Journal Home > Volume 3 , Issue 1
Journal of Social Computing 2022, 3(1): 1-17 https://doi.org/10.23919/JSC.2021.0020
Open Access | Issue | Published: 14 February 2022

Social Scale and Collective Computation: Does Information Processing Limit Rate of Growth in Scale?

Show Author's Information Timothy A. Kohler1( ),  Darcy Bird2,  David H. Wolpert3
Department of Anthropology, Washington State University, Pullman, WA 99164–4910, USA; Santa Fe Institute, Santa Fe, NM 87501, USA; Crow Canyon Archaeological Center, Cortez, CO 81321, USA; and Cluster of Excellence ROOTS, Christian-Albrechts-Universität, Kiel 24118, Germany
Department of Anthropology, Washington State University, Pullman, WA 99164–4910, USA; and also with Max Planck Institute for the Science of Human History, Jena 07745, Germany
Santa Fe Institute, Santa Fe, NM 87501, USA; Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85281, USA; and Complexity Science Hub, Vienna 1080, Austria
Keywords:
social evolution, thresholds model, information processing, writing, demographic scale, collective computation
Cite this article:
Kohler TA, Bird D, Wolpert DH. Social Scale and Collective Computation: Does Information Processing Limit Rate of Growth in Scale?. Journal of Social Computing, 2022, 3(1): 1-17. https://doi.org/10.23919/JSC.2021.0020
Download citation
EndNote(RIS)
BibTeX

1382

Views

85

Downloads

Citations

9

Crossref

N/A

WoS

10

Scopus

N/A

CSCD

Abstract Full text About this article

Collective computation is the process by which groups store and share information to arrive at decisions for collective behavior. How societies engage in effective collective computation depends partly on their scale. Social arrangements and technologies that work for small- and mid-scale societies are inadequate for dealing effectively with the much larger communication loads that societies face during the growth in scale that is a hallmark of the Holocene. An important bottleneck for growth may be the development of systems for persistent recording of information (writing), and perhaps also the abstraction of money for generalizing exchange mechanisms. Building on Shin et al., we identify a Scale Threshold to be crossed before societies can develop such systems, and an Information Threshold which, once crossed, allows more or less unlimited growth in scale. We introduce several additional articles in this special issue that elaborate or evaluate this Thresholds Model for particular types of societies or times and places in the world.


menu
Abstract
Full text
Outline
About this article

Social Scale and Collective Computation: Does Information Processing Limit Rate of Growth in Scale?

Show Author's information Timothy A. Kohler1( ), Darcy Bird2, David H. Wolpert3
Department of Anthropology, Washington State University, Pullman, WA 99164–4910, USA; Santa Fe Institute, Santa Fe, NM 87501, USA; Crow Canyon Archaeological Center, Cortez, CO 81321, USA; and Cluster of Excellence ROOTS, Christian-Albrechts-Universität, Kiel 24118, Germany
Department of Anthropology, Washington State University, Pullman, WA 99164–4910, USA; and also with Max Planck Institute for the Science of Human History, Jena 07745, Germany
Santa Fe Institute, Santa Fe, NM 87501, USA; Center for Biosocial Complex Systems, Arizona State University, Tempe, AZ 85281, USA; and Complexity Science Hub, Vienna 1080, Austria

Abstract

Collective computation is the process by which groups store and share information to arrive at decisions for collective behavior. How societies engage in effective collective computation depends partly on their scale. Social arrangements and technologies that work for small- and mid-scale societies are inadequate for dealing effectively with the much larger communication loads that societies face during the growth in scale that is a hallmark of the Holocene. An important bottleneck for growth may be the development of systems for persistent recording of information (writing), and perhaps also the abstraction of money for generalizing exchange mechanisms. Building on Shin et al., we identify a Scale Threshold to be crossed before societies can develop such systems, and an Information Threshold which, once crossed, allows more or less unlimited growth in scale. We introduce several additional articles in this special issue that elaborate or evaluate this Thresholds Model for particular types of societies or times and places in the world.

