26 June 2026
AI is here to stay, and Pitt is optimistic about its unbridled integration in existing learning and research processes. It mirrors the pace of embrace at the highest levels of corporate business development strategy. Institutional discourse supporting the development of AI literacy is important, yet the way we conceive of AI literacy can’t stay confined to a functional-use paradigm; it must also include the capacity to critique AI’s society-morphing development.
AI literacy, I argue, can’t do without an education responsive to the greater contextual moment in which AI resides and must confront troubling questions pertinent to a society at large that is reeling from the accelerationist attitude afflicting financial institutions, labor markets, and communication technologies responsible for shaping students’ future.
Pitt’s AWS VP partner praises “what’s possible when universities embrace AI thoughtfully and strategically,” but such thoughtfulness demands interrogating the emergent costs of integrating AI in education. For example, last year Pitt hosted the Global Innovation Summit, a “high-profile, multi-day, invitation-only conference” focused on “Health, AI & Tech.” Governor Josh Shapiro presented the keynote speech where he lauded the gathering’s exploration of ways that “AI can help cure diseases, treat the sick and advance public health nationwide.” Not just AI literacy, but critical AI literacy is needed to understand the contradictions inherent in this statement.
The rapid development of AI is intimately tied to data centers, and understanding their intertwined nature is crucial to conversant analyses. The very construction of data centers victimizes communities across the country who are trying to pierce the national consciousness about their deleterious effects. These include contaminated and unpotable water, direct damage to housing, sonic perturbations, reduction to mere trickles of cold-water pressure, and rises in utility prices—all for a monument to corporate capitalism that residents strongly opposed in the first place. Fluency in this discourse contributes to AI literacy, and robust academic discussion takes these manifold problematics into account.
The summit’s conspicuous lack of expertise in the area of literacy, to say nothing of the absence of representatives from humanities-aligned fields in general, bears mentioning. In the midst of arguments proclaiming that fulfilling their pedagogical missions requires universities to be enthusiastic about incorporating AI and not depriving students of their legitimate uses for education enhancement, the correlated perspective of the material consequences and ethical implications that make for socially aware AI literacy remain underdiscussed issues. The indelible integration of AI demands a critical capacity from students to contribute to a world that is still at a governance crossroad.
Looking outward to the political realm, critical AI literacy becomes more urgent as AI becomes a political flashpoint in upcoming elections that will determine the presence and direction of any potential legislation. I don’t expect the Musks and Altmans of the world to temper their rapid AI development, but our students are in line to endure the myriad outcomes firsthand. While the former types hype up discussions focused on buzzwords like innovation, competition, and machine-enabled human exceptionalism, the latter has deeper literacy needs as erudite individuals who can feasibly articulate the stratified contours and discourse of this monopolized tech. Fostering the literacy necessary to make sound social critiques strikes me as a compelling part of my mission as an educator aiming to cultivate civically minded and critically capacitated students.