It’s an analogy that goes back to the dawn of the computer age: Ever since we discovered that machines can solve problems by manipulating symbols, we’ve wondered whether our brains function in a similar way.
Dan Falk is a science journalist and lives in Toronto. His books include “The Science of Shakespeare” and “In Search of Time”.
The debate may sound academic, but it has real implications: if it could be shown that brains function radically differently from computers, this would call into question many traditional approaches to artificial intelligence. If, on the other hand, we see our brains only as highly developed calculating machines, the self-image of humanity would be touched as something unique and special.
We asked experts whether we should look at the brain “like a computer” – or not.
The new edition 8/2021 of Technology Review questions more about our brain and whether meditation and mindfulness really bring calm in everyday life. The magazine will be available from 11/11/2021 in stores and directly in the heise shop. Highlights from the magazine:
Cons: The brain cannot be a computer because it is biological.
Nobody would confuse the spongy material in your head, “designed” over billions of years by evolution, for the CPU in your laptop. The neurons behave very differently than digital switches and logic gates – they work in an analogue manner. “We have known since the 1920s that neurons cannot simply be switched on and off,” says biologist Matthew Cobb from the University of Manchester. “As the stimulus increases, so does the signal. The way a neuron behaves when stimulated is different from any computer we’ve ever built.”
Blake Richards, neuroscientist and computer scientist at McGill University in Montreal, agrees: brains “process everything in parallel and continuously” – not at discrete intervals like digital computers with “Von Neumann architecture” that process instructions step by step and thereby process them Access information in discrete storage locations. “None of this bears any resemblance to what’s going on in your brain,” says Richards.
Pro: Of course it can! The actual structure is irrelevant.
But maybe what brains and computers do is basically the same thing, even if the architecture is different. “What the brain seems to be doing can be described quite aptly as information processing,” says Megan Peters, a cognitive scientist at the University of California. “The brain picks up spikes, sound waves and photons and converts them into neural activity – and this neural activity represents information.”
Blake Richards also agrees – although he believes that brains work very differently from digital computers: “In terms of computer science, a computer is simply a device that can perform many different arithmetic functions.” According to this definition, the brain is not just like a computer. “It’s literally a computer,” said Richards.
Michael Graziano, a neuroscientist at Princeton, sees it similarly: “There is a broader concept of the computer than something that takes in and processes information. And that is exactly what a brain does.”
But Anthony Chemero, cognitive scientist and philosopher at the University of Cincinnati, contradicts: “Over time we have watered down the term ‘computer’ so that it no longer has any meaning. Yes, the brain helps us to see things, but that no longer really has anything to do with ‘computation’. “
Pro: Conventional computers may not be brain-like, but artificial neural networks are.
Artificial neural networks were involved in all of the great breakthroughs in artificial intelligence: recognizing faces, translating languages, imitating texts written by humans. “An artificial neural network is basically just a way to model the brain without going into its biological details,” says Richards. This was the express goal of pioneers like Frank Rosenblatt, David Rumelhart and Geoffrey Hinton. “They were specifically interested in understanding the algorithms that the brain uses.”
Recently, scientists have developed neural networks that are said to be even more similar to human brains by constantly trying to predict the next input from the outside world (“predictive coding”) – a behavior that has been favored by natural selection.
Cons: Even if brains function like neural networks, they are still not information processors.
Not everyone sees a suitable model for our brains in neural networks. One problem is that these networks are opaque. That makes it harder to argue that they are in any way similar to the brain. “The artificial neural networks that people like Hinton are now working on are so complicated that you can’t figure out which parts store which information and what is considered to be tampering with that information,” says Chemero.
However, this does not matter to the proponents of the analogy between the brain and the computer. “You can’t point to the ones and zeros,” says Graziano. “The information is distributed in a pattern of connections – but you know that it is there.”
Pros: The brain must be a computer; the alternative is magic.
If one adheres to the idea that physical brains create mind, then “computation” is the only feasible way to do it, says Richards: “The only alternative would be some kind of magical ‘soul’ or ‘mind’ or something like that. There are literally only two Possibilities: Either you run an algorithm or you use magic. “
Cons: The metaphor of the brain as a computer cannot explain how we create meaning.
No matter how sophisticated a neural network may be, its information has no real meaning, says Romain Brette, theoretical neuroscientist at the Vision Institute in Paris. For example, facial recognition software can classify a certain face as mine or yours, but ultimately it only tracks correlations between two series of numbers. “You still need someone who can figure it out, who thinks, who perceives,” says Brette.
That doesn’t mean that brains don’t process information – maybe they do. “Computation is probably very important in explaining mind, intelligence, and consciousness,” says Lisa Miracchi, a philosopher at the University of Pennsylvania. However, she emphasizes that the brain and mind don’t necessarily do the same thing. Even if the brain works like a computer, this does not necessarily apply to the mind as well: “Mental processes by nature have a meaning, but arithmetic processes do not.”
What does that mean for us now? The answer depends in part on the definition of “computer”. But even if the experts could agree on a definition, it seems unlikely that the question will be resolved anytime soon – perhaps because it is so closely related to delicate philosophical problems such as the mind-body problem and the riddle of consciousness.
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