Emre Kazim

Emre Kazim is a research fellow in the computer science department of University College London, working in the field of AI ethics. His current focus is on governance, policy and auditing of AI systems, including algorithm interpretability and certification. Emre has a PhD in philosophy.

projects by Emre Kazim

Mitigate Machine Learning Bias in Mortgage Lending Data

4 weeks · 5-9 hours per week average · INTERMEDIATE

In this series of liveProjects, you’ll apply techniques for measuring and mitigating bias in a machine learning algorithm. You’ll step into the role of a data scientist for a bank, and investigate the potential biases that arise when automated decision-making is applied to your company’s mortgage offers—in particular, whether your algorithm is biased by gender. Each project in this series covers a different aspect of fairness measurement and intervention, including exploring a dataset with a focus on fairness, and mitigating bias in a logistic regression model.