At Ronald Reagan High School, science teacher Brandt Champion is using Google Notebook LM to generate study guides, games, and podcasts from his own class notes. More than 80% of his students have accessed these AI-built materials - a concrete example of artificial intelligence moving out of policy discussions and directly into daily lesson review.
Champion uploads classroom presentations and review packets into the platform, training the AI model to pull answers only from that material. No internet searches are involved. For a unit on the skeletal system, Notebook LM produced a conversational podcast between two AI hosts in under ten minutes. Students listen to the episodes during car rides or bus commutes before exams, converting idle time into targeted review.
A practical AI tool in the high school classroom
Champion frames the technology as a supplement, not a substitute. "In my classroom, I encourage students to use these AI tools as that: as a tool, as a way to help you understand what you need to achieve better," he said. "On final submissions and where you are trying to demonstrate mastery of a skill, it's absolutely zero tolerance of AI-generated work."
The approach reflects a broader shift. Two years ago, K-12 and college instructors were primarily concerned about AI-assisted cheating, and many moved to ban the tools outright. Those worries haven't vanished, but a growing number of educators now argue that withholding AI literacy leaves students unprepared for a world where the technology is embedded in work and daily life.
Shifting attitudes toward AI literacy
Champion calls AI literacy non-negotiable. "No matter how a teacher feels about AI from like their worldview, we have to teach how to use these responsibly and successfully," he said. He also brings up the costs directly with students. Data centers that power AI systems drive up utility bills in rural communities, while artists and authors are fighting what they describe as intellectual property theft. Researchers warn that overreliance can erode a child's critical thinking. "We also have to teach students about the cost of AI as well. Every time I've introduced an AI tool, that conversation has come up in every single one of my classes," Champion said.
For teachers exploring AI integration, structured resources like an AI Learning Path for Teachers can help build responsible classroom practices.
Higher education grapples with AI's limits
At the university level, the conversation takes a different shape. Gillian Rodger, chair of the school of music at UW-Milwaukee, pushes back on words like "thinking" or "creating" when applied to the technology. "When you use AI, first of all, you can only trust it to make plausible combinations of words, which is all it does. There's no intelligence there. There's no knowing in AI," she said. Rodger points out that students cannot verify the sources behind AI-generated answers - a significant weakness in humanities scholarship.
To make that lesson stick, she lets students in her general history of music course use AI for one assignment early in the semester. They must generate an essay prompt, write the essay with AI, and include five to ten bibliographic citations produced by the tool. The results, Rodger said, almost always fall short, exactly the point she wants to make. Proper sourcing is a foundational skill that AI cannot reliably replicate.
The split on campus is stark. In March, the Milwaukee School of Engineering announced it would embed applied AI into every degree program, while researchers in data-heavy fields use the technology to accelerate analysis that once required teams of graduate students. Rodger, who works alongside scientists, accepts that what makes AI effective in a lab often fails in disciplines built on interpretation and argument. "If it's a hammer, I don't want all of us to be nails," she said.
Why this matters for educators
The contrast between a high school teacher generating custom podcasts and a university professor exposing AI's inability to handle citations captures the central tension for schools right now. AI tools are not a single thing - they perform well at some tasks and flounder at others. Treating them as a uniform threat or a universal solution misses where real learning occurs. Integrating AI means teaching its ethical costs, its sourcing failures, and the judgment to decide when it genuinely helps a student and when it gets in the way.
Your membership also unlocks:
