Artificial Intelligence: That’s the myth

AIMythThe holy grail of artificial intelligence is the creation of artificial “general” intelligence. That is, an artificial intelligence that is capable of every sort of perceptual and cognitive function that humans are and more. But despite great optimism in the early days of artificial intelligence research, this has turned out to be a very difficult thing to create. It’s unlikely that there is a “silver bullet”, some single algorithm, that will solve the problem of artificial general intelligence. And an important reason why, is that the human brain, which gives us our intelligence, is actually a massive collection of layers and modules that perform specialised processes.

The squiggly stuff on the outside of the brain, the neocortex, does a lot of the perceptual processing. The neocortex sits on a lot of “white matter” that connects it to the inner brain structures.  Different parts of the inner brain perform important processes like give us emotions, pleasure, hold memories, and form the centre of many “neural circuits”. Even though the structure of the neocortex is quite similar in all areas over the brain, it can be pretty neatly divided up into different sections that perform specific functions like: allow us to see movement, recognising objects and faces, provide conscious control and planning of body movements, and modulating our impulses.

Until we see an example of an intelligent brain or machine that works differently, we should probably admit that replicating the processes, if not the structure, of the human brain is what is most likely to produce artificial general intelligence. I’ll be making posts that discuss specifically some different approaches to artificial intelligence. These posts will mostly be on the high-level concepts of the algorithms and their relationship to “intelligence”. Hopefully these posts will be generally accessible and still interesting to the technically minded. I think there is benefit in grasping important concepts that underlie human intelligence that could direct the creation of intelligent machines.

If people are still looking for that silver bullet algorithm, they should probably be looking for an algorithm that can either create, or be generally applied to, each of these brain processes. If you know of someone that has done this, or has rational grounds for disagreeing that this is necessary, let me know. Then I can stop spreading misinformation or incorrect opinion. 🙂

To conclude with some philosophical questions, if we are successful in reproducing a complete human intelligence (and mind) on a computer, some interesting issues are raised. Is an accurate simulation of a human mind on a computer that different from the “simulation” of the human mind in our brains? And how “artificial” is this computer-based intelligence?

These questions might seem nonsensical if you happen to think that human intelligence and the mind are unassailable by computer software and hardware. Or if you think that the mind is really the soul, separate from the body. First of all, if you believe the latter, I’m surprised you’re reading this (unless you were tricked by the title :)). If you read later posts, I hope to discuss some evidence against both of these points of view in future posts, and I welcome rational counter-arguments.


5 responses to “Artificial Intelligence: That’s the myth

    • Hi Leo,

      Thanks for leaving a message! I think there are few undergraduate degrees you could look into and find a good pathway to work in these fields. My undergraduate study was in mechatronic engineering, and I would say a good computer science and/or robotics related engineering degree could be a good place to start. I think some universities might also be starting to offer degrees in computational neuroscience, so if you’e more interested in the modelling or simulation of the brain that would be a good way to go. Most of these courses should have some mathematics, but some people seem to find their way into working on AI after studying mathematics. I don’t think there is necessarily one best undergraduate degree to study, since all of these courses will offer a different perspective and slightly different skill set. Many large research groups these days are multi-disciplinary. In summary, in choosing an undergraduate degree I think you should weight up what you enjoy most, has a relevance to what you want to do (research AI?), and what you think you do best. Grades do matter if you want to get into research.

      Doing undergraduate studies should give you a good foundation, but in my experience undergraduate courses don’t often delve into the most recent advances in research. So if you’re really keen, I think access to a university library to find books that give an overview of any particular field is also useful. If you also have on-line or physical access to research journals, you can follow up anything interesting you turn up from general reading to find the current state of progress in these fields.

      • Thank you for the wise advises. My university offers Computer Science major with emphasis on A.I. and Psychology with emphasis on Neuroscience for undergrads. I think I will make full use of those. I am hoping that I can find some professors that are willing to take in undergrad students into researches so I can gain some first hand experience. Also I will definitely read up and get myself updated on the subject matter. Thank you for your advice!

  1. Reblogged this on The Binary Neuron Blog and commented:
    Wordpress is indeed an impressive site. Just two days into blogging and I have found someone with the exact same mindset as me. This article gave me a clear understanding of what he is trying to create through studying the inner brain structures. I fully agree that replicating the processes of the human brain is a very plausible way of generating intelligence. However what is intelligence what is knowledge? I’m sure it is not just a bunch of brain tissues and memories. I think I should target myself to find out what intelligence/knowledge/thought/cognition really is.

  2. Great post!

    This is really what I’ve been searching for in terms of AI discussion, and I think will help answer the question at the end of my last Turing post: “how is the intelligence of AI similar to humans and how is it different?”

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