[tialaramex]

> The problem with that line of reasoning is you're assuming the brain is a computer, or that it merely computes.

The brain can compute. That's extraordinary. I say one type of thing does that, computers. You say no, two things, computers and then also brains. But when pressed to explain what is a brain if not a computer you'll just sputter (probably at length) without offering any substance.

In a sense that's the wrong way up to explain it. Church-Turing intuitively defines computation (the things computers can do) in terms of what our brains can do, so the match is not a coincidence but it also isn't there for the reason you probably expect. Because it's an intuition Church-Turing isn't provable, but you may notice that we subsequently built an _entire world-changing industry_ upon it in a lifetime.

You pointed to a review, others have written entire books, always they can be summarised as simply arguments from incredulity. "What? Nonsense, the brain can't be a computer, I simply won't believe that". It's unfortunate that we have woken such people from their daydreaming, I have no doubt that if similarly aroused they'd give the mathematicians what for too, "What? Nonsense, how can there be numbers which aren't ratios of whole numbers, I simply won't believe it".

[Zaphods]

> The brain can compute.

You'll see in my comment and your quote that I don't say the brain can't compute. I agree, the brain can compute. But that doesn't mean it is a computer, because computing is an ability. People can do many other things aside from computing, none of which rely on computation, for instance they can imagine, which is the ability to think new thoughts. Computers can't imagine because all they do is compute: that's their programming. No amount of programming can produce imagination. Computation and imagination are categorically distinct as different intellectual powers and abilities.

You are conflating an ability with ontology. We know what a brain is. It's a collection of fatty material with neurons that do not explicitly fire exactly like a computer. Key word there is like. Church-Turing built a model of computational logic off of intuitions about the brain and formal mathematical logic. That's it's not provable doesn't prove your point; it removes any distinction between it being right or wrong: because it is a model (lets make something like the brain).

That an industry was built on computation doesn't prove anything. We know computation is an ability. For instance it's also something we can do with abacuses. We could have built an enormous industry on building elaborate abacuses. We built computers do be extremely fast at computation. We didn't build computers to be brains.

You'll notice, if you read the review, that the author of the review repeatedly cites cognitive neuroscientists, even evangelists of the singularity, philosophers, psychologists, and zoologists, who have published at length on this topic and repeatedly critcise and disrupt the simple idea that the brain is a computer or an algorithm or even a machine. An entire branch of philosophy developed off of Ludwig Wittgenstein to counter the computational model of consciousness. Numerous books in the Philosophy of Mind argue that the assumption that the brain is a computer is not just unsupported, it is logically nonsensical.

[parksy]

"No amount of programming can produce imagination" is a very bold statement to make.

The brain exists in a physical universe, made out of matter/energy, and its behaviours are entirely dictated by the laws of physics; that's a fairly accepted truth unless you have solid evidence otherwise.

The laws of physics are mathematical and can be computed by their very nature, and we are already pretty good at simulating physical interactions to a quantum level, and this ability improves over time.

At some point in time, unless there is "magic" or missing physics, a sufficiently powerful computer with a physically accurate simulation of a brain would produce virtually identical results to a real brain.

So either there must be new physics involved, or, the notion that a sufficiently advanced computer simulation can't produce imagination must be abandoned.

A team of scientists able to sufficiently model the physics of the brain (and presumably the entire central nervous system, I imagine a disembodied brain simulation would experience a horrific form of locked-in syndrome) would not need to be concerned about emergent properties of the simulation such as a sense of consciousness, or thought, or imagination. Those things will just happen once the simulation is perfected.

Indeed the cognitive neuroscience folk, etc, would be invaluable to actually understanding, training, interpreting and caring for the brain simulation, and figuring out if its behaviours and interactions constitute consciousness etc, so I do not think this has to even be framed as programmers pretending to know about brain stuff vs brain people who dismiss any notion of computationally recreating consciousness. It would be a team effort that works both ways, but is already doomed to fail if half the team thinks it's impossible from the get-go.

[Zaphods]

It's not a remotely bold statement. Think about what imagination is, and then think about whether computers can imagine. Computers can't imagine. Computers can't come up with new things because they are programmed. Programming prescribes the outputs to the same limitations as the inputs: it's a closed deterministic system.

