ARE WE SPIRITUAL MACHINES? | Chapter 5: Kurzweil’s Turing Fallacy

June 7, 2001
Author:
Thomas Ray
Publisher:
Discovery Institute (2001)

There are numerous directions from which to criticize Kurzweil’s proposal for strong AI. In this essay I will focus on his failure to consider the unique nature of the digital medium when discussing artificial intelligence. But before elaborating on this point, I would like briefly to call attention to some other issues.

Psychic Quantum Mechanics

Kurzweil’s interpretation of quantum mechanics leads him to the conclusion that “consciousness, matter, and energy are inextricably linked.” While this is true in the sense that consciousness arises from the interactions of matter and energy, it is not true in the sense that Kurzweil intends it: that quantum ambiguities are not resolved until they are forced to do so by a conscious observer.

Kurzweil’s error is most glaringly apparent in his description of the paper output from a quantum computer: “So the page with the answer is ambiguous, undetermined—until and unless a conscious entity looks at it. Then instantly all the ambiguity is retroactively resolved, and the answer is there on the page. The implication is that the answer is not there until we look at it.” He makes the same error in describing the evolution of the universe: “From one perspective of quantum mechanics—we could say that any Universe that fails to evolve conscious life to apprehend its existence never existed in the first place.”

Kurzweil does not understand that it is the act of measurement that causes the collapse of the wave function, not conscious observation of the measurement. In practice, the collapse is (probably always) caused by a completely unconscious measuring device. Printing of the result on a paper could be such a measuring device. Subsequent conscious observation of the measurement is irrelevant.

This psychic quantum mechanics did not originate with Kurzweil. It has been around for decades, apparently as a way to deal with Schrödinger’s cat. Thus, Kurzweil may be able to point to physicists who hold this view. Similarly, I could point to biologists who believe in the biblical story of creation rather than evolution. The existence of experts who believe a doctrine, however, is no argument for the truth of the doctrine.

Colloquial Chaos

Kurzweil’s suggestion that in a process, the time interval between salient events expands or contracts along with the amount of chaos (“the law of time and chaos”), is quite interesting. Yet, the definitions of “salient events” and “chaos” are quite subjective, making the “law” difficult to support. Technically, it would probably be more appropriate to use the word “entropy” in place of “chaos,” but for consistency, I will also use “chaos” in this discussion.

Most striking is the apparently inconsistent use of chaos. He states that in an evolutionary process order increases, and he says: “Evolution draws upon the chaos in the larger system in which it takes place for its options for diversity.” Yet he states that in the development of an individual organism chaos increases, and he says: “The development of an organism from conception as a single cell through maturation is a process moving toward greater diversity and thus greater disorder.” Kurzweil suggests that in evolution, diversity implies order, while in development, diversity implies disorder.

Through evolution, the diversity of species on Earth has increased, and through development, the diversity of cell types increases. I would characterize both as processes that generate order. Why does Kurzweil think that development generates chaos? His apparent reason is to make his law of time and chaos consistent with our perception of time: Our subjective unit of time grows with our age.

I believe that the scientific community would generally agree that the developmental process up to the period of reproduction is a process of increasing order. In humans, who live well beyond their reproductive years, the condition of the body begins to deteriorate after the reproductive years, and this senescence would generally be considered a process of increasing chaos.

In an effort to fit development seamlessly into his law of time and chaos, Kurzweil presents the whole life cycle from conception to death, as unidirectional, towards increasing chaos. This position is indefensible. The developmental process directly contradicts the law of time and chaos. Development is a process in which the time between salient events increases with order.

He attempts to be clear and concrete in his use of the term chaos: “If we’re dealing with the process of evolution of life-forms, then chaos represents the unpredictable events encountered by organisms, and the random mutations that are introduced in the genetic code.” He explains: “Evolution draws upon the great chaos in its midst—the ever increasing entropy governed by the flip side of the Law of Time and Chaos—for its options for innovation.” This implies that unpredictable events and mutations are becoming more frequent, a position that would be difficult to defend. His argument is that increasing rates of mutations and unpredictable events are, in part, driving the increasing frequency of “salient events” in evolution. He does not provide any support for this highly questionable argument.

Despite his attempt to be precise, his use of “chaos” is vernacular: “When the entire Universe was just a ‘naked’ singularity . . . there was no chaos.” “As the Universe grew in size, chaos increased exponentially.” “Now with billions of galaxies sprawled out over trillions of light-years of space, the Universe contains vast reaches of chaos . . .” “We start out as a single fertilized cell, so there’s only rather limited chaos there. Ending up with trillions of cells, chaos greatly expands.” It seems that he associates chaos with size, a very unconventional use of the term.

