The Banality of Big Data: A Review of Discriminating Data
Digital Humanities Quarterly
This review critically interrogates Wendy Chun’s book Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (MIT Press, 2021) from the perspective of the digital medical or health humanities. The monograph’s exploration of predictive machine learning and big data’s propensity to encode segregation through their default assumptions about correlation raises important questions about machine learning’s growing uses in fields, such as medicine and pharmacology, where the stakes of such digital experimentation are particularly high. Chun’s exploration of the predictive processes by which data analytics replicates 20th-century eugenics discourses makes an important contribution to the field of digital medical ethics and also offers unique insight into the mechanisms by which digital humanities scholars can disrupt and challenge the use and application of such predictive programs.
Creative Commons License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 International License.
Furiasse, A. (2022). The Banality of Big Data: A Review of Discriminating Data. Digital Humanities Quarterly, 16 (4) Retrieved from https://nsuworks.nova.edu/hcas_dhp_facarticles/61