Might humans not be the most intelligent animals?

I think the current record is suggestive that Neanderthals were more individually intelligent than the anatomically modern humans that displaced them, tho obviously anatomically modern human society was more capable than Neanderthal society (through a combination of superior communication ability, trade, and higher population density). [I think it's quite likely that Neanderthals were less intelligent than humans currently alive today.]

We also have some evidence that we've selectively destroyed the intelligence of other animals as part of domestication; wolves perform better than dogs on causal reasoning tasks (of the sort that would make them more obnoxious as pets; many people want a 'smart' dog and then discover how difficult it is to get them to take their medicine, or keep them out of the treat drawer, and so on). So even if most animals around today are 'dumb', it may be because 'we wanted it that way.'

When it comes to AI, tho, I think the right analogy is not "individual human vs. individual AI" but "human civilization (with computers)" vs. "AI civilization". It seems pretty clear to me that most of the things to worry about with AGI look like it getting the ability to do 'cultural accumulation', at least with regards to technological knowledge, and aren't related to "it has a much higher working memory!" or other sorts of individual intelligence tasks. In this lens, the superiority of artificial intelligence is mostly cultural superiority. (For example, this description of AI takeoff [LW(p) · GW(p)] hinges not on superior individual ability, but enhanced 'cultural learning'.)

One example is the chimpanzee, which may have better working memory

This isn’t what the linked paper says. It claims that

Chimps + practice > humans

but

Humans + practice >> chimps + practice

From the abstract:

There is no evidence for a superior or qualitatively different spatial memory system in chimpanzees.

We do see some initial signs that humans might not be the most intelligent species on Earth in the innovative sense. For instance,

Although humans have the highest encephalization quotient, we don't have the most neurons, or even the most neurons in our forebrain.

I don't find the facts about number of neurons very suggestive of humans not being the most intelligent. On the contrary, when I look at the lists, it reinforces the idea that humans are smartest individually.

For total neuron count, only one animal beats humans: the African elephant, with 50% more, and humans have more than 2x the next highest (which is the Gorilla). So if we think the total neuron count numbers tell us how smart an animal is, then either humans or elephants are at the top.

For forebrain neurons, the top 10 are 8 kinds of whale, with humans at number 3 and gorillas at number 10.

Notably, humans and gorillas are the only animals in the top 10 on both lists, with humans handily beating gorillas in both cases. And all the animals which beat humans having much higher body mass.

I think if you were an alien who thought neurons were important for intelligence, and saw the lists above, but didn't know anything else about the species, you'd probably have most of your probability mass on either elephants, primates, or whales being the smartest. Once you saw human behavior you'd update to most of the mass being on humans at the top.

And similarly, if you already had as one of your leading hypotheses that humans were smartest, based on their behavior, and also that neurons were important, then I'd think seeing humans so high on the lists above would tend to confirm the humans-are-smartest hypothesis, rather than disconfirm it.

I think one of the strongest arguments for humans being the smartest animals is that the social environment that language and human culture created lead to a massive increase in returns to intelligence, and I think there's some evidence from what we know about evolution that the human neocortex ballooned around the same time that we're theorized to have developed language and culture.

There's more than one thing that you could mean by raw innovative capacity separate from cultural processing ability. First, you could mean someone's ability to innovate on their own without any direct help from others on the task at hand, but where they're allowed to use skills that they previously acquired from their culture. Second, you could mean someone's counterfactual ability to innovate on their own if they hadn't learned from culture. You seem to be conflating these somewhat, though mostly focusing on the second?

The second is underspecified, as you'd need to decide what counterfactual upbringing you're assuming. If you compare the cognitive performance of a human raised by bears to the cognitive performance of a bear in the same circumstances, this is unfair to the human, since the bear is raised in circumstances that it is adapted for and the human is not, just like comparing the cognitive performance of a bear raised by humans to that of a human in the same circumstances would be unfair to the bear. Though a human raised by non-humans would still make a more interesting comparison to non-human animals than Genie would, since Genie's environment is even less conducive to human development (I bet most animals wouldn't cognitively develop very well if they were kept immobilized in a locked room until maturity either).

I think this makes the second notion less interesting than the first, as there's a somewhat arbitrary dependence on the counterfactual environment. I guess the first notion is more relevant when trying to reason specifically on genetics as opposed to other factors that influence traits, but the second seems more relevant in other contexts, since it usually doesn't matter to what extent someone's abilities were determined by genetics or environmental factors.

I didn't really follow your argument for the relevance of this question to AI development. Why should raw innovation ability be more susceptible to discontinuous jumps than cultural processing ability? Until I understand the supposed relevance to AI better, it's hard for me to say which of the two notions is more relevant for this purpose.

