Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The pace of modern culture

Abstract

Here we investigate the evolutionary dynamics of several kinds of modern cultural artefacts—pop music, novels, the clinical literature and cars—as well as a collection of organic populations. In contrast to the general belief that modern culture evolves very quickly, we show that rates of modern cultural evolution are comparable to those of many animal populations. Using time-series methods, we show that much of modern culture is shaped by either stabilizing or directional forces or both and that these forces partly regulate the rates at which different traits evolve. We suggest that these forces are probably cultural selection and that the evolution of many artefact traits can be explained by a shifting-optimum model of cultural selection that, in turn, rests on known psychological biases in aesthetic appreciation. In sum, our results demonstrate the deep unity of the processes and patterns of cultural and organic evolution.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Evolutionary trajectories of artefact and organic populations.
Fig. 2: Estimating Haldane rates from time series.
Fig. 3: Rates of evolution of artefact and organic populations.
Fig. 4: Distribution of Haldane rates for cultural and organic traits.
Fig. 5: Why the long-term rate of evolution of culture varies.

Similar content being viewed by others

Data availability

The data used in the study are available from https://github.com/Armand1/Pace-of-Modern-Culture.

References

  1. Cronk, L. Intelligent design in cultural evolution. Behav. Brain Sci. 29, 352–353 (2006).

    Article  Google Scholar 

  2. Richerson, P. J., Boyd, R. & Henrich, J. Gene–culture coevolution in the age of genomics. Proc. Natl Acad. Sci. USA 107, 8985–8992 (2010).

    Article  CAS  PubMed  Google Scholar 

  3. Mesoudi, A. Cultural Evolution: How Darwinian Theory Can Explain Human Culture and Synthesize the Social Sciences (Univ. Chicago Press, 2011).

  4. Perreault, C. The pace of cultural evolution. PLoS One 7, e45150 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Haldane, J. B. S. Suggestions as to quantitative measurement of rates of evolution. Evolution 3, 51–56 (1949).

    Article  CAS  PubMed  Google Scholar 

  6. Gingerich, P. D. Rates of evolution—effects of time and temporal scaling. Science 222, 159–161 (1983).

    Article  CAS  PubMed  Google Scholar 

  7. Gingerich, P. D. Quantification and comparison of evolutionary rates. Am. J. Sci. 293A, 453–478 (1993).

    Article  Google Scholar 

  8. Hendry, A. P. & Kinnison, M. T. The pace of modern life: measuring rates of contemporary microevolution. Evolution 53, 1637–1653 (1999).

    Article  PubMed  Google Scholar 

  9. Kinnison, M. T. & Hendry, A. P. The pace of modern life II: from rates of contemporary microevolution to pattern and process. Genetica 112, 145–164 (2001).

    Article  PubMed  Google Scholar 

  10. Kuhn, T. The Structure of Scientific Revolutions (Univ. Chicago Press, 1972).

  11. Rosen, C. & Zerner, H. Romanticism and Realism (Faber and Faber, 1984).

  12. Shapin, S. The Scientific Revolution (Univ. Chicago Press, 1996).

  13. Danto, A. C. After the End of Art: Contemporary Art and the Pale of History (Princeton University Press, 1997).

  14. Blanning, T. The Romantic Revolution (Weidenfeld & Nicholson, 2010).

  15. Wooton, D. The Invention of Science: a New History of the Scientific Revolution (Allen Lane, 2015).

  16. Heumakers, A. De Esthetische Revolutie (Boom, 2015).

  17. Mokyr, J. The Lever of Riches: Technological Creativity and Economic Progress (Oxford Univ. Press, 1992).

  18. Basalla, G. The Evolution of Technology (Cambridge Univ. Press, 1988).

  19. Ziman, J. (ed.) Technological Innovation as an Evolutionary Process (Cambridge Univ. Press, 2000).

  20. Steadman, P. The Evolution of Designs: Biological Analogy in Architecture and the Applied Arts (Cambridge Univ. Press, 2008).

