ACM-W Athena Lecture - Large-Scale Behavioral Data: Potential and Pitfalls.

Over the last decade, the rise of web services has made it possible to gather traces of human behavior in situ at a scale and fidelity previously unimaginable. Large-scale behavioral data enables researchers and practitioners to detect adverse drug reactions and interactions, to understand how information diffuses through social networks, how people browse and search for information, how individual learning strategies are related to educational outcome, etc. Using examples from search, I will highlight how observational logs provide a rich new lens onto the diversity of searchers, tasks, and interactivity that characterize information systems today, and how experimental logs have revolutionized the way in which web-based systems are designed and evaluated. Although logs provide a great deal of information about what people are doing, they provide little insight about why they are doing so or whether they are satisfied. Complementary methods from observations, laboratory studies and panels are necessary to provide a more complete understanding of and support for search which is increasingly a core fabric of people's everyday lives. The CHI community should lead the way in shaping best practices and policy in behavioral log studies. Susan Dumais is a Distinguished Scientist at Microsoft and Deputy Managing Director of the Microsoft Research Lab in Redmond. Prior to joining Microsoft Research, she was at Bell Labs and Bellcore, where she worked on Latent Semantic Analysis, techniques for combining search and navigation, and organizational impacts of new technology. Her current research focuses on user modeling and personalization, context and search and temporal dynamics of information. She has worked closely with several Microsoft product groups (Bing, Windows Desktop Search, SharePoint, and Office Online Help) on search-related innovations. Susan has published widely in the fields of information science, human-computer interaction and cognitive science, and holds several patents on novel retrieval algorithms and interfaces. Susan is also an adjunct professor in the Information School at the University of Washington. She is Past-Chair of ACM's Special Interest Group in Information Retrieval (SIGIR), and serves on several editorial boards, technical program committees, and government panels. She was elected to the CHI Academy in 2005, an ACM Fellow in 2006, received the SIGIR Gerard Salton Award for Lifetime Achievement 2009, was elected to the National Academy of Engineering (NAE) in 2011, and received the ACM Athena Lecturer Award, and Tony Kent Strix Award in 2014.