Why Minds Are Not Like Computers (2009)

It feels like this article sets up something of a straw man. The analogy that a mind is like a computer is just that, an analogy. It's used to present the high-level structure of the brain in a accessible, understandable way, not as a logical argument.

This analogy is not the justification for why people believe that "the mind can be replicated on a computer". And yet the article tries to disprove the latter, deep and meaningful point by attacking the relatively superficial analogy between [current] computers and minds.

To me, the reasoning behind why I think a computer can theoretically do anything a brain can is much simpler. Programs are ultimately nothing more and nothing less than mathematics. Their capabilities are a finite (but theoretically arbitrary) subset of what mathematics models. And so far, mathematics has been able to model everything. Purely inductively, it seems mathematics should be able to model the mind just like everything else. After all, there is nothing magical about the brain!

At the limit of plausibility, we could just reproduce a mind by modelling a brain using the laws of physics. Sure, this is wildly impractical with current hardware. Perhaps we will never have the hardware to make it practical. But it also demonstrates how it should be possible theoretically: and if something is possible, no matter how impractically, there's a reasonable chance that it's possible in some significantly easier ways.

Saying that a computer can never fundamentally replicate a human mind is the same as saying the mind is beyond mathematical description. To me, this idea does not make sense. I'm not even sure it's well-formed! Mathematics is not a finite set of ideas or a bounded language: it is more like a standard of formality which we can extend in an incredible amount of different ways.

Sure, math has some internal limitations like incompleteness. But these are not really absolute bounds, at least not in the most obvious way. One thing to keep in mind is that mathematics is purely self-contained: all that matters is internal consistency, not a parallel to anything in our actual universe. This means the fundamental limitations are inevitably meta-limitations: they come up when we turn math on itself. Moreover, they only come up when we start encountering the infinite. The human mind may present some meta facets, but it is not infinite, so incompleteness cannot prevent us from modelling it.

It's interesting to note that all the actual arguments for why a computer cannot represent the mind are not actually logical themselves. They rely on vague analogies and emotions, quoting Ionesco but not providing actual reasoning.

Ultimately, it feels like this article is trying to establish a false balance between the two sides of the argument. But they are not anywhere near equal: the people that don't think a computer can model the mind need to present an actual case for why it's beyond the capabilities of mathematics, the system which has fared so well in describing everything else. Where does the line between physics and cognition (which exists on a purely physical plane) come from? Why are they divided? To me, that line simply seems to arbitrary to accept without more cause.

I can see why this line of thought is appealing: consciousness certainly feels magical, so you want to find some real magic there. But I am not convinced real magic exists. Or even makes sense. It would require the human mind to somehow be special in a way that would, at best, be a really suspicious coincidence. I'm not buying it.

I could smell the "Chinese Room" argument coming from the first line of that article.

Of course the real answer is still and have been for a long long time. "We don't know"

And even though he seems to be trying to expand on the "Chinese Room" argument a little it still does not prove anything.

Of course the person in the room does not know Chinese as little as each individual neuron in my brain "knows" Chinese, it's the whole system that knows Chinese.

And if that is not enough for you you have to explain this.

If seemingly "dumb" matter can combine to become smart humans, then whats to hinder silicon to build so much complexity that a mind emerges?

No the real answer is still "we don't know"

I feel like I should share a perspective from Cognitive Science/Psychology.

In theoretical/experimental Psychology, the dominant paradigm is a computational/representational paradigm. Take vision for example. The accepted facts are that we receive as input an impoverished view of the world, insufficient to know what's really out there. So we have to take that input and build upon it, based on assumptions and past experiences and what-have-you, until we have an internal representation of the external world. And then we can reason with this internal representation, we can refer to it when planning actions, etc. So in this view, we are not really in contact with the external world, only our reconstruction of it in our heads.

