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Professor Stephen Roberts is Royal Academy of Engineering/Man Group Professor of Machine Learning in the Department of Engineering Science and Director of the Oxford-Man Institute of Quantitative Finance.

Areas of interest

Theory and methodology of machine learning for problems in the sciences, industry and the finance sector, especially those in which noise and uncertainty abound.

What makes Oxford such a good place to work in AI?

Machine learning is intrinsically broad in its academic foundation. Its core lies in deep understanding of mathematics and statistics; its pervasive use requires novel programming environments and concepts to flexibly respond to uncertain data at scale; its application requires the fusion of deep domain expertise into the artificial intelligences of the future. Oxford is rich in the breadth of its talent across all these domains, from probabilistic numerics to big data, from the theory of inference to meaningful industrial engagement.

What is the biggest opportunity or challenge in AI?

This is very personal, so no one answer is correct. For me, scale (how do we use AI at global data scales?); honesty (how do we make AI work with uncertainties at all levels, and communicate such ignorance when necessary?); bias and fairness (how do we ensure that AI doesn’t amplify cultural data bias at scale?); interpretability (how do we make sure AI can explain big decisions?); the ability to augment human capability (how do we ensure that AI works with us, not ignoring human expertise and experience?); and privacy (how do we ensure privacy in a world of big data and big inference?).

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