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Some Quick and Dirty Thoughts on "The empty brain" (aeon.co)
submitted 2 years ago* (last edited 2 years ago) by to c/morewrite@awful.systems
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This started as a summary of a random essay Robert Epstein (fuck, that's an unfortunate surname) cooked up back in 2016, and evolved into a diatribe about how the AI bubble affects how we think of human cognition.

This is probably a bit outside awful's wheelhouse, but hey, this is MoreWrite.

The TL;DR

The general article concerns two major metaphors for human intelligence:

  • The information processing (IP) metaphor, which views the brain as some form of computer (implicitly a classical one, though you could probably cram a quantum computer into that metaphor too)
  • The anti-representational metaphor, which views the brain as a living organism, which constantly changes in response to experiences and stimuli, and which contains jack shit in the way of any computer-like components (memory, processors, algorithms, etcetera)

Epstein's general view is, if the title didn't tip you off, firmly on the anti-rep metaphor's side, dismissing IP as "not even slightly valid" and openly arguing for dumping it straight into the dustbin of history.

His main major piece of evidence for this is a basic experiment, where he has a student draw two images of dollar bills - one from memory, and one with a real dollar bill as reference - and compare the two.

Unsurprisingly, the image made with a reference blows the image from memory out of the water every time, which Epstein uses to argue against any notion of the image of a dollar bill (or anything else, for that matter) being stored in one's brain like data in a hard drive.

Instead, he argues that the student making the image had re-experienced seeing the bill when drawing it from memory, with their ability to do so having come because their brain had changed at the sight of many a dollar bill up to this point to enable them to do it.

Another piece of evidence he brings up is a 1995 paper from Science by Michael McBeath regarding baseballers catching fly balls. Where the IP metaphor reportedly suggests the player roughly calculates the ball's flight path with estimates of several variables ("the force of the impact, the angle of the trajectory, that kind of thing"), the anti-rep metaphor (given by McBeath) simply suggests the player catches them by moving in a manner which keeps the ball, home plate and the surroundings in a constant visual relationship with each other.

The final piece I could glean from this is a report in Scientific American about the Human Brain Project (HBP), a $1.3 billion project launched by the EU in 2013, made with the goal of simulating the entire human brain on a supercomputer. Said project went on to become a "brain wreck" less than two years in (and eight years before its 2023 deadline) - a "brain wreck" Epstein implicitly blames on the whole thing being guided by the IP metaphor.

Said "brain wreck" is a good place to cap this section off - the essay is something I recommend reading for yourself (even if I do feel its arguments aren't particularly strong), and its not really the main focus of this little ramblefest. Anyways, onto my personal thoughts.

Some Personal Thoughts

Personally, I suspect the AI bubble's made the public a lot less receptive to the IP metaphor these days, for a few reasons:

  1. Articial Idiocy

The entire bubble was sold as a path to computers with human-like, if not godlike intelligence - artificial thinkers smarter than the best human geniuses, art generators better than the best human virtuosos, et cetera. Hell, the AIs at the centre of this bubble are running on neural networks, whose functioning is based on our current understanding of how the brain works. [Missed this incomplete sensence first time around :P]

What we instead got was Google telling us to eat rocks and put glue in pizza, chatbots hallucinating everything under the fucking sun, and art generators drowning the entire fucking internet in pure unfiltered slop, identifiable in the uniquely AI-like errors it makes. And all whilst burning through truly unholy amounts of power and receiving frankly embarrassing levels of hype in the process.

(Quick sidenote: Even a local model running on some rando's GPU is a power-hog compared to what its trying to imitate - digging around online indicates your brain uses only 20 watts of power to do what it does.)

With the parade of artificial stupidity the bubble's given us, I wouldn't fault anyone for coming to believe the brain isn't like a computer at all.

  1. Inhuman Learning

Additionally, AI bros have repeatedly and incessantly claimed that AIs are creative and that they learn like humans, usually in response to complaints about the Biblical amounts of art stolen for AI datasets.

Said claims are, of course, flat-out bullshit - last I checked, human artists only need a few references to actually produce something good and original, whilst your average LLM will produce nothing but slop no matter how many terabytes upon terabytes of data you throw at its dataset.

This all arguably falls under the "Artificial Idiocy" heading, but it felt necessary to point out - these things lack the creativity or learning capabilities of humans, and I wouldn't blame anyone for taking that to mean that brains are uniquely unlike computers.

