90-921/10-831, Special Topics in Machine Learning and Policy
Spring 2012: Harnessing the Wisdom of Crowds
Course Description
Special Topics in Machine Learning and Policy: Harnessing the Wisdom of Crowds (90-921/10-831) is intended for Ph.D. students in
Heinz College, the Machine Learning Department, and other university departments who wish to engage in detailed exploration of a
specific topic at the intersection of machine learning and public policy. Qualified master's students may also enroll with
permission of the instructor; all students are expected to have some prior background in machine learning and/or artificial
intelligence (10-601, 10-701, 90-866, 90-904/10-830, or a similar course). This year's course will focus on the topic of
Harnessing the Wisdom of Crowds. We will investigate a variety of approaches which involve mining massive quantities of data
created by many human users, from a machine learning perspective. We will consider both "active crowdsourcing", which requires
providing users with incentives (financial, entertainment, altruistic, etc.) to perform desired actions, and "passive
crowdsourcing", which exploits the various traces of data created by individuals' day-to-day behavioral patterns. Specific
machine learning challenges include evaluating and optimally combining individuals' different types and levels of expertise,
creating incentive structures which achieve desired goals, combining machine and human learning, effectively coordinating the
crowd to perform structured and creative tasks, and understanding when the wisdom of crowds can fail (e.g. cascade effects). We
will consider a variety of policy and management applications ranging from public health and human rights to mass collaboration,
microfinance, and marketing. We will explore these challenges and opportunities in detail through lectures, discussions on
current research articles and future directions, and course projects, with the goals of understanding and advancing the current
state of the art.
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