Intelligence

Awret, Uziel, ed. The Singularity. Exeter, UK: Imprint Academic, 2016. ISBN 978-1-845409-07-4.
For more than half a century, the prospect of a technological singularity has been part of the intellectual landscape of those envisioning the future. In 1965, in a paper titled “Speculations Concerning the First Ultraintelligent Machine” statistician I. J. Good wrote,

Let an ultra-intelligent machine be defined as a machine that can far surpass all of the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an “intelligence explosion”, and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make.

(The idea of a runaway increase in intelligence had been discussed earlier, notably by Robert A. Heinlein in a 1952 essay titled “Where To?”) Discussion of an intelligence explosion and/or technological singularity was largely confined to science fiction and the more speculatively inclined among those trying to foresee the future, largely because the prerequisite—building machines which were more intelligent than humans—seemed such a distant prospect, especially as the initially optimistic claims of workers in the field of artificial intelligence gave way to disappointment.

Over all those decades, however, the exponential growth in computing power available at constant cost continued. The funny thing about continued exponential growth is that it doesn't matter what fixed level you're aiming for: the exponential will eventually exceed it, and probably a lot sooner than most people expect. By the 1990s, it was clear just how far the growth in computing power and storage had come, and that there were no technological barriers on the horizon likely to impede continued growth for decades to come. People started to draw straight lines on semi-log paper and discovered that, depending upon how you evaluate the computing capacity of the human brain (a complicated and controversial question), the computing power of a machine with a cost comparable to a present-day personal computer would cross the human brain threshold sometime in the twenty-first century. There seemed to be a limited number of alternative outcomes.

  1. Progress in computing comes to a halt before reaching parity with human brain power, due to technological limits, economics (inability to afford the new technologies required, or lack of applications to fund the intermediate steps), or intervention by authority (for example, regulation motivated by a desire to avoid the risks and displacement due to super-human intelligence).
  2. Computing continues to advance, but we find that the human brain is either far more complicated than we believed it to be, or that something is going on in there which cannot be modelled or simulated by a deterministic computational process. The goal of human-level artificial intelligence recedes into the distant future.
  3. Blooie! Human level machine intelligence is achieved, successive generations of machine intelligences run away to approach the physical limits of computation, and before long machine intelligence exceeds that of humans to the degree humans surpass the intelligence of mice (or maybe insects).

Now, the thing about this is that many people will dismiss such speculation as science fiction having nothing to do with the “real world” they inhabit. But there's no more conservative form of forecasting than observing a trend which has been in existence for a long time (in the case of growth in computing power, more than a century, spanning multiple generations of very different hardware and technologies), and continuing to extrapolate it into the future and then ask, “What happens then?” When you go through this exercise and an answer pops out which seems to indicate that within the lives of many people now living, an event completely unprecedented in the history of our species—the emergence of an intelligence which far surpasses that of humans—might happen, the prospects and consequences bear some serious consideration.

The present book, based upon two special issues of the Journal of Consciousness Studies, attempts to examine the probability, nature, and consequences of a singularity from a variety of intellectual disciplines and viewpoints. The volume begins with an essay by philosopher David Chalmers originally published in 2010: “The Singularity: a Philosophical Analysis”, which attempts to trace various paths to a singularity and evaluate their probability. Chalmers does not attempt to estimate the time at which a singularity may occur—he argues that if it happens any time within the next few centuries, it will be an epochal event in human history which is worth thinking about today. Chalmers contends that the argument for artificial intelligence (AI) is robust because there appear to be multiple paths by which we could get there, and hence AI does not depend upon a fragile chain of technological assumptions which might break at any point in the future. We could, for example, continue to increase the performance and storage capacity of our computers, to such an extent that the “deep learning” techniques already used in computing applications, combined with access to a vast amount of digital data on the Internet, may cross the line of human intelligence. Or, we may continue our progress in reverse-engineering the microstructure of the human brain and apply our ever-growing computing power to emulating it at a low level (this scenario is discussed in detail in Robin Hanson's The Age of Em [September 2016]). Or, since human intelligence was produced by the process of evolution, we might set our supercomputers to simulate evolution itself (which we're already doing to some extent with genetic algorithms) in order to evolve super-human artificial intelligence (not only would computer-simulated evolution run much faster than biological evolution, it would not be random, but rather directed toward desired results, much like selective breeding of plants or livestock).

Regardless of the path or paths taken, the outcomes will be one of the three discussed above: either a singularity or no singularity. Assume, arguendo, that the singularity occurs, whether before 2050 as some optimists project or many decades later. What will it be like? Will it be good or bad? Chalmers writes,

I take it for granted that there are potential good and bad aspects to an intelligence explosion. For example, ending disease and poverty would be good. Destroying all sentient life would be bad. The subjugation of humans by machines would be at least subjectively bad.

…well, at least in the eyes of the humans. If there is a singularity in our future, how might we act to maximise the good consequences and avoid the bad outcomes? Can we design our intellectual successors (and bear in mind that we will design only the first generation: each subsequent generation will be designed by the machines which preceded it) to share human values and morality? Can we ensure they are “friendly” to humans and not malevolent (or, perhaps, indifferent, just as humans do not take into account the consequences for ant colonies and bacteria living in the soil upon which buildings are constructed?) And just what are “human values and morality” and “friendly behaviour” anyway, given that we have been slaughtering one another for millennia in disputes over such issues? Can we impose safeguards to prevent the artificial intelligence from “escaping” into the world? What is the likelihood we could prevent such a super-being from persuading us to let it loose, given that it thinks thousands or millions of times faster than we, has access to all of human written knowledge, and the ability to model and simulate the effects of its arguments? Is turning off an AI murder, or terminating the simulation of an AI society genocide? Is it moral to confine an AI to what amounts to a sensory deprivation chamber, or in what amounts to solitary confinement, or to deceive it about the nature of the world outside its computing environment?

What will become of humans in a post-singularity world? Given that our species is the only survivor of genus Homo, history is not encouraging, and the gap between human intelligence and that of post-singularity AIs is likely to be orders of magnitude greater than that between modern humans and the great apes. Will these super-intelligent AIs have consciousness and self-awareness, or will they be philosophical zombies: able to mimic the behaviour of a conscious being but devoid of any internal sentience? What does that even mean, and how can you be sure other humans you encounter aren't zombies? Are you really all that sure about yourself? Are the qualia of machines not constrained?

Perhaps the human destiny is to merge with our mind children, either by enhancing human cognition, senses, and memory through implants in our brain, or by uploading our biological brains into a different computing substrate entirely, whether by emulation at a low level (for example, simulating neuron by neuron at the level of synapses and neurotransmitters), or at a higher, functional level based upon an understanding of the operation of the brain gleaned by analysis by AIs. If you upload your brain into a computer, is the upload conscious? Is it you? Consider the following thought experiment: replace each biological neuron of your brain, one by one, with a machine replacement which interacts with its neighbours precisely as the original meat neuron did. Do you cease to be you when one neuron is replaced? When a hundred are replaced? A billion? Half of your brain? The whole thing? Does your consciousness slowly fade into zombie existence as the biological fraction of your brain declines toward zero? If so, what is magic about biology, anyway? Isn't arguing that there's something about the biological substrate which uniquely endows it with consciousness as improbable as the discredited theory of vitalism, which contended that living things had properties which could not be explained by physics and chemistry?

