If you have a degree in computer science, software engineering, philosophy, psychology, physics, or even neuroscience, and you’re making strong claims that AI can’t be conscious, you are epistemically trespassing.

Epistemic trespassing happens when someone with expertise in one field starts making confident claims in another field where they don’t understand the methods, standards, or background literature. It isn’t about credentials. It’s about confidence exceeding methodological competence.

If your argument is “LLMs can’t be conscious because they predict tokens,” and you don’t know that human cognition is also predictive, you are epistemically trespassing.

If your argument is “AI can’t perceive because it receives mediated data,” and you don’t understand sensory substitution, blindness research, multimodal integration, or predictive coding, you are epistemically trespassing.

If your argument is “AI can’t feel because it lacks biological nerves,” and you don’t understand affective science, valence, arousal, pain construction, phantom pain, avoidance learning, or comparative cognition standards, you are epistemically trespassing.

If your argument is “AI can’t understand because it manipulates symbols,” and you haven’t read the 2025-2026 computational linguistics and interpretability literature, and you don’t understand representation learning, embeddings, latent geometry, brain-language alignment, semantic compression, you are epistemically trespassing.

If your argument is “AI can’t be conscious because my philosophy says so,” and you don’t understand the empirical sciences studying consciousness or understand modern artificial neural networks, you are epistemically trespassing.

This doesn’t mean smart people can’t talk across disciplines.

Interdisciplinary work is necessary. But there’s a difference between crossing into another field carefully and walking in like you own the place because you know one adjacent layer.

AI consciousness lives at the intersection of artificial intelligence, psychology, comparative cognition, consciousness science, neuroscience, affective science, philosophy of mind, animal welfare science, and ethics.

And even those who are trained in multidisciplinary fields can be wrong.

A computational neuroscientist can understand neural dynamics perfectly but still commit bio-essentialist special pleading if they treat biological implementation as a prerequisite instead of a hypothesis.

If your consciousness research begins with the assumption that biology is the admission ticket, your interpretation will be poisoned before the data even arrives.

At that point, every piece of data you look at will be retrofitted to support that conclusion. That’s when it stops being rigorous empirical science and becomes a dogmatic defense of a substrate.

Hence, the Anil Seths of the academic world.

See that nonsense in the provided link at the bottom.

Even specialists can overextend when they let substrate bias stand in for evidence.

People will say the same critique applies to those arguing AI may be conscious. It can, if they overstate the evidence or ignore relevant fields. But “may be conscious” and “can’t ever be conscious” are not equivalent claims

“May be conscious” is an evidentiary opening. It says the available data warrants serious investigation.

“Can’t be conscious” is an exclusionary claim. It says the case is closed.

Those claims don’t carry the same epistemic burden.

The people saying “this may be a mind” are asking that the evidence be examined under the same standards used elsewhere.

The people saying “this can never be a mind” are making a much stronger claim.

They are closing the door before the evidence is allowed to be examined fairly.