Ray Kurzweil has responded to my criticisim of futurist fortune-telling. It really just compounds the problems, though, and gullible people who love Ray will think he’s answered me, while skeptical people who see through his hocus-pocus will be unimpressed. It’s kind of pointless to reply again, but here goes.

His first point is silly.

For starters, I said that we would be able to reverse-engineer the brain sufficiently to understand its basic principles of operation within two decades, not one decade, as Myers reports.

I don’t care.

I didn’t make an issue of his timescale in the first place; in fact, I said it made no difference. The problem is that he has provided no reason to specify a date, other than his vague mantra of “exponential growth”. Why not say 5 years? Why not 50? The heart of the Kurzweil method is to simply pick a date far enough in the future that we cannot predict what technological advances will occur, and also far enough forward that he isn’t likely to be confronted with his failure by people who remember what he said, and all is good. My complaint isn’t that he has set a date by which we’ll understand the brain, but that he has provided no baseline value for his exponential growth claim, and has no way to measure how much we know now, how much we need to know, and how rapidly we will acquire that knowledge. “Really fast” or “exponentially increasing” are not informative.

I mentioned the genome in a completely different context. I presented a number of arguments as to why the design of the brain is not as complex as some theorists have advocated. This is to respond to the notion that it would require trillions of lines of code to create a comparable system. The argument from the amount of information in the genome is one of several such arguments. It is not a proposed strategy for accomplishing reverse-engineering. It is an argument from information theory, which Myers obviously does not understand.

I think I understand it better than Kurzweil. If we have a seed of information that initiates a process, followed by many activities and interactions that add progressively more information to the process, you can’t use information theory to measure the amount of information in the seed and then announce that you’ve put an upper bound on the amount of complexity in the process.

For instance, you can’t measure the number of transistors in an Intel CPU and then announce, “A-ha! We now understand what a small amount of information is actually required to create all those operating systems and computer games and Microsoft Word, and it is much, much smaller than everyone is assuming.” Put it in those terms, and the Kurzweil fanboys would laugh at him; put it in terms of something they don’t understand at all, like the development and function of the brain, and they’re willing to go along with the pretense that the genome tells us that the whole organism is simpler than they thought.

I presume they understand that if you program a perfect Intel emulator, you don’t suddenly get Halo: Reach for free, as an emergent property of the system. You can buy the code and add it to the system, sure, but in this case, we can’t run down to GameStop and buy a DVD with the human OS in it and install it on our artificial brain. You’re going to have to do the hard work of figuring out how that works and reverse engineering it, as well. And understanding how the processor works is necessary to do that, but not sufficient.

Kurzweil does add another piece to his argument, although it doesn’t help: the modularity and repetitive organization of the human brain.

For example, the cerebellum (which has been modeled, simulated and tested) — the region responsible for part of our skill formation, like catching a fly ball — contains a module of four types of neurons. That module is repeated about ten billion times. The cortex, a region that only mammals have and that is responsible for our ability to think symbolically and in hierarchies of ideas, also has massive redundancy. It has a basic pattern-recognition module that is considerably more complex than the repeated module in the cerebellum, but that cortex module is repeated about a billion times. There is also information in the interconnections, but there is massive redundancy in the connection pattern as well.

This is true — the cortex is a layered structure with similar elements repeated over and over again, in broad arrays. Pyramidal neurons, for instance, are instantly recognizable and and share a whole suite of common morphological elements between each other — but each one is also as unique as a snowflake. Those differences matter, and they are not specified in the genome. (For that matter, you won’t find any blueprint in the genome for the dendrite pattern of pyramidal neurons, either). If you want to recreate a generic human brain, it won’t work if you just make every pyramidal neuron exactly identical; there have to be spatial differences and differences in connectivity. You especially won’t be able to carry out something far more specific, such as emulate Ray Kurzweil’s brain, if you decide to simplify and make his cortex a uniform array of identical modules.

In short, here’s Kurzweil’s claim: the brain is simpler than we think, and thanks to the accelerating rate of technological change, we will understand it’s basic principles of operation completely within a few decades. My counterargument, which he hasn’t addressed at all, is that 1) his argument for that simplicity is deeply flawed and irrelevant, 2) he has made no quantifiable argument about how much we know about the brain right now, and I argue that we’ve only scratched the surface in the last several decades of research, 3) “exponential” is not a magic word that solves all problems (if I put a penny in the bank today, it does not mean I will have a million dollars in my retirement fund in 20 years), and 4) Kurzweil has provided no explanation for how we’ll be ‘reverse engineering’ the human brain. He’s now at least clearly stating that decoding the genome does not generate the necessary information — it’s just an argument that the brain isn’t as complex as we thought, which I’ve already said is bogus — but left dangling is the question of methodology. I suggest that we need to have a combined strategy of digging into the brain from the perspectives of physiology, molecular biology, genetics, and development, and in all of those fields I see a long hard slog ahead. I also don’t see that noisemakers like Kurzweil, who know nothing of those fields, will be making any contribution at all.

So what exactly is the basis of Kurzweil’s expected magic great leap forward? And no, the miracle of exponential growth is not an answer. If all a futurist has to do is wave his hands and say things will change more rapidly than we expect, then futurists like Kurzweil are nothing but techno-gimmicky Criswells. Utterly useless.