Why Your Brain Isn't A Computer

Phrenology diagram. From People's Cyclopedia of Universal Knowledge (1883). (Photo credit: Wikipedia)

“If the human brain were so simple that we could understand it, we would be so simple that we couldn’t.”
- Emerson M. Pugh
Earlier this week, i09 featured a primer, of sorts, by George Dvorsky regarding how an artificial human brain could be built. It’s worth reading, because it provides a nice overview of the philosophy that underlies some artificial intelligence research, while simultaneously – albeit unwittingly – demonstrating the some of the fundamental flaws underlying artificial intelligence research based on the computational theory of mind.
The computational theory of mind, in essence, says that your brain works like a computer. That is, it takes input from the outside world, then performs algorithms to produce output in the form of mental state or action. In other words, it claims that the brain is an information processor where your mind is “software” that runs on the “hardware” of the brain.
Dvorsky explicitly invokes the computational theory of mind by stating “if brain activity is regarded as a function that is physically computed by brains, then it should be possible to compute it on a Turing machine, namely a computer.” He then sets up a false dichotomy by stating that “if you believe that there’s something mystical or vital about human cognition you’re probably not going to put too much credence” into the methods of developing artificial brains that he describes.

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This is a game that a lot of adherents of the computational theory of mind like to play – often, I think, without realize that they’re doing it. Adherents of the computational theory of mind often claim that the only alternative theories of mind would necessarily involve a supernatural or dualistic component. This is ironic, because fundamentally, this theory is dualistic. It implies that your mind is something fundamentally different from your brain – it’s just software that can, in theory, run on any substrate.
By contrast, a truly non-dualistic theory of mind has to state what is clearly obvious: your mind and your brain are identical. Now, this doesn’t necessarily mean that an artificial human brain is impossible – it’s just that programming such a thing would be much more akin to embedded systems programming rather than computer programming. Moreover, it means that the hardware matters a lot – because the hardware would have to essentially mirror the hardware of the brain. This enormously complicates the task of trying to build an artificial brain, given that we don’t even know how the 300 neuron roundworm brain works, much less the 300 billion neuron human brain.
But looking at the workings of the brain in more detail reveal some more fundamental flaws with computational theory. For one thing, the brain itself isn’t structured like a Turing machine. It’s a parallel processing network of neural nodes – but not just any network.  It’s a plastic neural network that can in some ways be actively changed through influences by will or environment. For example, so long as some crucial portions of the brain aren’t injured, it’s possible for the brain to compensate for injury by actively rewriting its own network.  Or, as you might notice in your own life, its possible to improve your own cognition just by getting enough sleep and exercise.
You don’t have to delve into the technical details too much to see this in your life. Just consider the prevalence of cognitive dissonance and confirmation bias. Cognitive dissonance is the ability of the mind to believe what it wants even in the face of opposing evidence. Confirmation bias is the ability of the mind to seek out evidence that conforms to its own theories and simply gloss over or completely ignore contradictory evidence. Neither of these aspects of the brain are easily explained through computation – it might not even be possible to express these states mathematically.
What’s more, the brain simply can’t be divided into functional pieces. Neuronal “circuitry” is fuzzy and from a hardware perspective, its “leaky.” Unlike the logic gates of a computer, the different working parts of the brain impact each other in ways that we’re only just beginning to understand. And those circuits can also be adapted to new needs. As Mark Changizi points out in his excellent book Harnessed, humans don’t have a portions of the brain devoted to speech, writing, or music. Rather, they’re emergent – they’re formed from parts of the brain that were adapted to simpler visual and hearing tasks.
If the parts of the brain we think of as being fundamentally human – not just intelligence, but self-awareness – are emergent properties of the brain, rather than functional ones, as seems likely, the computational theory of mind gets even weaker. Think of consciousness and will as something that emerges from the activity of billions of neural connections, similar to how a national economy emerges from billions of different business transactions. It’s not a perfect analogy, but that should give you an idea of the complexity. In many ways, the structure of a national economy is much simpler than that of the brain, and despite that fact that it’s a much more strictly mathematical proposition, it’s incredibly difficult to model with any kind of precision.

The mind is best understood, not as software, but rather as an emergent property of the physical brain. So building an artificial intelligence with the same level of complexity as that of a human intelligence isn’t a matter of  just finding the right algorithms and putting it together. The brain is much more complicated than that, and is very likely simply not amenable to that kind of mathematical reductionism, any more than economic systems are.
Getting back to the question of artificial intelligence, then, you can see why it becomes a much taller order to produce a human-level intelligence. It’s possible to build computers that can learn and solve complex problems. But it’s much less clear that there’s an easy road to a computer that’s geared towards the type of emergent properties that distinguish the human brain. Even if such properties did emerge, I’m willing to bet that the end result of a non-human, sapient intelligence would be very alien to our understanding, possibly to the point of non-comprehension. Electric circuits simply function differently then electrochemical ones, and so its likely that any sapient properties would emerge quite differently.