AI4Pandemics Talk #27: Adam Dunn, The University of Sydney
Title: What’s wrong with health misinformation research and how multidisciplinary research can fix it
Abstract: During the COVID-19 pandemic we saw a substantial increase in data-driven research on misinformation but there is a disconnect between applied machine learning and what is needed to make good local decisions about where to focus efforts or how to design localised communication interventions. Part of the reason is a disconnect between the goals of AI researchers and the needs of public health, and part is because of the challenge of working in multidisciplinary teams and communicating across disciplines. In this seminar, Adam will explain some of the study design flaws in the applied machine learning literature in the area, propose study designs that use machine learning and could be better suited to addressing the need for evidence in public health, and discuss some of the limitations associated with studies that require recruitment and participant involvemen
About AI4PAN Artificial Intelligence for Pandemics Seminar Series centred at UQ
Welcome to AI4PAN, the Artificial Intelligence for Pandemics group centered at The University of Queensland (UQ). The group's focus is the application of data science, machine learning, statistical learning, applied mathematics, computation, and other "artificial intelligence" techniques for managing pandemics both at the epidemic and clinical level.