Does AI engage in behavioralism? Chomsky says yes

Noam Chomsky, a long and persistent critic of artificial intelligence, says yes, or that it at least engages in the equivalent thereof, as related in this extended interview with the Atlantic.

If he is right, and I think he’s at least in the right ballpark, I think this arguably explains why AI, for all its self-touting, is the biggest research science and technology failure this side of peaceful fusion power. Indeed, progress on the two shares a remarkably similar arc.

Noam Chomsky/From The Atlantic

The interview is indeed worth a read. It’s in-depth, and as the Atlantic editor-reporter notes, it’s rare these days, because everybody wants to interview Chomsky on political topics, not scientific ones.

Beyond his “behaviorist” comments, he suggests AI researchers, and at least some people in fields such as his own cognitive science, are still doing research on mind and intelligence at what might be called the wrong level of abstraction. It brings to mind Dan Dennett’s comment (ironic at times, given Dennett) of “greedy reductionism.”

It also brings to mind Paul Davies’ book “The Eerie Silence,” which criticizes SETI, the Search for Extra-Terrestrial Intelligence, for various blinders it may be wearing in its search.

Chomsky, in the interview, also veers at least a bit into his home turf of linguistics. As part of that, he doesn’t have a lot of good to say about Bayesian statistics.

He says there are better ways for us to try to understand the “noise” with which we are bombarded on a daily basis.

I have to agree from a different, folk-level point of view.

To me, Bayesian statistics seems like “the hip thing” for pop and semi-pop observers of human cultural sociology. All it needs is a new book by Malcolm Gladwell.

From there, he ties linguistics back to cognitive science. And, hits the nail on the head, in my opinion:

It's worth remembering that with regard to cognitive science, we're kind of pre-Galilean, just beginning to open up the subject.

He notes that, with the likes of Paracelsus, natural philosophy before Galileo, in the hands of the likes of Paracelsus, was quasi-experimental. It had certainly become more empirical than the philosophical speculation of the Greeks. But, things like the null hypothesis, or the idea of using any particular hypothesis to direct experimentation, weren’t fully there.

Chomsky goes on to question issues related to algorithms. Again, I broadly agree with him. In a more technical way, certainly, than me, he appears to question the issue of claiming that mental processes in general, and especially those that would give us what we would call an intelligent consciousness, can be reduced to, or framed in terms of, algorithms. Indeed, when asked about it, in relation to some particular research and mental modeling, he specifically rejects the need for algorithms.

It sounds like in both cognitive science and artificial intelligence, if not already, Chomsky could soon become about as controversial as he is on U.S. foreign policy.

But, don’t stop there. Chomsky, getting into his theories of language, and with a nod to Wittgenstein, argues that something analogous to language could be used as part of new attempts to understand bodily systems, such as, say, how the immune system works. It’s true that biology already talks about things such as “signaling,” but in the past, it’s seemed to use these words and phrases anthropomorphically, and Chomsky is saying, “take the next step.”

Anyway, I’m just scratching the surface of my analysis, both in terms of how much of the interview I’m analyzing and how much analysis I’m putting forth. Go read the full thing yourself.

Let me just add that he closes by saying something else I agree with, and that I read Steve Toulmin saying 15 years or so ago: Scientists still need philosophers of science challenging them, now perhaps more than ever.

AI, computers, minds, algorithms, evolution, Dennett

If even artificial intelligence advocates have largely abandoned the idea that AI is ultimately algorithmic, it’s time to question a lot of related assumptions, some of which I already have.

First, the human mind, then, is clearly not algorithmic. And, it’s likely even less algorithmic than a computer.

Second, being “kludged” together by evolution, it’s most surely not a black box, like a modern software program, routine, or subroutine.

Third, running off that point, contra Dan Dennett, evolution is most assuredly not algorithmic, either, as I’ve said before.

Fourth, the Turing test, as stipulated by Alan Turing himself, was NOT about whether a machine could think, but about whether a machine could simulate thinking. In other words, in modern philosophy terminology, Turing was a functionalist, as is Dennett (on this issue, at least), even as he continues to deny it.

Anyway, read the full story linked above.

Human brain not built for theistic evolution

Boy, this Live Science post just jumped out at me.

Using an fMRI to measure brain responses, and using either “gOd” or “science” as a priming word for subjects who first read information about the Big Bang, at the cosmology level, or “primal soup” at the Earth level, psychologist Jesse Preston of the University of Illinois at Urbana-Champaign and her colleague Nicholas Epley of the University of Chicago found statistical signs that people who know the basics of both cannot hold on to both the naturalistic focus of science and the transcendent metaphysic of theism at the same time:

“We can only believe in one explanation at a time,” Preston told LiveScience. “So although people can report explicitly, ‘Look, I’ve been a Christian all my life, and yes, I also believe in science and I am a practicing chemist,’ the question is, are these people really reconciling belief in God and science, or are they just believing in one thing at a time?”

But, the researcher’s thesis is being questioned.

