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What science can do for democracy: a complexity science approach

Author

Listed:
  • Tina Eliassi-Rad

    (Northeastern University)

  • Henry Farrell

    (George Washington University)

  • David Garcia

    (Medical University of Vienna
    Complexity Science Hub Vienna)

  • Stephan Lewandowsky

    (University of Bristol)

  • Patricia Palacios

    (University of Salzburg)

  • Don Ross

    (University College Cork
    University of Cape Town
    Georgia State University)

  • Didier Sornette

    (ETH Zurich)

  • Karim Thébault

    (University of Bristol)

  • Karoline Wiesner

    (University of Bristol)

Abstract

Political scientists have conventionally assumed that achieving democracy is a one-way ratchet. Only very recently has the question of “democratic backsliding” attracted any research attention. We argue that democratic instability is best understood with tools from complexity science. The explanatory power of complexity science arises from several features of complex systems. Their relevance in the context of democracy is discussed. Several policy recommendations are offered to help (re)stabilize current systems of representative democracy.

Suggested Citation

  • Tina Eliassi-Rad & Henry Farrell & David Garcia & Stephan Lewandowsky & Patricia Palacios & Don Ross & Didier Sornette & Karim Thébault & Karoline Wiesner, 2020. "What science can do for democracy: a complexity science approach," Palgrave Communications, Palgrave Macmillan, vol. 7(1), pages 1-4, December.
    • Handle: RePEc:pal:palcom:v:7:y:2020:i:1:d:10.1057_s41599-020-0518-0
    DOI: 10.1057/s41599-020-0518-0
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    References listed on IDEAS

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    3. Hirokazu Shirado & Nicholas A. Christakis, 2017. "Locally noisy autonomous agents improve global human coordination in network experiments," Nature, Nature, vol. 545(7654), pages 370-374, May.
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    Cited by:

    1. Rick Szostak, 2024. "Restoring democratic stability: A backcasting wheel approach," Futures & Foresight Science, John Wiley & Sons, vol. 6(3), September.

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