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  • Can We Transcend Computation?



    This is Chapter 23 of The Future Does Not Compute: Transcending the Machines in Our Midst, by Stephen L. Talbott. Copyright 1995 O'Reilly & Associates. All rights reserved. You may freely redistribute this chapter in its entirety for noncommercial purposes. For information about the author's online newsletter, NETFUTURE: Technology and Human Responsibility, see http://www.netfuture.org/.

    Everyone seems to "know" that computers are one-sided. If we had to characterize computers as either logical or intuitive, we would say, "logical." Do computers deal in information or understanding? Information. Are they impersonal or personal? Impersonal. Highly structured or unstructured? Structured. Quantitative or qualitative? Quantitative.

    The problem is that we always seem to have a clear notion of the one side -- the attributes we assign to the computer -- while the other side remains suspiciously elusive despite representing our own "human dimension." What sort of personal understanding is intuitive, unstructured, and qualitative? Can we distinguish it precisely from impersonal information that is logical, structured, and quantitative?

    But the question rings an alarm bell. It asks for a precise distinction, but precision itself seems to be one of the terms we are required to distinguish. After all, what do we mean by precision if not quantitative and logical exactness? If this is so, however, then we appear to be stuck: clearly, we cannot distinguish precisely between precision itself and something incommensurable with precision, any more than we can visually distinguish between sight and smell. All we can do is contrast the precise with the imprecise, which leaves us firmly rooted to the scale of precision. And yet, the widespread impression of computational one-sidedness suggests that we are at least dimly aware of "another side of the story." Can we lay hold of it?

    The conviction that we can underlies every sentence of this book. The issues, however, are complex, and they confound virtually every debate about computer capabilities. When a problem haunts us in this way, we can be sure that we're up against a fundamental question of meaning -- very likely one that our deeply ingrained cultural biases or blind spots prevent us from encompassing.

    It so happens that Owen Barfield has spent some sixty-five years circling and laying bare the particular biases at issue here. His first, decisive insights applicable to the relation between computers and human beings date from the late 1920s -- although he was not then writing, and so far as I know has not since written, about computers. Unfortunately, I do not know of any others who have brought his work to bear upon artificial intelligence and related disciplines. My own effort here is a modest one: to suggest broadly and informally where Barfield's work strikes most directly at current confusions.

    A brief preview

    As I have just suggested, no one can strictly prove that the computer suffers decisive limitations relative to the human being. We co