Anna Mills, a writing teacher at the College of Marin, discusses how A.I. changes the rules for coursework and what faculty can do about it. She maps practical ways to use A.I. for learning and feedback while naming the real risks around privacy, security, and unregulated growth.

Key points:
• What A.I. agents are and why they matter in education
• Where A.I. can help faculty with OER, accessibility, and quick learning tools
• Using A.I. for writing feedback inside a human-centered process
• Building skeptical A.I. literacy through prompting and pushback
• STEM-friendly uses such as comparing explanations and checking reasoning
• A peer plus A.I. review workflow with required reflection and metacognition
• Academic integrity as a "wicked problem" with tradeoffs not perfect fixes
• Detection as a deterrent when paired with student conversations and trust
• Course design strategies that increase intrinsic motivation and reduce outsourcing
• Communities of practice that give faculty time to learn, test, and share
• Looking toward 2030 with concerns about AGI, guardrails, and valuing the human

"I like to say, 'A.I. for input and not A.I. for output.' [For example], ask A.I. to explain its reasoning for how it solves a problem, and ask that in two different ways that are contradictory. Then, the student looks at which way makes sense. Do either of them make sense? Using A.I. in ways that push us to be skeptical of it, I think is really valuable for students, especially as it becomes more sophisticated, more plausible. We can bring value by questioning it. You want to prepare for a workplace where students are going work with A.I. You have to be suspicious of A.I. You have to be ready to push back and not accept what it gives you. I favor pedagogical applications that help students practice that and help them build some confidence in relation to A.I." - Anna Mills

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