Ray Kurzweil is, by all accounts, a genius. He holds nineteen honorary doctorates, has founded a half-dozen successful companies, and was a major contributor to the field of artificial intelligence. He built some of the first practical systems for recognizing speech and scanning text. Time magazine recently featured Kurzweil on its cover, and Fortune described him as “a legendary inventor with a history of mind-blowing ideas.” And now he has a new book, with a subtitle that suggests he has found another such idea: “How to Create a Mind: The Secret of Human Thought Revealed.”
In the preface to the book Kurzweil argues, with good reason, that “reverse-engineering the human brain may be regarded as the most important project in the universe.” He then presents a theory he calls “the pattern recognition theory of mind (PRTM)” which he claims “describes the basic algorithm of the neocortex (the region of the brain responsible for perception, memory, and critical thinking).” Kurzweil suggests that his conclusions are “inescapable” and that the principles he espouses can be used “to vastly extend the power of our own intelligence.”
That would be big news. But does the book deliver? Kurzweil’s critics have not always been kind; the biologist PZ Myers once wrote, “Ray Kurzweil is a genius. One of the greatest hucksters of the age.” Doug Hofstadter, the Pulitzer Prize winning author of “Gödel, Escher, Bach” has been even harsher, saying once in an interview that “if you read Ray Kurzweil’s books … what I find is that it’s a very bizarre mixture of ideas that are solid and good with ideas that are crazy. It’s as if you took a lot of very good food and some dog excrement and blended it all up so that you can’t possibly figure out what’s good or bad.”
Which Kurzweil shows up to explain the mind? The brilliant inventor and autodidact or the man who has written one book on diets and another on immortality?
Kurzweil is at his best when explaining how machines work. There is a lucid discussion of the discoveries of the early computer pioneers Alan Turing and John von Neumann, clear explanations of several complex computer algorithms, and generous insights into the history of his own companies.
More dubious, however, is a chapter called “Transcendent Abilities,” which is a lyrical but scientifically empty chapter on love, creativity, and poetry. Kurzweil offers vague gestures toward an unusual kind of neuron called spindle cells, which he suggests are involved in “handling emotion and moral judgment,” but offers no references and very little direct evidence.
Fortunately, spindle cells, however, are only a tiny part of the narrative, introduced, perhaps, as a sop to Kurzweil’s new-agey readers (who read about them before, in language that is almost word-for-word the same, in his 2005 book, “The Singularity is Near”). In short order, Kurzweil returns to the business of explicating and defending his main thesis—according to which the part of the brain that is most associated with reasoning and conscious thought, the neocortex, is seen as a hierarchical set of pattern-recognition devices, in which complex entities are recognized as a statistical function of their constituent parts.
Kurzweil illustrates this thesis in the context of a system for reading words. At the lowest level, a set of pattern recognizers search for properties like horizontal lines, diagonal lines, curves, and so forth; at the next level up, a set of pattern recognizers hunt for letters (A, B, C, and so forth) that are built out of conjunctions of lines and curves; and at still a higher level, individual pattern recognizers look for particular words (like APPLE, PEAR, and so on that are built out of conjunctions of letters).
The acronym P.R.T.M., for Pattern Recognition Theory of Mind, is new, but to scientists in the field, the basic idea is significantly less new than Kurzweil’s subtitle (“The Secret of Human Thought Revealed”) lets on. Anyone who knows the history of A.I. will recognize that the basic theory (and even the diagrams that are used to illustrate it) is very much in the spirit of a textbook model of vision that was introduced in 1980, known as neocognitron. As Kurzweil fleshes it out, the P.R.T.M. is even more like the Hierarchical Temporary Memory system proposed several years ago by his fellow entrepreneur Jeff Hawkins (who founded PalmPilot). Kurzweil’s weak efforts at differentiating his theory from Hawkins’s—“the most important difference is the set of parameters that I have included for each input … especially the size and size variability parameters”—are likely to convince no one.
Even more disappointing is the fact that Kurzweil never bothers to do what any scientist, especially one trained in computer science, would immediately want to do, which is to build a computer model that instantiated his theory, and then compare the predictions of the model with real human behavior. Does the P.R.T.M. predict anything about human behavior that no other theory has predicted before? Does it give novel insight into any long-standing puzzles in human nature? Kurzweil never tries to find out.
Instead, Kurzweil compares his theory with the physical structure of the brain, hurling a huge amount of neuroanatomy at the reader, and asserting, without a lot of reflection, that it all fits his theory. A recent paper (more controversial than Kurzweil may have realized) claims that the brain is neatly organized into a kind of three-dimensional grid system. Kurzweil happily takes this as evidence that he was right all along, but the fact that the brain is organized doesn’t mean it is organized as Kurzweil suggests. We already knew that the brain is structured, but the real question is what all that structure does, in technical terms. How do the neural mechanisms in the brain map onto the brain’s cognitive mechanisms? Without an understanding of that, Kurzweil’s pointers to neuroanatomy serve more as razzle-dazzle than real evidence for his theory.