I'd be very surprised if any existing non-human animals are ahead of humans by the first notion, and there's a clear reason in this case why performance would correlate strongly with social learning ability: social learning will have helped people in the past develop skills that they keep in the present. Even for the second notion, though it's a bit hard to say without pinning down the counterfactual more closely, I'd still expect humans to outperform all other animals in some reasonable compromise environment that helps both develop but doesn't involve them being taught things that the non-humans can't follow. I think there are still reasons to expect social learning ability and raw innovative capability to be correlated even in this sense, because higher general intelligence will help for both; original discovery and understanding things that are taught to you by others both require some of the same cognitive tools.

Planned summary for the Alignment Newsletter:

We can roughly separate intelligence into two categories: _raw innovative capability_ (the ability to figure things out from scratch, without the benefit of those who came before you), and _culture processing_ (the ability to learn from accumulated human knowledge). It's not clear that humans have the highest raw innovative capability; we may just have much better culture. For example, feral children raised outside of human society look very "unintelligent", The Secret of Our Success documents cases where culture trumped innovative capability, and humans actually _don't_ have the most neurons, or the most neurons in the forebrain.

(Why is this relevant to AI alignment? Matthew claims that it has implications on AI takeoff speeds, though he doesn't argue for that claim in the post.)

Planned opinion:

It seems very hard to actually make a principled distinction between these two facets of intelligence, because culture has such an influence over our "raw innovative capability" in the sense of our ability to make original discoveries / learn new things. While feral children might be less intelligent than animals (I wouldn't know), the appropriate comparison would be against "feral animals" that also didn't get opportunities to explore their environment and learn from their parents, and even so I'm not sure how much I'd trust results from such a "weird" (evolutionarily off-distribution) setup.

Interestingly, we created selection pressure on other species to create something like human intelligence. First of all, dogs, which were selected for15 000 years to be more compatible with humans, which also includes a capability to understand human signals and language. Some dogs could understand few hundreds words.

If the reason for our technological dominance is due to our ability to process culture, however, then the case for a discontinuous jump in capabilities is weaker. This is because our AI systems can already process culture somewhat efficiently right now (see GPT-2) and there doesn't seem like a hard separation between "being able to process culture inefficiently" and "able to process culture efficiently" other than the initial jump from not being able to do it at all, which we have already passed.

I keep hearing people say this (the part "and there doesn't seem to be a hard separation"), but I don't intuitively agree! I've spelled out my position here [LW(p) · GW(p)]. I have the intuition that there's a basin of attraction for good reasoning ("making use of culture to improve how you reason") that can generate a discontinuity. You can observe this among humans. Many people, including many EAs, don't seem to "get it" when it comes to how to form internal world models and reason off of them in novel and informative ways. If someone doesn't do this, or does it in a fashion that doesn't sufficiently correspond to reality's structure, they predictably won't make original and groundbreaking intellectual contributions. By contrast, other people do "get it," and their internal models are self-correcting to some degree at least, so if you ran uploaded copies of their brains for millennia, the results would be staggeringly different.

Ehn. If other animals are so smart, why aren't they rich?

I think you can make a strong argument that processing culture is more important than raw innovative ability for growth over time. I don't think you can make much of an argument that any beast but us has a mix of the two that has allowed significant sustained improvements in individual or species longevity or adaptation to environment.

Isn't it the case that no non-human animal has ever been able to speak a language, even if we've tried to raise it as a human? (And that we have in fact tried this with chimps?) If that's true, why isn't that the end of the conversation? This is what's always confused me about this debate. It seems like everyone is ignoring the slam-dunk evidence that's right there.

If the reason for our technological dominance is due to our ability to process culture, however, then the case for a discontinuous jump in capabilities is weaker. This is because our AI systems can already process culture somewhat efficiently right now (see GPT-2) and there doesn't seem like a hard separation between "being able to process culture inefficiently" and "able to process culture efficiently" other than the initial jump from not being able to do it at all, which we have already passed.

I think you're giving GPT-2 too much credit here. I mean, on any dimension of intelligence, you can say there's a continuum of capabilities along that scale with no hard separations. The more relevant question is, might there be a situation where all the algorithms are like GPT-2, which can only pick up superficial knowledge, and then someone has an algorithmic insight, and now we can make algorithms that, as they read more and more, develop ever deeper and richer conceptual understandings? And if so, how fast could things move after that insight? I don't think it's obvious.

I do agree that pretty much everything that might make an AGI suddenly powerful and dangerous is in the category of "taking advantage of the products of human culture", for example: coding (recursive self-improvement, writing new modules, interfacing with preexisting software and code), taking in human knowledge (reading and deeply understanding books, videos, wikipedia, etc., a.k.a. "content overhang") , computing hardware (self-reproduction / seizing more computing power , a.k.a. "hardware overhang"), the ability of humans to coordinate and cooperate (social manipulation, earning money, etc.), etc. In all these cases and more, I would agree that one could in principle define a continuum of capabilities from 0 to superhuman with no hard separations, but still think that it's possible for a new algorithm to jump from "2019-like" (which is more than strictly 0) to "really able to take advantage of this tool like humans can or beyond" in one leap.

Sorry if I'm misunderstanding your point.

" some animals that are more intelligent than animals" --> " some animals that are more intelligent than HUMANS "