2017/09/04 by John G. Sotos · 2 voices · 1 citation
Physics and Astronomy · Social Sciences · #Evolutionary Game Theory and Cooperation #Origins and Evolution of Life #Space Science and Extraterrestrial Life #physics.pop-ph
paper · pdf · doi:10.1017/s1473550418000447
published as International Journal of Astrobiology 18 (2019) 445-454 · 4 figures. In press with: International Journal of Astrobiology
arxiv published 2017/09/04 · openalex created_date 2017/09/15 · arxiv created 2018/12/12 · openalex publication_date 2019/01/15 · arxiv updated 2019/08/15 · openalex updated_date 2026/07/28
The number of people able to end Earth's technical civilization has heretofore been small. Emerging dual-use technologies, such as biotechnology, may give similar power to thousands or millions of individuals. To quantitatively investigate the ramifications of such a marked shift on the survival of both terrestrial and extraterrestrial technical civilizations, this paper presents a two-parameter model for civilizational lifespans, i.e. the quantity L in Drake's equation for the number of communicating extraterrestrial civilizations. One parameter characterizes the population lethality of a civilization's biotechnology and the other characterizes the civilization's psychosociology. L is demonstrated to be less than the inverse of the product of these two parameters. Using empiric data from Pubmed to inform the biotechnology parameter, the model predicts human civilization's median survival time as decades to centuries, even with optimistic psychosociological parameter values, thereby positioning biotechnology as a proximate threat to human civilization. For an ensemble of civilizations having some median calculated survival time, the model predicts that, after 80 times that duration, only one in 1024 civilizations will survive -- a tempo and degree of winnowing compatible with Hanson's "Great Filter." Thus, assuming that civilizations universally develop advanced biotechnology, before they become vigorous interstellar colonizers, the model provides a resolution to the Fermi paradox.