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Complexity and the Limits of Revolution: What Will Happen to the Arab Spring?

  • Alexander S. Gard-Murray
  • Yaneer Bar-YamEmail author
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

The recent social unrest across the Middle East and North Africa has deposed dictators who had ruled for decades. While the events have been hailed as an “Arab Spring” by those who hope that repressive autocracies will be replaced by democracies, what sort of regimes will eventually emerge from the crisis remains far from certain. Here we provide a complex systems framework, validated by historical precedent, to help answer this question. We describe the dynamics of governmental change as an evolutionary process similar to biological evolution, in which complex organizations gradually arise by replication, variation, and competitive selection. Different kinds of governments, however, have differing levels of complexity. Democracies must be more systemically complex than autocracies because of their need to incorporate large numbers of people in decision-making. This difference has important implications for the relative robustness of democratic and autocratic governments after revolutions. Revolutions may disrupt existing evolved complexity, limiting the potential for building more complex structures quickly. Insofar as systemic complexity is reduced by revolution, democracy is harder to create in the wake of unrest than autocracy. Applying this analysis to the Middle East and North Africa, we infer that in the absence of stable institutions or external assistance, new governments are in danger of facing increasingly insurmountable challenges and reverting to autocracy.

Keywords

Middle East Democratic Government External Intervention Autocratic Government Governmental Change 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgments

We thank Greg Lindsay, Karla Z. Bertrand, Dominic Albino, Urbano França, and Yavni Bar-Yam for editorial assistance, Lawrence E Susskind, Robert H. Bates, and Dietrich Rueschemeyer for helpful comments on the manuscript. This work was supported in part by AFOSR under grant FA9550-09-1-0324, ONR under grant N000140910516.

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© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.New England Complex Systems InstituteCambridgeUSA

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