6: Using Data to Address Inequities in Healthcare with Muhammad Ahmad

In this episode of the Podcast, Seth interviews Muhammad Ahmad. Muhammad is an Affiliate Assistant Professor in the Department of Computer Science at University of Washington and a Research Scientist at KenSci. His research areas are machine learning in healthcare, accountability and ethics in AI. His recent work is focused on foundations of machine learning and cross-cultural perspectives on AI. Muhammad’s work combines academic rigor with extensive experience in deploying machine learning systems at scale in the healthcare sector and thus first-hand knowledge of many moral and ethical dilemmas that come with it. He has published over 50 research papers in machine learning and artificial intelligence. He has a PhD in Computer Science from University of Minnesota. This episode will be the second part of our look at race and healthcare.


In this interview, Seth and Muhammad explore a variety of topics. Muhammad talks about how he eventually turned his focus towards healthcare, specifically addressing discrepancies in care between different ethnic groups. He explains many technical problems in machine learning, including the challenges to applying different definitions of fairness. The key questions to this episode are: how has data served to both obscure and to illuminate discrepancies on healthcare? How can machine learning enhance our understanding of complex social problems?