In shades of Steven Jay Gould, Hampshire College science historian Salman Hameed says the conclusions depend on the “conflict” view of science and religion, vs. Gould’s non-oppositional magisteria or similar.

But, what Hameed overlooks is that among PhD scientists, especially top-tier post-doc PhDs, Gould’s two-domains theory is ignored even more than it is dismissed. Ditto among modern philosophers of science and non-science philosophers who aren’t explicit theists.

Darwinism looks to explain collective behavior

Wired has a great article on what the next frontier, or hurdle if you will, is for the explanatory power of modern neo-Darwinism — the development of groups and collectives. This includes bees in a hive, ants in a colony, bacteria in a collective, and even more complex things such as the vast array of bacteria that make up 90 percent of the cells in our own “human” bodies.

The main question is, how can neo-Darwinian theory as currently constituted explain these developments of evolutionary biology — if it can?

Down in front, creationists and IDers. Wired is a serious magazine and isn’t asking for “explanations” from you.

But, some of the evolutionary biologists quoted in the story say that something, either a greatly modified neo-Darwinianism or else some appended theory of emergent properties, based on things like chaos theory, complexity theory, and the “tipping points” popularized by Malcolm Gladwell, is going to be needed to do the trick.

”There’s nothing wrong with neo-Darwinian evolution in its own right,” Carl Woese said, “but it’s not large enough to encompass what we know now.”

Woese’s specialty is bacteria, and he’s not afraid of bold theories that turn conventional scientific wisdom on its head. In 1977, he and colleague George Fox rearranged the animal kingdom from five branches into three, two of which comprise microbes.

Microbes make up much of Earth’s biomass, and they also cast into relief the shortcomings of neo-Darwinian evolution. A bucket of seawater can contain 60,000 bacterial species, and to Woese, these must be seen as a collective rather than as disparate units.

At the collective level, said Woese, bacteria exhibit patterns of organization and behavior that emerge suddenly, at tipping points of population variation and density called “saltations.” Natural selection still favors — or disfavors — the ultimate outcome of these jumps, but the jumps themselves seem to defy explanation solely through genetic changes or individual properties.

Such jumps don’t just call into question whether evolution is capable of producing sudden rather than gradual change. That debate raged during the later stages of the last century, but has been largely settled in favor of what paleontologists Niles Eldredge and Stephen Jay Gould termed punctuated equilibrium. By contrast, Woese invokes yet-to-be-quantified rules of complexity and emergence. These, he said, may also explain other exceptional jumps, such as the transition from protein fragments to single cells and from single-celled organisms to multicellular ones.

Contrary to IDers, creationists, or New Agers, etc., Woese works with rules that have a basis in science and/or mathematics, rules that are ultimately testable through construction of hypotheses.

Part of the issue hinges on debate over an idea stated most forcefully by philosopher Daniel Dennett: Is neo-Darwinism algorithmic or not? I am guessing Woese would either say “I don’t know,” or “possibly not.” Other evolutionary biologists might agree with Dennett, yet others might reject his claim forcefully.

”Selection probably happens at all scales, from gene to individual to species to collection of species to ecosystem to we don’t even know what,” said Maya Paczuski, head of the Complexity Science Group at the University of Calgary.

Paczuski’s group sees evolution as taking place at all these levels, with what happens in ecosystems rippling down to individuals, back up to populations, across to other populations, and so on — all simultaneously, and in tandem with the mysterious dynamics of networked complexity.

But does it all happen mechanically? Or does evolution obey some larger imperative?

University of Nevada evolutionary biologist Guy Hoelzer calls that imperative biospheric self-organization. "The idea of evolution is embedded within self-organization,” he said. “It coordinates the ecological roles of species so that ecosystems persist and process a great deal of energy.”

I, too, doubt Dennett’s idea, though as a scientific layperson (but not a philosophical one), I don’t think I have enough of a scientific background to be able to reject it forcefully. I do think that, to some degree, the developmental processes we eventually discover in the emergent properties of biological groups, collectives and ecosystems will show enough discontinuity with neo-Darwinism to be likely to develop as separate subfield within evolutionary biology.

Evolution’s acceleration and the evolution of religious belief

Recent news that the pace of human evolution may have accelerated in the last 40,000 years, and accelerated a lot in the last 10,000, seems like it would fit both with books I’ve read on cognitive science and evolutionary psychology’s connection with religion by others such as Scott Atran and Pascal Boyer, but also with the dating of cave paintings in sites such as Lascaux.

Human evolution running at breakneck speed

And has been doing so for the past 5,000 years. Humans today are more different from humans of 5,000 years ago than those humans were from the last of the Neanderthals 30,000 years ago.

Among the main driving forces? The explosion in human population and the invention of agriculture. The main changes caused include digestive abilities, per the rise of agriculture, and resistance to disease, per the density growth in human population, which largely was an Old World phenomenon, as the disease non-resistant pre-Columbian Americans were to learn.

Global warming, increased human migration and other issues will certainly get a new look in light of this.