This view is probably familiar to you in some form. I am part of a group of scientists pushing an alternative view, however within Psychology we are considered fringe for questioning this dogma. We take a non-representational view of the mind. Going back to the vision debate, if you assume a stationary vantage point and a single snapshot of an "image", and if you assume that the final "output" of visual cognition is a representation in 3D-coordinates, then yes, the visual input is underspecified. However, if you assume a moving point of observation, if you realize that the really rich information is not in the snapshot but in the way the light changes over time, if you realize that in order to successfully control actions you don't need a full 3D map of the world, then there is enough input. Some of what we do is to work out mathematically that the information is there to support certain actions, then to demonstrate experimentally that indeed, people do seem to use these "shortcut" strategies that don't require intermediate representations.

Of course, there's a lot more to it than that. I could take about thermodynamics, self-organization, and lots of other interesting stuff. But what I wanted to show is that the debate about computation is alive and well within Psychology, and indeed the computation side is extremely dominant. It may take the tack of representationalism vs non-representationalism, however the representational theories are firmly computational. Research has the explicit goal of figuring out what is the storage/transmission format of these representations? What operations are performed on the input to create them? What operations are performed on them to use them? Etc.

Also, despite what some of the comments here suggest, at issue is not whether or not computers can model a mind. All the behaviors that we think are done without representations? We model them and study them with the aid of computer models. Of course. But that's not really interesting at all. And yes if you modeled a brain physically, you might get a mind (I'd argue you would need to model the body as well, not to mention quite a bit of environment). But that's not really the point. Today, Psychologists do research with the idea that they are setting out to discover the software that the brain is running. This is very different from the claim that a computer could model a brain, and it pervades how we think about minds, even (and especially) among experts in the field.

We don't have the computer power to simulate a brain quark-for-quark yet; when we can it'll be interesting to see what happens. Until that happens, it's all moot anyway as it's a religious argument. For me it's clear that brains are computers, just not the ones we are using right now. This has been obvious since the first time I touched a computer 30 years ago and I didn't grasp why we still needed humans for anything at that time and that is still true kind of today. The fight is strong against weak AI and I firmly am convinced strong will happen; there aren't too many good arguments against it. Most arguments now are lack of comprehension or religion (some form of saying there is more than just this but failing to explain what/how). And this article isn't even an argument.

The arguments in the article (and repeated here by some HNewsers) are familiar: "If a computer does it then it's not a mind." Well, if that's the definition of mind for the sake of discussion then there isn't much to discuss. I see it differently, I feel that mind is a property of a working brain and that someday we may say that mind is also a property of a working AI program.

I don't believe in magic. I don't believe that there is spooky stuff in my head. I think that my brain is an amazing biological machine. The idea that there is some fundamental insurmountable barrier that will prevent strong AI from succeeding (eventually, if humans survive) would mean that there is some magical property of brains (human brains, whale brains, chimp brains, dog/cat brains etc.) that we will never have access to. This seems so unlikely that I prefer to believe that there is no magic and that AI will succeed. And I'm not saying that we need to mimic brains to have thinking machines. The mind and its thinking, feelings, emotions, and so forth may simply be emergent properties of advanced enough artificial or natural computing structures (e.g. brains).

If space aliens landed on earth tomorrow, would we say "Oh, but they can't think. They don't have brains like we have here on earth so they don't really think. They just process inputs into outputs."

I've enjoyed many books on this subject, but two older ones I recommend are: Gödel, Escher, Bach: An Eternal Golden Braid by Hofstadter and Society of Mind by Minsky.

My the article rattles on a bit in the typical way of philosophers where it's hard to analyse what's up with their arguments because they lump about a hundred of them together. But I think there is a basic straw man argument in implying AI researchers think of the mind as software. I think a more reasonable model in AI is for software to simulate the computational action of the neurones and for the mind to be analogous to the data that the software or neurones operate on. If you believe the brain is a machine following the laws of physics then this should be possible. The proof is in the pudding. Researchers have already been able to produce functional simulations of the retina and parts of the hearing system and get similar signals out which can then be fed back in to the brain successfully as seen in the contraption on Rush Limbaugh's head.

Whether that extends to the rest of the brain we will see before long. The Blue Brain / Human Brain Project has a €1bn grant to get cracking on it. Time will tell.

http://www.theguardian.com/science/2013/oct/15/human-brain-p...

