Does Expertise Still Matter? Generative AI and the Crisis of Professional Identity
TL;DR
This positional paper interrogates the boundary between AI use and AI expertise, arguing that access to a tool that simulates expert output creates conditions under which the distinction between literacy and expertise becomes nearly impossible to perceive.
Abstract
The rapid diffusion of generative artificial intelligence (GenAI) tools has opened unimagined avenues for disrupting higher education, enabling professionals, especially researchers, to produce expert-seeming outputs and claim “expert-level status” without formal training in artificial intelligence. Yet, despite its popularity, concerns about AI’s effects on labor and expertise have largely overlooked a deeper categorical crisis: the collapse of the distinction between AI tool proficiency and genuine AI expertise and the consequences this has for professional identity and institutional decision-making. This positional paper interrogates the boundary between AI use and AI expertise, arguing that access to a tool that simulates expert output creates conditions under which the distinction between literacy and expertise becomes nearly impossible to perceive. Drawing on AI literacy frameworks, expertise theory, and professional identity. The paper maps this crisis by introducing simulated contributory expertise as a construct to name this condition at both individual and collective levels. The paper raises pressing implications for how higher education certifies expertise, designs AI literacy curricula, and governs institutional decision-making in an era where the professional identity, AI expertise, and its substance have become difficult to pinpoint.