Professor Brent Mittelstadt

About

Brent Mittelstadt is Professor of Data Ethics and Policy and Director of Research at the Oxford Internet Institute, University of Oxford. He also coordinates the Governance of Emerging Technologies research programme which operates at the crossroads of ethics, law, and emerging information technologies. He is a leading data ethicist and philosopher specializing in AI ethics, professional ethics, and technology law and policy.

Professor Mittelstadt is the author of highly cited works across topics including the ethics of algorithms, artificial intelligence (AI), and Big Data; fairness, accountability, and transparency in machine learning (ML); data protection and non-discrimination law; group privacy; ethical auditing of automated systems; digital epidemiology and public health ethics; and ethical design of personal health monitoring technologies.

Across these areas he has contributed several key policy analyses, technical fixes, and ethical frameworks to address the most pressing risks of emerging data-intensive technologies. These include (1) legal analysis of the enforceability of a “right to explanation” of automated decisions in the General Data Protection Regulation (GDPR); (2) the development of a method and ethical requirements for providing “meaningful explanations” of automated decisions in the form of ‘counterfactual explanations’; (3) a novel, legally compliant fairness metric to detect bias in AI and machine learning systems (‘Conditional Demographic Disparity’); and (4) a classification scheme for fairness metrics based on non-discrimination law. These contributions are widely cited and have been implemented by researchers, policy-makers, and industrial bodies internationally, featuring in policy proposals and guidelines from the UK government, Information Commissioner’s Office, and European Commission, as well as products from Google, Amazon, and Microsoft.

Professor Mittelstadt is the recipient of several prestigious awards recognising the impact of his work on scholarship, policy, and society. In 2018 and 2021 he received O2RB Excellence in Impact Awards for his work on explanations in AI, counterfactual explanations, and AI fairness and bias in non-discrimination law. In 2019 he was delighted to receive the best paper award at the Privacy Law Scholars Conference for his work on the ‘right to reasonable inferences’ in data protection law.