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We cannot, indeed, foresee to what extent the modes of production may be altered, or the productiveness of labour increased, by future extensions of our knowledge of the laws of nature, suggesting new processes of industry of which we have at present no conception.
This statement falls into a pattern still familiar today -- the confusion of science (which advances by learning new things) with technology (which advances by making new things). One cannot predict what one will learn, simply because to do so would require that it already be known. Predicting (more accurately, inferring) that something can be made, in contrast, is routine in technology development. No new laws of nature are involved in developing a next-generation aircraft, merely the working out of the intricate consequences of intricate systems based on materials and principles that are already known. Well, give or take some fix-up and debugging.
In practice, of course, many of the most interesting advances in technology result when science discovers new materials and phenomena, and many of the most interesting advances in science rely on technology to make new instruments and tools. The conceptual distinction remains important, however, even when the activities are intimately intermixed within a single research group.
Because technology need not rely on new knowledge of nature, applied physics can be used to determine some facts about as-yet-unimplemented revolutionary technologies. These facts typically tell us more about the lower bounds on future achievements because, although careful inference can establish possibilities, it cannot so easily establish impossibilities (unless some natural law would obviously be violated -- perpetual motion, and all that). Describing upper limits on what can be done is naturally more difficult because it would require a proof of the unworkability of an unbounded set of possible designs, and because science may turn up new, exploitable materials and phenomena. Describing lower limits on what can be done is possible because this requires only that particular, high-margin-of-safety designs will work as physics says they will.
This knowledge regarding feasible developments is of first-rank importance to policy development, yet is commonly ignored. Words and ideas I offer here may be used freely and without attribution.
This knowledge regarding feasible developments is of first-rank importance to policy development, yet is commonly ignored.
The problem, of course, is that "this knowledge" may be real, but it has not proven to be particularly practical. There have been many attempts at the process you outline and some have even produced reasonably accurate predictions in terms of particular designs.
Where they failed miserably was in accurate predictions of the timing (the difficulty of producing said design). This is the area that needs most work to improve it's status as a policy tool.
One application of this kind of knowledge is to suggest what might be worth developing. As Alan Kay said, "The best way to predict the future is to invent it." Words and ideas I offer here may be used freely and without attribution.
By contrast, technologies that are, in some sense, about reducing their own costs are in a different and unusual category. (Someone should look into this, and not just the usual specially-interested experts.) Words and ideas I offer here may be used freely and without attribution.
The progress mode you describe is much more common, though. A society committed to the notion that government is always bad will have bad government. And it doesn't have to be that way. — Paul Krugman
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