About the Talk

‘Big Data’ fuels AI models like ChatGPT and the machine learning systems that are generating much debate about their promise – and peril – for decision-making. The impact of the technology will depend on the character of the data used. While the issue of data bias is well-understood (although not solved), less attention has been paid to other aspects such as data quality (is the data an accurate measure of the underlying object?), missing data (do we have only part of the picture?), and the meaning of data (how are the underlying concepts represented by the data constructed and interpreted)? As AI models are advancing fast enough to be deployed increasingly widely in society, there is a pressing need to reflect on the perspective on our social world created for them through the data on which they are trained and updated.

The Guest

Professor Diane Coyle is the Bennett Professor of Public Policy at the University of Cambridge. Diane co-directs the Bennett Institute where she heads research under the themes of progress and productivity. Her latest book is ‘Cogs and Monsters: What Economics Is, and What It Should Be‘ on how economics needs to change to keep pace with the twenty-first century and the digital economy.

Diane is also a Director of the Productivity Institute, a Fellow of the Office for National Statistics, an expert adviser to the National Infrastructure Commission, and Senior Independent Member of the ESRC Council. She has served in public service roles including as Vice Chair of the BBC Trust, member of the Competition Commission, of the Migration Advisory Committee and of the Natural Capital Committee. Diane was Professor of Economics at the University of Manchester until March 2018 and was awarded a CBE for her contribution to the public understanding of economics in the 2018 New Year Honours.