How Should Students Document AI Usage in Academic Work?

As AI tools become deeply embedded in how we write, code, and think, universities are grappling with a deceptively hard question: how do you regulate something that's invisible by design? The Institute of Statistics at LMU Munich recently published guidelines for AI tool usage in academic work that I think strike a remarkably pragmatic balance. Rather than banning AI or pretending it doesn't exist, they treat it as what it is — a tool that needs the same transparency we already expect for other tools and sources. I want to walk through the key ideas here, because I believe they're relevant well beyond academia. The Core Philosophy: Responsibility and Transparency The guidelines rest on two pillars that are hard to argue with. Responsibility. Students bear full responsibility for every word they submit, regardless of which tools helped produce it. If you can't explain it, you shouldn't submit it. This applies to prose and program code equally. Transparency. AI tool usage must be documen