AI for atoms

Go back to programme

AI for atoms

Co-organized by the International Atomic Energy Agency (IAEA) and the International Telecommunication Union (ITU), this webinar will dive into the potential of AI to help accelerate the safe, secure and peaceful uses of nuclear science, technology and applications and aid progress towards the United Nations’ Sustainable Development Goals.

The event will showcase the ways in which AI-based approaches in nuclear science and applications have the potential to advance cancer staging in nuclear medicine and cancer treatment through radiotherapy; optimize remediation of radioactive contamination in agriculture; as well as accelerate progress in nuclear fusion and science research. It will also provide an insight into the AI-associated challenges, including issues of transparency, trust and security, and other ethical concerns.

Georg Lang will talk about machine learning in medical imaging for the prediction of individual disease course and treatment response. The talk will discuss the role of methods to identify new prognostic markers, and how machine learning can become part of the clinical reality.

To make agri-food systems sustainable and climate change resilient, decision-making about agriculture approaches and food production requires gathering extensive information at all scales. We have observed these last years that enhanced data availability through the implementation of open data policies and innovative data acquisition methods now enables the use of Artificial Intelligence to inform policies. This talk, through some examples of the use of Artificial Intelligence techniques in applications, such as the estimation of soil moisture through nuclear techniques, but also the remediation of environmental pollution, and the prediction of food fraud events, will present opportunities already in hand but also key aspects that still need to be considered to fully exploit the potential of Artificial Intelligence in Food and Agriculture applications.

Michelle Kuchera will give an overview of applications of AI and machine learning methods to nuclear physics research, ranging from data analysis, processing and management, to experimental design and optimization and facility operation.

 

Nuclear fusion is the process that powers the stars and could provide us with virtually unlimited clean energy for centuries to come. Lots of efforts are being made worldwide to overcome the scientific and technological challenges on the path to an electricity-producing power plant. In recent years, Machine Learning and Artificial Intelligence have greatly accelerated the progress in the field: this talk will provide some insights on how AI has boosted Nuclear Fusion progress and what are some of the most outstanding community gatekeepers when dealing with AI applications in Fusion.

Emma Ruttkamp-Bloem and Behnam Taebi will critically reflect on a new domain of normative applied ethics at the intersection of AI and nuclear technologies and applications which they refer to as the Ethics of Nuclear and AI (ENAI). This talk will provide some overview of the nature of and ways to mitigate ethical concerns in this new domain.

Share this session
In partnership with
Scroll Up