Dr. Adrian Weller

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Adrian Weller

Position

Head of Safe and Ethical AI, Turing AI Acceleration Fellow

Partner Institution

University of Cambridge

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Research areas

Social data science Privacy & trust Statistical methods & theory High dimensional inference Causality Combinatorics Computer systems & architectures Human computer interface Artificial intelligence Neural networks Applied mathematics Information theory (Applied mathematics) Machine learning Reinforcement learning Unsupervised learning Supervised learning Semi-supervised learning Pattern recognition Deep learning Computer vision Applications (Machine learning)

Bio

Adrian Weller is a Head of Safe and Ethical AI at The Alan Turing Institute, the UK national institute for data science and AI, and a Turing Fellow. Adrian is a Director of Research in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society.  He serves on several boards, and previously served on the advisory board for the Centre for Data Ethics and Innovation. He received an MBE for services to digital innovation in 2022. Previously, Adrian held senior roles in finance.

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Research publications

Racial Disparities in the Enforcement of Marijuana Violations in the US

Racial disparities in US drug arrest rates have been observed for decades, but their...

Bradley Butcher, Chris Robinson, Miri Zilka, Riccardo Fogliato, Carolyn Ashurst, and Adrian Weller. 2022. Racial Disparities in the Enforcement of Marijuana Violations in the US. In Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (AIES '22). Association for Computing Machinery, New York, NY, USA, 130–143. https://doi.org/10.1145/3514094.3534184
Research publications

Fairness Without Demographic Data: A Survey of Approaches

Detecting, measuring and mitigating various measures of unfairness are core aims of algorithmic fairness...

Carolyn Ashurst and Adrian Weller. 2023. Fairness Without Demographic Data: A Survey of Approaches. In Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO '23). Association for Computing Machinery, New York, NY, USA, Article 14, 1–12. https://doi.org/10.1145/3617694.3623234