A Meta-Epistemological Reason for Rejecting AI-Written Philosophy


“The fact that you, an expert human, generated the text is evidence that the view is worth thinking about—more so than if the text were generated by an LLM.”

That’s Eric Schwitzgebel (UCR), writing at The Splintered Mind about why he doesn’t want to receive AI-written emails about philosophy, and why philosophy journals should reject AI-written submissions.

Here’s more context:

I’m talking about evidence about evidence: meta-epistemology. Your email or your article presents evidence for a particular philosophical view (alternatively, evidence that you support a particular philosophical view). In a simple world, I could evaluate this evidence entirely on its face: How good is the proposed view? But in the actual, complex world, it helps to have evidence about the quality of the evidence. The fact that you, an expert human, generated the text is evidence that the view is worth thinking about—more so than if the text were generated by an LLM. This holds even if the text is exactly the same, which of course it wouldn’t be.

An increasingly large part of the function of journals is to provide evidence about evidence—the value of their imprimatur. The fact that an article appears in Nous or Ethics is evidence that it has been through rigorous review and was judged worthy by several expert humans applying unusually demanding standards of quality and importance. Its appearance in those journals is thus evidence (imperfect of course!) that the reasoning is of high quality and the arguments worth taking seriously.

Similarly, if I know that an email or an article was written by a respected colleague, reflecting their positive creative exertion in trying to choose the right words, guided by their intuitive expertise in how to phrase things, I have better reason to take it seriously than if I know that it was generated by an LLM and reflects only their passive after-the-fact assent.

Philosophers sometimes suggest that we shouldn’t care if an argument was human-generated or AI-generated—that insisting on human-generated prose is fetishizing personal human interaction rather than facts and argument quality. In a way, that’s true: A sound argument is a sound argument. Similarly, we shouldn’t care if an article was written by David Chalmers and published in Philosophical Review or whether it was written by someone with no institutional affiliation and published on an obscure blog. If the argument is good, it’s good—of course, of course!

But at the same time, we have limited attention, limited time, limited ability to understand the nuances when matters drift even a little from our tightest foci of expertise, and in these cases it’s helpful to have meta-evidence. What should I read? How far should I trust the author has the details right, versus how much should I pause critically and chase down independent sources? How much should I let their way of phrasing things, their habitual patterns of thinking, the presuppositions hidden in their word choices and sentence structures, slip gently into my brain, silently strengthening my own associations and predilections?

Why does “knowing this text was written by a human philosopher” provide some evidence that the text is worth a certain degree of attention?

Human experts think differently and better than LLMs. Their word choices, even subtle ones, reflect sensitivities that they might not themselves be aware of. Typically, an expert’s prose will be more sensitive to the matters on which they are expert than the output of a language model. 

And checking an LLM-written text to make sure it reflects your own thoughts is risky:

There’s a huge cognitive difference between nodding along while reading something and actually productively generating a text. Two reasons: First, once the text is on the page, it’s easy to passively let the approximate word suffice, rather than thinking about word choice in the same effortful, active way we do when generating prose de novo. Second… I doubt that human beings, even experts, have a good sense of all the factors that shape word choice—everything they’re being sensitive to. You would have phrased it slightly differently, and even if you don’t know that, or why, a different signal is sent and received.

See his post for a good example of what he’s getting at, along with an explanation for why his argument “is not a call for blanket rejection of the use of LLMs in philosophical (or other) writing.”


Related:
Ethics Announces AI Policy
The Ethics of Using AI in Philosophical Research

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Matt
Matt
55 minutes ago

Eric Schwitzgebel makes valuable points about AI-written papers ‘nodded-through’ by their human instigator; the value of one’s de novo, even clumsy, own wording; and (in the underlying post) about careful use of AI. However, there is a slightly concerning note of anthropocentric self-satisfaction. The assertion, ‘Human experts think differently and better than LLMs’, appears open to challenge on both counts. It seems that human brains may predict continuations subconsciously in a similar manner to LLMs (https://www.sciencedaily.com/releases/2026/06/260624025514.htm), while (from personal observation) higher-version LLMs, at least, seem rather good at grasping what we wanted to say but didn’t quite manage to. Humans, at least for the time being, have advantages, e.g. the passion to press deeper into an idea, the ability to say what matters. But a little more circumspection might be in order.