These threads are always massive, embarrassing trainwrecks of naive takes on cognition and consciousness.
It's like HN just woke up and refuses to acknowledge the relevance of the extensive prior literature on these subjects. Instead, people seem mostly fine with making shit up.
Embarrassing.
It's fine. We're social animals, we discuss topics even if we lack perfect expertise, at our present level of understanding. I've certainly had, for example, many opinions on programming that were later superseded by deeper understanding or evolving priorities.
It's just important to remember there's probably a bigger and better expert out there, and stay humble and interested, and let yourself be corrected.
Among the other technical and scientific topics often discussed here, there is a basic general expectation of grounded reference to existing research and bodies of knowledge. Deviations from this standard are usually met with corrections.
With the topic of cognition and consciousness, this is not so (generally). The standard is to absolutely not reference existing research and to basically pretend it doesn't exist.
Instead, the vacuum of ignorance is filled with whatever comes to mind and threads engage in freeform speculation.
This is also ironic since these topics are usually about how LLMs don't understand and just fill the vacuum of its ignorance with whatever happens to be next on the statistical chain, regardless of veracity.
With physics, for example, people have an understanding that there's a large existing body of work, and that physics has been remarkably successful at building on earlier knowledge for decades without having to debunk a lot of earlier results. It's a familiar story.
With AI, however, the popular narrative is that earlier approaches to the problem were all laughing stocks that went nowhere. There's not a good sense for how old some the ideas that work now actually are, and how many of the older theoretical and thought frameworks are still perfectly valid, in particular at the interfaces toward other branches of science and engineering. There's some more nuanced and balanced primers on the topic (e.g. the Wooldridge book), but an awful lot more writing on AI Winters and what not.
This snowballs into a lack of awareness of the overlap between "AI" and, say, the body of knowledge in statistics.
In other words: Sure, I agree - HN collectively is less knowledge on this than on some other topics (myself included!), and it's worth taking stock of that, I suppose.
The onus [1] should go the other way.
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[1] Today's conversation-derailing trivium: "onus" means ass in Greek. As in donkey.
A colleague at my first job was working on some software that wrapped around other software, and he dubbed it "Burrito". When his project turned out not to be as useful as expected, he was pleasantly surprised that he could also use the original meaning of the word burrito, being "little donkey" in Spanish [1].
These silly generalisations about HN are pointless. HN has a pretty diverse set of worldviews, approaches, and levels of expertise across a range of topics. There is zero point in lumping people into a single, or even a majority, behaviour.
The idea that generalities can't be true or useful is pretty insidious, since it prevents reasoning about groups.
This idea was not mentioned, whether or not you attest that it was.
This means we have to be lucky to have some expert with current knowledge join in. Given that most people here are billionaires with a passion for dynamic typing, and not philosophers of mind, I am actually fairly surprised at the reasonable level of discussion.
Also, I doubt that referencing prior literature in the context of cognition and consciousness would be of much help. HN writes a lot of nonsense about it, but so have many professional philosophers. After sifting through all of that, one still has to add a lot of convincing arguments to advance an unpopular opinion.
A friend once suggested to build forum software that would allow discussions to reach a certain level of trustworthiness or truth. After several lengthy discussions I still doubt that such a thing is feasible. But it might spark your interest? :)
What does it mean to understand something? To think? How is a human any different than predicting the next “thing” given a series of inputs?