Superexponential long-term trends in information technology
Author(s)
Nagy, Béla
Farmer, J. Doyne
Gonzales, John Paul
Trancik, Jessika
Date Issued
September 2011
Journal
Technological Forecasting and Social Change
Publisher
Elsevier
Citation
Nagy, Béla, J. Doyne Farmer, Jessika E. Trancik, and John Paul Gonzales. “Superexponential Long-Term Trends in Information Technology.” Technological Forecasting and Social Change 78, no. 8 (October 2011): 1356-1364.
Version
Author's final manuscript
Abstract
Moore's Law has created a popular perception of exponential progress in information technology. But is the progress of IT really exponential? In this paper we examine long time series of data documenting progress in information technology gathered by [1]. We analyze six different historical trends of progress for several technologies grouped into the following three functional tasks: information storage, information transportation (bandwidth), and information transformation (speed of computation). Five of the six datasets extend back to the nineteenth century. We perform statistical analyses and show that in all six cases one can reject the exponential hypothesis at statistically significant levels. In contrast, one cannot reject the hypothesis of superexponential growth with decreasing doubling times. This raises questions about whether past trends in the improvement of information technology are sustainable.
MIT Department
Massachusetts Institute of Technology. Engineering Systems Division
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.techfore.2011.07.006
