Anjali Mazumder is the Theme Lead on AI and Justice & Human Rights. Her work focuses on empowering government and non-profit organisations by co-designing and developing responsible and inclusive data and AI methods, tools and frameworks for safeguarding people from harm – particularly those most vulnerable, building resilient institutions and systems, and accelerating the opportunity for inclusive, fair and just services, systems, economies, and communities. She is passionate about fostering multi-disciplinary collaborations and multi-sector partnerships to co-create pathways for innovation that improves services, policy, and actions to safeguard human rights and address humanitarian challenges. Her research interests are in developing integrated Bayesian decision support systems to manage uncertainty with complex data structures, value of evidence, causal reasoning in the wild; expert judgement; detecting bias and algorithmic fairness; socio-technical solutions to harnessing multiple disparate sources of data whilst enabling responsible and inclusive data and AI principles and practices; communicating uncertainty and risk; and safeguarding rights and the Rule of Law.
She has over 15 years’ experience tackling fundamental statistical problems of societal importance – human rights, justice, security, the Law, education, public health & safety – working at the interface of research, policy and practice in the UK, the US, and Canada, fostering multi-disciplinary and cross-sector collaborations. She was appointed to Canada’s National DNA Databank Advisory Committee (2012-2018) and currently serves on the UK Forensic Science Regulator’s fingerprint interpretation subgroup, and the senior management board of the UK’s Policy and Evidence Centre for Modern Slavery and Human Rights. She has also served the Royal Statistical Society in a variety of ways, most recently appointed to the Statistics & Law Section and the Data Science Section committees. She holds a doctorate in Statistics from the University of Oxford and two masters’ degrees in Measurement and Evaluation, and Statistics from the University of Toronto.