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Improving Prediction of Human Behaviour Using Behaviour Modification
The fields of machine learning and statistics have invested great efforts into designing algorithms, models, and approaches that better predict future observations. While machine learning algorithmic and data efforts are directed at improving predicted values, the internet platforms can minimize prediction error by "pushing" users' actions towards their predicted values using behavior modification techniques. The better the internet platform is able to make users conform to their predicted outcomes, the more it can boast both its predictive accuracy and its ability to induce behavior change.
Our formulation and derivation make transparent the impact and implications of such behavior modification to data scientists, internet platforms and their clients, and importantly, to the humans whose behavior is manipulated.

25/03/2021 10:00 (Israel Time) / 16:00 (Taiwan Time)

Mar 25, 2021 10:00 AM in Jerusalem

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Galit Shmueli, PHD
Distinguished Professor and Institute Director @National Tsing Hua University, Taiwan
Professor Shmueli obtained her PhD from the Technion in 2000. Before joining NTHU, she was the SRITNE Chaired Professor of Data Analytics and Associate Professor of Statistics & Information Systems at the Indian School of Business, tenured Associate Professor at University of Maryland's Smith School of Business, and Visiting Assistant Professor at Carnegie Mellon University's Department of Statistics. Prof. Shmueli’s research focuses on statistical and data mining methodology with applications in information systems and healthcare, and an emphasis on human behavior. She authored multiple books, including the popular textbook Data Mining for Business Analytics, the book with Prof Kenett titled Information Quality: The Potential of Data and Analytics to Generate Knowledge and over 100 publications in peer-reviewed journals and books. Prof. Shmueli is the inaugural editor-in-chief of the new INFORMS Journal on Data Science. She is an IMS Fellow and ISI elected member.