  1. Eau de Tech Asshole

Given how much public resentment the AI bubble has built towards the tech industry (which I covered in my previous post), my gut instinct's telling me that the IP metaphor is also starting to be viewed in a harsher, more "tech asshole-ish" light - not just merely a reductive/incorrect view on human cognition, but as a sign you put tech over human lives, or don't see other people as human.

Of course, AI providing a general parade of the absolute worst scumbaggery we know (with Mira Murati being an anti-artist scumbag and Sam Altman being a general creep as the biggest examples) is probably helping that fact, alongside all the active attempts by AI bros to mimic real artists (exhibit A, exhibit B).

other discussions
63
Your brain does not process information & it is not a computah (aeon.co)
submitted 4 months ago* by to c/science@hexbear.net
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----------> https://archive.ph/5FUvT

No matter how hard they try, brain scientists and cognitive psychologists will never find a copy of Beethoven’s 5th Symphony in the brain – or copies of words, pictures, grammatical rules or any other kinds of environmental stimuli. The human brain isn’t really empty, of course. But it does not contain most of the things people think it does – not even simple things such as ‘memories’.

Our shoddy thinking about the brain has deep historical roots, but the invention of computers in the 1940s got us especially confused. For more than half a century now, psychologists, linguists, neuroscientists and other experts on human behaviour have been asserting that the human brain works like a computer.

To see how vacuous this idea is, consider the brains of babies. Thanks to evolution, human neonates, like the newborns of all other mammalian species, enter the world prepared to interact with it effectively. A baby’s vision is blurry, but it pays special attention to faces, and is quickly able to identify its mother’s. It prefers the sound of voices to non-speech sounds, and can distinguish one basic speech sound from another. We are, without doubt, built to make social connections.

A healthy newborn is also equipped with more than a dozen reflexes – ready-made reactions to certain stimuli that are important for its survival. It turns its head in the direction of something that brushes its cheek and then sucks whatever enters its mouth. It holds its breath when submerged in water. It grasps things placed in its hands so strongly it can nearly support its own weight. Perhaps most important, newborns come equipped with powerful learning mechanisms that allow them to change rapidly so they can interact increasingly effectively with their world, even if that world is unlike the one their distant ancestors faced.

Senses, reflexes and learning mechanisms – this is what we start with, and it is quite a lot, when you think about it. If we lacked any of these capabilities at birth, we would probably have trouble surviving.

But here is what we are not born with: information, data, rules, software, knowledge, lexicons, representations, algorithms, programs, models, memories, images, processors, subroutines, encoders, decoders, symbols, or buffers – design elements that allow digital computers to behave somewhat intelligently. Not only are we not born with such things, we also don’t develop them – ever.

We don’t store words or the rules that tell us how to manipulate them. We don’t create representations of visual stimuli, store them in a short-term memory buffer, and then transfer the representation into a long-term memory device. We don’t retrieve information or images or words from memory registers. Computers do all of these things, but organisms do not.

Computers, quite literally, process information – numbers, letters, words, formulas, images. The information first has to be encoded into a format computers can use, which means patterns of ones and zeroes (‘bits’) organised into small chunks (‘bytes’). On my computer, each byte contains 8 bits, and a certain pattern of those bits stands for the letter d, another for the letter o, and another for the letter g. Side by side, those three bytes form the word dog. One single image – say, the photograph of my cat Henry on my desktop – is represented by a very specific pattern of a million of these bytes (‘one megabyte’), surrounded by some special characters that tell the computer to expect an image, not a word.

Computers, quite literally, move these patterns from place to place in different physical storage areas etched into electronic components. Sometimes they also copy the patterns, and sometimes they transform them in various ways – say, when we are correcting errors in a manuscript or when we are touching up a photograph. The rules computers follow for moving, copying and operating on these arrays of data are also stored inside the computer. Together, a set of rules is called a ‘program’ or an ‘algorithm’. A group of algorithms that work together to help us do something (like buy stocks or find a date online) is called an ‘application’ – what most people now call an ‘app’.

Forgive me for this introduction to computing, but I need to be clear: computers really do operate on symbolic representations of the world. They really store and retrieve. They really process. They really have physical memories. They really are guided in everything they do, without exception, by algorithms.

Humans, on the other hand, do not – never did, never will. Given this reality, why do so many scientists talk about our mental life as if we were computers?

77
Your brain does not process information and it is not a computer | Aeon Essays (aeon.co)
submitted 2 years ago by to c/chapotraphouse@hexbear.net
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the-podcast guy recently linked this essay, its old, but i don't think its significantly wrong (despite gpt evangelists) also read weizenbaum, libs, for the other side of the coin