Singualrity
It's time to poke some fun at the Church of Singularity. It's a very scientific cult and it doesn't ask you to pay money for the enlightenment--quite the opposite in fact! Like many other religions it comes with some dietary recommendations (eat a lot of antioxidants and supplements, otherwise starve yourself as much as possible). Most of the people living today are to witness the coming of Singularity (remember early Christianity with its promise of the Second Coming before the end of the generation?).
The arguments made by Singularitarians make a lot of sense. They claim that the scientific and technological progress follows the exponential curve. At the present rate of acceleration, we are bound to reach a level of development that will make possible the creation of a superior artificial intelligence that will solve all our problems. Singularitarians' back-of-the-envelope calculations show that the breakthrough will happen within tens rather than hundreds or thousands of years.
I must confess that Singularitarianism is a very attractive proposition and when I occasionally shut down my rational mind, I believe in it. Just imagine being able to undo the ravages of time suffered by your body and mind and keep them in top shape forever. I'll take that over the promise of Heaven any time (Singularitarianism doesn't impose any undue restrictions on sex, drugs, and rock-and-roll!).
So why do I (with a heavy heart!) dismiss the whole idea as technologically based wishful thinking? Because it's obvious to me (and anybody who doesn't succumb to the allure of quick eternity) that creating an AI that is comparable, not to mention superior, to human mind is much more complex than the Singularitarians imagine. If intelligence were only a matter of brute force--like playing chess, for instance--the naive extrapolations of Singularitarians would make sense. The density of transistors, capacity of RAM, connectivity of computers, etc., indeed grow exponentially, and in a few dozen years will catch up with the superficial complexity of the human brain (considering that a neuron could be simulated with a bunch of transistors).
Unfortunately such arguments are as valid as the following reasoning: It takes nine months for a woman to create a child. If we put 40 women to work, we can shorten the process to a week!
For one, the brain of an idiot usually contains the same number of neurons as the brain of a genius. Also, a hundred thousand idiots will not come up with the theory of relativity. So much for brute force!
There is a certain amount of irreducible complexity that goes into intelligence. This complexity might be implemented in hardware or in software (or in wetware, as biological systems are sometimes called). However impressive the technological progress, it doesn't deal with irreducible complexity. Its main advances are in terms of repetition of the same patterns (which most of the current hardware and software development is about). What's more, we don't even have a good handle on estimating complexity. Superficial measures, such as size or number of connections, are very misleading.
I think Kurzweil at al. are too fascinated with the progress in hardware and pay too little attention to the glacial pace of progress in software. We are still in Stone Age as far as software development is concerned. And that's where the complexity frontier is.
It doesn't matter how many genomes we map, as long as the functional study of a single gene is worthy of a Ph.D. thesis. The number of Ph.D students does not grow exponentially and that's the biggest bottleneck. Having a complete genome or a complete neuron map of a human brain is useless if we don't have the software to creatively study it. And by creatively I mean not just statistically. We need software that can generate hypotheses and test them. The closest we came to this was the shotgun approach of chess-playing programs. Unfortunately this approach doesn't scale.
Finally, even if we could keep the exponential pace of progress, there are many things that are more powerful than the exponential. How about the factorial, which is characteristic of combinatorial problems? When you plot exponential growth using logarithmic scale, you get a straight line: log en = n. With the factorial, you get log n! ~ n log n - n (Stirling's formula). I believe the complexity of biological organisms, and brains in particular, grows like a factorial of the number of parts. So considering that our understanding of nervous systems is currently at the level of C. Elegans--a brainless worm with 302 neurons and 7000 synapses, we have a long way to go before we reach the Singularity.
The arguments made by Singularitarians make a lot of sense. They claim that the scientific and technological progress follows the exponential curve. At the present rate of acceleration, we are bound to reach a level of development that will make possible the creation of a superior artificial intelligence that will solve all our problems. Singularitarians' back-of-the-envelope calculations show that the breakthrough will happen within tens rather than hundreds or thousands of years.
I must confess that Singularitarianism is a very attractive proposition and when I occasionally shut down my rational mind, I believe in it. Just imagine being able to undo the ravages of time suffered by your body and mind and keep them in top shape forever. I'll take that over the promise of Heaven any time (Singularitarianism doesn't impose any undue restrictions on sex, drugs, and rock-and-roll!).
So why do I (with a heavy heart!) dismiss the whole idea as technologically based wishful thinking? Because it's obvious to me (and anybody who doesn't succumb to the allure of quick eternity) that creating an AI that is comparable, not to mention superior, to human mind is much more complex than the Singularitarians imagine. If intelligence were only a matter of brute force--like playing chess, for instance--the naive extrapolations of Singularitarians would make sense. The density of transistors, capacity of RAM, connectivity of computers, etc., indeed grow exponentially, and in a few dozen years will catch up with the superficial complexity of the human brain (considering that a neuron could be simulated with a bunch of transistors).
Unfortunately such arguments are as valid as the following reasoning: It takes nine months for a woman to create a child. If we put 40 women to work, we can shorten the process to a week!
For one, the brain of an idiot usually contains the same number of neurons as the brain of a genius. Also, a hundred thousand idiots will not come up with the theory of relativity. So much for brute force!
There is a certain amount of irreducible complexity that goes into intelligence. This complexity might be implemented in hardware or in software (or in wetware, as biological systems are sometimes called). However impressive the technological progress, it doesn't deal with irreducible complexity. Its main advances are in terms of repetition of the same patterns (which most of the current hardware and software development is about). What's more, we don't even have a good handle on estimating complexity. Superficial measures, such as size or number of connections, are very misleading.
I think Kurzweil at al. are too fascinated with the progress in hardware and pay too little attention to the glacial pace of progress in software. We are still in Stone Age as far as software development is concerned. And that's where the complexity frontier is.
It doesn't matter how many genomes we map, as long as the functional study of a single gene is worthy of a Ph.D. thesis. The number of Ph.D students does not grow exponentially and that's the biggest bottleneck. Having a complete genome or a complete neuron map of a human brain is useless if we don't have the software to creatively study it. And by creatively I mean not just statistically. We need software that can generate hypotheses and test them. The closest we came to this was the shotgun approach of chess-playing programs. Unfortunately this approach doesn't scale.
Finally, even if we could keep the exponential pace of progress, there are many things that are more powerful than the exponential. How about the factorial, which is characteristic of combinatorial problems? When you plot exponential growth using logarithmic scale, you get a straight line: log en = n. With the factorial, you get log n! ~ n log n - n (Stirling's formula). I believe the complexity of biological organisms, and brains in particular, grows like a factorial of the number of parts. So considering that our understanding of nervous systems is currently at the level of C. Elegans--a brainless worm with 302 neurons and 7000 synapses, we have a long way to go before we reach the Singularity.