The Arctic is undergoing rapid changes due to climate change, making sea ice forecasting increasingly important. In this episode of the Turing Podcast, hosts Amelia Jabry and Dr. Sophie Arana discuss the critical role of AI models like IceNet in predicting sea ice conditions and aiding conservation efforts. Featuring Dr. Ellie Bowler from the British Antarctic Survey, the conversation dives into the technical details of IceNet, its applications for wildlife conservation, and the challenges of predicting sea ice dynamics. The discussion also covers the importance of these predictions for indigenous communities and wildlife that rely on the frozen Arctic landscape. Learn how AI is revolutionising our approach to these urgent environmental challenges.

Read more about our environmental forecasting work here: https://www.turing.ac.uk/blog/democratising-environmental-forecasting-age-ai

Explore IceNet: https://icenet.ai/

Find out more about Dr Ellie Bowler's publications: https://www.bas.ac.uk/profile/eller/

Read more about Dr Sophie Arana here: https://www.turing.ac.uk/people/dr-sophie-arana

Chapters:

00:00 Introduction to Arctic Climate Change 00:39 Meet the your host Amelia and co-host Dr Sophie Arana 00:57 Understanding the Role of a Research Application Manager 01:47 Introduction to ICE Net 02:47 AI vs. Traditional Physics-based Forecasting Models 03:40 Human Expertise and AI Collaboration 04:56 Introducing Dr. Ellie Bowler and her sea ice and caribou migration forecasting research 06:21 Challenges in Sea Ice Forecasting 10:01 Caribou Migration and Conservation 12:30 Impact of Human Activities on Arctic Wildlife 16:38 Innovative Conservation Methods 23:25 Future of ICE Net and AI in Conservation 26:54 Conclusion and Further Resources

Navigating Change: AI in Arctic Sea Ice Forecasting