  21. Arthur, W. The Nature of Technology: What It Is and How It Evolves (Allen Lane, 2009).

  22. Michel, J. B. et al. Quantitative analysis of culture using millions of digitized books. Science 331, 176–182 (2011).

    Article  CAS  PubMed  Google Scholar 

  23. Serrà, J., Corral, A., Boguñá, M., Haro, M. & Arcos, J. L. I. Measuring the evolution of contemporary western popular music. Sci. Rep. 2, 521 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Hughes, J. M., Foti, N. J., Krakauer, D. C. & Rockmore, D. N. Quantitative patterns of stylistic influence in the evolution of literature. Proc. Natl Acad. Sci. USA 109, 7682–7686 (2012).

    Article  CAS  PubMed  Google Scholar 

  25. Rodriguez Zivic, P. H., Shifres, F. & Cecchic, G. A. Perceptual basis of evolving western musical styles. Proc. Natl Acad. Sci. USA 110, 10034–10038 (2013).

    Article  PubMed  Google Scholar 

  26. Mauch, M., MacCallum, R. M., Levy, M. & Leroi, A. M. The evolution of popular music: USA 1960–2010. R. Soc. Open Sci. 2, 150081 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Estes, S. & Arnold, S. J. Resolving the paradox of stasis: models with stabilizing selection explain evolutionary divergence on all timescales. Am. Nat. 169, 227–244 (2007).

    Article  PubMed  Google Scholar 

  28. Hunt, G. Evolution in fossil lineages: paleontology and the origin of species. Am. Nat. 176, S61–S76 (2010).

    Article  PubMed  Google Scholar 

  29. Hunt, G. Measuring rates of phenotypic evolution and the inseparability of tempo and mode. Paleobiology 38, 351–373 (2012).

    Article  Google Scholar 

  30. Hunt, G., Hopkins, M. J. & Lidgard, S. Simple versus complex models of trait evolution and stasis as a response to environmental change. Proc. Natl Acad. Sci. USA 112, 4885–4890 (2015).

    Article  CAS  PubMed  Google Scholar 

  31. Uyeda, J. C., Hansen, T. F., Arnold, S. J. & Pienaar, J. The million-year wait for macroevolutionary bursts. Proc. Natl Acad. Sci. USA 108, 15908–15913 (2011).

    Article  CAS  PubMed  Google Scholar 

  32. Arnold, S. J. Phenotypic evolution: the ongoing synthesis. Am. Nat. 183, 729–746 (2014).

    Article  PubMed  Google Scholar 

  33. Dobzhansky, T. Mendelian populations and their evolution. Am. Nat. 84, 401–418 (1950).

    Article  Google Scholar 

  34. Hey, J. Regarding the confusion between the population concept and Mayr’s population thinking. Q. Rev. Biol. 86, 253–264 (2011).

    Article  PubMed  Google Scholar 

  35. Cavalli-Sforza, L. L. & Feldman, M. W. Cultural Transmission and Evolution: a Quantitative Approach. (Princeton Univ. Press, 1981).

  36. Boyd, R. & Richerson, P. J. Culture and the Evolutionary Process (Univ. Chicago Press, 1985).

  37. Mesoudi, A., Whiten, A. & Laland, K. N. Is human cultural evolution Darwinian? Evidence reviewed from the perspective of the origin of species. Evolution 58, 1–11 (2004).

    PubMed  Google Scholar 

  38. O’Brien, M. J. & Lyman, R. L. Applying Evolutionary Archaeology: a Systematic Approach (Springer, 2000).

  39. Mesoudi, A. & O’Brien, M. J. The cultural transmission of Great Basin projectile-point technology I: an experimental simulation. Am. Antiq. 73, 3–28 (2008).

