Citation: “Liberal Arts Pantocrator: Addendum to ‘Data Science and the Post-Liberal Arts University.’” KCWorks, 24 Sept 2025. https://doi.org/10.17613/vnybw-f6a84.
- Abstract: The following fragment discussing two early pictorial illustrations of the liberal arts was originally part of my article on “Data Science and the Post-Liberal Arts University” (Critical Inquiry 51, no. 4 (2025): 597–618) but had to be cut due to length limitations. The fragment complements the article’s final section on “A Post-Liberal Arts Curriculum (2),” which discusses what is “needed for the post-liberal arts to enhance existing efforts in the liberal arts to be more inclusive of their social margins and global peripheries—in particular, by acknowledging the heritage of applied knowledge embedded in the very notion of such margins and peripheries” (612-618).
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.
“AI Virtue: Generativity and Epistemic Value,” Santa Fe Institute workshop on “The New New Science,” Santa Fe, NM, 16 September 2025.
- Abstract: In the age of AI, what will be “good” knowledge? This talk maps epistemic virtues (like “true,” “accurate,” “creative”) used to discuss AI in a corpus of 553 journal articles on AI published in 2024. “Creativity” comes in for special attention as an example. The goal is to theorize how a more integrated framework might be developed for evaluating the worth of AI—one less locked into understandings of value adapted to pre-AI agents and structures of knowledge work. The talk is accompanied by a digital kit for exploring data models of discourse on AI.
