At Bard Early College, asking questions such as, “How much can we rely on machines to interpret the past?” is a natural extension of the Bard model of liberal arts, inquiry-based education. In the year-long Bard Seminar sequence, the first semester is devoted to the question, “What does it mean to be human?” whereas the second semester is devoted to the question, “How do we know what we know?” In the past year as A.I. has taken our society and world by storm, these questions seem more pertinent in the classroom than ever. On the one hand, A.I. has the potential to revolutionize historical research, allowing historians to analyze centuries-old documents and bridge gaps across the historical record in new and exciting ways. By automating data collection and analysis, A.I. can allow historians to sift through vast amounts of information much more efficiently to possibly uncover new connections and trends. However, A.I.’s role in historical research raises critical questions for teachers and students of history alike. These questions can be seen as an opportunity to think through foundational questions about the nature of historical inquiry. How much should we rely on machines to interpret the past? What are the limits of machine knowledge when it comes to historical interpretation? How does A.I. highlight the essential nature of human expertise in historical inquiry? Ultimately, A.I. can complement our understanding of the past—just as the rise of computers and digital databases did decades ago—but it is the human historian that interprets meaning, crafts historical narratives, and makes scholarly interventions with the potential to transform how we think about and know the past.
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