Digital Health Equity seminar: An introduction to algorithmic fairness
| Dates: | 13 November 2024 |
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| Times: | 13:00 - 14:00 |
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| What is it: | Seminar |
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| Organiser: | The Christabel Pankhurst Institute |
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| Who is it for: | University staff, External researchers, Adults, General public |
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The next seminar in the Digital Health Inequities Seminar Series is on 13th of November 1-2pm via Zoom: https://zoom.us/j/96704384543. Matt Sperrin and Jose Benitez-Aurioles will provide “An introduction to algorithmic fairness”.
Abstract
Fairness can be defined as ' 'the absence of any prejudice or favouritism toward an individual or a group based on their inherent or acquired characteristics'. The role of fairness in the development and implementation of statistical and machine learning algorithms has now been studied for some years, with origins in insurance pricing and recidivism. In healthcare (as is often the case!) things become more complex, and determining whether an algorithm is 'fair' or not becomes a difficult and nuanced question. In this talk we will begin by explaining some of the common ways that algorithmic fairness is assessed, and some of the challenges with them, with examples. Jose will then give a focused example of some latest work in understanding algorithmic fairness from the perspective of the benefit that an algorithm bestows on individuals or (protected) groups.
Speakers’ biography
Matthew Sperrin is a senior lecturer in health data science at the University of Manchester. He is a statistician by background with a PhD from Lancaster University. His main current research interest concerns the role of causal inference in supporting prediction. One application of this is in understanding the role of fairness in prediction models.
Jose Benitez-Aurioles is a PhD student in the University of Manchester, working in clinical prediction models. His work is focused on developing methodological approaches to make these models more in line with health equity principles, with applications to current UK lung cancer screening efforts and type-2 diabetes prognosis.
Travel and Contact Information
