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The Brain is not a Computer.

How often do you hear someone say that the brain is a computer?  This statement is not literally true. The brain is certainly not like a desktop computer. Brains don’t look like computers; there’s no CPU in the head.  Neurons aren’t all wired together to an executive control center.  Human brains have a massively parallel architecture. Cognitive scientists who have carefully thought through this issue arrive at this same conclusion:  the brain does not really resemble a computer, certainly not any sort of computer in general use today.

The brain as computer is a seductive metaphor. According to Edwin Hutchins, “The last 30 years of cognitive science can be seen as attempts to remake the person in the image of the computer.” See Cognition in the Wild (1996).

Metaphors are models, however, and models are imperfect versions of the reality they portray.  Metaphors accentuate certain parts of reality while downplaying other parts. 

Unfortunately, many people “reify” the brain-as-computer metaphor: they accept this metaphor as literal truth, leading to various misunderstandings about human cognition.

Here’s another big difference between brains and computers: human cognition is fault-tolerant and robust.  In other words, our minds continue to function even when the information is incomplete (e.g., while we’re driving in the rain) or when our purposes or options are unclear (e.g., navigating a cocktail party).  Computers, on the other hand, are always one line of code away from freezing up. 

In Bright Air, Brilliant Fire:  On the Matter of the Mind (1992) Gerald M. Edelman writes that “The world is not a piece of [computer] tape . . . and the brain is not a computer.”  Brain as computer invites rampant functionalism: that any old hardware will do.  I could implement my own cognition on any other piece of hardware. 

Just because brains and desktop computers often arrive at similar results, though, doesn’t mean that the brain works like a computer. Edelman also points out people often believe that there are computer-like rules that govern thoughts, that the brain thinks by manipulating context-free symbols according to some sort of “rules” that have yet to be specified.  To have any sort of “rules,” though, there must first be uncontested “facts.”  But there is no such thing as context-free facts.  Perhaps there could be if people used identical methods of categorizing the world. Contrary to what many people believe, however, human categorization does not occur by use of necessary and sufficient conditions.  See Cognitive Psychology:  An Overview for Cognitive Scientists, by Larry Barsalou (1992) and Women, Fire, and Dangerous Things, by Lakoff, George (1987).  The world is unlabeled. Without pre-labeled “things,” computers flounder.  Human brains are different.  They thrive primarily on pattern matching, something with which computers struggle.  See What Computers Still Can’t Do, by Hubert L. Dreyfus (1992).

Scott Kelso points out that the brain is not a computer that manipulates symbols. “The nervous system may act as if it were performing Boolean functions . . . People can be calculating, but the brain does not calculate.”  See Dynamic Patterns (1995). Even those who believe that the brain is (an extremely sophisticated) machine, cognitive scientists such as Patricia Churchland, warn us to handle the computer metaphor with extreme caution. We are pattern matchers and pattern completers. Neurophilosophy: Toward a Unified Science of the Mind/Brain, Patricia Smith Churchland (1986).

As Andy Clark points out, we are great at Frisbee, but bad at math.  See Being There: Putting Brain, Body and World Together Again, by Andy Clark (1997).  Clark suggests that a better understanding of the brain is that it is a complex ever-evolving control system, connecting brain, body and world.  Paul Churchland also notes that we are horrible at logic and other types of systematic thinking.  How many years do we study math, but look how we still struggle as adults!  If the brain were a computer, this would not be the case. The Engine of Reason, the Seat of the Soul, Paul M. Churchland (1995).  

The “frame problem” is another proof that brains are not like computer. We can almost instantly bring relevant information to bear.  No computer can do this like human brains.

Because of these many problems, William Bechtel concludes that the brain as computer metaphor is now dated: “[T]he inspiration for developing accounts of how cognition works is no longer the digital computer; instead, knowledge about how the brain works increasingly provides the foundation for theoretical modeling.” A Companion to Cognitive Science,” ed. by W. Bechtel and G. Graham (1998).

Why does it matter whether we ignore all of this evidence and insist that the brain is a computer?  Here are some reasons:

  1. The brain-as-computer metaphor sees the brain as hardware, insisting that the all people for whom meaning can be shared do so by manipulating the same symbols in their heads based on the same “rules.”  This view overlooks the tremendously complex and idiosyncratic wiring that makes your brain different than mine.  As though that lifetime of wiring and pruning of tens of billions of neural connections wasn’t integral to you being you!  As though there isn’t a critical connection between that three-pound wet “computer” in your head and your body!
  2. Insisting that brains are computers makes brains commodities, thereby denigrating the sanctity and idiosyncratic history of each individual.
  3. The brain as computer fails to explain how words can have meaning.  What do symbols in the head ultimately refer to?  More symbols?  That’s a non-starter.  An alternate approach to cognition, embodied cognition gives word meaning roots.  http://dangerousintersection.org/?p=177
  4. Because the brain-as-computer metaphor sees thinking as symbol-manipulation in the head, it fails to explain the connection between world, body and cognition.  It also ignores the well-established interplay between emotion and rationality.  http://dangerousintersection.org/?p=146
  5. The brain as computer metaphor can erroneously lead to a belief in disembodied thought, along with related mischief, such as the possibility of the fully-functioning disembodied soul.  
  6. None of the above is to deny that the brain can sometimes be seen, for limited purposes, to be like a computer.  This comparison can is be fun and sometimes useful, but we must be careful that we don’t reify the brain-as-computer metaphor. Why? Because the brain is not a computer.

Signed,
A Head in a Jar

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About the Author

Erich Vieth is an iconoclastic attorney, musician and writer living in the Shaw neighborhood of St. Louis, Missouri. He and his wife Anne Jay have two daughters, aged 9 and 11.

Comments (22)

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  2. Erich Vieth says:

    From “Why Minds are not like computers,” by Ari Schulman:

    As Ray Kurzweil wrote in The Singularity is Near:

    Computers do not have to use only zero and one…. The nature of computing is not limited to manipulating logical symbols. Something is going on in the human brain, and there is nothing that prevents these biological processes from being reverse engineered and replicated in nonbiological entities.

    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.

    If we achieve artificial intelligence without really understanding anything about intelligence itself—without separating it into layers, decomposing it into modules and subsystems—then we will have no idea how to control it. We will not be able to shape it, improve upon it, or apply it to anything useful. Without having understood and replicated specific mental properties on their own terms, we will not be able to abstract them away—or, as the transhumanists hope, to digitize abilities and experiences, and thus upload and download them in order to transfer our consciousnesses into virtual worlds and enter into the minds of others.

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