Should you use AI for a task? A Harvard professor has a simple test

Key points

• Bruce Schneier teaches public policy at Harvard Kennedy School and the University of Toronto's Munk School.
• His students regularly use AI to complete writing assignments, which he argues wastes their tuition investment.
• AI researcher Daniel Meissler's "work versus gym" framework offers a clean way to decide when AI help hurts you.
• The key question is not whether AI can do the task, but whether doing it yourself is the point.

Bruce Schneier has a problem shared by professors everywhere. His students, enrolled in some of the most competitive public policy programmes in the world, hand in AI-written essays.

He teaches at Harvard Kennedy School and at the Munk School of Global Affairs and Public Policy at the University of Toronto. His students are paying considerable fees to learn. And then they quietly hand the thinking to a chatbot.

Why does that matter if AI is their future?

It matters because the writing was never really the product. The thinking was.

Schneier, writing in The Guardian, borrows a framework from AI researcher Daniel Meissler to explain the trap. Meissler calls it the difference between work and the gym.

At work, output is what counts. If a piece of software can process your invoices faster, use it. The invoice does not care how it got filed.

The gym is different. You do not hire someone to lift weights on your behalf and expect to get stronger. The struggle is the mechanism. Skip it and you skip the benefit.

Writing, Meissler and Schneier argue, is often a gym activity dressed up as work.

So when should you actually use AI?

Ask one question before you start: is the finished product the point, or is producing it the point?

If you are drafting a standard contract clause, formatting a report, or summarising a meeting you already attended, the output is what matters. AI is a reasonable tool.

If you are trying to learn to argue clearly, think through a policy problem, or build the kind of judgment that gets you promoted in ten years, the process is the point. Handing that process to a large language model, the technology behind chatbots like ChatGPT, means you hand away the benefit you came for.

The same logic applies outside the classroom. A nurse writing incident reports for compliance is doing work. A nurse using AI to avoid learning how to document clinical observations is skipping the gym.

What should students and professionals actually do?

Schneier does not say never use AI. He says be honest about what you are giving up when you do.

For students, that means treating AI as a checking tool or a starting prompt, not a ghostwriter. Draft the argument yourself. Then ask the AI where it is weak. That order matters.

For anyone building a skill, the same discipline applies. Fluency comes from repetition. There is no shortcut that leaves the fluency behind.

The framework is almost insultingly simple once you hear it. Work versus gym. Output versus process. It will not stop students submitting AI essays, but it gives anyone willing to think honestly a clear place to start.

Common questions

Does this mean AI tools are bad for learning?

Not automatically. AI can be a useful checking or feedback tool when you do the underlying thinking first. The problem is using it to skip the thinking entirely.

How do I know if a task is "work" or "gym"?

Ask whether completing the task yourself would make you better at something you care about. If yes, do it yourself. If the only thing that matters is the finished result, AI assistance is reasonable.