Adrian Weller
Adrian Weller researches machine learning and its social effects, including explainability, fairness, privacy, robustness and safety. His papers examine why transparency is useful in some settings, how uncertainty can help people understand predictions and how algorithmic tools are governed in criminal justice. He has conducted research at Cambridge and held leadership roles at the Alan Turing Institute and the Leverhulme Centre for the Future of Intelligence. He received an MBE in 2022 and served as an ICML program chair in 2024.
- Now at
- University of Cambridge and Alan Turing Institute
- Works
- 259
- Citations
- 6,031
- h-index
- 37
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
-
2017
Ask what transparency is for
Weller’s survey Transparency: Motivations and Challenges examines different reasons for making intelligent systems understandable. It discusses context, measurement and settings where disclosure can cause harm, connecting transparency with privacy, economics, fairness and trust.
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2020
Communicate uncertainty
He coauthored Uncertainty as a Form of Transparency. The study examines how uncertainty can be measured, communicated and used, extending the question of understandable AI beyond explanations of individual predictions.
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2022
Study governance of criminal-justice tools
With Miri Zilka and Holli Sargeant, Weller examined transparency, governance and regulation of algorithmic tools in the UK criminal justice system. This connects technical scrutiny with institutional decisions about AI use.
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2022–2024
Research leadership and public service
He received an MBE for digital innovation in 2022 and served as ICML program chair in 2024. He has conducted research at Cambridge and held a leadership role at the Turing Institute, linking trustworthy machine learning research with public and scientific institutions.
Sources and credits
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