Let librarians lead AI literacy

Are librarians the key to teaching AI literacy?

Short answer: yes. Librarians already teach students how to find, judge, and use information. AI literacy fits that mission, and they're stepping up with practical workshops, resources, and coaching that classrooms often can't squeeze in.

At Toronto Metropolitan University (TMU), library-led AI workshops give students a place to test tools, ask messy questions, and build habits before grades are on the line. As library lead Reece Steinberg puts it, the point is a flexible space to think and apply AI without the pressure of marks.

Why libraries are built for this work

• They teach research, media literacy, and copyright - the same muscles AI use demands.
• They're tool-neutral and evidence-first. AI becomes "simply another tool," not a shortcut.
• They serve every department, so guidance is consistent across courses and years.
• They're trusted. Students ask questions in the library they won't ask in class.

Janice Kung, a health services librarian, frames it cleanly: AI literacy is information literacy. Librarians have done this work for decades; the interface changed, the job didn't.

What students actually gain

Computer science student Kavya Raval treats AI like an always-on tutor. It explains tough Java concepts, generates practice problems, and critiques her answers. The workshop didn't push her to use AI for everything; it showed her how to use it well - and when to step away.

MBA student Steven Guirguis liked that the sessions were optional. When learning is voluntary, buy-in goes up. No scramble for notes. More time to reflect, test, and internalize the lessons.

K-12: the quiet gap no one sees

Teacher-librarians are often the most constant adults in a student's school life. They help kids "untangle" what they see online and build the confidence to create their own work. That's essential as AI shows up in search, feeds, and classroom tools.

But cuts have thinned their numbers. Many schools use limited library time just to check out books. The result: a widening gap between students who get real information and media instruction and those who don't, notes district teacher-librarian Joseph Jeffery.

Start early - and name what's happening

Toronto teacher-librarian Diana Maliszewski introduces algorithms and AI to young learners. The goal isn't technical depth; it's language and awareness. Kids as early as kindergarten can point and say, "I think that's an algorithm."

When middle-graders look at AI output and say, "That looks fake," that's progress. The wow factor fades. Judgment takes over.

What education leaders can do next

• Make libraries co-leads on AI policy and practice. Give them a seat at the table with teaching and academic integrity teams.
• Launch opt-in AI literacy workshops with a badge. Modules: effective prompts for learning, verification skills, bias and ethics, citation norms, and privacy.
• Build faculty support. Librarians can produce short guides, model syllabus statements, and host drop-in hours for instructors.
• Set course-level norms. Where is AI allowed, restricted, or banned? Require "show your process" artifacts when AI is used.
• Measure it. Track sign-ups, pre/post quizzes, student confidence, and actual use cases in assignments.
• Fund time, not just tools. Restore teacher-librarian capacity and schedule recurring library time, especially in K-9.

A simple 4-session AI literacy series your library can run

• Session 1: What AI can and can't do. Strengths, failure modes, hallucinations, and how to evaluate outputs.
• Session 2: Prompts for learning. Break down problems, ask for step-by-step feedback, and convert AI help into your own work.
• Session 3: Ethics and safety. Bias, privacy, data handling, accessibility, and clear citation practices.
• Session 4: Discipline labs. Coding, writing, design, health - with reflective assignments and "show your work" logs.

Guardrails that stick

• Transparency: Students disclose AI use and include prompt-response snippets when allowed.
• Verification: Cross-check facts and citations; treat AI as a draft partner, not a source of truth.
• Equity: Provide no-cost access and alternatives so policies don't penalize students without devices.
• Alignment: Tie AI guidance to existing information literacy outcomes and academic integrity policies.

For a solid policy reference, see UNESCO's guidance on generative AI in education: UNESCO AI guidance.

If you need a ready-made path

Don't stall on tooling or curriculum development. Start with a pilot run in the library, test with volunteers, then scale. If your team wants curated AI learning paths by role, you can browse training options here: Complete AI Training - courses by job.

The bottom line

AI literacy isn't a side project. It's part of information literacy. Put librarians in the lead, fund their time, and make space for students to practice before the stakes are high. Do that, and you'll see better judgment, cleaner work, and fewer shortcuts - from kindergarten to grad school.