I agree with you on a lot of points, I’m just saying that text-based responses to prompts are an imperfect test for phenomenology in the case of large language models.
I think the key step still needs an extra premise. “Same external behavior (even including self-reports) ⇒ same internal causal organization” doesn’t follow in general; many different internal mechanisms can be behaviorally indistinguishable at the interface, especially at finite resolution. You, me, and every other human mind only ever observe systems at a limited “resolution” or “frame rate.” If, as observers, we had a much lower resolution or frame rate we might very well think that GPT2 is indistinguishable from human output.
To make the inference go through, you’d need something like: (a) consciousness just is the minimal functional structure required for those outputs, or (b) the internal-to-output mapping is constrained enough to be effectively one-to-one. Otherwise, we’re back in an underdetermination problem, which is why I find the intervention-based discriminants so interesting.
I agree with you on a lot of points, I’m just saying that text-based responses to prompts are an imperfect test for phenomenology in the case of large language models.
I think the key step still needs an extra premise. “Same external behavior (even including self-reports) ⇒ same internal causal organization” doesn’t follow in general; many different internal mechanisms can be behaviorally indistinguishable at the interface, especially at finite resolution. You, me, and every other human mind only ever observe systems at a limited “resolution” or “frame rate.” If, as observers, we had a much lower resolution or frame rate we might very well think that GPT2 is indistinguishable from human output.
To make the inference go through, you’d need something like: (a) consciousness just is the minimal functional structure required for those outputs, or (b) the internal-to-output mapping is constrained enough to be effectively one-to-one. Otherwise, we’re back in an underdetermination problem, which is why I find the intervention-based discriminants so interesting.