Keywords: social evolution, thresholds model, information processing, writing, demographic scale, collective computation

References(54)

1
D. P. Waters, Behavior and Culture in One Dimension: Sequences, Affordances, and the Evolution of Complexity. New York, NY, USA: Routledge, 2021.https://doi.org/10.4324/9781003148210
DOI
2

L. M. A. Bettencourt, Impact of changing technology on the evolution of complex informational networks, Proceedings of the IEEE, vol. 102, no. 12, pp. 1878–1891, 2014.
DOI Google Scholar
3
T. M. Cover and J. A. Thomas, Elements of Information Theory (2nd edition). Hoboken, NJ, USA: John Wiley & Sons Inc., 2006.
4

A. Kolchinsky and D. H. Wolpert, Semantic information, autonomous agency and non-equilibrium statistical physics, Interface Focus, vol. 8, no. 6, p. 20180041, 2018.
DOI Google Scholar
5
J. Flack, Life’s information hierarchy, in From Matter to Life: information and Causality, S. I. Walker, P. C. W. Davies, and G. F. R. Ellis, eds. Cambridge, UK: Cambridge University Press, 2017, pp. 283–302.https://doi.org/10.1017/9781316584200.012
DOI
6
D. M. Bondarenko, Introduction, in The Evolution of Social Institutions: Interdisciplinary Perspectives, D. M. Bondarenko, S. A. Kowalewski, and D. B. Small, eds. Berlin, Germany: Springer, 2020, pp. 1–25.https://doi.org/10.1007/978-3-030-51437-2
DOI
7
J. H. Turner, The Institutional Order: Economy, Kinship, Religion, Polity, Law, and Education in Evolutionary and Comparative Perspective. London, UK: Longman Publishing Group, 1997.
8
M. Olson, The Logic of Collective Action: Public Goods and the Theory of Groups. Cambridge, MA, USA: Harvard University Press, 1971.
9

M. González-Forero and A. Gardner, Inference of ecological and social drivers of human brain-size evolution, Nature, vol. 557, no. 7706, pp. 554–557, 2018.
DOI Google Scholar
10
S. C. Levinson, On “Technologies of the Intellect”, https://www.eth.mpg.de/5682990/Goody_Lecture_2020.pdf, 2020.
11
S. K. Langer, Philosophy in A New Key: A Study in the Symbolism of Reason, Rite and Art. New York, NY, USA: Penguin books, 1948.
12

K. Hart, Heads or tails? Two sides of the coin, Man, vol. 21, no. 4, pp. 637–656, 1986.
DOI Google Scholar
13
Thucydides, The History of the Peloponnesian War (Project Gutenberg ebook, translated by Richard Crawley), https://www.gutenberg.org/files/7142/7142-h/7142-H.htm, https://doi.org/10.1093/oseo/instance.00266037, 431 BC.
DOI
14

B. H. Mayhew and R. L. Levinger, Size and the density of interaction in human aggregates, American Journal of Sociology, vol. 82, no. 1, pp. 86–110, 1976.
DOI Google Scholar
15
G. B. West, Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. New York, NY, USA: Penguin Press, 2017.
16

V. G. Childe, The urban revolution, The Town Planning Review, vol. 21, no. 1, pp. 3–17, 1950.
DOI Google Scholar
17

P. Turchin, R. Brennan, T. Currie, K. Feeney, P. Francois, D. Hoyer, J. Manning, A. Marciniak, D. Mullins, A. Palmisano, et al., Seshat: The global history databank, Cliodynamics, vol. 6, no. 1, pp. 77–107, 2015.
DOI Google Scholar
18

P. Turchin, D. Hoyer, J. Bennett, K. Basava, E. Cioni, K. Feeney, P. Francois, S. Holder, J. Levine, S. Nugent, et al., The Equinox2020 Seshat data release, Cliodynamics, vol. 11, no. 1, pp. 41–50, 2020.
DOI Google Scholar
19

P. Turchin, T. E. Currie, H. Whitehouse, P. François, K. Feeney, D. Mullins, D. Hoyer, C. Collins, S. Grohmann, P. Savage, et al., Quantitative historical analysis uncovers a single dimension of complexity that structures global variation in human social organization, Proceedings of the National Academy of Sciences of the United States of America, vol. 115, no. 2, pp. E144–E151, 2018.
DOI Google Scholar
20
I. Ibn-Ḫaldūn, The Muqaddimah: An Introduction to History. Princeton, NJ, USA: Princeton University Press, 1967.
21

J. Shin, M. H. Price, D. H. Wolpert, H. Shimao, B. Tracey, and T. A. Kohler, Scale and information-processing thresholds in Holocene social evolution, Nature Communications, vol. 11, no. 1, p. 2394, 2020.
DOI Google Scholar
22

