The next time you’re at cocktail party and someone says “Computing power doubles every 18 months,” jump in with this before they can qualify the statement:
“Actually, the 1965 Moore’s Law seems to be a special case of Wright’s Law, spelled out by Theodore P. Wright in a 1936 paper, ‘Factors affecting the costs of airplanes.’ In fact, Wright’s Law seems to describe technological evolution a bit better than Moore’s—not just in electronics, but in dozens of industries.”
Your interlocutors will gaze at you with admiration and wonder. Or, more probably, edge away and leave you in peace.
A new Santa Fe Institute (SFI) working paper (Statistical Basis for Predicting Technological Progress, by Bela Nagy, J. Doyne Farmer, Quan M. Bui, and Jessika E. Trancik) compares the performance of six technology-forecasting models with constant-dollar historical cost data for 62 different technologies—what the authors call the largest database of such information ever compiled. The dataset includes stats on hardware like transistors and DRAMs, of course, but extends to products in energy, chemicals, and a catch-all “other” category (beer, electric ranges) during the periods when they were undergoing technological evolution. The datasets cover spans of from 10 to 39 years; the earliest dates to 1930, the most recent to 2009.