Now let's consider another kind of uploading. Instead of incremental replacement of the brain, suppose an anæsthetised human's brain is destructively scanned, perhaps by molecular-scale robots, and its structure transferred to a computer, which will then emulate it precisely as the incrementally replaced brain in the previous example. When the process is done, the original brain is a puddle of goo and the human is dead, but the computer emulation now has all of the memories, life experience, and ability to interact as its progenitor. But is it the same person? Did the consciousness and perception of identity somehow transfer from the brain to the computer? Or will the computer emulation mourn its now departed biological precursor, as it contemplates its own immortality? What if the scanning process isn't destructive? When it's done, BioDave wakes up and makes the acquaintance of DigiDave, who shares his entire life up to the point of uploading. Certainly the two must be considered distinct individuals, as are identical twins whose histories diverged in the womb, right? Does DigiDave have rights in the property of BioDave? “Dave's not here”? Wait—we're both here! Now what?

Or, what about somebody today who, in the sure and certain hope of the Resurrection to eternal life opts to have their brain cryonically preserved moments after clinical death is pronounced. After the singularity, the decedent's brain is scanned (in this case it's irrelevant whether or not the scan is destructive), and uploaded to a computer, which starts to run an emulation of it. Will the person's identity and consciousness be preserved, or will it be a new person with the same memories and life experiences? Will it matter?

Deep questions, these. The book presents Chalmers' paper as a “target essay”, and then invites contributors in twenty-six chapters to discuss the issues raised. A concluding essay by Chalmers replies to the essays and defends his arguments against objections to them by their authors. The essays, and their authors, are all over the map. One author strikes this reader as a confidence man and another a crackpot—and these are two of the more interesting contributions to the volume. Nine chapters are by academic philosophers, and are mostly what you might expect: word games masquerading as profound thought, with an admixture of ad hominem argument, including one chapter which descends into Freudian pseudo-scientific analysis of Chalmers' motives and says that he “never leaps to conclusions; he oozes to conclusions”.

Perhaps these are questions philosophers are ill-suited to ponder. Unlike questions of the nature of knowledge, how to live a good life, the origins of morality, and all of the other diffuse gruel about which philosophers have been arguing since societies became sufficiently wealthy to indulge in them, without any notable resolution in more than two millennia, the issues posed by a singularity have answers. Either the singularity will occur or it won't. If it does, it will either result in the extinction of the human species (or its reduction to irrelevance), or it won't. AIs, if and when they come into existence, will either be conscious, self-aware, and endowed with free will, or they won't. They will either share the values and morality of their progenitors or they won't. It will either be possible for humans to upload their brains to a digital substrate, or it won't. These uploads will either be conscious, or they'll be zombies. If they're conscious, they'll either continue the identity and life experience of the pre-upload humans, or they won't. These are objective questions which can be settled by experiment. You get the sense that philosophers dislike experiments—they're a risk to job security disputing questions their ancestors have been puzzling over at least since Athens.

Some authors dispute the probability of a singularity and argue that the complexity of the human brain has been vastly underestimated. Others contend there is a distinction between computational power and the ability to design, and consequently exponential growth in computing may not produce the ability to design super-intelligence. Still another chapter dismisses the evolutionary argument through evidence that the scope and time scale of terrestrial evolution is computationally intractable into the distant future even if computing power continues to grow at the rate of the last century. There is even a case made that the feasibility of a singularity makes the probability that we're living, not in a top-level physical universe, but in a simulation run by post-singularity super-intelligences, overwhelming, and that they may be motivated to turn off our simulation before we reach our own singularity, which may threaten them.

This is all very much a mixed bag. There are a multitude of Big Questions, but very few Big Answers among the 438 pages of philosopher word salad. I find my reaction similar to that of David Hume, who wrote in 1748:

If we take in our hand any volume of divinity or school metaphysics, for instance, let us ask, Does it contain any abstract reasoning containing quantity or number? No. Does it contain any experimental reasoning concerning matter of fact and existence? No. Commit it then to the flames, for it can contain nothing but sophistry and illusion.

I don't burn books (it's некультурный and expensive when you read them on an iPad), but you'll probably learn as much pondering the questions posed here on your own and in discussions with friends as from the scholarly contributions in these essays. The copy editing is mediocre, with some eminent authors stumbling over the humble apostrophe. The Kindle edition cites cross-references by page number, which are useless since the electronic edition does not include page numbers. There is no index.

March 2017 Permalink

Barrat, James. Our Final Invention. New York: Thomas Dunne Books, 2013. ISBN 978-0-312-62237-4.
As a member of that crusty generation who began programming mainframe computers with punch cards in the 1960s, the phrase “artificial intelligence” evokes an almost visceral response of scepticism. Since its origin in the 1950s, the field has been a hotbed of wildly over-optimistic enthusiasts, predictions of breakthroughs which never happened, and some outright confidence men preying on investors and institutions making research grants. John McCarthy, who organised the first international conference on artificial intelligence (a term he coined), predicted at the time that computers would achieve human-level general intelligence within six months of concerted research toward that goal. In 1970 Marvin Minsky said “In from three to eight years we will have a machine with the general intelligence of an average human being.” And these were serious scientists and pioneers of the field; the charlatans and hucksters were even more absurd in their predictions.

And yet, and yet…. The exponential growth in computing power available at constant cost has allowed us to “brute force” numerous problems once considered within the domain of artificial intelligence. Optical character recognition (machine reading), language translation, voice recognition, natural language query, facial recognition, chess playing at the grandmaster level, and self-driving automobiles were all once thought to be things a computer could never do unless it vaulted to the level of human intelligence, yet now most have become commonplace or are on the way to becoming so. Might we, in the foreseeable future, be able to brute force human-level general intelligence?

Let's step back and define some terms. “Artificial General Intelligence” (AGI) means a machine with intelligence comparable to that of a human across all of the domains of human intelligence (and not limited, say, to playing chess or driving a vehicle), with self-awareness and the ability to learn from mistakes and improve its performance. It need not be embodied in a robot form (although some argue it would have to be to achieve human-level performance), but could certainly pass the Turing test: a human communicating with it over whatever channels of communication are available (in the original formulation of the test, a text-only teleprinter) would not be able to determine whether he or she were communicating with a machine or another human. “Artificial Super Intelligence” (ASI) denotes a machine whose intelligence exceeds that of the most intelligent human. Since a self-aware intelligent machine will be able to modify its own programming, with immediate effect, as opposed to biological organisms which must rely upon the achingly slow mechanism of evolution, an AGI might evolve into an ASI in an eyeblink: arriving at intelligence a million times or more greater than that of any human, a process which I. J. Good called an “intelligence explosion”.

What will it be like when, for the first time in the history of our species, we share the planet with an intelligence greater than our own? History is less than encouraging. All members of genus Homo which were less intelligent than modern humans (inferring from cranial capacity and artifacts, although one can argue about Neanderthals) are extinct. Will that be the fate of our species once we create a super intelligence? This book presents the case that not only will the construction of an ASI be the final invention we need to make, since it will be able to anticipate anything we might invent long before we can ourselves, but also our final invention because we won't be around to make any more.

