by Akim Reinhardt

A little over a year ago I published an essay here at 3QD that implored my fellow educators not to panic amid the dawning of Artificial Intelligence. Since then I’ve had two and a half semesters to consider what it all means. That first semester, many of my students had not even heard of AI. By the very next semester, a shocking number of them were tempted to have it research and write for them.

Many of my earlier observations about how to avoid AI plagiarism still hold: an ounce of prevention is worth a pound of cure; good policies and clear communication from the jump are vital; assignments such as in-class writing and oral exams are foolproof inoculators.

However, other, more abstract questions with profound pedagogical implications are emerging. These can be put under the larger canopy of: What am I teaching them and why?

Us Historians specifically, and Liberal Artists more generally, help students develop certain skill sets. We train them in the Humanities and Social Sciences, teaching them to find or develop data and use it effectively through critical and creative thinking. Obviously a political scientist and a continental philosopher go about this differently. However, the venn diagram of their techniques and goals probably overlaps a fair bit more than a lay person might realize. For starters, we all have the same broad subject matter. Everyone in the Liberal Arts, from art historians and literature profs to psychologists and economists, studies some aspect of the human condition. And while we each have our own angles of observation and methodologies, there are also substantial similarities among them. We all find or generate data (even if forms of data are different), analyze them, draw conclusions, and present our findings. And those presentations of findings, even when centered around quantitative data, include a narrative.

In other words, words. Read more »