Miri Zilka is a Research Associate in the Machine Learning Group at the University of Cambridge where she works on Trustworthy Machine Learning. Her research centres around the deployment of algorithmic tools in criminal justice. Before coming to Cambridge, she was a Research Fellow in Machine Learning at the University of Sussex, focusing on fairness, equality, and access. Miri obtained a PhD from the University of Warwick in 2018. She holds an M.Sc. in Physics and a dual B.Sc. in Physics and Biology from Tel Aviv University.
Miri was awarded a Leverhulme Early Career Fellowship to develop a human-centric framework for evaluating and mitigating risk in causal models, set to start in May 2022. She is a College Research Associate at King’s College Cambridge and is currently on a part-time secondment to the Alan Turing Institute.
This blog was written by Dr Miri Zilka, a CFI Associate Fellow. It is based on her paper, Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement, co-authored with Caitlin Kearney, Jiri Hron and Helen Kosc, published on June 3, 2024 and presented asynchronously at FAccT 2024. In an era of shrinking budgets and […]