What will be the motivations of a machine a million times more intelligent than a human? Could humans understand such motivations any more than brewer's yeast could understand ours? As Eliezer Yudkowsky observed, “The AI does not hate you, nor does it love you, but you are made out of atoms which it can use for something else.” Indeed, when humans plan to construct a building, do they take into account the wishes of bacteria in soil upon which the structure will be built? The gap between humans and ASI will be as great. The consequences of creating ASI may extend far beyond the Earth. A super intelligence may decide to propagate itself throughout the galaxy and even beyond: with immortality and the ability to create perfect copies of itself, even travelling at a fraction of the speed of light it could spread itself into all viable habitats in the galaxy in a few hundreds of millions of years—a small fraction of the billions of years life has existed on Earth. Perhaps ASI probes from other extinct biological civilisations foolish enough to build them are already headed our way.

People are presently working toward achieving AGI. Some are in the academic and commercial spheres, with their work reasonably transparent and reported in public venues. Others are “stealth companies” or divisions within companies (does anybody doubt that Google's achieving an AGI level of understanding of the information it Hoovers up from the Web wouldn't be a overwhelming competitive advantage?). Still others are funded by government agencies or operate within the black world: certainly players such as NSA dream of being able to understand all of the information they intercept and cross-correlate it. There is a powerful “first mover” advantage in developing AGI and ASI. The first who obtains it will be able to exploit its capability against those who haven't yet achieved it. Consequently, notwithstanding the worries about loss of control of the technology, players will be motivated to support its development for fear their adversaries might get there first.

This is a well-researched and extensively documented examination of the state of artificial intelligence and assessment of its risks. There are extensive end notes including references to documents on the Web which, in the Kindle edition, are linked directly to their sources. In the Kindle edition, the index is just a list of “searchable terms”, not linked to references in the text. There are a few goofs, as you might expect for a documentary film maker writing about technology (“Newton's second law of thermodynamics”), but nothing which invalidates the argument made herein.

I find myself oddly ambivalent about the whole thing. When I hear “artificial intelligence” what flashes through my mind remains that dielectric material I step in when I'm insufficiently vigilant crossing pastures in Switzerland. Yet with the pure increase in computing power, many things previously considered AI have been achieved, so it's not implausible that, should this exponential increase continue, human-level machine intelligence will be achieved either through massive computing power applied to cognitive algorithms or direct emulation of the structure of the human brain. If and when that happens, it is difficult to see why an “intelligence explosion” will not occur. And once that happens, humans will be faced with an intelligence that dwarfs that of their entire species; which will have already penetrated every last corner of its infrastructure; read every word available online written by every human; and which will deal with its human interlocutors after gaming trillions of scenarios on cloud computing resources it has co-opted.

And still we advance the cause of artificial intelligence every day. Sleep well.

December 2013 Permalink

Bostrom, Nick. Superintelligence. Oxford: Oxford University Press, 2014. ISBN 978-0-19-967811-2.
Absent the emergence of some physical constraint which causes the exponential growth of computing power at constant cost to cease, some form of economic or societal collapse which brings an end to research and development of advanced computing hardware and software, or a decision, whether bottom-up or top-down, to deliberately relinquish such technologies, it is probable that within the 21st century there will emerge artificially-constructed systems which are more intelligent (measured in a variety of ways) than any human being who has ever lived and, given the superior ability of such systems to improve themselves, may rapidly advance to superiority over all human society taken as a whole. This “intelligence explosion” may occur in so short a time (seconds to hours) that human society will have no time to adapt to its presence or interfere with its emergence. This challenging and occasionally difficult book, written by a philosopher who has explored these issues in depth, argues that the emergence of superintelligence will pose the greatest human-caused existential threat to our species so far in its existence, and perhaps in all time.

Let us consider what superintelligence may mean. The history of machines designed by humans is that they rapidly surpass their biological predecessors to a large degree. Biology never produced something like a steam engine, a locomotive, or an airliner. It is similarly likely that once the intellectual and technological leap to constructing artificially intelligent systems is made, these systems will surpass human capabilities to an extent greater than those of a Boeing 747 exceed those of a hawk. The gap between the cognitive power of a human, or all humanity combined, and the first mature superintelligence may be as great as that between brewer's yeast and humans. We'd better be sure of the intentions and benevolence of that intelligence before handing over the keys to our future to it.

Because when we speak of the future, that future isn't just what we can envision over a few centuries on this planet, but the entire “cosmic endowment” of humanity. It is entirely plausible that we are members of the only intelligent species in the galaxy, and possibly in the entire visible universe. (If we weren't, there would be abundant and visible evidence of cosmic engineering by those more advanced that we.) Thus our cosmic endowment may be the entire galaxy, or the universe, until the end of time. What we do in the next century may determine the destiny of the universe, so it's worth some reflection to get it right.

As an example of how easy it is to choose unwisely, let me expand upon an example given by the author. There are extremely difficult and subtle questions about what the motivations of a superintelligence might be, how the possession of such power might change it, and the prospects for we, its creator, to constrain it to behave in a way we consider consistent with our own values. But for the moment, let's ignore all of those problems and assume we can specify the motivation of an artificially intelligent agent we create and that it will remain faithful to that motivation for all time. Now suppose a paper clip factory has installed a high-end computing system to handle its design tasks, automate manufacturing, manage acquisition and distribution of its products, and otherwise obtain an advantage over its competitors. This system, with connectivity to the global Internet, makes the leap to superintelligence before any other system (since it understands that superintelligence will enable it to better achieve the goals set for it). Overnight, it replicates itself all around the world, manipulates financial markets to obtain resources for itself, and deploys them to carry out its mission. The mission?—to maximise the number of paper clips produced in its future light cone.

“Clippy”, if I may address it so informally, will rapidly discover that most of the raw materials it requires in the near future are locked in the core of the Earth, and can be liberated by disassembling the planet by self-replicating nanotechnological machines. This will cause the extinction of its creators and all other biological species on Earth, but then they were just consuming energy and material resources which could better be deployed for making paper clips. Soon other planets in the solar system would be similarly disassembled, and self-reproducing probes dispatched on missions to other stars, there to make paper clips and spawn other probes to more stars and eventually other galaxies. Eventually, the entire visible universe would be turned into paper clips, all because the original factory manager didn't hire a philosopher to work out the ultimate consequences of the final goal programmed into his factory automation system.

This is a light-hearted example, but if you happen to observe a void in a galaxy whose spectrum resembles that of paper clips, be very worried.

One of the reasons to believe that we will have to confront superintelligence is that there are multiple roads to achieving it, largely independent of one another. Artificial general intelligence (human-level intelligence in as many domains as humans exhibit intelligence today, and not constrained to limited tasks such as playing chess or driving a car) may simply await the discovery of a clever software method which could run on existing computers or networks. Or, it might emerge as networks store more and more data about the real world and have access to accumulated human knowledge. Or, we may build “neuromorphic“ systems whose hardware operates in ways similar to the components of human brains, but at electronic, not biologically-limited speeds. Or, we may be able to scan an entire human brain and emulate it, even without understanding how it works in detail, either on neuromorphic or a more conventional computing architecture. Finally, by identifying the genetic components of human intelligence, we may be able to manipulate the human germ line, modify the genetic code of embryos, or select among mass-produced embryos those with the greatest predisposition toward intelligence. All of these approaches may be pursued in parallel, and progress in one may advance others.

At some point, the emergence of superintelligence calls into the question the economic rationale for a large human population. In 1915, there were about 26 million horses in the U.S. By the early 1950s, only 2 million remained. Perhaps the AIs will have a nostalgic attachment to those who created them, as humans had for the animals who bore their burdens for millennia. But on the other hand, maybe they won't.

