If you require accommodation to attend this event, please contact us at uchi@uconn.edu or by phone (860) 486-9057. We can request ASL interpreting and other accommodations offered by the Center for Students with Disabilities.
The Digital Humanities and Media Studies Initiative and the Future of Truth project invite you to a book discussion group about:
Discriminating Data
by Wendy Hui Kyong Chun
led by Alexis L. Boylan and Yohei Igarashi
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November 15, 2021, 3:00–4:00pm
Homer Babbidge Library, 4-209
To participate, please email uchi@uconn.edu. The first twenty participants to sign up will receive a free copy of Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (MIT Press, 2021).
In Discriminating Data, Wendy Hui Kyong Chun reveals how polarization is a goal—not an error—within big data and machine learning. These methods, she argues, encode segregation, eugenics, and identity politics through their default assumptions and conditions. Correlation, which grounds big data’s predictive potential, stems from twentieth-century eugenic attempts to “breed” a better future. Recommender systems foster angry clusters of sameness through homophily. Users are “trained” to become authentically predictable via a politics and technology of recognition. Machine learning and data analytics thus seek to disrupt the future by making disruption impossible.
Chun, who has a background in systems design engineering as well as media studies and cultural theory, explains that although machine learning algorithms may not officially include race as a category, they embed whiteness as a default. Facial recognition technology, for example, relies on the faces of Hollywood celebrities and university undergraduates—groups not famous for their diversity. Homophily emerged as a concept to describe white U.S. resident attitudes to living in biracial yet segregated public housing. Predictive policing technology deploys models trained on studies of predominantly underserved neighborhoods. Trained on selected and often discriminatory or dirty data, these algorithms are only validated if they mirror this data.
How can we release ourselves from the vice-like grip of discriminatory data? Chun calls for alternative algorithms, defaults, and interdisciplinary coalitions in order to desegregate networks and foster a more democratic big data.
[Book description from MIT Press site]
In conjunction with this event, Wendy Chun will give a virtual book talk on November 18, 2021 at 1:00pm. To attend the talk, register here.
2006–2007 faculty fellow Anke Finger is professor of German, Media Studies, and Comparative Literary and Cultural Studies in the department of Literatures, Cultures, and Languages at UConn. A co-founder and co-editor (2005–2015) of the multilingual, peer reviewed, open access journal 
2004–2005 faculty fellow V. Penelope Pelizzon’s last poetry collection, Whose Flesh Is Flame, Whose Bone Is Time, was published in 2014 (Waywiser Press). Pelizzon’s awards include a 2020 Quarterly West editor’s choice award for her chapbook Of Vinegar Of Pearl, a 2019 Hawthornden Fellowship, an Amy Lowell Traveling Scholarship, and the Center for Book Arts chapbook award for her collection Human Field. New poems from her next book appear or are forthcoming in Tin House online, Ecotone, 32 Poems, The Bennington Review, The Gettysburg Review, The New England Review, The Harvard Review, Plume, and Orion.
