By Koki Kato

English is not my first language, so generative artificial intelligence (AI) can be particularly helpful when I write academic papers in English. It can make my sentences clearer, more concise and more natural. But I have also encountered a curious problem: sometimes AI makes my writing better and my argument worse. A revised sentence may read better in English while no longer saying quite what I mean. Sometimes I restore my original wording, even though the English may be less elegant. These experiences made me think differently about authorship. If AI can generate ideas, draft passages, suggest connections and criticise arguments, what exactly am I doing when I put my name on the finished work?

At the time, I had also been thinking about a seemingly different question arising from my work as a family physician: how does trust develop through continuity? A patient’s trust in a doctor is not created by a single reassuring statement or clinical decision. Through repeated encounters, patients come to know how their doctor listens, responds to uncertainty and acts when circumstances change. What happens in one consultation acquires meaning partly through what has happened before.

That made me wonder whether an author’s final approval also has a history. Simply clicking ‘approve’ at the end of the publication process cannot explain why an author’s approval matters. Before that moment, the author has spent time reading, writing, reconsidering, discussing and revising. Through these encounters, new connections may become visible, arguments may change, and the work may come to mean something that was not fully apparent at the beginning. The significance of the final ‘yes’ may lie in this history of engagement. I found a useful way of thinking about this in the work of anthropologist Tim Ingold. He describes making as a responsive process rather than simply putting an already completed idea into practice. As we engage with what we are making, possibilities emerge that were not fully visible at the beginning. Academic writing often feels like this. Reading the literature may reveal an unexpected connection that changes an argument. A collaborator may introduce a perspective I had not considered. A reviewer may expose a weakness that forces me to reconsider a claim. And now AI can suggest connections and alternative formulations that change the direction of my thinking.

AI also makes something about this process unusually visible. A suggestion can sound persuasive while subtly weakening an argument. A beautifully rewritten paragraph may no longer say what I mean. Each suggestion therefore requires judgement. Does this connection really hold? Is this claim supported by the evidence? Does this formulation fit with the argument I am trying to make? Which possibilities should I develop, and which should I reject? Through making these judgements, the paper changes. So does my own understanding of what I am trying to say.

This is what led me to the idea of meaningful approval. An author’s final approval matters because it can express an understanding formed through sustained engagement in making the work. The author can ultimately say: ‘Yes, this is what I mean, and I am prepared to answer for it.’ This changes how I think about AI and authorship. We often ask how much AI assistance is too much, or whether particular ideas or passages originated with a human or a machine. Those questions matter. But as AI becomes more deeply involved in scholarly work, another question becomes increasingly important: has the human author remained engaged enough to understand, endorse and answer for what the finished work says?

Generative AI has taken over some activities that we once associated closely with authorship. Paradoxically, that may help us see authorship more clearly. Authorship may lie less in producing every word or originating every idea than in participating in the formation of an understanding that one can ultimately stand behind. AI can contribute substantially to that process. But when I put my name on a paper, I am making a claim that AI cannot currently make: this is the understanding I have come to, and I stand behind it.

Paper title: What authorship recognises: meaningful approval in the age of generative AI

Author: Koki Kato

Affiliations: Madoka Family Clinic, Ogori, Fukuoka, Japan

Competing interests: None declared

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