Professor Ted Underwood will present his research on machine learning at the University of Pittsburgh on September 19. His talk is part of the University's Sawyer Seminar, a year-long project funded by The Andrew W. Mellon Foundation that brings together a diverse range of practitioners and disciplinary specialists to analyze the co-evolution of data and method across more than a century.
In his talk, "Machine Learning and Historical Perspective," Underwood will explore tensions and affinities between the knowledge produced by machine learning and the mode of interpretation emphasized in the humanities.
"These two approaches to knowledge are not as alien as we perhaps assume," Underwood said. "Critics of machine learning are entirely right to emphasize that it can't produce a 'neutral' representation of the world. But often, humanists aren't looking for neutrality. Machine learning can do a great job of crystallizing the perspective implicit in a particular selection of evidence, which is often what we need for a better understanding of history."
Underwood is a professor in the iSchool and also holds an appointment with the Department of English in the College of Liberal Arts and Sciences. He has authored three books about literary history, including Distant Horizons (The University of Chicago Press Books, 2019), Why Literary Periods Mattered: Historical Contrast and the Prestige of English Studies (Stanford University Press, 2013), and The Work of the Sun: Literature, Science and Political Economy 1760-1860 (New York: Palgrave, 2005). His articles have appeared in PMLA, Representations, MLQ, and Cultural Analytics. Underwood earned his PhD in English from Cornell University.