Statistical analysis approach can be a good educated guess at most. But if we keep observing human brain to get input/ouput dataset, we can develop a field that much like Physics, where the theory comes from experiments and even those do not must need future experimental proof to be considered valid. Yes, not all these theory based on expriments is true (that is why I say it is a good educated guess) because maybe our observed set is just a subset of all test cases we need. But using this approach like Physics we can keep pushing the limit of (AI) theory and expriements forward.

As I mentioned another half (theory first, then experimental validation) of this approach is another Einstein came along and made amazing thoeries once and for all. Then the expriments proves it is true to our best knowledge up to date. The the loop starts again.

I think the first cases may be the most prevalent because insights are not very easy to come by without seeing experimental result first. If we can make a organized way to keep working on the first half, the second half might come by some time. Just some random thoughts, primarily made to inspire some followup conversations amongst us.

The argument in this paper comes down to "computers can't think because I don't label what they do as 'thinking'".

Now if you make the argument that we're very unlikely to build a conscious machine without knowing what consciousness is, and simply assuming that it's an emergent property of complexity is probably foolish. OK. Maybe. Who knows?

Is brain a machine? If you don't believe in souls and that kind of thing - then the brain is material and thus a machine for me.

Can you replicate the way brain works in another machine? If it is a machine than most probably yes.

Can you replicate the way brain works in a digital computer? It is possible that there are physical processes going on in the brain that cannot be feasibly approximated by digital algorithms (i.e. it is possible that there are analog machines that are for some problems faster than any digital computer can be). There used to be analogue computers and it is entirely possible that some day they again will be useful.

Can you build a brain without knowing how it works? Well we know how to build a brain without knowing how it works - you need a woman and a man and ...

What is the definition of artificial then?

Can you control AI if you don't know how exactly it works? Probably not - just like we cannot really control humans, but we have pretty good ways of influencing them.

I haven't read that article (yet) but I strongly agree with the title. I've been thinking about this for years and have come to the following conclusions:

* Physics will never be able to explain consciousness. That's because consciousness is fundamentally subjective and therefore out of the scope of science. This is very counterintuitive, because science was able to explain almost everything so far, why would consciousness be different? One way to answer that would be that consiousness has a "meta" relation to science, it's one level above science (in a sense, don't take it too literally).

* The Descarte's mind-matter duality model is correct in principle.

* The solipsism theory is about right too.

(I'm a very rational and sceptical percon btw.)

We have gone leaps and bounds since we started building an "artificial brain". Look at where deep learning is leading to. Ofcourse, we can't mimic the brain in all its majesty anytime soon but short of that, there's so much we can achieve.

I'd take the argument to the physical level. Do we know how the brain works? To some degree, yes. Neural networks: nodes, weights and activation functions.

If one day we can map exactly an animal brain's architecture, how new ideas are learned etc. (is it backwards propagation or something else?) then we can replicate that behaviour using logic gates and floating point numbers.

Mapping a brain to a digital neural network architecture is such a prohibitively expensive problem I wouldn't know where to begin. Perhaps a biologist would have a better idea than a computer scientist. But it's enough to say that intelligence can theoretically exist on electronic circuits.

Human brains are made of the same fundamental particles as computers or anything else in the universe, and they obey the same laws of physics. Thus I believe that it is only a matter of scale.

The fundamental difference between minds and computers, which many people don't understand, is that computers are modelling things. They are calculating outcomes from preconditions. Minds on the other hand, while they might also be doing that, are experiencing things. They feel, see and hear. You might make the argument that we don't know whether a computer is doing that as well, because it can't tell us - but then I could just as well propose that minds are like popcorn.

I would have thought it was obvious that minds are not like computers, the really interesting question is are minds Turing machines?

Why minds are not like computers? I guess computers are being build trying to mimic humans. So the question has to be "Why computers are not like minds?"

Computers are based on Boolean logic and algebra, Human minds are based on we don't know what. Computer logic is a subset of the Human Mind.

Mind is not a computer. It's actually two computers, maybe three. They co-evolved, each with different goals, and they work together as a team, with all the competition and cooperation that it entails.

Are minds are not like computers because we humans have 'emotions.'

Emotions affects the mind's performance and what memories are activated.