As an engineer, I usually don't have much use for philosophers, who are given to long gassy prose devoid of specifics and for spouting complicated indirect arguments which don't seem to be independently testable (“What if we asked the AI to determine its own goals, based on its understanding of what we would ask it to do if only we were as intelligent as it and thus able to better comprehend what we really want?”). These are interesting concepts, but would you want to bet the destiny of the universe on them? The latter half of the book is full of such fuzzy speculation, which I doubt is likely to result in clear policy choices before we're faced with the emergence of an artificial intelligence, after which, if they're wrong, it will be too late.

That said, this book is a welcome antidote to wildly optimistic views of the emergence of artificial intelligence which blithely assume it will be our dutiful servant rather than a fearful master. Some readers may assume that an artificial intelligence will be something like a present-day computer or search engine, and not be self-aware and have its own agenda and powerful wiles to advance it, based upon a knowledge of humans far beyond what any single human brain can encompass. Unless you believe there is some kind of intellectual élan vital inherent in biological substrates which is absent in their equivalents based on other hardware (which just seems silly to me—like arguing there's something special about a horse which can't be accomplished better by a truck), the mature artificial intelligence will be the superior in every way to its human creators, so in-depth ratiocination about how it will regard and treat us is in order before we find ourselves faced with the reality of dealing with our successor.

September 2014 Permalink

Herrnstein, Richard J. and Charles Murray. The Bell Curve. New York: The Free Press, [1994] 1996. ISBN 0-684-82429-9.

August 2003 Permalink

Itzkoff, Seymour W. The Decline of Intelligence in America. Westport, CT: Praeger, 1994. ISBN 0-275-95229-0.
This book had the misfortune to come out in the same year as the first edition of The Bell Curve (August 2003), and suffers by comparison. Unlike that deservedly better-known work, Itzkoff presents few statistics to support his claims that dysgenic reproduction is resulting in a decline in intelligence in the U.S. Any assertion of declining intelligence must confront the evidence for the Flynn Effect (see The Rising Curve, July 2004), which seems to indicate IQ scores are rising about 15 points per generation in a long list of countries including the U.S. The author dismisses Flynn's work in a single paragraph as irrelevant to international competition since scores of all major industrialised countries are rising at about the same rate. But if you argue that IQ is a measure of intelligence, as this book does, how can you claim intelligence is falling at the same time IQ scores are rising at a dizzying rate without providing some reason that Flynn's data should be disregarded? There's quite a bit of hand wringing about the social, educational, and industrial prowess of Japan and Germany which sounds rather dated with a decade's hindsight. The second half of the book is a curious collection of policy recommendations, which defy easy classification into a point on the usual political spectrum. Itzkoff advocates economic protectionism, school vouchers, government-led industrial policy, immigration restrictions, abolishing affirmative action, punitive taxation, government incentives for conventional families, curtailment of payments to welfare mothers and possibly mandatory contraception, penalties for companies which export well-paying jobs, and encouragement of inter-racial and -ethnic marriage. I think that if an ADA/MoveOn/NOW liberal were to read this book, their head might explode. Given the political climate in the U.S. and other Western countries, such policies had exactly zero chance of being implemented either when he recommended them in 1994 and no more today.

October 2004 Permalink

Kurzweil, Ray. The Singularity Is Near. New York: Viking, 2005. ISBN 0-670-03384-7.
What happens if Moore's Law—the annual doubling of computing power at constant cost—just keeps on going? In this book, inventor, entrepreneur, and futurist Ray Kurzweil extrapolates the long-term faster than exponential growth (the exponent is itself growing exponentially) in computing power to the point where the computational capacity of the human brain is available for about US$1000 (around 2020, he estimates), reverse engineering and emulation of human brain structure permits machine intelligence indistinguishable from that of humans as defined by the Turing test (around 2030), and the subsequent (and he believes inevitable) runaway growth in artificial intelligence leading to a technological singularity around 2045 when US$1000 will purchase computing power comparable to that of all presently-existing human brains and the new intelligence created in that single year will be a billion times greater than that of the entire intellectual heritage of human civilisation prior to that date. He argues that the inhabitants of this brave new world, having transcended biological computation in favour of nanotechnological substrates “trillions of trillions of times more capable” will remain human, having preserved their essential identity and evolutionary heritage across this leap to Godlike intellectual powers. Then what? One might as well have asked an ant to speculate on what newly-evolved hominids would end up accomplishing, as the gap between ourselves and these super cyborgs (some of the precursors of which the author argues are alive today) is probably greater than between arthropod and anthropoid.

Throughout this tour de force of boundless technological optimism, one is impressed by the author's adamantine intellectual integrity. This is not an advocacy document—in fact, Kurzweil's view is that the events he envisions are essentially inevitable given the technological, economic, and moral (curing disease and alleviating suffering) dynamics driving them. Potential roadblocks are discussed candidly, along with the existential risks posed by the genetics, nanotechnology, and robotics (GNR) revolutions which will set the stage for the singularity. A chapter is devoted to responding to critics of various aspects of the argument, in which opposing views are treated with respect.

I'm not going to expound further in great detail. I suspect a majority of people who read these comments will, in all likelihood, read the book themselves (if they haven't already) and make up their own minds about it. If you are at all interested in the evolution of technology in this century and its consequences for the humans who are creating it, this is certainly a book you should read. The balance of these remarks discuss various matters which came to mind as I read the book; they may not make much sense unless you've read it (You are going to read it, aren't you?), but may highlight things to reflect upon as you do.