His completely false interpretation of quantum mechanics, his vague and inconsistent use of terms such as “chaos” and “salient events,” and his failure to understand the thermodynamics of development represent errors in the basic science from which he constructs his view of the world. These misunderstandings of basic science seriously undermine the credibility of his arguments.

I am not comfortable with the equation of technological development and evolution. I think that most evolutionary biologists would consider these to be quite separate processes, yet, their equation represents a point of view consistent with Kurzweil’s arguments and also consistent with the concept of “meme” developed by the evolutionary biologist Richard Dawkins.

Intelligence in the Digital Medium

The primary criticism that I wish to make of Kurzweil’s book, however, is that he proposes to create intelligent machines by copying human brains into computers. We might call this the Turing Fallacy. The Turing Test suggests that we can know that machines have become intelligent when we cannot distinguish them from human, in free conversation over a teletype. The Turing Test is one of the biggest red-herrings in science.

It reminds me of early cinema when we set a camera in front of a stage and filmed a play. Because the cinema medium was new, we really didn’t understand what it is and what we can do with it. At that point we completely misunderstood the nature of the medium of cinema. We are in almost the same position today with respect to the digital medium.

Over and over again, in a variety of ways, we are shaping cyberspace in the form of the 3D material space that we inhabit. But cyberspace is not a material space and it is not inherently 3D. The idea of downloading the human mind into a computer is yet another example of failing to understand and work with the properties of the medium. Let me give some other examples and then come back to this.

I have heard it said that cyberspace is a place for the mind, yet we feel compelled to take our bodies with us. 3D virtual worlds and avatars are manifestations of this. I have seen virtual worlds where you walk down streets lined by buildings. In one I saw a Tower Records store, whose front looked like the real thing. You approached the door, opened it, entered, and saw rows of CDs on racks and an escalator to take you to the next floor. Just Like The Real Thing!

I saw a demo of Alpha World, built by hundreds of thousands of mostly teenagers. It was the day after Princess Diana died, and there were many memorials to her, bouquets of flowers by fountains, photos of Diana with messages. It looked Just Like The Real memorials to Diana.

I wondered, why do these worlds look and function as much as possible like the real thing? This is cyberspace, where we can do anything. We can move from point A to point B instantly without passing through the space in between. So why are we forcing ourselves to walk down streets and halls and to open doors?

Cyberspace is not a 3D Euclidean space. It is not a material world. We are not constrained by the same laws of physics, unless we impose them upon ourselves. We need to liberate our minds from what we are familiar with before we can use the full potential of cyberspace. Why should we compute collision avoidance for avatars in virtual worlds when we have the alternative to find out how many avatars can dance on the head of a pin?

The WWW is a good counter-example, because it recognizes that in cyberspace it doesn’t matter where something is physically located. Amazon.com is a good alternative to the mindlessly familiar 3D Tower Record store.

Let me come back to Kurzweil’s ideas on AI. Kurzweil states that it is “ultimately feasible” to:

. . . scan someone’s brain to map the locations, interconnections, and contents of the somas, axons, dendrites, presynaptic vesicles, and other neural components. Its entire organization could then be re-created on a neural computer of sufficient capacity, including the contents of its memory . . . we need only to literally copy it, connection by connection, synapse by synapse, neurotransmitter by neurotransmitter.

This passage most clearly illustrates Kurzweil’s version of the Turing Fallacy. It is not only infeasible to “copy” a complex organic organ into silicon without losing its function, but it is the least imaginative approach to creating an AI. How do we copy a seratonin molecule or a presynaptic vesicle into silicon? This passage of the book does not explicitly state whether he is proposing a software simulation from the molecular level up, of a copy of the brain, or if he is proposing the construction of actual silicon neurons, vesicles, neurotransmitters, and their wiring together into an exact copy of a particular brain. Yet in the context of the preceding discussion, it appears that he is proposing the latter.

Such a proposal is doomed to failure. It would be a fantastic task to map the entire physical, chemical, and dynamic structure of a brain. Even if this could be accomplished, there would be no method for building a copy. There is no known technology for building complexly differentiated microscopic structures on such a large scale. If a re-construction method existed, we might expect that a copy made of the same materials, carbon chemistry, if somehow jump-started into the proper dynamic activity, would have the same function (though such a copied brain would require a body to support it). But a copy made of metallic materials could not possibly have the same function. It would be a fantastically complex and intricate dynamic sculpture, whose function would bear no relation to a human brain. And what of the body and its essential sensory integration with the brain?

