Two recent statements, one from Nature Reviews Bioengineering and another from the Modern Language Association, arrive at the same conclusion from different directions:
Writing is part of thinking and assessing writing is part of teaching.
The Nature editorial makes the cognitive case. Writing forces structure onto ideas. It turns scattered research into a narrative, and in doing so, reveals what the work actually means. If that’s true, then outsourcing writing of scientific works to an LLM is not just a productivity play. It is also a shift that threatens to weaken academic work.
The MLA statement makes the institutional case. Assessment is a human act of communication. It depends on context, judgment, and experience. Automating it risks hollowing out the role of the educator and redefining learning as something that can be measured mechanically, without being understood.
Both land in the same place. While AI can assist, it should not replace.
This lines up with an emerging broader pattern as institutions deal with the rise of generative AI. The real risk is not just hallucination or misplaced confidence. It is the steady removal of the steps where people develop skill. Things like drafting, struggling, revising, interpreting, etc. The parts that feel slow, that provide friction, are often the parts where the most important work is done.
This is where an AI coaching model, like the one I’ve been exploring, fits in. When used properly, AI can support the creative thinking and writing process: prompting reflection, offering alternatives, helping organize ideas, etc. Used poorly, generative AI short-circuits that creative struggle process and delivers a shallow answer without the thinking that is needed behind it.
Generative AI tools can be used to, as Doug Engelbart said, help people “get better and getting better.”
Academia, at least in these cases, is leaning into that approach. That’s a good sign.
