Comment by ben_w
7 days ago
Copying what I said 9 days ago when this post first appeared but didn't catch enough attention and only got two replies including my own:
> I fail to make sense of the claim that there is such an “explanatory gap.”
This is essentially saying "I don't understand therefore you are wrong".
> We do not need to explain why it looks red for the same reason that we do not have to explain why the animal that we call “cat” looks like a cat. Why should we have to explain why “red” looks red?
We did in fact need this to get AI to recognise cats.
If we wish to actually know if some AI is or is not conscious, and not simply re-hashing conversations ancient Greeks will probably have had as animism faded from their culture and they stopped believing in dryads and anima loci, then it needs to be testable *by something outside the intelligence being tested for conscious*.
> Scientific knowledge is ultimately first-personal. The world is real, but any account of it can exist only from within it. Any knowledge is perspectival. Subjectivity is not mysterious
Mysteriousness isn't the problem with subjectivity, lack of repeatability is. This is why we make instruments to measure things: my "about the size of a cat" is subjective and likely different from yours, while my "31.4 cm" is only going to differ from yours if one of us is surprisingly bad at using a ruler; my "pleasantly warm" may or may not be yours, but my "21.3 C" will only differ from yours if one of our thermometers has broken.
The "hard problem of consciousness" is that we not only don't have a device to measure consciousness, but even worse than that we don't even know what its equivalent of a ruler or thermometer would do.
(At least for this meaning of consciousness; there's at least 40, we can at least test for the presence or absence of the meaning that e.g. anesthesiologists care about, but that's not the hard problem).
> We did in fact need this to get AI to recognise cats.
I believe that this is simply because of the way we train ML, with labelled data. It is quite conceivable that we could get an ML model to recognise cats just by some form of multidimensional clustering of training data.
I wish I'd phrased it better, my point was more that early vision systems had weird issues, which we were able to figure out by looking at what part of the image those models paid attention to and realising it often wasn't even part of the animal in the photo, but e.g. the plants around them. We literally had to think about what made a cat a cat to make AI good at recognising cats.
This would also impact clustering.
That said, I think even for humans there's a similar issue: we spent millennia clustering things into groups and labelling those groups, which is why the Catholic church had rules about no meat on Good Friday but fish was fine and beavers counted as fish (and there is now a podcast titled around the idea there is no such thing as a fish*). For cats, I don't see it myself but the fossa is described as "cat-like".
* https://en.wikipedia.org/wiki/No_Such_Thing_as_a_Fish#Title
the quote from the article is just a contrived tautology that misunderstands the nature of the problem. the dualism problem is not about finding an explanation for why what we call a cat is what we call a cat. it's that you can measure anything you want but nevertheless despite confidently establishing the size of a cat, the appearance of a cat, the behavior of cats, a sophisticated taxonomy of related species labeled "felines", surveying people to find out what cats are to them, what a cat is to me is not what a cat is to you
I'm not particularly well-versed in philosophy, but what's the dualism here?
Of course what a cat _is_ to me is not what a cat _is_ to you, because we necessarily have different memories of interactions with cat-like beings. If you show some babies a cat for the first time, they'll necessarily see it from different viewing perspectives. Even if you put VR glasses on them and show the exact same video, they'll have different contexts: "I first saw a cat when I was sitting next to my friend", "I first saw a cat when I was thinking of ice cream", etc.
But they all saw the same cat, they'll see many other cats, who are all similar. So everyone will understand that "things like these are cats", but everyone will have their own understanding of a "cat" because their memory is different.
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