In order for the metallic “copy” to have the same function, we would have to abstract the functional properties out of the organic neural elements, and find structures and processes in the new metallic medium that provide identical functions. This abstraction and functional-structural translation from the organic into the metallic medium would require a deep understanding of the natural neural processes, combined with the invention of many computing devices and processes which do not yet exist.

However, Kurzweil has stated that one advantage of the brain-copy approach is that “we don’t need to understand all of it; we need only to literally copy it.” Yet he is ambivalent on this critical point, adding: “To do this right, we do need to understand what the salient information-processing mechanisms are. Much of a neuron’s elaborate structure exists to support its own structural integrity and life processes and does not directly contribute to its handling of information.”

The structure and function of the brain or its components cannot be separated. The circulatory system provides life support for the brain, but it also delivers hormones that are an integral part of the chemical information processing function of the brain. The membrane of a neuron is a structural feature defining the limits and integrity of a neuron, but it is also the surface along which depolarization propagates signals. The structural and life-support functions cannot be separated from the handling of information.

The brain is a chemical organ, with a broad spectrum of chemical communication mechanisms ranging from microscopic packets of neurotransmitters precisely delivered at target synapses, to nitrogen oxide gas and hormones spread through the circulatory system or diffusing through the intercellular medium of the brain. There also exist a wide range of chemical communications systems with intermediate degrees of specificity of delivery. The brain has evolved its exquisitely subtle and complex functionality based on the properties of these chemical systems. A metallic computation system operates on fundamentally different dynamic properties and could never precisely and exactly “copy” the function of a brain.

The materials of which computers are constructed have fundamentally different physical, chemical, and electrical properties than the materials from which the brain is constructed. It is impossible to create a “copy” of an organic brain out of the materials of computation. This applies not only to the proposition of copying an individual human brain with such accuracy as to replicate a human mind along with its memories, but also to the somewhat less extreme proposition of creating an artificial intelligence by reverse engineering the human brain.

Structures and processes suitable for information processing in the organic medium are fundamentally different from those of the metallic computational medium. Intelligent information processing in the computational medium must be based on fundamentally different structures and processes, and thus cannot be copied from organic brains.

I see three separate processes which are sometimes confounded. Machines having:

1) computing power equal to the level of human intelligence

2) computing performance equal to the level of human intelligence

3) computing like human intelligence

A large portion of Kurzweil’s book establishes the first process by extrapolating Moore’s Law into the future until individual machines can perform the same number of computations per second as is estimated for the human brain (~2020 A.D.).

I accept that this level of computing power is likely to be reached, someday. But no amount of raw computer power will be intelligent in the relevant sense unless it is properly organized. This is a software problem, not a hardware problem. The organizational complexity of software does not march forward according to Moore’s Law.

While I can accept that computing power will inevitably reach human levels, I am not confident that computing performance will certainly follow. The exponential increase of computing power is driven by higher densities and greater numbers of components on chips, not by exponentially more complex chip designs.

The most complex of artifacts designed and built by humans are much less complex that living organisms. Yet the most complex of our creations are showing alarming failure rates. Orbiting satellites and telescopes, space shuttles, interplanetary probes, the Pentium chip, computer operating systems, all seem to be pushing the limits of what we can effectively design and build through conventional approaches.

It is not certain that our most complex artifacts will be able to increase in complexity by an additional one, two or more orders of magnitude, in pace with computing power. Our most complex software (operating systems and telecommunications control systems) already contains tens of millions of lines of code. At present it seems unlikely that we can produce and manage software with hundreds of millions or billions of lines of code. In fact there is no evidence that we will ever be able to design and build intelligent software.

This leads to the next distinction, which is central to my argument, and requires some explanation:

2) computing performance equal to the level of human intelligence

3) computing like human intelligence

A machine might exhibit an intelligence identical to and indistinguishable from humans, a Turing AI, or a machine might exhibit a fundamentally different kind of intelligence, like some science fiction alien intelligence. I expect that intelligences which emerge from the digital and organic media will be as different as their respective media, even if they have comparable computing performance.

Everything we know about life is based on one example of life, namely, life on earth. Everything we know about intelligence is based on one example of intelligence, namely, human intelligence. This limited experience burdens us with preconceptions and limits our imaginations.

