The UK government has recently pledged to put around £14 billion into supporting the development of artificial intelligence over the next few years. But because AI comes with perils as well as promises, careful policy decision are going to be crucial. In order to make such decision in an informed way, politicians need to interact with the mathematicians and scientist who develop AI.
In this episode of Maths on the Move we talk to mathematician Chris Budd who recently went to Parliament for something called Evidence Week, where he and other AI researchers talked with MPs and Peers from the House of Lords. Chris tells us about the discussions he had with politicians — about the worrying issue of bias in AI, its promising applications, for example in the medical arena, and also about the fact that AI is built on mathematics. A strong maths education, starting at primary school, is therefore essential if we're going to make the best of AI in the future.
Chris Budd OBE is Professor of Applied Mathematics at the University of Bath, co-lead of the research project Maths4DL, and Director of Knowledge Exchange for the Bath Institute for Mathematical Innovation (IMI). He attended Evidence week with a team of researchers which included Yolanne Lee, a Maths4DL PhD student who recently featured in another Maths on the Move episode. The image above shows, from left to right, Dáire O'Kane (Maths4DL), Jenny Power (IMI), Yolanne Lee (Maths4DL), and Alexandra Freeman, Baroness Freeman of Steventon.
To find out more about some of the topics discussed in this episode see
- AI be the judge: The use of algorithms in the criminal justice system
- Can AI help with breast cancer screening?
- Maths4DL AI policy brief: Black boxes of AI - watch maths open them
This podcast was produced as part of our collaboration with the Mathematics for Deep Learning (Maths4DL) research programme. Maths4DL brings together researchers from the universities of Bath and Cambridge, and University College London and aims to combine theory, modelling, data and computation to unlock the next generation of deep learning. You can see more content produced with Maths4DL here.
