Part 2 of 2 Parts (Please read Part 1 first)
Nuclear Power
     Nuclear power is a reliable, low carbon energy source. It can benefit significantly from the incorporation of AI. By combining digital simulations of real nuclear with AI systems, the nuclear industry can optimize complex procedures and improve reactor design, performance and reduce maintenance costs.
     Machine learning is a process in which AI systems learn by analyzing huge amounts of data. It can help to automate tasks and thereby increase reliability and avoid errors. In addition, AI has considerable analytical and predictive potential to help monitor power plant processes and detect anomalies.
Nuclear Security and radiation protection
     More and more countries have chosen to employ nuclear technology for peaceful purposes and adopt power programs. The IAEA works continuously to ensure the protection of people and the environment from the potential harmful effects of ionizing radiation.
     AI can contribute to nuclear security and safety in a variety of ways. It can be used in the processing and analysis of data from radiation detection systems to enhance the detection and identification of nuclear and other radioactive material. AI can be applied to analyze data from physical protection systems to improve the detection of intruders at nuclear facilities. It can also assist in spotting anomalies that could indicate a cyber-attack on a nuclear facility. In the realm of radiation protection, the integration of AI in safety standards-related software can reinforce the protection of the millions of workers with occupational exposure in medicine, construction, mining, shipping, agriculture and nuclear power.
Safeguards
     Safeguards are technical verification measures that allows the IAEA to provide credible assurances that countries are honoring their legal obligations to use nuclear material for peaceful purposes only. The IAEA analyzes countries’ declared nuclear material and nuclear related activities. It then attempts to verify the absence of undeclared materials and activities through measures, such as inspections at nuclear facilities and sites.
     Safeguards rely on huge amounts of data obtained by various means. These include satellite imagery, environmental sampling, gamma ray spectroscopy and video surveillance. AI can assist nuclear inspectors and safeguard analysts by the analysis of collected data. Machine learning methods have already been used to detect outliers in large datasets. These methods assist in verifying spent fuel and analyzing surveillance recordings. AI is expected to further improve the efficiency of safeguard implementation by reducing the number of repetitive tasks that have to be performed by inspectors.
Final thoughts on the future
     The IAEA provides interdisciplinary forums for professionals to discuss and foster collaboration on the use of AI in nuclear applications, science and technology. It is committed to sharing knowledge and forging partnerships through its AI for Atoms platform. As part of this initiative, the IAEA collaborates with the International Telecommunication Union, the UN Interagency Working Group on AI and forty other UN organizations to provide a solid foundation for accelerated sustainable development of AI. (The AI for Good program is a year-round digital platform of the U.N. system. On the platform, AI innovators and problem owners learn, discuss and connect to identify practical AI solutions to advance U.N. Sustainable Development Goals.)