The deepest problem is that Kurzweil wants badly to provide a theory of the mind and not just the brain. Of course, the mind is a product of the brain, as Kurzweil well knows, but any theory that seriously engages with what the mind is has to reckon with human psychology—with human behavior and the mental operations that underlie it. Here, Kurzweil seems completely out of his depth. The main place where the book discusses psychology is a chapter called “Thought Experiments on Thinking,” a scant nine pages devoted to “thought experiments” that Kurzweil seems to have performed while sitting in his arm chair. Not a single cognitive psychologist or study is referred to, and he scarcely engages the phenomena that make the human mind so distinctive. There’s no mention, for example, of Daniel Kahneman’s Nobel Prize winning work on human irrationality, Chomsky’s arguments about innate knowledge that sparked the cognitive revolution, or Elizabeth Spelke’s work on cognitive development demonstrating the highly nuanced structure that is present within the mind even from an extremely early age. Similarly absent is any reference to the vast literature on anthropology, and what is and isn’t culturally universal.
At the end Kurzweil leaves us with a theory that is generic. Almost anything any creature does could at some level be seen as hierarchical-pattern recognition; that’s why the idea has been around since the late nineteen-fifties. But simply asserting that the mind is a hierarchical-pattern recognizer by itself tells us too little: it doesn’t say why human beings are the sort of creatures that use language (rodents presumably have a capacity for hierarchical-pattern recognition, too, but don’t talk), and it doesn’t explain why many humans struggle constantly with issues of self-control, nor why we are the sort of creatures who leave tips in restaurants in towns to which we will never return.
Kurzweil is so confident in his theory that he insists it simply has to be correct. Early in the book, he claims that “the model I have presented is the only possible model that satisfies all the constraints that the research and our thought experiments have established.” He later declares that “there must be an essential mathematical equivalence to a high degree of precision between the actual biology and our attempt to emulate it; otherwise these [A.I.] systems would not work as well as they do.”
What Kurzweil doesn’t seem to realize is that a whole slew of machines have been programmed to be hierarchical-pattern recognizers, and none of them works all that well, save for very narrow domains like postal computers that recognize digits in handwritten zip codes. This summer, Google built the largest pattern recognizer of them all, a system running on sixteen thousand processor cores that analyzed ten million YouTube videos and managed to learn, all by itself, to recognize cats and faces—which initially sounds impressive, but only until you realize that in a larger sample (of twenty thousand categories), the system’s overall score fell to a dismal 15.8 per cent.
The real lesson from Google’s “cat detector” is that, even with the vast expanses of data and computing power available to Google, hierarchical-pattern recognizers still stink. They cannot come close to actually understanding natural language, or anything else for which complex inference is required. The world’s most impressive A.I. system, Watson (the I.B.M. system that beat the world’s best humans on “Jeopardy”) does some statistical analysis in a fashion that is reminiscent of Kurzweil’s proposal. But it supplements that with a vast array of other systems, many of which work on entirely different principles (derived from symbolic logic). The kind of one-size-fits-all principle of hierarchical-pattern learning that Kurzweil advocates doesn’t work on its own in artificial intelligence, and it doesn’t provide an adequate explanation of the brain, either.
At the beginning of the book, Kurzweil promises to reverse engineer the human brain in hopes of using the brain’s secrets to advance artificial intelligence, but what he’s really done is the opposite: reverse engineer his own companies’ computer systems in order to propose a theory about how the mind works.
Ultimately Kurzweil is humbled by a challenge that has beset many a great thinker extending far beyond his field—Kurzweil doesn’t know neuroscience as well as he knows artificial intelligence, and doesn’t understand psychology as well as either. (And for that matter he doesn’t know contemporary A.I. as well as the A.I. of his heyday, when he was running his companies thirty years ago.)
To truly reverse-engineer the human mind, we may need a real consilience, to borrow a word from the Harvard biologist E. O. Wilson, a coming together of workers in A.I. with researchers who study the human mind from a wide range of perspectives—neuroscientists and cognitive psychologists, and maybe even artists, musicians, and writers, too. The challenge of figuring out how the mind works is too complicated for even the smartest of entrepreneurs to solve on their own.
Gary Marcus, a professor of psychology at N.Y.U., is the author of “Guitar Zero: The Science of Becoming Musical at Any Age” and “Kluge: The Haphazard Evolution of the Human Mind.”
Photograph by Kaushik Roy/India Today Group/Getty.