    Article  Google Scholar 

  40. Benjamin, W. Illuminations: Essays and Reflections (Schocken, 1969).

  41. Jockers, M. Macroanalysis: Digital Methods and Literary History (Univ. Illinois Press, 2013).

  42. Blei, D. M., Ng, A. Y. & Jordan, M. I. Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003).

    Google Scholar 

  43. O’Brien, M. J., Lyman, R. L., Mesoudi, A. & VanPool, T. L. Cultural traits as units of analysis. Philos. Trans. R. Soc. B 365, 3797–3806 (2010).

    Article  Google Scholar 

  44. Jones, D. A. 50 years of studying the scarlet tiger moth. Trends Ecol. Evol. 4, 298–301 (1989).

    Article  CAS  PubMed  Google Scholar 

  45. Cook, L. M. The rise and fall of the carbonaria form of the peppered moth. Q. Rev. Biol. 78, 399–417 (2003).

    Article  PubMed  Google Scholar 

  46. Grant, P. R. & Grant, B. R. Unpredictable evolution in a 30-year study of Darwin’s finches. Science 296, 707–711 (2002).

    Article  CAS  PubMed  Google Scholar 

  47. Cain, A. J., Cook, L. M. & Currey, J. D. Population size and morph frequency in a long-term study of Cepaea nemoralis. Proc. R. Soc. B 240, 231–250 (1990).

    Google Scholar 

  48. Kurten, B. Rates of evolution in fossil mammals. Cold Spring Harb. Symp. Quant. Biol. 24, 205–215 (1959).

    Article  CAS  PubMed  Google Scholar 

  49. Sheets, H. & Mitchell, C. Uncorrelated change produces the apparent dependence of evolutionary rate on interval. Paleobiology 27, 429–445 (2001).

    Article  Google Scholar 

  50. Roopnarine, P. Analysis of rates of morphologic evolution. Annu. Rev. Ecol. Evol. Syst. 34, 605–632 (2003).

    Article  Google Scholar 

  51. Gingerich, P. D. Rates of evolution. Annu. Rev. Ecol. Evol. Syst. 40, 657–675 (2009).

    Article  Google Scholar 

  52. Bell, M. A. & Aguirre, W. E. Contemporary evolution, allelic recycling, and adaptive radiation of the threespine stickleback. Evol. Ecol. Res. 15, 377–411 (2013).

    Google Scholar 

  53. Grant, P. R. & Grant, B. R. 40 Years of Evolution: Darwin’s Finches on Daphne Major Island (Princeton Univ. Press, 2014).

  54. Beacham, T. Variability in median size and age at sexual maturity of Atlantic cod, Gadus morhua, on the Scotian shelf in the Northwest Atlantic Ocean. Fish. Bull. 81, 303–321 (1983).

    Google Scholar 

  55. Coltman, D. W. et al. Undesirable evolutionary consequences of trophy hunting. Nature 426, 655–658 (2003).

    Article  CAS  PubMed  Google Scholar 

  56. Pigeon, G., Festa-Bianchet, M., Coltman, D. W. & Pelletier, F. Intense selective hunting leads to artificial evolution in horn size. Evol. Appl. 9, 521–530 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Seeley, R. Intense natural selection caused a rapid morphological transition in a living marine snail. Proc. Natl Acad. Sci. USA 83, 6897–6901 (1986).

    Article  CAS  PubMed  Google Scholar 

  58. Trussell, G. & Smith, L. Induced defenses in response to an invading crab predator: an explanation of historical and geographic phenotypic change. Proc. Natl Acad. Sci. USA 97, 2123–2127 (2000).

    Article  CAS  PubMed  Google Scholar 

  59. Olsen, E. et al. Maturation trends indicative of rapid evolution preceded the collapse of northern cod. Nature 428, 932–935 (2004).

    Article  CAS  PubMed  Google Scholar 

  60. Carroll, S. et al. And the beak shall inherit—evolution in response to invasion. Ecol. Lett. 8, 944–951 (2005).

    Article  Google Scholar 

  61. Reznick, D. N., Shaw, F. H., Rodd, F. H. & Shaw, R. G. Evaluation of the rate of evolution in natural populations of guppies (Poecilia reticulata). Science 275, 1934–1937 (1997).

