Associate Professor Jana Diesner will present her research on biases in data science at the Big Data Summit, which will be held virtually on November 12. The annual summit brings together experts from the University of Illinois Research Park, industry, and academia to share knowledge about big data and its business applications through panel discussions, keynote presentations, and networking opportunities. This year's summit will include sessions on machine learning, artificial intelligence, and digital transformation.
"Using computational methods, such as techniques from machine learning and AI, for studying social structure and behavior requires scholars and practitioners to make a plethora of unavoidable choices," said Diesner. "This includes choices about how to sample, index, and preprocess data, implement algorithms, measure effects, and validate results."
In her talk, Diesner will present findings from her group's research on assessing the impact of some of these choices on our understanding of social systems, give an overview on sources of potential biases, and suggest strategies for mitigating biased insights.
Diesner's research in human-centered data science and responsible computing combines the benefits of machine learning, AI, network analysis and natural language processing with the consideration of social science theories, social contexts, and ethical concerns. At the University of Illinois, recognition for her research expertise includes a Linowes Fellowship from the Cline Center for Advanced Social Research, an R.C. Evans Data Analytics Fellowship from the Deloitte Foundation Center for Business Analytics, and an appointment as the CIO Scholar for Information Research & Technology. She holds a PhD in computation, organizations and society from Carnegie Mellon University's School of Computer Science.