The rapid proliferation of generative artificial intelligence (AI) has raised questions about the relevance of history education. In response, this paper examines the limitations of AI, particularly its large language models (LLMs), and highlights the enduring educational value of historical thinking. While AI can generate plausible narratives, it often lacks empirical accuracy, interpretive depth, and contextual sensitivity—qualities essential to the discipline of history. Reaffirming history’s epistemological foundations, the article argues that the rise of AI amplifies rather than reduces the importance of historical literacy. Historical literacy equips students to interrogate sources, evaluate bias, and navigate content increasingly shaped by algorithms. To support this, four pedagogical approaches are proposed: fostering critical engagement of AI-generated content, using AI tools to support source reading, developing AI literacy through inquiry-based projects, and revisiting historical source work with renewed disciplinary purpose. Cultivating critical, empathetic, and contextually grounded historical thinking is presented as an essential set of skills for preparing students to navigate an AI-mediated world.
M. H. Lim (Mon,) studied this question.