The Statistical Methods for Health Equity Series is a monthly online series co-hosted by the Data Science for Health Equity community, the Alan Turing Institute Health Equity Interest Group, and the Department of Statistical Science at University College London.

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We are excited to announce next week's instalment of our webinar series with speaker Dr Wiebke Hutiri from SONY AI . 

Dr Hutiri will be joining us to explore some discussions around trustworthy AI and the responsible design patterns that can lead us there.

Specific details on the topic are as below:

Topic: 

Responsible Design Practices for Trustworthy AI: A Design Patterns Approach

Abstract:

Many recent incidents of bias and discrimination in AI systems caution that algorithmic prediction and generation should be scrutinised when used in real-world applications. To this end, the EU’s Trustworthy AI guidelines require that AI systems are inclusive, non-discriminatory and applicable to diverse users. However, realising fair and non-discriminatory AI in real-world applications is difficult. In particular, many engineers encounter challenges when trying to detect and mitigate bias. Algorithmic approaches to bias detection and mitigation have been well explored in the literature, but fall short of offering practical guidance to engineers, developers and designers. In this talk Dr Hutiri will present design patterns as a solution for capturing knowledge on how to  detect and mitigate bias in the development of AI systems. Beyond offering a novel solution to a practical problem, the design patterns expand the algorithmic perspective on AI fairness to responsible design practices that account for the socio-technical realities of developing AI systems.

Speaker Biography:

Wiebke Hutiri is an applied computer scientist working on trustworthy AI, with a focus on responsible design practices. She works as a research scientist at Sony AI, where she focuses on evaluation and benchmarking of AI systems. Wiebke’s research seeks to address the limitations of AI systems once deployed to anticipate risks, mitigate harms and ensure that AI technology aligns with societal values. Wiebke obtained her PhD from the faculty of Technology, Policy and Management at Delft University of Technology in the Netherlands. She received a Mozilla Technology Fund Award to support her work on fairness in voice technologies, and is a fellow of the Heidelberg Laureate Forum Young Researchers, the Data Science for Social Good Initiative and Diverse Intelligences Summer Institute.

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Please direct any questions about the webinar series to Dr Brieuc Lehmann at b.lehmann@ucl.ac.uk.