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In principle, Kurzweil is correct: we have as yet no positive proof that his vision is impossible. But it must be acknowledged that the project he describes is entirely different from the original task of strong AI to replicate the mind on a digital computer. When the task shifts from dealing with the stuff of minds and computers to the stuff of brains and matter — and when the instruments used to achieve AI are thus altogether different from those of the digital computer — then all of the work undertaken thus far to make a computer into a mind will have had no relevance to the task of AI other than to disprove its own methods. The fact that the mind is a machine just as much as anything else in the universe is a machine tells us nothing interesting about the mind. If the strong AI project is to be redefined as the task of duplicating the mind at a very low level, it may indeed prove possible — but the result will be something far short of the original goal of AI.

That the neuron even has such a specification is hardly a foregone conclusion. It has been shown that mental processes are strongly affected by anatomical changes in the brain: a person’s brain structure and chemical composition change over the course of his lifetime, chemical imbalances and disorders of the neurons can cause mental disorders, and so on. The persistence of the mind despite the replacement of the particles of the brain clearly indicates some causal autonomy at the high level of the mind, but the fact that the mind is affected by structural changes in the brain also indicates some causal autonomy at the low level of the brain. So while transhumanists may join Ray Kurzweil in arguing that “we should not associate our fundamental identity with a specific set of particles, but rather the pattern of matter and energy that we represent,” we must remember that this supposed separation of particles and pattern is false: Every indication is that, rather than a neatly separable hierarchy like a computer, the mind is a tangled hierarchy of organization and causation. Changes in the mind cause changes in the brain, and vice versa. To successfully replicate the brain in order to simulate the mind, it will be necessary to replicate every level of the brain that affects and is affected by the mind.

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More importantly, a description at a lower level may be practically impossible to translate back into an original higher-level description. Returning again to our sorting example, suppose now that a friend hires you to do some task that his boss asked him to perform. All he gives you is a list of instructions, each of which is about as simple as “decide if these two numbers are equal.” When you follow these instructions, you will perform the task exactly as your friend has specified, but you may have no idea what task you are performing beyond comparing lots of numbers. Even if you are able to figure out that, say, you are also doing some kind of sort, it could be impossible to know whether you are sorting books rather than addresses or names. The steps you execute still clearly embody the higher-level concepts designed by your friend and intended by his boss, but simply ­knowing those steps may not be sufficient to allow you to deduce those original concepts. In the computer, then, a low-level description of a program does provide a causally closed description of its behavior, but it obscures the higher-level concepts originally used to create the program. One may very likely, then, be unable to deduce the intended purpose and design of a program, or its internal structure, simply from its lower-level behavior.

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ince the inception of the AI project, the use of computer analogies to try to describe, understand, and replicate mental processes has led to their widespread abuse. Typically, an exponent of AI will not just use a computer metaphor to describe the mind, but will also assert that such a description is a sufficient understanding of the mind — indeed, that mental processes can be understood entirely in computational terms. One of the most pervasive abuses has been the purely functional description of mental processes. In the black box view of programming, the internal processes that give rise to a behavior are irrelevant; only a full knowledge of the input-output behavior is necessary to completely understand a module. Because humans have “input” in the form of the senses, and “output” in the form of speech and actions, it has become an AI creed that a convincing mimicry of human input-output behavior amounts to actually achieving true human qualities in computers.

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