S. van der Leeuw and C. Folke, The social dynamics of basins of attraction, Ecology and Society, vol. 26, no. 1, p. 33, 2021.
DOI Google Scholar
23
D. N. Keightley, These Bones Shall Rise Again: Selected Writings on Early China. Albany, NY, USA: State University of New York Press, 2014.
24

S. A. Crabtree, R. K. Bocinsky, P. L. Hooper, S. C. Ryan, and T. A. Kohler, How to make a polity (in the central mesa verde region), American Antiquity, vol. 82, no. 1, pp. 71–95, 2017.
DOI Google Scholar
25
C. Renfrew and E. V. Level, 6-Exploring dominance: Predicting polities from centers, in Transformations, C. Renfrew and K. L. Cooke, eds. Pittsburgh, PA, USA: Academic Press, 1979, pp. 145–167.https://doi.org/10.1016/B978-0-12-586050-5.50016-6
DOI
26
J. Ober, Democracy and Knowledge: Innovation and Learning in Classical Athens. Princeton, NJ, USA: Princeton University Press, 2008.https://doi.org/10.1515/9781400828807
DOI
27

P. Turchin, T. E. Currie, E. A. L. Turner, and S. Gavrilets, War, space, and the evolution of Old World complex societies, Proceedings of the National Academy of Sciences, vol. 110, no. 41, pp. 16384–16389, 2013.
DOI Google Scholar
28
G. A. Johnson, Organizational structure and scalar stress, in Theory and Explanation in Archaeology, C. Renfrew, M. Rowlands, and B. A. Segraves, eds. Pittsburgh, PA, USA: Academic Press, 1982, pp. 389–421.
29

J. Baron and J. Millhauser, A place for archaeology in the study of money, finance, and debt, Journal of Anthropological Archaeology, vol. 62, p. 101278, 2021.
DOI Google Scholar
30
M. Hudson, Debt, land and money, from Polanyi to the new economic archaeology, https://michael-hudson.com/2020/09/debt-land-and-money-from-polanyi-to-the-new-economic-archaeology/, 2020.
31

J. Goody and I. Watt, The consequences of literacy, Comparative Studies in Society and History, vol. 5, no. 3, pp. 304–345, 1963.
DOI Google Scholar
32
J. Goody, The Logic of Writing and the Organization of Society. Cambridge, UK: Cambridge University Press, 1986.https://doi.org/10.1017/CBO9780511621598
DOI
33

J. Halverson, Goody and the implosion of the literacy thesis, Man, vol. 27, no. 2, pp. 301–317, 1992.
DOI Google Scholar
34

D. Schmandt-Besserat, The earliest precursor of writing, Scientific American, vol. 238, no. 6, pp. 50–59, 1978.
DOI Google Scholar
35
J. C. Scott, Against the Grain: A Deep History of the Earliest States. New Haven, CT, USA: Yale University Press, 2017.https://doi.org/10.2307/j.ctv1bvnfk9
DOI
36

R. Blanton, Collective action and adaptive socioecological cycles in premodern states, Cross-Cultural Research:Official Journal of the Society for Cross-Cultural Research / Sponsored by the Human Relations Area Files, vol. 44, no. 1, pp. 41–59, 2010.
DOI Google Scholar
37
J. C. Moreno Garcia, The State in Ancient Egypt: Power, Challenges and Dynamics. London, UK: Bloomsbury Academic, 2020.
38
D. Schmandt-Besserat and M. Erard, Origins and forms of writing, in Handbook of Research on Writing: History, Society, School, Individual, Text, C. Bazerman ed. New York, NY, USA: Routledge, 2008, pp. 7–22.
39
P. J. Boyes and P. M. Steele, Introduction: Issues in studying early alphabets, in Understanding Relations Between Scripts II: Early Alphabets [Hardback], P. J. Boyes and P. M. Steele, eds. South Yorkshire, UK: Oxbow, 2019.
40
G. Yeo, Record-Making and Record-Keeping in Early Societies. New York, NY, USA: Routledge, 2021.https://doi.org/10.4324/9780429054686
DOI
41