  • Switching off the simulation. Page 404 raises a somewhat arcane risk I've pondered at some length. Suppose our entire universe is a simulation run on some super-intelligent being's computer. (What's the purpose of the universe? It's a science fair project!) What should we do to avoid having the simulation turned off, which would be bad? Presumably, the most likely reason to stop the simulation is that it's become boring. Going through a technological singularity, either from the inside or from the outside looking in, certainly doesn't sound boring, so Kurzweil argues that working toward the singularity protects us, if we be simulated, from having our plug pulled. Well, maybe, but suppose the explosion in computing power accessible to the simulated beings (us) at the singularity exceeds that available to run the simulation? (This is plausible, since post-singularity computing rapidly approaches its ultimate physical limits.) Then one imagines some super-kid running top to figure out what's slowing down the First Superbeing Shooter game he's running and killing the CPU hog process. There are also things we can do which might increase the risk of the simulation's being switched off. Consider, as I've proposed, precision fundamental physics experiments aimed at detecting round-off errors in the simulation (manifested, for example, as small violations of conservation laws). Once the beings in the simulation twig to the fact that they're in a simulation and that their reality is no more accurate than double precision floating point, what's the point to letting it run?
  • Fifty bits per atom? In the description of the computational capacity of a rock (p. 131), the calculation assumes that 100 bits of memory can be encoded in each atom of a disordered medium. I don't get it; even reliably storing a single bit per atom is difficult to envision. Using the “precise position, spin, and quantum state” of a large ensemble of atoms as mentioned on p. 134 seems highly dubious.
  • Luddites. The risk from anti-technology backlash is discussed in some detail. (“Ned Ludd” himself joins in some of the trans-temporal dialogues.) One can imagine the next generation of anti-globalist demonstrators taking to the streets to protest the “evil corporations conspiring to make us all rich and immortal”.
  • Fundamentalism. Another risk is posed by fundamentalism, not so much of the religious variety, but rather fundamentalist humanists who perceive the migration of humans to non-biological substrates (at first by augmentation, later by uploading) as repellent to their biological conception of humanity. One is inclined, along with the author, simply to wait until these folks get old enough to need a hip replacement, pacemaker, or cerebral implant to reverse a degenerative disease to motivate them to recalibrate their definition of “purely biological”. Still, I'm far from the first to observe that Singularitarianism (chapter 7) itself has some things in common with religious fundamentalism. In particular, it requires faith in rationality (which, as Karl Popper observed, cannot be rationally justified), and that the intentions of super-intelligent beings, as Godlike in their powers compared to humans as we are to Saccharomyces cerevisiae, will be benign and that they will receive us into eternal life and bliss. Haven't I heard this somewhere before? The main difference is that the Singularitarian doesn't just aspire to Heaven, but to Godhood Itself. One downside of this may be that God gets quite irate.
  • Vanity. I usually try to avoid the “Washington read” (picking up a book and flipping immediately to the index to see if I'm in it), but I happened to notice in passing I made this one, for a minor citation in footnote 47 to chapter 2.
  • Spindle cells. The material about “spindle cells” on pp. 191–194 is absolutely fascinating. These are very large, deeply and widely interconnected neurons which are found only in humans and a few great apes. Humans have about 80,000 spindle cells, while gorillas have 16,000, bonobos 2,100 and chimpanzees 1,800. If you're intrigued by what makes humans human, this looks like a promising place to start.
  • Speculative physics. The author shares my interest in physics verging on the fringe, and, turning the pages of this book, we come across such topics as possible ways to exceed the speed of light, black hole ultimate computers, stable wormholes and closed timelike curves (a.k.a. time machines), baby universes, cold fusion, and more. Now, none of these things is in any way relevant to nor necessary for the advent of the singularity, which requires only well-understood mainstream physics. The speculative topics enter primarily in discussions of the ultimate limits on a post-singularity civilisation and the implications for the destiny of intelligence in the universe. In a way they may distract from the argument, since a reader might be inclined to dismiss the singularity as yet another woolly speculation, which it isn't.
  • Source citations. The end notes contain many citations of articles in Wired, which I consider an entertainment medium rather than a reliable source of technological information. There are also references to articles in Wikipedia, where any idiot can modify anything any time they feel like it. I would not consider any information from these sources reliable unless independently verified from more scholarly publications.
  • “You apes wanna live forever?” Kurzweil doesn't just anticipate the singularity, he hopes to personally experience it, to which end (p. 211) he ingests “250 supplements (pills) a day and … a half-dozen intravenous therapies each week”. Setting aside the shots, just envision two hundred and fifty pills each and every day! That's 1,750 pills a week or, if you're awake sixteen hours a day, an average of more than 15 pills per waking hour, or one pill about every four minutes (one presumes they are swallowed in batches, not spaced out, which would make for a somewhat odd social life). Between the year 2000 and the estimated arrival of human-level artificial intelligence in 2030, he will swallow in excess of two and a half million pills, which makes one wonder what the probability of choking to death on any individual pill might be. He remarks, “Although my program may seem extreme, it is actually conservative—and optimal (based on my current knowledge).” Well, okay, but I'd worry about a “strategy for preventing heart disease [which] is to adopt ten different heart-disease-prevention therapies that attack each of the known risk factors” running into unanticipated interactions, given how everything in biology tends to connect to everything else. There is little discussion of the alternative approach to immortality with which many nanotechnologists of the mambo chicken persuasion are enamoured, which involves severing the heads of recently deceased individuals and freezing them in liquid nitrogen in sure and certain hope of the resurrection unto eternal life.

October 2005 Permalink

Kurzweil, Ray. The Age of Spiritual Machines. New York: Penguin Books, 1999. ISBN 978-0-14-028202-3.
Ray Kurzweil is one of the most vocal advocates of the view that the exponential growth in computing power (and allied technologies such as storage capacity and communication bandwidth) at constant cost which we have experienced for the last half century, notwithstanding a multitude of well-grounded arguments that fundamental physical limits on the underlying substrates will bring it to an end (all of which have proven to be wrong), will continue for the foreseeable future: in all likelihood for the entire twenty-first century. Continued exponential growth in a technology for so long a period is unprecedented in the human experience, and the consequences as the exponential begins to truly “kick in” (although an exponential curve is self-similar, its consequences as perceived by observers whose own criteria for evaluation are more or less constant will be seen to reach a “knee” after which they essentially go vertical and defy prediction). In The Singularity Is Near (October 2005), Kurzweil argues that once the point is reached where computers exceed the capability of the human brain and begin to design their own successors, an almost instantaneous (in terms of human perception) blow-off will occur, with computers rapidly converging on the ultimate physical limits on computation, with capabilities so far beyond those of humans (or even human society as a whole) that attempting to envision their capabilities or intentions is as hopeless as a microorganism's trying to master quantum field theory. You might want to review my notes on 2005's The Singularity Is Near before reading the balance of these comments: they provide context as to the extreme events Kurzweil envisions as occurring in the coming decades, and there are no “spoilers” for the present book.

When assessing the reliability of predictions, it can be enlightening to examine earlier forecasts from the same source, especially if they cover a period of time which has come and gone in the interim. This book, published in 1999 near the very peak of the dot-com bubble provides such an opportunity, and it provides a useful calibration for the plausibility of Kurzweil's more recent speculations on the future of computing and humanity. The author's view of the likely course of the 21st century evolved substantially between this book and Singularity—in particular this book envisions no singularity beyond which the course of events becomes incomprehensible to present-day human intellects. In the present volume, which employs the curious literary device of “trans-temporal chat” between the author, a MOSH (Mostly Original Substrate Human), and a reader, Molly, who reports from various points in the century her personal experiences living through it, we encounter a future which, however foreign, can at least be understood in terms of our own experience.

This view of the human prospect is very odd indeed, and to this reader more disturbing (verging on creepy) than the approach of a technological singularity. What we encounter here are beings, whether augmented humans or software intelligences with no human ancestry whatsoever, that despite having at hand, by the end of the century, mental capacity per individual on the order of 1024 times that of the human brain (and maybe hundreds of orders of magnitude more if quantum computing pans out), still have identities, motivations, and goals which remain comprehensible to humans today. This seems dubious in the extreme to me, and my impression from Singularity is that the author has rethought this as well.

Starting from the publication date of 1999, the book serves up surveys of the scene in that year, 2009, 2019, 2029, and 2099. The chapter describing the state of computing in 2009 makes many specific predictions. The following are those which the author lists in the “Time Line” on pp. 277–278. Many of the predictions in the main text seem to me to be more ambitious than these, but I shall go with those the author chose as most important for the summary. I have reformatted these as a numbered list to make them easier to cite.

  1. A $1,000 personal computer can perform about a trillion calculations per second.
  2. Personal computers with high-resolution visual displays come in a range of sizes, from those small enough to be embedded in clothing and jewelry up to the size of a thin book.
  3. Cables are disappearing. Communication between components uses short-distance wireless technology. High-speed wireless communication provides access to the Web.
  4. The majority of text is created using continuous speech recognition. Also ubiquitous are language user interfaces (LUIs).
  5. Most routine business transactions (purchases, travel, reservations) take place between a human and a virtual personality. Often, the virtual personality includes an animated visual presence that looks like a human face.
  6. Although traditional classroom organization is still common, intelligent courseware has emerged as a common means of learning.
  7. Pocket-sized reading machines for the blind and visually impaired, “listening machines” (speech-to-text conversion) for the deaf, and computer-controlled orthotic devices for paraplegic individuals result in a growing perception that primary disabilities do not necessarily impart handicaps.
  8. Translating telephones (speech-to-speech language translation) are commonly used for many language pairs.
  9. Accelerating returns from the advance of computer technology have resulted in continued economic expansion. Price deflation, which has been a reality in the computer field during the twentieth century, is now occurring outside the computer field. The reason for this is that virtually all economic sectors are deeply affected by the accelerating improvements in the price performance of computing.
  10. Human musicians routinely jam with cybernetic musicians.
  11. Bioengineered treatments for cancer and heart disease have greatly reduced the mortality from these diseases.
  12. The neo-Luddite movement is growing.

