I think the anthropomorphic view of this is dangerous in the long term as it starts the argument that anything that isn't reasoned by a human isn't reasoning at all. This just changes the argument from LLMs can reason like a human to LLMs can't reason at all while ignoring the third possibility of "LLMs can reason not like a human".

One of the biggest things I've learned after the event of LLMs is that humans definitions of intelligence/thinking/reasoning/consciousness/etc are very poorly defined. Not just across society at large, but the sciences themselves.

> I think the anthropomorphic view of this is dangerous in the long term as it starts the argument that anything that isn't reasoned by a human isn't reasoning at all.

Something like this is actually a stance in the tradition of inferentialism (see the term sapience). Though "reasoning" isn't like, turing machine computability in this space; from what I understand, it's some abstract notion of the "space of reasons". I don't really understand it, honestly.

There's some merit to this, IMO. When an LLM goes wrong, do you blame the person or the LLM? As in, would you throw said LLM in jail, and hold the LLM accountable? Not right now, at least. I'm not sure if that's what is meant by the "space of reasons", but the intuition is that 'reason' can mean a lot of different things, pragmatically speaking. Reason as a legible audit trail is one of those ways.

But that's arguably getting into the social aspect of 'reason' (important!) and not like, what STEM people traditionally think of as 'reason'.

I may be wrong but I think the word you want is anthropocentric, not anthropomorphic. Anthropomorphism is turning something that isn't human into something human, e.g. an AI, while anthropocentrism is taking human as the center and default state of things.