M. del C. R. Martínez, P. O. Ceballos, M. D. Coe, R. A. Diehl, S. D. Houston, K. A. Taube, and A. D. Calderon, Oldest writing in the New World, Science, vol. 313, no. 5793, pp. 1610–1614, 2006.
DOI Google Scholar
42
J. Justeson, Early Mesoamerican Writing Systems, https://doi.org/10.1093/oxfordhb/9780195390933.013.0063, 2012.
DOI
43
S. Martin, Ancient Maya Politics: A Political Anthropology of the Classic Period 150–900 CE. Cambridge, UK: Cambridge University Press, 2020.https://doi.org/10.1017/9781108676694
DOI
44

A. Sofaer, M. P. Marshall, and R. M. Sinclair, The great north road: A cosmographic expression of the Chaco culture of New Mexico, World Archaeoastronomy, pp. 365–376, 1989.
Google Scholar
45
T. C. Windes, The prehistoric road network at Pueblo Alto, Chaco Canyon, New Mexico, in Ancient Road Networks and Settlement Hierarchies in the New World, C. D. Trombold, ed. Cambridge, UK: Cambridge University Press, 1991, pp. 111–131.
46

R. M. Van Dyke, R. K. Bocinsky, T. C. Windes, and T. J. Robinson, Great houses, shrines, and high places: Intervisibility in the Chacoan World, American Antiquity, vol. 81, no. 2, pp. 205–230, 2016.
DOI Google Scholar
47

S. Ortman and J. Lobo, Smithian growth in a nonindustrial society, Science Advances, vol. 6, no. 25, p. eaba5694, 2020.
DOI Google Scholar
48

K. V. Flannery, The cultural evolution of civilizations, Annual Review of Ecology and Systematics, vol. 3, pp. 399–426, 1972.
DOI Google Scholar
49
S. van der Leeuw, Social Sustainability, Past and Future. Cambridge, UK: Cambridge University Press, 2020.https://doi.org/10.1017/9781108595247
DOI
50

T. A. Kohler, M. E. Smith, A. Bogaard, G. M. Feinman, C. E. Peterson, A. Betzenhauser, M. Pailes, E. C. Stone, A. M. Prentiss, T. J. Dennehy, et al., Greater post-Neolithic wealth disparities in Eurasia than in North America and Mesoamerica, Nature, vol. 551, no. 7682, pp. 619–622, 2017.
DOI Google Scholar
51
E. Gellner, Positivism against Hegelianism, in Relativism and the Social Sciences. Cambridge, UK: Cambridge University Press, 1985, pp. 4–67.
52

J. B. Bak-Coleman, M. Alfano, W. Barfuss, C. T. Bergstrom, M. A. Centeno, I. D. Couzin, J. F. Donges, M. Galesic, A. S. Gersick, J. Jacquet, et al., Stewardship of global collective behavior, Proceedings of the National Academy of Sciences of the United States of America, vol. 118, no. 27, p. e2025764118, 2021.
DOI Google Scholar
53

K. Shaw-Williams, The social trackways theory of the evolution of language, Biological Theory, vol. 12, no. 4, pp. 195–210, 2017.
DOI Google Scholar
54
M. McLuhan, W. Terrence Gordon, E. Lamberti, and D. Scheffel-Dunand, The Gutenberg Galaxy: The Making of Typographic Man. Toronto, Canada: University of Toronto Press, 2011.
Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 05 August 2021
Revised: 17 November 2021
Accepted: 21 November 2021
Published: 14 February 2022
Issue date: March 2022

Copyright

© The author(s) 2021

Acknowledgements

Acknowledgment

We thank several colleagues (Elizabeth Bradley, Stefani Crabtree, Anna Frishman, Adam Green, Juergen Jost, Jin Hong Kuan, Cameron Petrie, Hajime Shimao, Michael E. Smith, and Miriam Stark) who offered talks at the SFI Working Group but did not contribute papers here. Their presentations, enthusiasm, discussion points, and comments on both Seshat and on the Thresholds Model were instrumental in developing this special issue. We would further like to thank James Evans, who suggested this journal as a destination for these papers. Finally, we greatly appreciated the many non-presenting participants at the WG for their contributions via discussion, email, and interest in the topic.

This material is based upon work supported by the National Science Foundation (No. SMA-1620462). T. A. Kohler further acknowledges support from the Cluster of Excellence ROOTS, EXC 2150, funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy.

Rights and permissions

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).

Return