Hostname: page-component-586b7cd67f-t8hqh Total loading time: 0 Render date: 2024-11-24T04:03:55.107Z Has data issue: false hasContentIssue false

Artificial versus biological intelligence in the Cosmos: clues from a stochastic analysis of the Drake equation

Published online by Cambridge University Press:  23 June 2020

Alex De Visscher*
Affiliation:
Department of Chemical and Materials Engineering, Gina Cody School of Engineering and Computer Science, Concordia University, Montreal, Quebec, Canada
*
Author for correspondence: Alex De Visscher, E-mail: [email protected]

Abstract

The Drake equation has been used many times to estimate the number of observable civilizations in the galaxy. However, the uncertainty of the outcome is so great that any individual result is of limited use, as predictions can range from a handful of observable civilizations in the observable universe to tens of millions per Milky Way-sized galaxy. A statistical investigation shows that the Drake equation, despite its uncertainties, delivers robust predictions of the likelihood that the prevalent form of intelligence in the universe is artificial rather than biological. The likelihood of artificial intelligence far exceeds the likelihood of biological intelligence in all cases investigated. This conclusion is contingent upon a limited number of plausible assumptions. The significance of this outcome for the Fermi paradox is discussed.

Type
Research Article
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ball, JA (1973) The zoo hypothesis. Icarus 19, 347349.CrossRefGoogle Scholar
Bloetscher, F (2019) Using predictive Bayesian Monte Carlo-Markov Chain methods to provide a probabilistic solution for the Drake equation. Acta Astronautica 155, 118130.CrossRefGoogle Scholar
Drake, F (1965) The radio search for intelligent extraterrestrial life. In Mamikunian, G, Briggs, MH (eds), Current Aspects of Exobiology. New York: Pergamon, pp. 323345.CrossRefGoogle Scholar
Engler, JO and von Wehrden, H (2019) ‘Where is everybody?’ An empirical appraisal of occurrence, prevalence and sustainability of technological species in the universe. International Journal of Astrobiology 18, 495501.CrossRefGoogle Scholar
Forgan, DH (2009) A numerical testbed for hypothesis of extraterrestrial life and intelligence. International Journal of Astrobiology 8, 121131.CrossRefGoogle Scholar
Freitas, RA (1985) There is no Fermi paradox. Icarus 62, 518520.CrossRefGoogle Scholar
Gale, J, Wandel, A and Hill, H (2020) Will recent advances in AI result in a paradigm shift in Astrobiology and SETI? International Journal of Astrobiology 19(3), 295298.CrossRefGoogle Scholar
Glade, N, Ballet, P and Bastien, O (2012) A stochastic process approach of the Drake equation parameters. International Journal of Astrobiology 11, 103108.CrossRefGoogle Scholar
Grimaldi, C (2017) Signal coverage approach to the detection probability of hypothetical extraterrestrial emitters in the Milky Way. Scientific Reports 7, 46273.CrossRefGoogle ScholarPubMed
Hart, MH (1975) Explanation for the absence of extraterrestrials on earth. Quarterly Journal of the Royal Astronomical Society 16, 128135.Google Scholar
Kurzweil, R (2005) The Singularity is Near: When Humans Transcend Biology. New York, USA: Viking Press.Google Scholar
Lingam, M and Loeb, A (2018) Physical constraints on the likelihood of life on exoplanets. International Journal of Astrobiology 17, 116126.CrossRefGoogle Scholar
Lingam, M and Loeb, A (2019) Subsurface exolife. International Journal of Astrobiology 18, 112141.CrossRefGoogle Scholar
Maccone, C (2010) The statistical Drake equation. Acta Astronautica 67, 13661383.CrossRefGoogle Scholar
Mix, LJ (2018) Philosophy and data in astrobiology. International Journal of Astrobiology 17, 189200.CrossRefGoogle Scholar
Newman, WI and Sagan, C (1981) Galactic civilizations: population dynamics and interstellar diffusion. Icarus 46, 293327.CrossRefGoogle Scholar
Olson, SJ (2018) Long-term implications of observing an expanding cosmological civilization. International Journal of Astrobiology 17, 8795.CrossRefGoogle Scholar
Ramirez, R, Gomez-Munoz, MA, Vazquez, R and Nunez, PG (2018) New numerical determination of habitability in the galaxy: the SETI connection. International Journal of Astrobiology 17, 3443.CrossRefGoogle Scholar
Sagan, C (1983) The solipsist approach to extraterrestrial intelligence. Quarterly Journal of the Royal Astronomical Society 24, 113121.Google Scholar
Sandberg, A, Drexler, E and Ord, T (2018) Dissolving the Fermi paradox. ArXiv:1806.02404v1.Google Scholar
Schneider, D (2016) $100 million SETI initiative starts listening for E.T. IEEE Spectrum 53, 4142.CrossRefGoogle Scholar
Seager, S (2018) The search for habitable planets with biosignature gases framed by a ‘Biosignature Drake Equation’. International Journal of Astrobiology 17, 294302.CrossRefGoogle Scholar
Shostak, S (2018) Introduction: the true nature of aliens. International Journal of Astrobiology 17, 281.CrossRefGoogle Scholar
Sotos, JG (2019) Biotechnology and the lifetime of technical civilizations. International Journal of Astrobiology 18, 445454.CrossRefGoogle Scholar
Spiegel, DS and Turner, EL (2012) Bayesian Analysis of the astrobiological implications of life's early emergence on earth. Proceedings of the National Academy of Sciences of the United States of America 109, 395400.CrossRefGoogle ScholarPubMed
Tipler, FJ (1980) Extraterrestrial intelligent beings do not exist. Quarterly Journal of the Royal Astronomical Society 21, 267281.Google Scholar
Totani, T (2020) Emergence of life in an inflationary universe. Scientific Reports 10, 1671.CrossRefGoogle Scholar
Ulam, S (1958) John von Neumann. 1903–1957. Bulletin of the American Mathematical Society 64, 149.CrossRefGoogle Scholar
Vinge, V. (1993) The coming technological singularity: How to survive in the post-human era. In: NASA. Lewis Research Center, Vision 21: Interdisciplinary Science and Engineering in the Era of Cyberspace, NASA, United States, (SEE N94-27358 07-12), pp. 1122.Google Scholar
Yudkowsky, E (2008) Artificial intelligence as a positive and negative factor in global risk. In Bostrom, N and Ćirković MM, (eds), Global Catastrophic Risks. New York: Oxford University Press, pp. 308345.Google Scholar