Generative AI in the Political Science Classroom: Bringing Politics Back In

Large language models (LLMs) have disrupted higher education, prompting a wave of scholarship on generative AI in the Political Science classroom. This emerging literature largely converges in arguing that educators should incorporate those tools into instruction and assessment. In this article, I challenge this view. I first provide a typology of current arguments for incorporating LLMs, showing that those rest on the notion that the proliferation of AI is inevitable, inescapable, and irreversible. Given theoretical frameworks beyond technological determinism within Political Science, I argue that the call to integrate AI into the classroom not only lags behind insights of our own discipline, but also risks undermining its primary learning objectives. Instead, I suggest we need to bring politics back into the debate, which not only recovers educators’ agency but also refocuses it on the core interest of a Political Science degree—the study of politics, orders, and power.