The IAEA will hold its first ever technical meeting on artificial intelligence (AI) for nuclear technology and applications from 25 to 29 October 2021. Those interested to participate in the virtual event have until 30 September to submit a completed participation form through their official national authorities and until 31 August to submit their abstracts. More information on the event and application process is here.
Targeting primarily nuclear and data experts, the event will cover AI applications, methodologies and tools to advance nuclear technology and applications across various fields and will foster international cooperation in this specialised area.
AI refers to a collection of technologies that combine numerical data, process algorithms and continuously increasing computing power to develop systems capable of approaching complex problems in ways similar to human logic and reasoning. AI technologies can analyse large amounts of data to learn and assess how to complete a particular task, a technique called machine learning.
Advancing exponentially, AI is already applied across various nuclear fields. In nuclear medicine for example, AI-based approaches are used to boost diagnosis and treatment of cancer through improved image interpretation, more accurate treatment plans and precise tumour contouring as well as through adaptive radiotherapy – a radiation therapy process that adapts to internal anatomical variants of the individual patient.
Researchers and professionals in the nuclear industry can use AI to simulate behaviour of nuclear reactors and based on the results improve reactor design, performance, safety and fuel loading. AI can also help manage environmental, hydrological and ecological resources by analysing huge amounts of isotopic data stored in global networks and repositories, including the GNIP database of the IAEA. AI will also play an important role in the IAEA’s Zoonotic Disease Integrated Action (ZODIAC) initiative to help experts predict, identify, assess and contain future zoonotic disease outbreaks.
However, the transformative power of AI also comes with challenges, including issues of transparency, trust, security and other ethical concerns. For instance, AI poses also significant regulatory challenges and therefore, as industry innovates, so must the regulators. The IAEA, as the global focal point for nuclear cooperation, supports and promotes AI application in nuclear technologies and its enormous potential to help accelerate their safe, secure and peaceful uses.
The expected output of the meeting will be a report highlighting challenges and opportunities related to AI-based approaches in nuclear science and technology and will discuss the role of the IAEA in this field.
Among the topics discussed at the event will be:
- enabling infrastructure, machine learning, open data science and standardized frameworks;
- advanced modelling and simulation methodologies, including integrated modelling, multi-physics multiscale modelling and optimized system design;
- ethics;
- food and agriculture, including food authentication, food safety early warning systems and soil type prediction;
- human health, including diagnosis and treatment of cancer, image interpretation, treatment plans and contouring, adaptive radiotherapy and medical processes;
- nuclear data, data analysis, verification and information discovery;
- nuclear fusion, including plasma prediction, control system and model generation;
- nuclear physics, including data analysis and management, experimental design and optimization and facility operation;
- nuclear power, including outage, maintenance, planning and inspection;
- nuclear security, including anomaly detection, data analysis, integration and management;
- radiation protection, including radiation exposure with algorithms and radiological data across machines;
- radioisotopes and radiation technology, including radiopharmaceutical design and modelling;
- non-destructive assay measurements, robotics and surveillance applied to safeguards verification activities;
- water resources optimization and the environment, including water security and protection, groundwater modelling and climate models.
