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Sandra Wachter
Transform AI governance with Sandra Wachter, speaker on algorithmic ethics and technology regulation. Sandra helps organisations implement explainable AI and combat algorithmic bias, recognized by major tech companies including Google, IBM, and Microsoft for her award-winning research.
Professor Dr Sandra Wachter is a leading authority on the legal and ethical challenges of artificial intelligence, big data, and emerging technologies. As Professor of Technology and Regulation at the University of Oxford’s Oxford Internet Institute, she leads research on AI governance, algorithmic bias, and the societal impact of machine learning. Her work informs global policy discussions and shapes regulation and ethical standards for AI and platform governance.
Professor Wachter's academic contributions are widely recognised. She has been published in journals such as Nature and Science and is frequently cited in major media outlets, including The New York Times, The Guardian, and the BBC. Her insights have been featured in documentaries and reports examining the broader impact of AI on society.
Professor Wachter has held positions at Harvard Law School and the Alan Turing Institute and is affiliated with the Oxford Martin School and the Berkman Klein Center at Harvard. Her work has earned several prestigious awards, including the Alexander von Humboldt Foundation Research Award and the Privacy Law Scholar Award.
Professor Wachter’s work has also made significant real-world impact. Her work on opening the ‘AI Blackbox’ to increase accountability, transparency, and explainability has been widely successful. Her explainability tool – Counterfactual Explanations – has been implemented by major tech companies such as Google, Accenture, IBM, Microsoft, Arthur, and Vodafone.
Professor Wachter has also contributed to major developments in combating bias. She developed a bias test (‘Conditional Demographic Disparity’ or CDD), which Amazon and IBM have since implemented in their cloud services. In 2024, CDD was used to uncover systemic bias in education in the Netherlands. The Dutch Minister for Education, Culture and Science apologised for indirect discrimination and is now working to improve the algorithmic system in question as a result.
Professor Wachter's paper The Unfairness of Fair Machine Learning also revealed the harmful impact of enforcing many ‘group fairness’ measures in practice by making everyone worse off, rather than helping disadvantaged groups. The NHS and the Medicines and Healthcare products Regulatory Agency (MHRA) are now using these findings internally to revise practices for licensing medical devices to ensure equal and safe access to medical care.
Topics, sessions and talks
In this talk, Professor Sandra Wachter will explore the legal and ethical challenges posed by artificial intelligence. She will discuss key issues such as data privacy, accountability, and bias in AI systems. Attendees will gain insights into the regulatory landscape and the implications for businesses and society. By the end of the session, participants will have a clearer understanding of how to navigate the complexities of AI in a responsible manner.
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frequently asked questions
Something we've not covered here?
To book Sandra Wachter, email sandra.wachter@getapeptalk.com or call PepTalk on +44 20 3835 2929 (UK) or +1 737 888 5112 (US), and one of our speaker agents will contact you within hours to confirm Prof Sandra's availability and speaking fee. If you can, please include your budget upfront – it helps us fast-track your request. It’s also helpful to know the date, format (virtual or in-person), location, and about your audience.
Sandra Wachter structures her talks around the legal and ethical frameworks governing AI, drawing on her own peer-reviewed research — including her bias test Conditional Demographic Disparity and her explainability tool Counterfactual Explanations — to illustrate how regulatory and technical decisions produce measurable real-world outcomes.
Professor Sandra Wachter specialises in the legal and ethical challenges of AI, covering data privacy, accountability, algorithmic bias, and AI governance and regulation. She holds a professorship in Technology and Regulation at the University of Oxford's Oxford Internet Institute, and her bias detection tool, Conditional Demographic Disparity, has been adopted by Amazon and IBM in their cloud services.
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