Speaker: Emily Wall (Emory University)
Abstract: Recent high-profile scenarios have demonstrated that, in spite of the “data” in data-driven decision making, analysis practices nonetheless can lead to poor outcomes, given numerous junctures where bias can be introduced. Data may contain culturally embedded biases, algorithms may propagate or exacerbate those biases, and people’s decisions can be influenced by their own cognitive biases. While it is not yet possible to completely remove these varying biases from data analysis, some techniques exist to mitigate the effects by providing guidance or other forms of intervention. In this talk, I describe the development of complementary measures and mitigation strategies for addressing human biases: via perspectives on awareness, behavior, and decisions. This talk will detail recent and ongoing work in the Cognition and Visualization Lab at Emory University on metacognitive awareness of biases, observable and interruptible behavioral patterns, and resulting decisions that contribute to biased analysis processes. Interventions can thus lead to more socially responsible and conscientious data analysis practices.
Bio: Emily Wall is an Assistant Professor in the Computer Science Department at Emory University where she directs the Cognition and Visualization Lab. Her research interests lie at the intersection of cognitive science and data visualization. Particularly, her research has focused on increasing awareness of unconscious and implicit human biases through the design and evaluation of (1) computational approaches to quantify bias from user interaction and (2) interfaces to support visual data analysis. Her research has been funded by the National Science Foundation and Emory Office of the Provost on Racial Justice and Racial Equity.
