Citation: “Data Science and the Post-Liberal Arts University.” Critical Inquiry 51, no. 4 (2025): 597–618. https://doi.org/10.1086/735621.

  • Abstract: Data science has grown explosively in higher education, offering undergraduate degrees in the US on a “core and domains” curricular model that overlaps with—and in an intriguing way—replicates the multidisciplinary model of liberal arts education. This essay treats data science as a pathfinder for the continuing evolution of American higher education from the liberal arts to a post-liberal arts centered on applied knowledge, including today’s new modes of predictive/generative knowledge. The essay builds toward a consideration of how the post-liberal arts university can teach students both to apply knowledge and to know the meaning (historical, intellectual, and social) of application. A key for the post-liberal arts university will be to teach preprofessionalism in ways that do not just acknowledge the historical exclusion of the people of applied knowledge (at the social margins and global peripheries) from liberal arts education for the “free man” but turns such acknowledgement into new forms of liberal arts knowledge. Data science, the essay concludes, has the potential to contribute novel ways of conceptualizing intersectionality in general and in relation to applied knowledge. But data science is also constrained in this regard on the global scene where data power belongs to many regions and actors without a shared tradition of liberal arts education and thus a framework for a post-liberal arts carrying on shared ideas and practices of freedom.