You'll see in my comment above this one that I agree that the brain is a physical thing. But abilities and powers are not physical. That's not voodoo magic. That's what abilities are. Think about horsepower. The horsepower of a car does not reside in any one physical thing, not the carburetor, or the intake manifold, or the piston, or the wheels; it's an ability of the car: it is able to go at such and such horsepower. That is what horsepower is.

The same applies to computation. Computing something is an ability, but we have many more intellectual and cognitive abilities beside computing things.

As a result

> a sufficiently powerful computer with a physically accurate simulation of a brain would produce virtually identical results to a real brain.

is just you are assuming that it will work, but nothing about computers supports that in the slightest. That's just a guess.

> A team of scientists able to sufficiently model the physics of the brain (and presumably the entire central nervous system, I imagine a disembodied brain simulation would experience a horrific form of locked-in syndrome) would not need to be concerned about emergent properties of the simulation such as a sense of consciousness, or thought, or imagination. Those things will just happen once the simulation is perfected.

All of this is still an assumption.

Again, that doesn't mean you are right or wrong: it means its an assumption. You have to accept the limitations of your assumption and the limitations of modelling the brain on a computer are large and glaring.

> Indeed the cognitive neuroscience folk, etc, would be invaluable to actually understanding, training, interpreting and caring for the brain simulation, and figuring out if its behaviours and interactions constitute consciousness etc, so I do not think this has to even be framed as programmers pretending to know about brain stuff vs brain people who dismiss any notion of computationally recreating consciousness. It would be a team effort that works both ways, but is already doomed to fail if half the team thinks it's impossible from the get-go.

You are assuming here that only the programmers are heading down the right path. But you don't know that. It's entirely reasonable (and I would say much more supportable) to say that the programmers are heading down the wrong path: their path will lead to nothing at all. That's because the programmers have fallen to a category error.

You think they need to model the brain on a computer for it to make sense. But there is actually very little if anything to support that.

Brains are brains. Computers are computers. That computer science can be fuzzily applied to the study of brains around the ability to compute does not mean the study of brains is computer science or that brains are computers.

[vinceguidry]

Not so extraordinary. What's extraordinary isn't that brains can compute, it's that anything else can. Brains computing is ordinary. What's extraordinary about the brain isn't that it can compute. What's extraordinary about the brain is that it can be rational and self-aware, things that computers cannot do. Computers can only be deterministic. Brains can be deterministic, but they can also be non-deterministic

[TeMPOraL]

Computers can become non-deterministic in practice as soon as you botch your random number handling, or hook your input up to environmental noise. Is there anything suggesting the brain is non-deterministic in a theoretical way, not just the way computers are?

[vinceguidry]

Deterministic means that given the same input, the system gives the same output. Computers would be useless if they were not deterministic. Hooking up random input to a deterministic process will give random output. Garbage in, garbage out.

What you're asking is for computers to be rational. That given garbage input, it will produce intelligible output. Computers cannot do this unless you program them to.

Human minds are non-deterministic in many, many, many ways. Hand the same input to the same mind and you'll get a different output every single time, unless the mind willed itself to act rationally. But they are deterministic enough that you can study their behavior. Other brains are not as non-deterministic, so their behavior is easier to study.

Look at it from a thermodynamic standpoint. Biological systems arose to conserve order against entropy. A fully-deterministic system will shed order, it's only through non-deterministic means that biological systems can conserve order.

The mind is the most complex system nature has devised that can not only slow the aggregation of entropy, but also create order! It's not breaking the laws of physics, but yet it can create all kinds of order.

Conway's Game of Life is an excellent illustration of the concept. You have to work hard and study the domain in order to find stable systems. Otherwise they just drop to equilibrium fast.

[TeMPOraL]

Thermodynamics is defined in a deterministic universe. It's only through sheer amount of states any interesting system could be in that entropy arises. Chaotic systems (as studied in mathematics) are deterministic too. Conway's Game of Life is indeed an excellent illustration of the concept - of how chaotic and "surprising" behavior can arise in a fully deterministic system.

> Human minds are non-deterministic in many, many, many ways. Hand the same input to the same mind and you'll get a different output every single time

That's not non-deterministic. That's simply stateful. Most human-made systems you interact with daily are stateful, so it's not exactly surprising.

