Disciplinary bodies issuing guidance on generative AI in scholarship, teaching, and learning is important. The American Historical Association’s Guiding Principles for Artificial Intelligence in Education provides a set of guiding principles and calls for more community-based conversations about the intersection of labor and AI. The AHA warns that rapid technological change and local considerations prevent comprehensive directives for every classroom instance, offering principles informed by committee conversations and member input. Teaching and learning remain inherently context-dependent, with small variables producing meaningful differences, and the communal human chemistry of learning makes full systematization difficult.
Given the speed at which technologies are changing, and the many local considerations to be taken into account, the AHA will not attempt to provide comprehensive or concrete directives for all instances of AI use in the classroom. Instead, we offer a set of guiding principles that have emerged from ongoing conversations within the committee, and input from AHA members via a survey and conference sessions.
I think this is obviously correct because teaching and learning are inherently, inevitably context-dependent, sometimes down to the smallest variables. I've used this example many times, but as someone who frequently taught the same course three or even four times a day, I could detect variances based on what seems like the smallest differences, including the time of day a particular section met.
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