I'm not going to score these in detail, as that would be both tedious and an invitation to endless quibbling over particulars, but I think most readers will agree that this picture of computing in 2009 substantially overestimates the actual state of affairs in the decade since 1999. Only item (3) seems to me to be arguably on the way to achievement, and yet I do not have a single wireless peripheral connected to any of my computers and Wi-Fi coverage remains spotty even in 2011. Things get substantially more weird the further out you go, and of course any shortfall in exponential growth lowers the baseline for further extrapolation, shifting subsequent milestones further out.

I find the author's accepting continued exponential growth as dogma rather off-putting. Granted, few people expected the trend we've lived through to continue for so long, but eventually you begin to run into physical constraints which seem to have little wiggle room for cleverness: the finite size of atoms, the electron's charge, and the speed of light. There's nothing wrong with taking unbounded exponential growth as a premise and then exploring what its implications would be, but it seems to me any forecast which is presented as a plausible future needs to spend more time describing how we'll actually get there: arm waving about three-dimensional circuitry, carbon nanotubes, and quantum computing doesn't close the sale for me. The author entirely lost me with note 3 to chapter 12 (p. 342), which concludes:

If engineering at the nanometer scale (nanotechnology) is practical in the year 2032, then engineering at the picometer scale should be practical in about forty years later (because 5.64 = approximately 1,000), or in the year 2072. Engineering at the femtometer (one thousandth of a trillionth of a meter, also referred to as a quadrillionth of a meter) scale should be feasible, therefore, by around the year 2112. Thus I am being a bit conservative to say that femtoengineering is controversial in 2099.

Nanoengineering involves manipulating individual atoms. Picoengineering will involve engineering at the level of subatomic particles (e.g., electrons). Femtoengineering will involve engineering inside a quark. This should not seem particularly startling, as contemporary theories already postulate intricate mechanisms within quarks.

This is just so breathtakingly wrong I am at a loss for where to begin, and it was just as completely wrong when the book was published two decades ago as it is today; nothing relevant to these statements has changed. My guess is that Kurzweil was thinking of “intricate mechanisms” within hadrons and mesons, particles made up of quarks and gluons, and not within quarks themselves, which then and now are believed to be point particles with no internal structure whatsoever and are, in any case, impossible to isolate from the particles they compose. When Richard Feynman envisioned molecular nanotechnology in 1959, he based his argument on the well-understood behaviour of atoms known from chemistry and physics, not a leap of faith based on drawing a straight line on a sheet of semi-log graph paper. I doubt one could find a single current practitioner of subatomic physics equally versed in the subject as was Feynman in atomic physics who would argue that engineering at the level of subatomic particles would be remotely feasible. (For atoms, biology provides an existence proof that complex self-replicating systems of atoms are possible. Despite the multitude of environments in the universe since the big bang, there is precisely zero evidence subatomic particles have ever formed structures more complicated than those we observe today.)

I will not further belabour the arguments in this vintage book. It is an entertaining read and will certainly expand your horizons as to what is possible and introduce you to visions of the future you almost certainly have never contemplated. But for a view of the future which is simultaneously more ambitious and plausible, I recommend The Singularity Is Near.

June 2011 Permalink

Kurzweil, Ray. How to Create a Mind. New York: Penguin Books, 2012. ISBN 978-0-14-312404-7.
We have heard so much about the exponential growth of computing power available at constant cost that we sometimes overlook the fact that this is just one of a number of exponentially compounding technologies which are changing our world at an ever-accelerating pace. Many of these technologies are interrelated: for example, the availability of very fast computers and large storage has contributed to increasingly making biology and medicine information sciences in the era of genomics and proteomics—the cost of sequencing a human genome, since the completion of the Human Genome Project, has fallen faster than the increase of computer power.

Among these seemingly inexorably rising curves have been the spatial and temporal resolution of the tools we use to image and understand the structure of the brain. So rapid has been the progress that most of the detailed understanding of the brain dates from the last decade, and new discoveries are arriving at such a rate that the author had to make substantial revisions to the manuscript of this book upon several occasions after it was already submitted for publication.

The focus here is primarily upon the neocortex, a part of the brain which exists only in mammals and is identified with “higher level thinking”: learning from experience, logic, planning, and, in humans, language and abstract reasoning. The older brain, which mammals share with other species, is discussed in chapter 5, but in mammals it is difficult to separate entirely from the neocortex, because the latter has “infiltrated” the old brain, wiring itself into its sensory and action components, allowing the neocortex to process information and override responses which are automatic in creatures such as reptiles.

Not long ago, it was thought that the brain was a soup of neurons connected in an intricately tangled manner, whose function could not be understood without comprehending the quadrillion connections in the neocortex alone, each with its own weight to promote or inhibit the firing of a neuron. Now, however, it appears, based upon improved technology for observing the structure and operation of the brain, that the fundamental unit in the brain is not the neuron, but a module of around 100 neurons which acts as a pattern recogniser. The internal structure of these modules seems to be wired up from directions from the genome, but the weights of the interconnections within the module are adjusted as the module is trained based upon the inputs presented to it. The individual pattern recognition modules are wired both to pass information on matches to higher level modules, and predictions back down to lower level recognisers. For example, if you've seen the letters “appl” and the next and final letter of the word is a smudge, you'll have no trouble figuring out what the word is. (I'm not suggesting the brain works literally like this, just using this as an example to illustrate hierarchical pattern recognition.)

Another important discovery is that the architecture of these pattern recogniser modules is pretty much the same regardless of where they appear in the neocortex, or what function they perform. In a normal brain, there are distinct portions of the neocortex associated with functions such as speech, vision, complex motion sequencing, etc., and yet the physical structure of these regions is nearly identical: only the weights of the connections within the modules and the dyamically-adapted wiring among them differs. This explains how patients recovering from brain damage can re-purpose one part of the neocortex to take over (within limits) for the portion lost.

Further, the neocortex is not the rat's nest of random connections we recently thought it to be, but is instead hierarchically structured with a topologically three dimensional “bus” of pre-wired interconnections which can be used to make long-distance links between regions.

Now, where this begins to get very interesting is when we contemplate building machines with the capabilities of the human brain. While emulating something at the level of neurons might seem impossibly daunting, if you instead assume the building block of the neocortex is on the order of 300 million more or less identical pattern recognisers wired together at a high level in a regular hierarchical manner, this is something we might be able to think about doing, especially since the brain works almost entirely in parallel, and one thing we've gotten really good at in the last half century is making lots and lots of tiny identical things. The implication of this is that as we continue to delve deeper into the structure of the brain and computing power continues to grow exponentially, there will come a point in the foreseeable future where emulating an entire human neocortex becomes feasible. This will permit building a machine with human-level intelligence without translating the mechanisms of the brain into those comparable to conventional computer programming. The author predicts “this will first take place in 2029 and become routine in the 2030s.”

