authors

Ridoan Karim



Contributors

Farhad Taghizadeh-Hesary
Editor

Dayong Zhang
Editor

Abstract

The sheer magnitude of process parameters and interactions between the systems in a nuclear power plant’s operation poses complications for operators. The operations became more challenging, especially during emergencies. Any recovery from an emergency relies heavily on modifying the system rapidly based on accessible data analysis. Artificial intelligence (AI) technology, working as expert guidance and quick access to a broad knowledge base, may resolve most of the complexities. Hence, experts believe that AI can be the expert system for operating a complex technology like the nuclear power plant. Nevertheless, AI deployment in the energy sector can also introduce several risks and challenges, including physical damage to the power plant. The existing nuclear liability laws and regulations promises a robust compensation packages for nuclear damages; nevertheless, the damage resulting from AI in nuclear power plant is still yet to be tested. Hence, this chapter particularly analyze whether the existing nuclear liability regimes and the tort law, possibly in combination with insurance and strict liability provisions, can constitute a sufficient nuclear damage claims or not.

Citation

Karim, R., & Muhammad Sukki, F. (2023). Artificial Intelligence (AI) in the Nuclear Power Plants: Who Is Liable When AI Fails to Perform. In F. Taghizadeh-Hesary, & D. Zhang (Eds.), The Handbook of Energy Policy (587-607). Springer. https://doi.org/10.1007/978-981-19-6778-8_27

Acceptance Date Jun 29, 2022
Online Publication Date Apr 30, 2023
Publication Date 2023
Deposit Date Sep 30, 2022
Publisher Springer
Pages 587-607
Book Title The Handbook of Energy Policy
ISBN 978-981-19-6777-1
DOI https://doi.org/10.1007/978-981-19-6778-8_27
Public URL http://researchrepository.napier.ac.uk/Output/2926298
Publisher URL https://link.springer.com/referenceworkentry/10.1007/978-981-16-9680-0_27-1


You might also like



Downloadable Citations