 Links between entropy, complexity, and the technological singularityTheodore Modis Technological Forecasting and Social Change, 2022, vol. 176, issue C Abstract: Entropy always increases monotonically in a closed system but complexity increases at first and then decreases as equilibrium is approached. Commonsense information-related definitions for entropy and complexity demonstrate that complexity behaves like the time derivative of entropy, which is proposed here as a new definition for complexity. A 20-year old study had attempted to quantify complexity (in arbitrary units) for the entire Universe in terms of 28 milestones, breaks in historical perspective, and had concluded that complexity will soon begin decreasing. That conclusion is now corroborated by other researchers. In addition, the exponential runaway technology trend advocated by supporters of the singularity hypothesis—which was in part based on the trend of the very 28 milestones mentioned above—would have anticipated five new such milestones by now, but none have been observed. The conclusions of the 20-year old study remain valid: we are at the maximum of complexity and we should expect the next two milestones at around 2033 and 2078. Keywords: Entropy; Complexity; Singularity; Logistic growth; S-curve (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:176:y:2022:i:c:s0040162521008921 DOI: 10.1016/j.techfore.2021.121457 Access Statistics for this article Technological Forecasting and Social Change is currently edited by Fred Phillips More articles in Technological Forecasting and Social Change from Elsevier |
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