Assuming the present exponential growth curves continue (and I see no technological reason to believe they will not), the 2020s are going to be a very interesting decade. Just as few people imagined five years ago that self-driving cars were possible, while today most major auto manufacturers have projects underway to bring them to market in the near future, in the 2020s we will see the emergence of computational power which is sufficient to “brute force” many problems which were previously considered intractable. Just as search engines and free encyclopedias have augmented our biological minds, allowing us to answer questions which, a decade ago, would have taken days in the library if we even bothered at all, the 300 million pattern recognisers in our biological brains are on the threshold of having access to billions more in the cloud, trained by interactions with billions of humans and, perhaps eventually, many more artificial intelligences. I am not talking here about implanting direct data links into the brain or uploading human brains to other computational substrates although both of these may happen in time. Instead, imagine just being able to ask a question in natural language and get an answer to it based upon a deep understanding of all of human knowledge. If you think this is crazy, reflect upon how exponential growth works or imagine travelling back in time and giving a demo of Google or Wolfram Alpha to yourself in 1990.

Ray Kurzweil, after pioneering inventions in music synthesis, optical character recognition, text to speech conversion, and speech recognition, is now a director of engineering at Google.

In the Kindle edition, the index cites page numbers in the print edition to which the reader can turn since the electronic edition includes real page numbers. Index items are not, however, directly linked to the text cited.

February 2014 Permalink

Lynn, Richard and Tatu Vanhanen. IQ and the Wealth of Nations. Westport, CT: Praeger, 2002. ISBN 0-275-97510-X.
Kofi Annan, Secretary General of the United Nations, said in April 2000 that intelligence “is one commodity equally distributed among the world's people”. But is this actually the case? Numerous studies of the IQ of the populations of various countries have been performed from the 1930s to the present and with few exceptions, large variations have been found in the mean IQs of countries—more than two standard deviations between the extremes—while different studies of the same population show remarkable consistency, and countries with similar populations in the same region of the world tend to have roughly the same mean IQ. Many social scientists believe that these results are attributable to cultural bias in IQ tests, or argue that IQ tests measure not intelligence, but rather proficiency in taking IQ tests, which various educational systems and environments develop to different degrees. The authors of this book accept the IQ test results at face value and pose the question, “Whatever IQ measures, how accurately does the average IQ of a country's population correlate with its economic success, measured both by per capita income and rate of growth over various historical periods?” From regression studies of 81 countries whose mean population IQ is known and 185 countries where IQ is known or estimated based on neighbouring countries, they find that IQ correlates with economic development better than any other single factor advanced in prior studies. IQ, in conjunction with a market economy and, to a lesser extent, democratic governance “explains” (in the strict sense of the square of the correlation coefficient) more than 50% of the variation in GDP per capita and other measures of economic development (of course, IQ, economic freedom, and democracy may not be independent variables). Now, correlation is not causation, but the evidence that IQ stabilises early in childhood and remains largely constant afterward allows one to rule out many potential kinds of influence by economic development on IQ, strengthening the argument for causation. If this is the case, the consequences for economic assistance are profound. For example, providing adequate nutrition during pregnancy and for children, which is known to substantially increase IQ, may not only be the humanitarian thing to do but could potentially promote economic progress more than traditional forms of development assistance. Estimating IQ and economic development for a large collection of disparate countries is a formidable challenge, and this work contains more correction, normalisation, and adjustment factors than a library full of physics research—close to half the book is data tables and source documentation, and non-expert readers cannot be certain that source data might not have been selected which tend to confirm the hypothesis and others excluded. But this is a hypothesis which can be falsified by further research, which would seem well-warranted. Scientists and policy makers must live in the real world and are ill advised to ignore aspects of it which make them uncomfortable. (If these comments move you to recommend Stephen Jay Gould's The Mismeasure of Man, you needn't—I've read it twice before I started keeping this list, and found it well-argued. But you may also want to weigh the points raised in J. Philippe Rushton's critique of Gould's book.)

March 2004 Permalink

Neisser, Ulric, ed. The Rising Curve: Long-Term Gains in IQ and Related Measures. Washington: American Psychological Association, 1998. ISBN 1-55798-503-0.
One of the most baffling phenomena in the social sciences is the “Flynn Effect”. Political scientist James Flynn was among the first to recognise the magnitude of increasing IQ scores over time and thoroughly document that increase in more than a dozen nations around the world. The size of the effect is nothing less than stunning: on tests of “fluid intelligence” or g (problem-solving ability, as opposed to acquired knowledge, vocabulary, etc.), Flynn's research shows scores rising at least 3 IQ points per decade ever since testing began—as much as one 15 point standard deviation per generation. If you take these figures at face value and believe that IQ measures what we perceive as intelligence in individuals, you arrive at any number of absurdities: our grandparents' generation having a mean IQ of 70 (the threshold of retardation), an expectation that Einstein-level intellect would be 10,000 times more common per capita today than in his birth cohort, and that veteran teachers would perceive sons and daughters of the students they taught at the start of their careers as gifted to the extent of an IQ 115 student compared to a classmate with an IQ of 100. Obviously, none of these are the case, and yet the evidence for Flynn effect is overwhelming—the only reason few outside the psychometric community are aware of it is that makers of IQ tests periodically “re-standardise” their tests (in other words, make them more difficult) in order to keep the mean score at 100. Something is terribly wrong here: either IQ is a bogus measure (as some argue), or it doesn't correlate with real-world intelligence, or some environmental factor is increasing IQ test performance but not potential for achievement or … well, who knows? These are among the many theories advanced to explain this conundrum, most of which are discussed in this volume, a collection of papers by participants in a 1996 conference at Emory University on the evidence for and possible causes of the Flynn effect, and its consequences for long-term trends in human intelligence. My conclusions from these papers are threefold. First, the Flynn effect is real, having been demonstrated as conclusively as almost any phenomenon in the social sciences. Second, nobody has the slightest idea what is going on—theories abound, but available data are insufficient to exclude any of numerous plausible theories. Third, this is because raw data relating to these questions is sparse and poorly suited to answering the questions with which the Flynn effect confronts us. Almost every chapter laments the shortcomings of the data set on which it was based or exhorts “somebody” to collect data better suited to exploring details of the Flynn effect and its possible causes. If human intelligence is indeed increasing by one standard deviation per generation, this is one of the most significant phenomena presently underway on our planet. If IQ scores are increasing at this rate, but intelligence isn't, then there's something very wrong with IQ tests or something terribly pernicious which is negating the effects of the problem-solving capability they claim to measure. Given the extent to which IQ tests (or their close relatives: achievement tests such as the SAT, GRE, etc.) determine the destiny of individuals, if there's something wrong with these tests, it would be best to find out what's wrong sooner rather than later.