    Article  CAS  PubMed  Google Scholar 

  62. Gotanda, K. M., Correa, C., Turcotte, M. M., Rolshausen, G. & Hendry, A. P. Linking macrotrends and microrates: re-evaluating microevolutionary support for Cope’s rule. Evolution 69, 1345–1354 (2015).

    Article  PubMed  Google Scholar 

  63. Kimura, M. & Ohta, T. The average number of generations until fixation of a mutant gene in a finite population. Genetics 61, 763–771 (1969).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Henrich, J. Demography and cultural evolution: how adaptive cultural processes can produce maladaptive losses: the Tasmanian case. Am. Antiq. 69, 197–214 (2004).

    Article  Google Scholar 

  65. Aoki, K., Lehmann, L. & Feldman, M. W. Rates of cultural change and patterns of cultural accumulation in stochastic models of social transmission. Theor. Popul. Biol. 79, 192–202 (2011).

    Article  PubMed  Google Scholar 

  66. Nakahashi, W. The effect of cultural interaction on cumulative cultural evolution. J. Theor. Biol. 352, 6–15 (2014).

    Article  PubMed  Google Scholar 

  67. Hunt, G. Fitting and comparing models of phyletic evolution: random walks and beyond. Paleobiology 32, 578–601 (2006).

    Article  Google Scholar 

  68. Hunt, G. The relative importance of directional change, random walks, and stasis in the evolution of fossil lineages. Proc. Natl Acad. Sci. USA 104, 18404–18408 (2007).

    Article  CAS  PubMed  Google Scholar 

  69. Hunt, G. & Rabosky, D. L. Phenotypic evolution in fossil species: pattern and process. Annu. Rev. Earth Planet. Sci. 42, 421–441 (2014).

    Article  CAS  Google Scholar 

  70. Sheets, H. & Mitchell, C. Why the null matters: statistical tests, random walks and evolution. Genetica 112, 105–125 (2001).

    Article  PubMed  Google Scholar 

  71. Pagel, M., Atkinson, Q. D. & Meade, A. Frequency of word-use predicts rates of lexical evolution throughout Indo-European history. Nature 449, 717 (2007).

    Article  CAS  PubMed  Google Scholar 

  72. Martin, G. in Technological Innovation as an Evolutionary Process (ed. Ziman, J.) Ch. 8 (Cambridge Univ. Press, 2000).

  73. Moore, G. E. Cramming more components onto integrated circuits. Electronics 38, 114–117 (1965).

    Google Scholar 

  74. Shennan, S. & Wilkinson, J. Ceramic style change and neutral evolution: a case study from neolithic europe. Am. Antiq. 66, 577–593 (2001).

    Article  Google Scholar 

  75. Hahn, M. & Bentley, R. Drift as a mechanism for cultural change: an example from baby names. Proc. R. Soc. B 270, S120–S123 (2003).

    Article  PubMed  Google Scholar 

  76. Bentley, R., Hahn, M. & Shennan, S. Random drift and culture change. Proc. R. Soc. B 271, 1443–1450 (2004).

    Article  PubMed  Google Scholar 

  77. Bentley, R. A., Lipo, C. P., Herzog, H. A. & Hahn, M. W. Regular rates of popular culture change reflect random copying. Evol. Hum. Behav. 28, 151–158 (2007).

    Article  Google Scholar 

  78. Lycett, S. J. Acheulean variation and selection: does handaxe symmetry fit neutral expectations? J. Archaeol. Sci. 35, 2640–2648 (2008).

    Article  Google Scholar 

  79. Bentley, R. A., Ormerod, P. & Shennan, S. Population-level neutral model already explains linguistic patterns. Proc. R. Soc. B 278, 1770–1772 (2011).

