Colloquium: Bias Mitigation Methods: Applicability, Legality, and Recommendations for Development

Title: Bias Mitigation Methods: Applicability, Legality, and Recommendations for Development

Abstract: As algorithmic decision-making systems (ADMS) are increasingly deployed across various sectors, the importance of research on fairness in Artificial Intelligence (AI) continues to grow. In this talk, we discuss the practical limitations and regulatory challenges associated with the application of existing bias mitigation methods to ADMS.  Our analysis of existing methods indicates a pressing need for a change in the approach to the development of new methods. We provide recommendations for key factors to consider in the development of new bias mitigation methods that aim to be effective in real-world scenarios and comply with legal requirements in the European Union, United Kingdom and United States, such as non-discrimination, data protection and sector-specific regulations.

Bio: Madeleine Waller is a PhD researcher at King’s College London in the UKRI Safe and Trusted AI Centre for Doctoral Training. Her research focuses on the fairness of algorithmic decision-making systems. Madeleine’s main interest is in AI policy, specifically around preventing the use of discriminatory AI systems. She is also an Affiliate of the King’s Institute for Artificial Intelligence and was previously part of an Enrichment Scheme at The Alan Turing Institute and worked on projects funded by the European Lighthouse on Secure and Safe AI.