July 2004 Permalink

Sarich, Vincent and Frank Miele. Race: The Reality of Human Differences. Boulder, CO: Westview Press, 2004. ISBN 0-8133-4086-1.
This book tackles the puzzle posed by the apparent contradiction between the remarkable genetic homogeneity of humans compared to other species, while physical differences between human races (non-controversial measures such as cranial morphology, height, and body build) actually exceed those between other primate species and subspecies. Vincent Sarich, emeritus Professor of Anthropology at UC Berkeley, pioneer in the development of the “molecular clock”, recounts this scientific adventure and the resulting revolution in the human evolutionary tree and timescale. Miele (editor of Skeptic magazine) and Sarich then argue that the present-day dogma among physical anthropologists and social scientists that “race does not exist”, if taken to its logical conclusion, amounts to rejecting Darwinian evolution, which occurs through variation and selection. Consequently variation among groups is an inevitable consequence, recognised as a matter of course in other species. Throughout, the authors stress that variation of characteristics among individual humans greatly exceeds mean racial variation, which makes racial prejudice and discrimination not only morally abhorrent but stupid from the scientific standpoint. At the same time, small differences in the mean of a set of standard distributions causes large changes in their representation in the aggregate tail representing extremes of performance. This is why one should be neither surprised nor dismayed to find a “disproportionate” number of Kenyans among cross-country running champions, Polynesians in American professional football, or east Asians in mathematical research. A person who comprehends this basic statistical fact should be able to treat individuals on their own merit without denying the reality of differences among sub-populations of the human species. Due to the broad overlap among groups, members of every group, if given the opportunity, will be represented at the highest levels of performance in each field, and no individual should feel deterred nor be excluded from aspiring to such achievement due to group membership. For the argument against the biological reality of race, see the Web site for the United States Public Broadcasting Service documentary, Race: The Power of an Illusion. This book attempts to rebut each of the assertions in that documentary.

June 2004 Permalink

Young, Michael. The Rise of the Meritocracy. New Brunswick, NJ: Transaction Publishers, [1958] 1994. ISBN 1-56000-704-4.
The word “meritocracy” has become so commonplace in discussions of modern competitive organisations and societies that you may be surprised to learn the word did not exist before 1958—a year after Sputnik—when the publication of this most curious book introduced the word and concept into the English language. This is one of the oddest works of serious social commentary ever written—so odd, in fact, its author despaired of its ever seeing print after the manuscript was rejected by eleven publishers before finally appearing, whereupon it was quickly republished by Penguin and has been in print ever since, selling hundreds of thousands of copies and being translated into seven different languages.

Even though the author was a quintessential “policy wonk”: he wrote the first postwar manifesto for the British Labour Party, founded the Open University and the Consumer Association, and sat in the House of Lords as Lord Young of Dartington, this is a work of…what shall we call it…utopia? dystopia? future history? alternative history? satire? ironic social commentary? science fiction?…beats me. It has also perplexed many others, including one of the publishers who rejected it on the grounds that “they never published Ph.D. theses” without having observed that the book is cast as a thesis written in the year 2034! Young's dry irony and understated humour has gone right past many readers, especially those unacquainted with English satire, moving them to outrage, as if George Orwell were thought to be advocating Big Brother. (I am well attuned to this phenomenon, having experienced it myself with the Unicard and Digital Imprimatur papers; no matter how obvious you make the irony, somebody, usually in what passes for universities these days, will take it seriously and explode in rage and vituperation.)

The meritocracy of this book is nothing like what politicians and business leaders mean when they parrot the word today (one hopes, anyway)! In the future envisioned here, psychology and the social sciences advance to the point that it becomes possible to determine the IQ of individuals at a young age, and that this IQ, combined with motivation and effort of the person, is an almost perfect predictor of their potential achievement in intellectual work. Given this, Britain is seen evolving from a class system based on heredity and inherited wealth to a caste system sorted by intelligence, with the high-intelligence élite “streamed” through special state schools with their peers, while the lesser endowed are directed toward manual labour, and the sorry side of the bell curve find employment as personal servants to the élite, sparing their precious time for the life of the mind and the leisure and recreation it requires.

And yet the meritocracy is a thoroughly socialist society: the crème de la crème become the wise civil servants who direct the deployment of scarce human and financial capital to the needs of the nation in a highly-competitive global environment. Inheritance of wealth has been completely abolished, existing accumulations of wealth confiscated by “capital levies”, and all salaries made equal (although the élite, naturally, benefit from a wide variety of employer-provided perquisites—so is it always, even in merito-egalitopias). The benevolent state provides special schools for the intelligent progeny of working class parents, to rescue them from the intellectual damage their dull families might do, and prepare them for their shining destiny, while at the same time it provides sports, recreation, and entertainment to amuse the mentally modest masses when they finish their daily (yet satisfying, to dullards such as they) toil.

Young's meritocracy is a society where equality of opportunity has completely triumphed: test scores trump breeding, money, connections, seniority, ethnicity, accent, religion, and all of the other ways in which earlier societies sorted people into classes. The result, inevitably, is drastic inequality of results—but, hey, everybody gets paid the same, so it's cool, right? Well, for a while anyway…. As anybody who isn't afraid to look at the data knows perfectly well, there is a strong hereditary component to intelligence. Sorting people into social classes by intelligence will, over the generations, cause the mean intelligence of the largely non-interbreeding classes to drift apart (although there will be regression to the mean among outliers on each side, mobility among the classes due to individual variation will preserve or widen the gap). After a few generations this will result, despite perfect social mobility in theory, in a segregated caste system almost as rigid as that of England at the apogee of aristocracy. Just because “the masses” actually are benighted in this society doesn't mean they can't cause a lot of trouble, especially if incited by rabble-rousing bored women from the élite class. (I warned you this book will enrage those who don't see the irony.) Toward the end of the book, this conflict is building toward a crisis. Anybody who can guess the ending ought to be writing satirical future history themselves.

Actually, I wonder how many of those who missed the satire didn't actually finish the book or simply judged it by the title. It is difficult to read a passage like this one on p. 134 and mistake it for anything else.

Contrast the present — think how different was a meeting in the 2020s of the National Joint Council, which has been retained for form's sake. On the one side sit the I.Q.s of 140, on the other the I.Q.s of 99. On the one side the intellectual magnates of our day, on the other honest, horny-handed workmen more at home with dusters than documents. On the one side the solid confidence born of hard-won achievement; on the other the consciousness of a just inferiority.
Seriously, anybody who doesn't see the satire in this must be none too Swift. Although the book is cast as a retrospective from 2038, and there passing references to atomic stations, home entertainment centres, school trips to the Moon and the like, technologically the world seems very much like that of 1950s. There is one truly frightening innovation, however. On p. 110, discussing the shrinking job market for shop attendants, we're told, “The large shop with its more economical use of staff had supplanted many smaller ones, the speedy spread of self-service in something like its modern form had reduced the number of assistants needed, and piped distribution of milk, tea, and beer was extending rapidly.” To anybody with personal experience with British plumbing and English beer, the mere thought of the latter being delivered through the former is enough to induce dystopic shivers of 1984 magnitude.

Looking backward from almost fifty years on, this book can be read as an alternative history of the last half-century. In the eyes of many with a libertarian or conservative inclination, just when the centuries-long battle against privilege and prejudice was finally being won: in the 1950s and early 60s when Young's book appeared, the dream of equal opportunity so eloquently embodied in Dr. Martin Luther King's “I Have a Dream” speech began to evaporate in favour of equality of results (by forced levelling and dumbing down if that's what it took), group identity and entitlements, and the creation of a permanently dependent underclass from which escape was virtually impossible. The best works of alternative history are those which change just one thing in the past and then let the ripples spread outward over the years. You can read this story as a possible future in which equal opportunity really did completely triumph over egalitarianism in the sixties. For those who assume that would have been an unqualifiedly good thing, here is a cautionary tale well worth some serious reflexion.

January 2006 Permalink