When I say "deterministic in practice" vs. "deterministic in theory" I mean this: a system is deterministic in practice if you can actually predict its outputs based on its inputs with reasonable amount of effort. A LED hooked up to a switch and a battery is deterministic in practice. So is a program computing GCD on 32-bit integers. A system is deterministic in theory if it's deterministic, but actually predicting its outputs requires absurd amount of computation. Lorenz system and weather are two examples. So is protein folding and turbulent flow. I see no reason why a fly brain, a mouse brain, or a human brain wouldn't be such systems either. The entire universe could be one, if you subscribe to many-worlds interpretation of quantum mechanics.

[vinceguidry]

> I mean this: a system is deterministic in practice if you can actually predict its outputs based on its inputs with reasonable amount of effort.

You're changing the meaning of determinism and bringing it closer to rationalism. Your introduction of the element of theory to the mix is a violation of Occam's Razor. We already have philosophy and a word that covers what you want it to cover. Theory is a component of rationalism, not of determinism. If you need theory to understand a system, then it already has elements of non-determinism. Theory is what you need to make sense of the non-deterministic. Because theory deals with uncertainty, you wouldn't need any validation of your hypotheses if the system was truly deterministic. One observation would be enough to ascertain the whole thing.

A considered study of history would reveal where you're going wrong here. The Greeks invented empiricism and philosophy and science while the Egyptians never got there despite only being a tiny distance away. They wanted to distance themselves from theological frames. Despite all this, the Egyptians built pyramids. They understood determinism. They could not understand science. Determinism made them good engineers. Engineering is not science.

> A system is deterministic in theory if it's deterministic, but actually predicting its outputs requires absurd amount of computation.

Now you're starting to dip into computational complexity territory. Predicting outputs is the domain that the halting problem puts a backstop to.

To prove to you that a brain is better than a computer, all I have to do is state the obvious, humans make algorithms, not the other way around. Sure, there are programs that will devise algorithms, but humans have to understand the domain before they can make computers do their work for them.

Your examples of Lorenz systems and weather do not change things at all. Humans have a better understanding of weather than computers do. In fact, humans have an entire body of theory that attempts to make sense of why such things have difficult-to-determine causation, chaos theory. Humans devised it, not computers. And they devised it using the tools of epistemology, working out the details of justification of knowledge via seeking rigor, not in the scientific method of dreaming up hypotheses based on empirical analysis and testing them. Chaos theory is more math than science.

In other real ways, humans outclass other mammals, even though we largely share the same macro brain structures. We keep monkeys in cages, monkeys do not keep us in cages.

I'm not sure how much more I have to state the obvious here. You seem to be the one seeking out a special domain in which the rules don't apply, one in which computers are wholly analogous to brains. It may, and this is speculation, be true in degree rather than kind.

But the halting problem itself illustrates a domain in which humans are able to reason past, whereas we cannot possibly program a computer to do it. Computers cannot program themselves to find gradations of the halting problem. Humans have to write algo-generating algos. The pace of comp-sci progress at the moment is fully dictated by human ingenuity, and if you think about it, any change in this means that the singularity is upon us.

I suspect that we'll never be able to get computers to fully take the place of brains. There will always be domains where brains are better than algos. Prove me wrong. Humans are capable of wanting things, even the best machine learning algos at the moment struggle with finding purpose. Finding purpose is something even the most basic virus can achieve. And we can't even determine whether virii are alive or not.

And that's super basic. How much more self-awareness do you think algos can find before running into hard physical limits? The computational and memory concerns are huge. I predict the hard limit of engineered systems will be well below full self-awareness. Instead we'll have to create biological systems to carry on progress. Dogs will get smarter, mice will get smarter, apes will eventually start doing things that humans do now, once we can fit our ethics around it.

[ryukafalz]

>Hand the same input to the same mind and you'll get a different output every single time, unless the mind willed itself to act rationally.

Are you sure? Remember that memory also counts as an input if it's used in a computation; it seems to me that this applies to both humans and computers.

For a harrowing account of what a mind may do when exposed to very nearly the same inputs, you may be interested in one segment from this Radiolab episode: https://www.wnycstudios.org/story/radiolab-loops

It describes a patient with transient global amnesia who has a looping conversation with her daughter. (There's a link to a video of the conversation on that page as well.) Under normal circumstances this wouldn't happen, as once you've had a conversation you also have memories of having that conversation. But if you're unable to form memories...