    Article  PubMed  Google Scholar 

  80. Acerbi, A. & Bentley, R. A. Biases in cultural transmission shape the turnover of popular traits. Evol. Hum. Behav. 35, 228–236 (2014).

    Article  Google Scholar 

  81. Lynch, M. The rate of morphological evolution in mammals from the standpoint of the neutral expectation. Am. Nat. 136, 727–741 (1990).

    Article  Google Scholar 

  82. Hubbell, S. P. The Unified Neutral Theory of Biodiversity and Biogeography (Princeton Univ. Press, 2001).

  83. Rosindell, J., Hubbell, S. P., He, F., Harmon, L. J. & Etienne, R. S. The case for ecological neutral theory. Trends Ecol. Evol. 27, 203–208 (2012).

    Article  PubMed  Google Scholar 

  84. Fama, E. F. Efficient capital markets: a review of theory and empirical work. Finance 25, 383–417 (1970).

    Article  Google Scholar 

  85. Piotroski, J. D. Value investing: the use of historical financial statement information to separate winners from losers. J. Account. Res. 38, 1–41 (2000).

    Article  Google Scholar 

  86. Poterba, J. M. & Summers, L. H. Mean reversion in stock prices: evidence and implications. J. Financ. Econ. 22, 27–59 (1988).

    Article  Google Scholar 

  87. Lo, A. W. Adaptive markets: Financial Evolution at the Speed of Thought (Princeton, 2017).

  88. Bentley, R. A. Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords. PLoS One 3, e3057 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  89. Brantingham, P. J. & Perreault, C. Detecting the effects of selection and stochastic forces in archaeological assemblages. J. Archaeol. Sci. 37, 3211–3225 (2010).

    Article  Google Scholar 

  90. Crema, E. R., Kandler, A. & Shennan, S. Revealing patterns of cultural transmission from frequency data: equilibrium and non-equilibrium assumptions. Sci. Rep. 6, 39122 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. MacCallum, R. M., Mauch, M., Burt, A. & Leroi, A. M. Evolution of music by public choice. Proc. Natl Acad. Sci. USA 109, 12081–12086 (2012).

    Article  CAS  PubMed  Google Scholar 

  92. Sperber, D. Explaining Culture (Blackwell, 1996).

  93. Sperber, D. & Hirschfeld, L. A. The cognitive foundations of cultural stability and diversity. Trends Cogn. Sci. 8, 40–46 (2004).

    Article  PubMed  Google Scholar 

  94. Claidière, N. & Sperber, D. Imitation explains the propagation, not the stability of animal culture. Proc. R. Soc. B 277, 651–659 (2010).

    Article  PubMed  Google Scholar 

  95. Claidière, N., Kirby, S. & Sperber, D. Effect of psychological bias separates cultural from biological evolution. Proc. Natl Acad. Sci. USA 109, E3526–E3526 (2012).

    Article  PubMed  Google Scholar 

  96. Leroi, A. M., MacCallum, R. M., Mauch, M. & Burt, A. Reply to Claidière et al.: Role of psychological bias in evolution depends on the kind of culture. Proc. Natl Acad. Sci. USA 109, E3527–E3527 (2012).

    Article  CAS  Google Scholar 

  97. Cladière, N., Scott-Phillips, T. & Sperber, D. How Darwinian is cultural evolution? Philos. Trans. R. Soc. B 369, 1471–297 (2014).

    Google Scholar 

  98. Gould, S. J. The Structure of Evolutionary Theory (Harvard Univ. Press, Cambridge, MA, 2002).

    Book  Google Scholar 

  99. Charlesworth, B., Lande, R. & Slatkin, M. A neo-Darwinian commentary on macroevolution. Evolution 36, 474–498 (1982).

    Article  PubMed  Google Scholar 

  100. Charlesworth, B. & Lande, R. Morphological stasis and developmental constraint—no problem for neo-Darwinism. Nature 296, 610 (1982).

