Our cultures must be the principal source of much of our personal knowledge and skills, because no single individual would have enough time to learn so much.
Almost everyone understands the extent to which each person’s knowledge and beliefs have been passed down centuries from those of our cultural ancestors. No person, alone, could ever invent as many conceptions as we can observe in any typical four-year old. But fewer of us appreciate the extent of how much such knowledge hides in virtually every language word.[212]
Listen closely to anything anyone says, and soon you’ll hear analogies. We speak of time in terms of space, as like a fluid that’s ‘running out’; we talk of our friendships in physical terms, as in “Carol and Joan are very close.” All of our language is riddled and stitched with such ways of portraying things—and sometimes we call these “metaphors.” Some metaphors seem utterly pedestrian, as when we speak of “taking steps” to cause or prevent some happening. Other metaphors seem more remarkable—as when a scientist solves a problem by conceiving of a fluid as made of tubes. When such analogies play surprisingly productive roles, we notice them, but we rarely notice how frequently we use the same techniques in commonsense thinking.
Some metaphors and analogies have very simple origins, as when they come from stripping away enough details to make two different objects seem the same. But other forms of metaphor are as complex as can be. In either case, metaphors are useful when they represent things in ways that help us to transport knowledge into other realms, where we can still apply the same already -developed skills. And in many cases this results in our most productive, systematic, cross-realm correspondences. In this book these are called ‘panalogies.’
How do we learn our most precious panalogies? I suspect that many of them are virtually born into our brains—because the regions, which represent various realms, have basically such similar wiring that we can discover those metaphors by ourselves. However, we also learn many of our metaphors from the patterns of usage of words by other members of our communities.
On rare occasion, some individual discover a new representation or formulation that is both so fruitful and so easy to explain that it becomes part of the general culture. Naturally, we’d like to know how those greatest discoveries were made. But because this is buried in the past, most of those great rare events may never be explained at all—because, like our evolutionary genes, these need happen by accident only once, and then can spread from brain to brain.
All this has empowered us to deal with huge classes of new situations. The previous chapters discussed many aspects of what gives us so much resourcefulness:
Nevertheless, our brains still have bugs. Similarly, in the coming decades of research toward Artificial Intelligence, every system that we build will keep showing unexpected flaws. In some cases, we’ll be able to diagnose specific errors in those designs, and hence be able to correct them. But when we can find no such simple fix, then we will be forced instead to evolve increasingly complex systems in which each process needs to be supervised by various Critics. [edit] And through all this, we can never expect to find any foolproof strategy to balance the advantage of immediate action against the benefit of more careful, reflective thought. Whatever we do, we can be sure that the road toward designing ‘post-human minds’ will be rough.
Bibliography
Acerra 1999: Francesca Acerra, Yves Burnod and Scania de Schonen, European Symposium on Artificial Neural Networks, Bruges (Belgium), 1999, ISBN 26000499X, pp. 129-134. Text at http://www.dice.ucl.ac.be/Proceedings/esann/esannpdf/es1999-22.pdf
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Aristotle b:
Arnold 1865: Matthew Arnold,
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Bowlby 1973. John Bowlby [1907-1990]
Bowlby 1973b: John Bowlby,
