Emerging technologies such as artificial intelligence (AI), machine learning, and advanced data analytics both shape and are shaped by society, posing novel challenges that must be addressed across legal, ethical, and social dimensions.
As these technologies evolve, there is a need for robust, interdisciplinary research to ensure that they are governed in a cohesive way that maximizes societal benefits while minimizing harm.
Legal, ethical, and technological experts must come together to develop solutions that are not only legally sound but also morally responsible and technically feasible.
Professor of Data Ethics and Policy
Professor Brent Mittelstadt is a data ethicist and philosopher specializing in AI ethics, professional ethics, and technology law and policy. He is the founder/coordinator of the Governance of Emerging Technologies (GET) programme.
Professor of Technology and Regulation
Professor Sandra Wachter is Professor of Technology and Regulation focusing on law and ethics of AI, Big Data, and robotics as well as Internet regulation at the Oxford Internet Institute at the University of Oxford
Dieter Schwarz Associate Professor, AI, Government & Policy.
Chris Russell is the Dieter Schwarz Associate Professor, AI, Government and Policy. Dr Russell’s work lies at the intersection of computer vision and responsible AI.
Within the Governance of Emerging Technologies (GET) research group, we investigate the governance of new technologies through an inclusive, interdisciplinary lens. Our work spans law, philosophy, computer science, and related disciplines, and focuses on how to design, deploy and govern emerging technologies.
Our research projects address critical issues such as:
These challenges demand expertise not just in law and ethics but also in the technical aspects of AI and machine learning. Our interdisciplinary approach ensures that we consider these issues from multiple perspectives, including legal requirements, ethical considerations and technical feasibility.
Through interdisciplinary research and collaboration, we are working to ensure that powerful emerging technologies are developed and deployed for the public good.
Our work has been recognised through awards such as Cognition X, the Computer Weekly Awards, the Privacy Law Scholars Conference (PLSC), and the O2RB Excellence in Impact Awards. Our research on AI explainability has been cited in influential reports on data governance by the UK Government and European Commission. The counterfactual explanation method we developed has been implemented by leading tech companies like Google, Vodafone, IBM, and Accenture. Our proposal for a ‘right to reasonable inferences’ to protect privacy in the era of big data was cited in discussions on the GDPR and featured in the UK’s 2021 Research Excellence Framework (REF). Additionally, our fairness measure, ‘conditional demographic disparity,’ has shaped the EU Artificial Intelligence Act and been adopted by Amazon in their cloud computing and machine learning products.
Through our research, we continue to inform policy, influence international discussions on technology ethics, and provide practical solutions for designing AI systems that are fair, accountable, and transparent.
This programme supports research on AI, Government and Policy.
This project will evaluate the effectiveness of accountability tools addressing explainability, bias, and fairness in AI. A ‘trustworthiness auditing meta-toolkit’ will be developed and validated via case studies in healthcare and open science.
This OII research programme investigates legal, ethical, and social aspects of AI, machine learning, and other emerging information technologies.
PhD Student, University of Reading
Lizzie is Associate Medical Director at Annalise.AI, a former NHS doctor and also a PhD student at the University of Reading. She has a particular interest in the clinical use of medical imaging AI.
DPhil Student
Ben is a part-time DPhil (PhD) student at the University of Oxford, researching the ethics and governance of agentic artificial intelligence.
Former Research Associate
Fyonna Boateng is a Psychology undergraduate at the University of Reading. With Dr. Netta Weinstein, she is investigating public opinions of AI and its potential biases.
DPhil Student
Ryan is a DPhil student at the Oxford Internet Institute, focused on AI fairness, with research interests in technical fairness methodologies, NLP, and deep learning.
Former Recognised Student
Sofie is a Recognized Student at the OII. Her research is focused on ethical machine learning.
DPhil Student
Will is a part-time DPhil student in Information, Communication and the Social Sciences at the OII. Will’s research focuses on examining the safety impacts of fine-tuning on generative models.
Departmental Research Lecturer
Johann Laux works at the intersection of law and the social sciences. His current research is interested in the governance of emerging technologies as well as the design of institutions.
Former Postdoctoral Researcher
Prashan Madumal is a computer scientist specialising in Artificial Intelligence. His work mainly focuses on Explainable and Trustworthy AI, Reinforcement learning and Causal Learning.
Former Research Associate
Silvia is a philosopher interested mainly in epistemology and ethics of Artificial Intelligence, working with Dr Brent Mittelstadt.
DPhil Student
Mathilda is a DPhil candidate at the Oxford Internet Institute. Her research focuses on AI systems deployed in explicitly social settings (Social AI), like companion chatbots, sexbots, or griefbots.
Research Associate
Dr Daria Onitiu researches and publishes on the legal, ethical and governance aspects surrounding Artificial Intelligence (AI) technologies, generative AI and deepfakes.
Former Recognised Student
Paula Pedigoni Ponce is a Recognised Student at the OII. Her research is focused on the regulation of health personal data in Brazil.
Former MSc Student
Trisha was an OII Rhodes Scholar interested in building tech and policy to counter harmful online speech. She is the inventor of ReThink, an anti-hate app, and holds a BA in Gov & Tech Science from Harvard.
DPhil Student
Kaivalya worked on AI explainability and fairness at Oxford. He built upon his work auditing and testing machine learning models in industry and in academia, making AI systems safe and trustworthy.
DPhil student
Former Visiting Research Fellow
Yashwinie Shivanand is a Visiting Research Fellow in ethical artificial intelligence, specializing in trustworthy AI policy and practice.
Former Recognised Student
Jake is a PhD candidate in philosophy with the Australian National University and a Recognised Student at the Oxford Internet Institute.
Former Research Associate
Dr Anna Tovmasyan is currently working to systematically examine the factors that shape trustworthiness in healthcare technology, as well as value-based decision-making regarding transparency in communication about potential bias in AI applications.
Research Associate
Netta Weinstein is a professor of clinical and social psychology at the University of Reading. She studies human motivation, behaviour and well-being in collaboration with Professors Wachter and Mittelstadt.
Research Associate
Zihao Fu was in the Trustworthiness Auditing for AI project. His research interests included Natural Language Processing, Large Language Model, Machine Learning, Biomedical Applications, Large Language Model safety fairness among other areas.
Research Associate
7 May 2025
New Oxford study uncovers explosion of accessible deepfake AI image generation models intended for the creation of non-consensual, sexualised images of women.
19 August 2024
Professor Sandra Wachter highlights the regulatory loopholes in EU AI legislation and proposes how these can be closed to address key ethical issues around the development of AI.
7 August 2024
Leading experts in regulation and ethics at the Oxford Internet Institute, part of the University of Oxford, have identified a new type of harm created by LLMs which they believe poses long-term risks to democratic societies and needs to be addressed
