Join renowned artificial intelligence authority Sir Nigel Shadbolt for an exclusive exploration of the critical issues shaping data and AI today.
Chaired by the Open Data Institute’s Head of Research, Dr. June Brawner, this accessible webinar welcomes participants of all backgrounds and includes a live Q&A session.
Speakers
Sir Nigel Shadbolt is Executive Chair of the Open Data Institute, which he co-founded with Sir Tim Berners-Lee in 2012. He is one of the UK’s foremost computer scientists. Sir Nigel was one of the originators of the interdisciplinary field of web science and is a leading researcher in artificial intelligence. He is the Chair of AI@Oxford Research at the University of Oxford, having previously been the Principal of Jesus College, Oxford, and is a visiting Professor of Artificial Intelligence at the University of Southampton.
In 2009, the Prime Minister, Gordon Brown, appointed him and Sir Tim Berners-Lee as Information Advisors to transform access to Public Sector Information. This work led to the data.gov.uk site that now provides a portal to tens of thousands of datasets. In 2010, he joined the UK government’s Public Sector Transparency Board, overseeing Open Data releases across the public sector. He continues to advise the Government in a number of roles and in 2025 he was appointed to the Council for Science and Technology, which advises the Prime Minister and the Cabinet on strategic science and technology policy issues that cut across the responsibilities of individual government departments.
In May 2024 he published ‘As If Human: Ethics and Artificial Intelligence’, co-written with Roger Hampson, which provides a new approach to the challenges surrounding AI.
He is a Fellow of the Royal Society and the Royal Academy of Engineering, and a Fellow and former President of the British Computer Society. He was knighted in 2013 for ‘services to science and engineering’.
Dr June Brawner is the Head of Research at the Open Data Institute. June is an anthropologist of data, studying how societies create knowledge through data, measurement and AI.
Her work explores how data, metrics and classification systems are created; what they make visible, what they leave out, and how these choices shape decisions across science, policy and public life.