The Singularity is Near - Book Review
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The Final Answer, the One Truth, the Single Cause
Julian Jaynes rounds out his wonderful The Origins of Consciousness in the Breakdown of the Bicameral Mind with a sanguine remark that the idea of science is rooted in the same impulse that drives religion: the desire for “the Final Answer, the One Truth, the Single Cause”.
Nowhere is this impulse better illustrated, or the scientific mien so resembling of a religious one, than in Ray Kurzweil’s hymn to forthcoming technology, The Singularity is Near. For if ever a man were committed overtly – fervently, even – to such a unitary belief, it is Ray Kurzweil. And the sceptics among our number could hardly have asked for a better example of the pitfalls, or ironies, of such an intellectual fundamentalism: on one hand, this sort of essentialism features prominently in the currently voguish denouncements of the place of religion in contemporary affairs, often being claimed as a knock-out blow to the spiritual disposition. On the other, it is too strikingly similar in its own disposition to be anything of the sort. Ray Kurzweil is every inch the millenarian, only dressed in a lab-coat and not a habit.
Kurzweil believes that the “exponentially accelerating” “advance” of technology has us well on the way to a technological and intellectual utopia/dystopia (this sort of beauty being, though Kurzweil might deny it, decidedly in the eye of the beholder) where computer science will converge on and ultimately transcend biology and, in doing so, will transport human consciousness into something quite literally cosmic. This convergence he terms the “singularity”, a point at which he expects that the universe will “wake up”, and many immutable limitations of our current sorry existence (including, he seems to say, the very laws of physics) will simply fall away.
Some, your correspondent included, might wonder whether, this being the alternative, our present existence is all that sorry in the first place.
But not Raymond Kurzweil. This author seems to be genuinely excited about a prospect which sounds rather desolate, bordering on the apocalyptic, in those aspects where it manages to transcend sounding simply absurd. Which isn’t often. One thing you could not accuse Ray Kurzweil of is a lack of pluck; but there’s a fine line between bravado and foolhardiness. Kurzweil drives a truck over it.
Evolution is not about solving problems
His approach to evolution is a good example. He talks often, and modishly, of the algorithmic nature of evolution, but then makes observations not quite out of the playbook, such as: “the key to an evolutionary algorithm ... is defining the problem. ... in biological evolution the overall problem has always been to survive” and “evolution increases order, which may or may not increase complexity”.
But to suppose an evolutionary algorithm has “a problem it is trying to solve” – in other words, a design principle – is to emasculate its very power, namely the facility of explaining how a sophisticated phenomenon comes about *without* a design principle. Evolution works because organisms (or genes) have a capacity – not an intent – to replicate themselves. Nor, necessarily, does evolution increase order. It will tend to increase complexity, because the evolutionary algorithm, having no insight, cannot “perceive” the structural improvements implied in a design simplification. Evolution has no way of rationalising design except by fiat. The adaptation required to replace an overly elaborate design with more effective but simpler one is, to use Richard Dawkins’ expression, an implausible step back down “Mount Improbable”. That’s generally not how evolutionary processes work: in nature, over-engineering is legion; economy of design isn’t.
This sounds like a picky point, but it gets to the nub of Kurzweil’s outlook, which is to assume that technology evolves like biological organisms do – that a laser printer, for example, is a direct evolutionary descendent of the printing press. This, I think, is to superimpose a convenient narrative over a process that is not directly analogous: a laser printer is no more a descendent of a printing press than a mammal is a descendent of a dinosaur. Successor, perhaps; descendant, no. But the “exponential increase in progress” arguments that Kurzweil repeatedly espouses depend for their validity on this distinction.
The “evolutionary process” from woodblock printing to the Gutenberg press, to lithography, to hot-metal typing, to photo-typesetting, to the ink jet printer (thanks, Wikipedia!) involves what Kurzweil would call “paradigm shifts” but which a biologist might call extinctions; each new technology arrives, supplements and obliterates the existing ones, not just by doing the same job more effectively, but – and this is critical – by opening up new vistas and possibilities altogether that weren’t even conceived of in the earlier technology – sometimes even at the cost of a certain flexibility inherent in the older technology.
