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Professor Brent Mittelstadt

Director of Research, Associate Professor, Senior Research Fellow

Brent Mittelstadt

Director of Research, Associate Professor, Senior Research Fellow



Professor Brent Mittelstadt is the OII’s Director of Research, an Associate Professor and Senior Research Fellow. He also coordinates of the Governance of Emerging Technologies (GET) research programme which works across 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.

In his current role he leads the Trustworthiness Auditing for AI project, a three-year multi-disciplinary project with University of Reading cutting across ethics, law, computer science, and psychology to determine how to use AI accountability tools most effectively to create and maintain trustworthy AI systems. He also co-leads the A Right to Reasonable Inferences in Advertising and Financial Services project which examines opportunities and challenges facing sectoral implementation of a right to reasonable inferences in advertising and financial services. 

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 (PLSC) for his work on the ‘right to reasonable inferences’ in data protection law.  

Professor Mittelstadt has substantial experience in leading and coordinating multi-disciplinary work across large-scale, multi-partner projects.  His work has been funded by a variety of fellowships including a British Academy Postdoctoral Fellowship as well as research grants from funders such as the Wellcome Trust, Department of Health and Social Care, Sloan Foundation, Miami Foundation, and Luminate Group. In addition to his current roles, Professor Mittelstadt previously led a team of researchers on the ROADMAP project working on the ethics and governance of a pan-European data platform for Alzheimer’s research. He also led work on the ‘Privacy and Trust’ stream as part of the EPSRC PETRAS National Centre of Excellence for loT Systems Cybersecurity. 

Research Interests

Ethics; data ethics; moral philosophy; applied ethics; AI ethics; professional ethics; medical ethics; technology governance and policy; data protection law; non-discrimination law; fairness, accountability, and transparency in machine learning; medical expert systems; epistemology

Positions at the OII

  • Associate Professor, June 2022 -
  • Director of Research, April 2022 -
  • Senior Research Fellow, September 2019 -
  • British Academy Postdoctoral Fellow, January 2018 - June 2021
  • Research Fellow, January 2018 - August 2019
  • Research Associate, October 2014 - February 2017


Integrity Statement

In the past five years my work has been financially supported by the Wellcome Trust, Sloan Foundation, Department of Health and Social Care via the AI Lab at NHSx, British Academy, John Fell Fund, Alan Turing Institute, Engineering and Physical Sciences Research Council, Miami Foundation, and Luminate Group. As part of my science communication and policy outreach, I have served in an advisory capacity for the Office for National Statistics, Fable Data, Mind Foundry, and GSK Consumer Healthcare.

I conduct my research in line with the University's academic integrity code of practice.



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Current Courses

Foundations of Social Data Science

This course will introduce to some of the fundamental questions that have been raised in this domain across the social sciences.