Artificial intelligence for the support of regulator decision making

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Abstract

This study was aimed at providing views on new areas where AI could be reasonably utilised in regulatory activities in the nuclear energy domain. The goal was to review the possibilities of AI in nuclear safety research and development from different point of views, including the existing authority processes, but also chains of processes in which different stakeholders are involved. In addition, tasks, processes and activities, in which the other stakeholders could apply AI and which affect the authority and nuclear safety in general, were included.

The study contained detailed discussions with experts of different fields, both in nuclear energy sector as well as in the research and especially in the AI research sector. One small scale workshop was organised to get information about the needs and bottlenecks of the main organisations in the nuclear energy sector in Finland. In the workshop, the participants shared with others the status of applying AI in their organisation as well as their ideas of potential applications of AI and interesting fields of research. The study included a large set of background material to illustrate the landscape of the nuclear energy domain and its needs, the tasks, operations and processes of the nuclear authority, STUK, and the research and development activities of applying AI in the global nuclear energy domain.

During the process, potential large research themes as well as detailed research topics were collected to have enough data for an analysis of future research themes. From the potential research and development themes, the most promising ones are proposed for the future research projects in the next national research programme of this domain.
Original languageEnglish
Place of PublicationEspoo
PublisherVTT Technical Research Centre of Finland
Number of pages30
Publication statusPublished - 15 Oct 2020
MoE publication typeD4 Published development or research report or study

Publication series

SeriesVTT Research Report
NumberVTT-R-01225-20

Keywords

  • artificial intelligence
  • authority process
  • decision making
  • knowledge engineering
  • machine learning
  • systems engineering

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