kalkin

This basically Searle's Chinese Room argument. It's got a respectable history (... Searle's personal ethics aside) but it's not something that has produced any kind of consensus among philosophers. Note that it would apply to any AI instantiated as a Turing machine and to a simulation of human brain at an arbitrary level of detail as well.

There is a section on the Chinese Room argument in the book.

(I personally am skeptical that LLMs have any conscious experience. I just don't think it's a ridiculous question.)

He talks pretty specifically about what he means by "the architectures many consciousness scientists associate with conscious systems" - Global Workspace theory, Higher Order theory and Integrated Information theory. This is on the second and third pages of the intro chapter.

You seem to be confusing the training task with the architecture. Next-token prediction is a task, which many architectures can do, including human brains (although we're worse at it than LLMs).

Note that some of the theories Schwitzgebel cites would, in his reading, require sensors and/or recurrence for consciousness, which a plain transformer doesn't have. But neither is hard to add in principle, and Anthropic like its competitors doesn't make public what architectural changes it might have made in the last few years.

> I'm not convinced he's trying to make the point you think he is

What point do you think he's trying to make?

(TBH, before confidently accusing people of "delusion" or "grift" I would like to have a better argument than a sequence of 4-6 word sentences which each restate my conclusion with slightly variant phrasing. But clarifying our understanding of what Schwitzgebel is arguing might be a more productive direction.)

That two things can or should be discussed independently doesn't mean either is unimportant. And insisting that you know what I meant better than I do is not a good way to have a productive conversation.

As for the Doctorow article, I don't understand exactly what you're trying to say about "focus", but it's incoherent to read the discussion about replacement of your current job as talking purely about the present - since the job is currently yours, the replacement must happen in the future.

Neither in my previous comment nor in my actual views do I dismiss the human element or expect to isolate myself from societal effects.

> I was pleasantly surprised that this was not yet another argument of "AI is (not) good enough"

The article does assert that, and that's important for its argument that ordinary workers just need to convince decisionmakers that things will go poorly if they replace us.

"Now, if AI could do your job, this would still be a problem... But AI can’t do your job."

This isn't ambiguous.

This book (from a philosophy professor AFAIK unaffiliated with any AI company) makes what I find a pretty compelling case that it's correct to be uncertain today about what if anything an AI might experience: https://faculty.ucr.edu/~eschwitz/SchwitzPapers/AIConsciousn...

From the folks who think this is obviously ridiculous, I'd like to hear where Schwitzgebel is missing something obvious.

I don't think the commenter to whom you're replying is any more aggressive than, e.g., this one: https://news.ycombinator.com/item?id=46668988

It's unfortunately the case that even understanding what AI can and cannot do has become a matter of, as you say, "ideological world view". Ideally we'd be able to discuss what's factually true of AI at the beginning of 2026, and what's likely to be true within the next few years, independently of whether the trends are good for most humans or what we ought to do about them. In practice that's become pretty difficult, and the article to which we're all responding does not contribute positively.

I agree with the thrust of your comment, but I think the comment to which you're replying was referring to Scott Alexander's "problematic past with reactionaries and race science", not Adams'.

https://gist.github.com/segyges/f540a3dadeb42f49c0b0ab4244e4...

(To be honest I would love for someone to write an essay engaging with Alexander in something of the spirit he engages with Adams here; he writes both good things, including IMHO this eulogy, but also a certain amount of garbage, and I do not claim to be wise enough to always distinguish on my own.)

The article does a pretty lazy* job of defending its assumption that "solving really gnarly, abstract puzzles" is going to remain beyond AI capabilities indefinitely, but that is a load-bearing part of the argument and Doctorow does try to substantiate it by dismissing LLMs as next-word predictors. This is a description which is roughly accurate at some level of reduction but has not helped anyone predict the last three years of advances and so seems pretty unlikely to be a helpful guide to the next three years.

The other argument Doctorow gives for the limits of LLMs is the example of typo-squatting. This isn't an attack that's new to LLMs and, while I don't know if anyone has done a study, I suspect it's already the case in January 2026 that a frontier model is no more susceptible to this than the median human, or perhaps less; certainly in general Claude is less likely to make a typo than I am. There are categories of mistakes it's still more likely to make than me, but the example here is already looking out of date, which isn't promising for the wider argument.

*to be fair, it's clearly not aimed at a technical audience.

> AI is a statistical inference engine. All it can do is predict what word will come next based on all the words that have been typed in the past.

If we keep saying this hard enough over and over, maybe model capabilities will stop advancing.

Hey, there's even a causal story here! A million variations of this cope enter the pretraining data, the model decides the assistant character it's supposed to be playing really is dumb, human triumph follows. It's not _crazier_ than Roko's Basilisk.

I don't think you write a eulogy this long about someone unless you have something more than a simple dislike or even hatred for them.

It's way too far into the Trump administration for people to still be responding to authoritarian moves by Trump by finding Biden administration actions that sound vaguely similar if you don't think too hard and then pretending nothing new is going on here. (Even if it wasn't, "that's nothing" would be a pretty weird inference to draw with a comparison to something that clearly upsets you, and an article is a "piece", not a "peace".)