    Article  Google Scholar 

  101. Bond, A. B. The evolution of color polymorphism: crypticity searching images, and apostatic selection. Annu. Rev. Ecol. Evol. Syst. 38, 489–514 (2007).

    Article  Google Scholar 

  102. Cook, L. M. Selection and disequilibrium in Cepaea nemoralis. Biol. J. Linn. Soc. 108, 484–493 (2013).

    Article  Google Scholar 

  103. Stanley, S. & Yang, X. Approximate evolutionary stasis for bivalve morphology over millions of years—a multivariate, multilineage study. Paleobiology 13, 113–139 (1987).

    Article  Google Scholar 

  104. Bell, G. Fluctuating selection: the perpetual renewal of adaptation in variable environments. Philos. Trans. R. Soc. B 365, 87–97 (2010).

    Article  Google Scholar 

  105. Bergland, A., Behrman, E., O’Brien, K., Schmidt, P. & Petrov, D. Genomic evidence of rapid and stable adaptive oscillations over seasonal time scales in Drosophila. PLoS Genetics 10, e1004775 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  106. Hendry, A., Day, T. & Taylor, E. Population mixing and the adaptive divergence of quantitative traits in discrete populations: a theoretical framework for empirical tests. Evolution 55, 459–466 (2001).

    Article  CAS  PubMed  Google Scholar 

  107. Jones, J., Leith, B. & Rawlings, P. Polymorphism in Cepaea: a problem with too many solutions? Annu. Rev. Ecol. Evol. Syst. 8, 109–143 (1977).

    Article  Google Scholar 

  108. Leroi, A. et al. On revolutions. Palgrave Commun. (in the press).

  109. Berlyne, D. Novelty, complexity, and hedonic value. Percept. Psychophys. 8, 279–286 (1970).

    Article  Google Scholar 

  110. Berlyne, D. E. Aesthetics and Psychobiology (Appleton-Century-Crofts, 1971).

  111. Sreenivasan, S. Quantitative analysis of the evolution of novelty in cinema through crowd sourced keywords. Sci. Rep. 3, 2758 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Simpson, G. G. Tempo and Mode in Evolution (Columbia Univ. Press, 1944).

  113. Lê, S., Josse, J. & Husson, F. FactoMineR: an R package for multivariate analysis. J. Stat. Softw. 25, 1–18 (2008).

    Article  Google Scholar 

  114. Josse, J. & Husson, F. missMDA: a package for handling missing values in multivariate data analysis. J. Stat. Softw. 70, 1–31 (2016).

    Article  Google Scholar 

  115. McCallum, A. K. MALLET: a Machine Learning for Language Toolkit (Univ. Massachussets, 2002).

  116. Carpenter, B. et al. Stan: a probabilistic programming language. J. Stat. Softw. 76, 1–32 (2017).

    Article  Google Scholar 

  117. Gelman, A. & Rubin, D. B. Inference from iterative simulation using multiple sequences. Stat. Sci. 7, 457–472 (1992).

    Article  Google Scholar 

Download references

Acknowledgements

We thank A. Burt, G. Bell, L. Cook, D. Coltman, P. Grant, K. Gotanda, M. Fortelius, A. Hendry, M. Johnson, G. Pigeon and M. Pagel for data, advice or comments on the manuscript. The authors received no specific funding for this work.

Author information

Authors and Affiliations

Authors

Contributions

B.L. and A.M.L. designed the study, carried out analysis and wrote the paper. G.K., M.M., M.J. and S.A. supplied data and carried out analysis. T.K. supplied data.

Corresponding author

Correspondence to Armand M. Leroi.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Primary handling editors: Charlotte Payne and Aisha Bradshaw

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Supplementary Figs. 1–4, Supplementary Tables 1–7 and Supplementary References.

Reporting Summary

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lambert, B., Kontonatsios, G., Mauch, M. et al. The pace of modern culture. Nat Hum Behav 4, 352–360 (2020). https://doi.org/10.1038/s41562-019-0802-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41562-019-0802-4

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing