The question I get most often about AI in academic writing isn’t about plagiarism policies or detection software. It’s: “what am I actually allowed to do with this?” My honest answer is that the policy question is less interesting than the cognitive one.
Large language models are trained predominantly on open-access English text, skewed toward the global north and recent publications. Even though this will likely change, their accuracy drops as topics get more specialized, while their confidence doesn’t. That’s a bad combination for graduate researchers working at the edges of their fields. A model will produce a citation that looks exactly right: plausible authors, real journal names, correct formatting, for a source that doesn’t exist. For a dissertation researcher, a fabricated citation that survives to submission is a career-level problem.
There’s also what I think of as the statistically average register problem. AI defaults to the most common academic prose patterns, which strips out the disciplinary specificity and productive complexity that distinguishes good scholarly writing from text that merely passes at a glance. Good paraphrasing requires knowing why you’re using a source. AI-generated synthesis doesn’t know that, and it shows. Well, it shows for experts in certain fields anyway.
The framework I use in workshops is a traffic light, which is pretty common and usable in a variety of contexts. Green uses are structural and linguistic: building a rough outline from your notes, translating specialist concepts into plainer language, asking the tool to push back on your reasoning. Yellow uses require more caution and transparency: drafting from a detailed outline you’ve already written, restructuring prose for flow. Red uses are where the intellectual work itself gets handed over : having AI write your literature review, generating conclusions from sources you haven’t read, submitting output you can’t explain or defend. The underlying question is the one worth holding onto: is the AI thinking for me?
It matters because Writing is the thinking. A writer who asks AI to draft a section has a document. They don’t have the understanding that comes from working through the ideas on the page yourself. The discomfort of difficult drafting isn’t a problem to solve. It’s evidence that something substantive is happening.