Who is Lonsdale referring to as the "good guys"?

(It's one thing to ask people to be fair in responding to your actual comment and not a strawman. It's another to ask us to pretend we were born yesterday. We do in fact have external sources of information about Lonsdale's political allegiences.)

This is interesting partly because Alex Karp (at least used to) occasionally claim to be a socialist when it was inconvenient or uncool to be defined as a standard issue rightwinger. Never thought that meant much myself - any more than it's meaningful for Lonsdale to define himself as against "evil authoritarian forces" here while advocating the murder of his political opponents - but I know people who took him seriously for some reason.

It's good to have these guys out in the open as Pinochet types, though. Silver lining of the Trump era.

More the former. Re the latter, it's not so much that I'm annoyed he doesn't agree with the AI2027 people, it's that (he spends a few paragraphs talking about them while) he doesn't appear to have bothered trying to even understand them.

I have nonspecific positive associations with Dan Wang's name, so I rolled my eyes a bit but kept going when "If the Bay Area once had an impish side, it has gone the way of most hardware tinkerers and hippie communes" was followed up by "People aren’t reminiscing over some lost golden age..."

But I stopped at this:

> “AI will be either the best or the worst thing ever.” It’s a Pascal’s Wager

That's not what Pascal's wager is! Apocalyptic religion dates back more than two thousand years and Blaise Pascal lived in the 17th century! When Rosa Luxemburg said to expect "socialism or barbarism", she was not doing a Pascal's Wager! Pascal's Wager doesn't just involve infinite stakes, but also infinitesimal probabilities!

The phrase has become a thought-terminating cliche for the sort of person who wants to dismiss any claim that stakes around AI are very high, but has too many intellectual aspirations to just stop with "nothing ever happens." It's no wonder that the author finds it "hard to know what to make of" AI 2027 and says that "why they put that year in their title remains beyond me."

It's one thing to notice the commonalities between some AI doom discourse and apocalyptic religion. It's another to make this into such a thoughtless reflex that you also completely muddle your understanding of the Christian apologetics you're referencing. There's a sort of determined refusal to even grasp the arguments that an AI doomer might make, even while writing an extended meditation on AI, for which I've grown increasingly intolerant. It's 2026. Let's advance the discourse.

How do you imagine existing benchmarks were created?

If you can't define intelligence in a way that distinguishes AIs from people (and doesn't just bake that conclusion baldly into the definition), consider whether your insistence that only one is REAL is a conclusion from reasoning or something else.

Charitably I'm guessing it's supposed to be an allusion to the chart with cost per word? Which is measuring an input cost not an output value, so the criticism still doesn't quite make sense, but it's the best I can do...

Did they turn out to be right? Maybe, I'm not familiar with the research here, but no evidence for that has actually been posted. This study being untrustworthy doesn't make it prove its opposite instead.

Scale AI wrote a paper a year ago comparing various models performance on benchmarks to performance on similar but held-out questions. Generally the closed source models performed better, and Mistral came out looking pretty badly: https://arxiv.org/pdf/2405.00332

Yes, this is by no means only a U.S. problem. Some countries are worse, even where birth rate trends seem like they should make it more obviously self-destructive. A tendency towards xenophobia seems to be an unfortunate human universal, although one we can sometimes overcome.

In many circumstances - including when that person is married to a US citizen, or when they'll likely be killed on return to their country of birth - it is indeed crazy and cruel.

(In more ordinary circumstances it's merely arbitrary and unjust.)

I appreciate that this comment is much less prescriptive. I don't think I disagree with you about any general best practices here (although I do think unwrap can be fine when you can locally verify the error or nil case is unreachable but proving that to the compiler is impractical.)

Unless you work at Cloudflare it seems very unlikely that you have enough information about systems and tradeoffs there to make these flat assertions about what "should have" happened. Systems can do worse things than crashing in response to unexpected states. Blue/green deployment isn't always possible (eg due to constrained compute resources) or practical (perhaps requiring greatly increased complexity), and is by no means the only approach to reducing deploy risk. We don't know that any of the related code was shipped with a "move fast, break things" mindset; the most careful developers still write bugs.

Actually learning from incidents and making systems more reliable requires curiosity and a willingness to start with questions rather than mechanically applying patterns. This is standard systems-safety stuff. The sort of false confidence involved in making prescriptions from afar suggests a mindset I don't want anywhere near the operation of anything critical.

Ah cool that site's robots.txt is still broken, just like it was when it first came up on HN...

That's not Pascal's Wager unless they're saying AGI has infinitesimal probability but infinite payoff, or something like that. If they think AGI is likely, they may be wrong but it's just technological optimism.

Seems like a philosophy question, with maybe some input from neuroscience and ML interpretability. I'm not sure what faith in science fiction has to do with it.

What is the definition of Pascal's Wager in your mind?

Conflating consciousness and intelligence is going to hopelessly confuse any attempt to understand if or when a machine might achieve either.

(I think there's no reasonable definition of intelligence under which LLMs don't possess some, setting aside arguments about quantity. Whether they have or in principle could have any form of consciousness is much more mysterious -- how would we tell?)