My draft review of Ray Kurzweil’s Singularity is below. Comments much appreciated, and thanks to commenters on earlier posts on this topic.
Update Lots of great comments, thanks. This will improve the final version a lot, and is one of the ways in which blogging works really well for me. Keep ‘em coming.
I’ve finally received my copy of Ray Kurzweil’s Singularity, which was posted to me by its American publisher six weeks ago …
The title refers to the claim that the process of technological change, notably in relation to computing, biotechnology and nanotechnology is accelerating to the point where it will produce a fundamental, and almost instantaneous, change in what it means to be human, arising from the combination of artificial intelligence and the use of biotechnology to re-engineer our bodies and minds.
The term Singularity, used to describe this event, apparently arose in discussions between the mathematicians Stanislaw Ulam and John von Neumann. The idea of the Singularity was popularised in the 1980s and 1990s by mathematician and science fiction writer Vernor Vinge, and later by Kurzweil, a prominent technologist and innovator.
Kurzweil’s argument has two main components. The first is the claim that continuing progress in microelectronics and computer software will, over the next few decades, realise the ultimate ambitions of the artificial intelligence (AI) program, producing computers that first equal, and then dramatically outstrip, the reasoning capacities of the human mind.
The key to all this Moore’s Law. This is the observation, first made by Intel CEO Gordon Moore in the mid-1960s, that computer processing power, roughly measured by the number of transistors on an integrated circuit, doubles every eighteen months to two years. Over the intervening forty years, the number of transistors on a typical integrated circuit has gone from less than a thousand to hundreds of millions.
No exponential trend can continue indefinitely, and the end of the expansion described in Moore’s Law has been predicted on many occasions, often with reference to seemingly unavoidable constraints dictated by the laws of physics. The constraint most commonly cited at present relates to the size of components. On present trends, transistors will be smaller than atoms within 15 years or so; this does not appear to be feasible, and current industry plans only extend to two or three more generations of progress, enough for perhaps a 100-fold increase in computing power.
Not surprisingly, Kurzweil dismisses such talk, arguing that just as transistors displaced vacuum tubes and integrated circuits displaced discrete transistors, new computing paradigms based on quantum effects will allow continued progress along the lines of Moores Law right through this century, and well past the point at which computers are powerful enough to permit functional emulation of human brains.
The second part of Kurzwei’s argument is based on three overlapping revolutions in genetics, nanotechnology and robotics. These revolutions are presented as being in full swing today but iin any case it is assumed that AI will smooth out any rough spots. Between them, Kurzweil argues, developments in these three fields will transform medicine, science, finance and the economy. Although all sorts of miracles are promised, the most dramatic is human immortality, achieved first through dramatic extensions in lifespans delivered by nanorobots in our bloodstreams and, more completely, by the ability to upload ourselves into infinitely-lived computers.
Not surprisingly, Kurzweil has attracted a passionate support from a small group of people and derision from a much larger group, particularly within the blogosphere which might have been expected to sympathise more with techno-utopianism. The wittiest critique was probably that of Daniel Davies at the Crooked Timber blog (disclosure: I’m also a blogger there) who modified Arthur C Clarke’s observation about technology and magic to produce the crushing ‘Any sufficiently advanced punditry is indistinguishable from bollocks’. Riffing off a link from Tyler Cowen on the expected value of extreme forecasts, and a trope popularised by Belle Waring, Davies outbid Kurzweil by predicting not only that all the Singularity predictions would come true, but that everyone would have a pony (“ Not just any old pony by the way, but a super technonanopony!”).
Before beginning my own critical appraisal of the Singularity idea, I’ll observe that the fact that I’ve been waiting so long for the book is significant in itself. If my great-grandfather had wanted to read a book newly-published in the US, he would have had to wait six weeks or so for the steamship to deliver the book. A century later, nothing has changed, unless I’m willing to shell out the price of the book again in air freight. On the other hand, whereas international communication for great-grandad consisted of the telegraph, anyone with an Internet connection can now download shelves full of books from all around the world in a matter of minutes and at a cost measured in cents rather than dollars.
This is part of a more general paradox, only partially recognised by the prophets of the Singularity. Those of us whose lives are centred on computers and the Internet have experienced recent decades as periods of unprecedently rapid technological advance. Yet outside this narrow sector the pace of technological change has slowed to a crawl, in some cases failing even to keep pace with growth in population. The average American spends more time in the car, just to cover the basic tasks of shopping and getting to work, than was needed a generation ago, and in many cases, travels more slowly.
