Faculty practice becomes institutional policy
Generative AI can help instructors prepare material, let students test ideas, and accelerate parts of research. It can also conceal weak reasoning, reproduce errors, and make premium access part of the grade. The important line is therefore not use versus prohibition. It is whether the institution can see and govern how the tool changes the work.
A course rule should state what is permitted, what must be disclosed, what evidence must be retained, and which parts of the assignment must remain demonstrably the student's own. Those expectations should be legible before work begins, not inferred after a disputed submission.
Assessment must reveal judgment
Polished text is becoming a weak proxy for learning. Students should be asked to show sources, explain choices, defend reasoning, and revise under questioning. These practices assess the intellectual process whether or not AI was used.
Faculty need the same accountability. AI-assisted course material and research claims still require verification, attribution, privacy safeguards, and a named human who owns the result. Institutional experimentation should expand only with evidence about learning and error, not because the output looks efficient.
Go to the source
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The New York Times — Harvard faculty and AI