That is, technology and even science itself is constantly forking off in un-envisaged, unexpected directions. This plays havoc with Kurzweil’s loopy idea of a perfect, upwardly arcing parabola of Utopian progress.
It is what I call “perspective chauvinism” to judge former technologies by prevailing technological orthodoxy. Superseded technologies will, by degrees, necessarily seem more and more primitive and useless if viewed in this way. And this prism is the source of many of Ray Kurzweil’s superficially impressive charts of exponential progress. But we are not progressing ever more quickly onward; rather, the place whence we have come is falling exponentially further away as our we meander, like a deflating balloon, through design space. Our rate of progress doesn’t necessarily change; our discarded technologies simply seem more and more irrelevant as we move onwards.
The rate of change in technology may have undergone a secular increase, but it isn’t necessarily permanent. I dare say a similar thing happened during the agricultural revolution and again in the industrial revolution: we got from Stephenson’s rocket to the diesel locomotive within 75 years; in the subsequent century or so the train’s evolution been more sedate. Eventually, the “S” curves Kurzweil mentions flatten out. They aren’t exponential, and pretending that an exponential parabola might emerge from a conveniently concatenated series of “S” curves seems credulous to the point of disingenuity. This extrapolation into a single “parabola of best fit” has heavy resonances of the planetary “epicycle”, a famously desperate attempt of Ptolemaic astronomers to fit “misbehaving” data into what Copernicans would ultimately convince the world was a fundamentally broken model.
If this is right, then Kurzweil’s corollary assumption – that there is a technological nirvana to which we’re ever more quickly headed – commits the inverse fallacy of supposing the questions we will ask in the future – when the universe “wakes up”, as he puts it – will be exactly the ones we anticipate now. History would say this is a naïve, parochial, chauvinistic and false assumption.
And that, I think, is the nub of it. I’m somewhat uneasy pooh-poohing a theory put together with such elan (and to be sure, buried in Kurzweil’s breathless prose is plenty of learning about technology which, if even half-way right, is fascinating), but that seems to be it. I am fortified by the nearby predictions made just four years ago, seeming not to have come anything like true just yet:
“By the end of this decade [i.e., by 2011] computers will disappear as distinct physical objects, with displays built in our eyeglasses and electronics woven into our clothing”
Whither cloud computing?
On the other hand I could find scant reference to “cloud computing” or equivalent phenomena like the Berkeley Open Infrastructure for Network Computing project which spawned schemes like SETI@home in Kurzweil’s book. Now here is a rapidly evolving technological phenotype, for sure: hooking up thousands of serially processing computers into a massive parallel network, giving processing power way beyond any technology currently envisioned. It may be that this adaptation means we simply don’t need to incur the mental challenge of molecular transistors and so on, since there must, at some point, be an absolute limit to miniaturisation, as we approach it the marginal utility of developing the necessary technology will swan dive just as the marginal cost ascends to the heavens; whereas the parallel network involves none of those limitations. You can always hook up yet another computer, and everyone will increase performance.
Evolution explains what’s happened. It doesn’t predict what happens next
I suppose it’s easy to be smug as I type on my decidedly physical computer, showing no signs of being superseded with VR Goggles just yet and we’re not far from the new decade, but the point is that the evolutionary process is notoriously bad at making predictions (until, that is, the results are in!), being as path-dependent as it is.
You can’t predict for developments that haven’t yet happened. Kurzweil glosses over this shortfall at his theory’s cost.
- I am grateful to my friend Mr. Finney for reminding of the correct chronological conventions.
- Coda:Even that seems to have gone off the boil in the last decade. Which proves, rather than undermines, the point.
- I wrote this in 2009; as I edit it ten years later, still on a PC (admittedly a smaller, more powerful one), we’re no closer, but who would have guessed at the explosion of smart phones?