SCHEDULE • RESOURCES
PEOPLE • GLOSSARY
The following schedule runs from June 5 – 9, 2023. (Last January’s institute schedule is available on the Winter page.) Each day will involve a mix of seminar-style discussion and hands-on technical work. Morning sessions will be 10:00a to 12:30p, afternoon sessions will be 1:30p to 4:00p.
An orientation and tech setup day will be held on May 24, 2023, 2-4PM.
How are data science methods being used in the humanities? How are humanists studying the automation of decision-making and cultural production?
*Must be logged into a Princeton institutional Google account to access these PDFs.
Brian Beaton et al., “Debating Data Science: A Roundtable,” Radical History Review, no. 127 (January 2017): 133–48.
Wai Chee Dimock, “AI and the Humanities,” PMLA 135, no. 3 (May 2020): 449–54.
Anne Helmreich, Matthew Lincoln, and Charles van den Heuvel, “Data Ecosystems and Futures of Art History,” Histoire de l’art, no. 87 (June 29, 2021): 45–54.
Barbara McGillivray et al., “The Challenges and Prospects of the Intersection of Humanities and Data Science: A White Paper from The Alan Turing Institute,” 2020.
An introduction to the baseline statistical concepts used in machine learning, from distribution to regression. What does it mean to be “unsupervised”? How do we evaluate a model?
Meredith Broussard, “Machine Learning: The DL on ML,” in Artificial Unintelligence: How Computers Misunderstand the World (Cambridge, Massachusetts & London, England: The MIT Press, 2018).
Wendy Hui Kyong Chun, excerpt from Discriminating Data: Correlation, Neighborhoods, and the New Politics of Recognition (Cambridge, Massachusetts & London, England: The MIT Press, 2021).
Richard So, “‘All Models Are Wrong,’” PMLA 132, no. 3 (May 2017): 668–73, https://doi.org/10.1632/pmla.2017.132.3.668.
Tony Chu and Stephanie Yee, “A Visual Introduction to Machine Learning,” R2D3.
Amy Winecoff, “Introduction to Machine Learning for the Humanities” (2023)
On the historical epistemology of quantification. How did measurement practices in the past cross the now-accepted divide between the sciences and humanities?
Hasok Chang, “Spirit, Air, and Quicksilver: The Search for the ‘Real’ Scale of Temperature,” Historical Studies in the Physical and Biological Sciences 31, no. 2 (2001): 249–84.
On the use of industry-created tools for influential humanities scholarship. How did software for speech recognition and image tagging end up in a literary text analysis tool?
Selections from Richard So, Redlining Culture: A Data History of Racial Inequality and Postwar Fiction (Columbia University Press, 2020).
Ted Underwood, “Machine Learning and Human Perspective,” PMLA 135, no. 1 (January 2020): 92–109, https://doi.org/10.1632/pmla.2020.135.1.92.
HDSI-ThursSession.ipynb, part 1
HDSI-ThursSession.ipynb, part 2
An opportunity for participants to workshop their own project ideas. Moderated by Natalia Ermolaev and Meredith Martin.