The advocates of the Singularity tend either to ignore these facts or to brush them aside. If there has been limited progress in transport, this doesn’t matter, since advances in nanotech, biotechn and infotech will make existing technological limits irrelevant. Taking transport as an example, if we can upload our brains into computers and transmit them at the speed of light, it doesn’t matter that cars are still slow. Similarly, transport of goods will be irrelevant since we can assemble whatever we want, wherever we want it, from raw atoms.
Much of this is unconvincing. Kurzweil lost me on biotech, for example, when he revealed that he had invented his own cure for middle age, involving the daily consumption of a vast range of pills and supplements, supposedly keeping his biological age at 40 for the last 15 years (the photo on the dustjacket is that of a man in his early 50s). In any case, nothing coming out of biotech in the last few decades has been remotely comparable to penicillin and the Pill for medical and social impact (a case could be made that ELISA screening of blood samples, was crucial in limiting the death toll from AIDS, but old-fashioned public health probably had a bigger impact.
As for nanotech, so far there has been a lot of hype but little real progress. This is masked by the fact that, now that the size of features in integrated circuits is measured in tens of nanometers, the term “nanotech” can be applied to what is, in essence, standard electronics, though pushed to extremes that would have been unimaginable a few decades ago.
Purists would confine the term “nanotechnology” to the kind of atomic-level engineering promoted by visionaries like Eric Drexler and earnestly discussed by journals like Wired. Two decades after Drexler wrote his influential PhD thesis, any products of such nanotechnology are about as visible to the naked eye as their subatomic components.
Only Kurzweil’s appeal to Moore’s Law seems worth taking seriously. There’s no sign that the rate of progress in computer technology is slowing down noticeably. A doubling time of two years for chip speed, memory capacity and so on implies a thousand-fold increase over twenty years. There are two very different things this could mean. One is that computers in twenty years time will do mostly the same things as at present, but very fast and at almost zero cost. The other is that digital technologies will displace analog for a steadily growing proportion of productive activity, in both the economy and the household sector, as has already happened with communications, photography, music and so on. Once that transition is made these sectors share the rapid growth of the computer sector.
In the first case, the contribution of computer technology to economic growth gradually declines to zero, as computing services become an effectively free good, and the rest of the economy continues as usual. Since productivity growth outside the sectors affected by computers has been slowing down for decades, the likely outcome is something close to a stationary equilibrium for the economy as a whole.
But in the second case, the rate of growth for a steadily expanding proportion of the economy accelerates to the pace dictated by Moore’s Law. Again, communications provides an illustration – after decades of steady productivity growth at 4 or 5 per cent a year, the rate of technical progress jumped to 70 per cent a year around 1990, at least for those types of communication that can be digitized (the move from 2400-baud modems to megabit broadband in the space of 15 years illustrates this). A generalized Moore’s law might not exactly produce Kurzweil’s singularity, but a few years of growth at 70 per cent a year would make most current economic calculations irrelevant.
One way of expressing this dichotomy is in terms of the aggregate elasticity of demand for computation. If it’s greater than one, the share of computing in the economy, expressed in value terms, rises steadily as computing gets cheaper. If it’s less than one, the share falls. It’s only if the elasticity is very close to one that we continue on the path of the last couple of decades, with continuing growth at a rate of around 3 per cent.
This kind of result, where only a single value of a key parameter is consistent with stable growth, is sometimes called a knife-edge. Reasoning like this can be tricky – maybe there are good reasons why the elasticity of demand for computation should be very close to one. One reason this might be so is if most problems eventually reach a point, similar to that of weather forecasting, where linear improvements in performance require exponential growth in computation (such problems are said to be polynomial in complexity).
If the solution to a problem involves components that are polynomial (or worse) in complexity, initial progress may be rapid as non-polynomial components of the problem are solved, but progress with the polynomial component will at best be linear, even if the cost of computation falls exponentially.
So far it seems as if the elasticity of demand for computation is a bit greater than one, but not a lot. The share of IT in total investment has risen significantly, but the share of the economy driven primarily by IT remains small. In addition, non-economic activity like blogging has expanded rapidly, but also remains small. The whole thing could easily bog down in an economy-wide version of ‘Intel giveth and Microsoft taketh away’.
In summary, I’m unconvinced that the Singularity is near. But unlike the majority of critics of Kurzweil’s argument, I’m not prepared to rule out the possibility that information technology will spread through large sectors of the economy, producing unprecedently rapid economic growth. Even a small probability of such an outcome would make a big difference to the expected returns to investments, and would be worth planning for. So it’s certainly worthwhile reading Kurzweil’s book and taking the time to consider his argument.
At this stage, though, the Singularity is still best considered as science fiction. If you really want to get a feel for the ideas that drive discussion of the Singularity, read Ian McDonald’s River of Gods or, better still, Charles Stross’ Accelerando.