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Data Rhetoric: From Deductive to Inductive to Abductive Demonstrations of Big Data
WhenWednesday, Feb. 13, 2019, 4 – 5 p.m.
Campus roomWRF Data Science Studio, 6th Floor of the Physics/Astronomy Tower
Event typesLectures/Seminars
Event sponsorseScience Institute

Science, Technology & Society Studies

Digital rhetoric employs demonstrations to argue that an idea, institution, or practice can be translated into software. Computer simulations, “big data” visualizations, and computer “demos” are all examples of digital rhetoric. This talk recounts a history of the demonstration: How does the ancient Greek demonstration become the data visualization pitch of today? The history starts in ancient Greece, where definitive demonstration was a matter of deduction exemplified by demonstrations in geometry. Deductive demonstration was displaced by inductive demonstration in the seventeenth century, during the “scientific revolution.” Inductive demonstration was made necessary when arguments began to be based on empirical data and not just derived from statements taken to be obviously true. For example, the remaking of alchemy into chemistry required the invention of a form of rigorous, inductive demonstration from empirical observations. Today, arguments are made on the basis of so much data—“big data”—that no one person could possibly read it all, much less observe its collection. This has necessitated the invention of yet another form of argumentation, which I term “abductive demonstration.” Data visualization “demos” are in the genus of abductive demonstrations. At the end of the talk, we will carefully read some technical papers Google published during the 2016 overhaul of its translation system. The papers claim that a universal language, an “interlingua,” emerges from their machine learning processes and that it can be seen in the data visualizations presented in their paper. An interlingua that connects diverse languages by meaning has been a dream of mathematicians and logicians at least since Leibniz. It seems unlikely that it would emerge spontaneously from machine learning so, I ask, what is the contemporary form of big data demonstration that makes such a claim seem plausible?


Warren Sack is a media theorist, software designer, and artist whose work explores theories and designs for online public space and public discussion. He is Chair and Professor of Film + Digital Media at the University of California, Santa Cruz where he teaches digital arts and digital studies. He has been a visiting professor in France at Sciences Po, the Fondation Maison des sciences de l'homme, and Télécom ParisTech. His artwork has been exhibited by SFMOMA (San Francisco), the Whitney Museum of American Art (New York), the New Museum of Contemporary Art (New York), the Walker Art Center (Minneapolis), and the ZKM (Karlsruhe, Germany).  His scholarship and research has been supported by the Paris Institute for Advanced Study, the American Council of Learned Societies, the Sunlight Foundation, and the National Science Foundation.  Warren received his PhD from the MIT Media Lab and was an undergraduate at Yale College.  His talk will be based on The Software Arts, his book for the MIT Press "Software Studies" series forthcoming in April:…

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