Consider this thought experiment:

We are all robots. Our bodies are made of metal and our brains of silicon chips. We have no experience or knowledge of carbon-based life, not even in our science fiction. Now one of us robots comes to an AI discussion with a flask of methane, ammonia, hydrogen, water, and some dissolved minerals. The robot asks: “Do you suppose we could build a computer from this stuff?”

The engineers among us might propose nano-molecular devices with fullerene switches, or even DNA-like computers. But I am sure they would never think of neurons. Neurons are astronomically large structures compared to the molecules we are starting with.

Faced with the raw medium of carbon chemistry, and no knowledge of organic life, we would never think of brains built of neurons, supported by circulatory and digestive systems, in bodies with limbs for mobility, bodies which can only exist in the context of the ecological community that feeds them.

We are in a similar position today as we face the raw medium of digital computation and communications. The preconceptions and limited imagination deriving from our organic-only experience of life and intelligence make it difficult for us to understand the nature of this new medium, and the forms of life and intelligence that might inhabit it.

How can we go beyond our conceptual limits, find the natural form of intelligent processes in the digital medium, and work with the medium to bring it to its full capacity, rather than just imposing the world we know upon it by forcing it to run a simulation of our physics, chemistry, and biology?

In the carbon medium it was evolution that explored the possibilities inherent in the medium, and created the human mind. Evolution listens to the technology that it is embedded in. It has the advantage of being mindless, and therefore devoid of preconceptions, and not limited by imagination.

I propose the creation of a digital nature. A system of wildlife reserves in cyberspace, in the interstices between human colonizations, feeding off of unused CPU-cycles (and permitted a share of our bandwidth). This would be a place where evolution can spontaneously generate complex information processes, free of the demands of human engineers and market analysts telling it what the target applications are.

Digital naturalists can then explore this cyber-nature in search of applications for the products of digital evolution in the same way that our ancestors found applications among the products of organic nature such as: rice, wheat, corn, chickens, cows, pharmaceuticals, silk, mahogany. But, of course, the applications that we might find in the living digital world would not be material; they would be information processes.

It is possible that out of this digital nature there might emerge a digital intelligence, truly rooted in the nature of the medium, rather than brutishly copied and downloaded from organic nature. It would be a fundamentally alien intelligence, but one which would complement rather than duplicate our talents and abilities.

I think it would be fair to say that the main point of Kurzweil’s book is that artificial entities with intelligence equal to and greater than humans will inevitably arise, in the near future. While his detailed explanation of how this might happen focuses on what I consider to be the Turing Fallacy, that is, that it will initially take a human form, Kurzweil would probably be content with any route to these higher intelligences, Turing or non-Turing.

While I feel that AIs must certainly be non-Turing—unlike human intelligences—I feel ambivalent about whether they will emerge at all. It is not the certainty that Kurzweil paints, like the inexorable march of Moore’s Law. Raw computing power is not intelligence. Our ability ever to create information processes of a complexity comparable to the human mind is completely unproven and absolutely uncertain.

I have suggested evolution as an alternate approach to producing intelligent information processes. These evolved AIs would certainly be non-Turing AIs. Yet evolution in the digital medium remains a process with a very limited record of accomplishments. We have been able to establish active evolutionary processes, by both natural and artificial selection in the digital medium. But the evolving entities have always contained at most several thousand bits of genetic information.

We do not yet have a measure on the potential of evolution in this medium. If we were to realize a potential within several orders of magnitude of that of organic evolution, it would be a spectacular success. But if the potential of digital evolution falls ten orders of magnitude below organic evolution, then digital evolution will lose its luster. There is as yet no evidence to suggest which outcome is more likely.

The hope for evolution as a route to AI is not only that it would produce an intelligence rooted in and natural to the medium, but that evolution in the digital medium is capable of generating levels of complexity comparable to what it has produced in the organic medium. Evolution is the only process that is proven to be able to generate such levels of complexity. That proof, however, is in the organic rather than the digital medium. Like an artist who can express his creativity in oil paint but not stone sculpture, evolution may be capable of magnificent creations in the organic medium but not the digital.

Yet the vision of the digital evolution of vast complexity is still out there, waiting for realization or disproof. It should encourage us, although we are at the most rudimentary level of our experience with evolution in the digital medium. Nevertheless, the possibilities are great enough to merit a serious and sustained effort.

Copyright © 2002 by the Discovery Institute. Used with permission.