Perspective | Published:

Globally networked risks and how to respond

Nature volume 497, pages 5159 (02 May 2013) | Download Citation

Abstract

Today’s strongly connected, global networks have produced highly interdependent systems that we do not understand and cannot control well. These systems are vulnerable to failure at all scales, posing serious threats to society, even when external shocks are absent. As the complexity and interaction strengths in our networked world increase, man-made systems can become unstable, creating uncontrollable situations even when decision-makers are well-skilled, have all data and technology at their disposal, and do their best. To make these systems manageable, a fundamental redesign is needed. A ‘Global Systems Science’ might create the required knowledge and paradigm shift in thinking.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

References

  1. 1.

    World Economic Forum. Global Risks 2012 and 2013 (WEF, 2012 and 2013); .

  2. 2.

    , & Critical infrastructure interdependencies. IEEE Control Syst. 21, 11–25 (2001)

  3. 3.

    et al. Modelling interdependent infrastructures using interacting dynamical models. Int. J. Critical Infrastruct. 4, 63–79 (2008)

  4. 4.

    , , , & Catastrophic cascade of failures in interdependent networks. Nature 464, 1025–1028 (2010)

  5. 5.

    , , & Robustness of networks of networks. Phys. Rev. Lett. 107, 195701 (2011)

  6. 6.

    The fragility of interdependency. Nature 464, 984–985 (2010)

  7. 7.

    , & The scaling laws of human travel. Nature 439, 462–465 (2006)

  8. 8.

    Predicting the behavior of techno-social systems. Science 325, 425–428 (2009)

  9. 9.

    Modelling to contain pandemics. Nature 460, 687 (2009)

  10. 10.

    & The anthropocene. Global Change Newsl. 41, 17–18 (2000)

  11. 11.

    , , eds. Participatory science and computing for our complex world. Eur. Phys. J. Spec. Top. 214, (special issue). 1–666 (2012)

  12. 12.

    , ed. Catastrophe Theory (Addison-Wesley, 1977)

  13. 13.

    Introduction to Phase Transitions and Critical Phenomena (Oxford Univ. Press, 1987)

  14. 14.

    A simple model of global cascades on random networks. Proc. Natl Acad. Sci. USA 99, 5766–5771 (2002)

  15. 15.

    Cascade control and defense in complex networks. Phys. Rev. Lett. 93, 098701 (2004)

  16. 16.

    , , , & Transient dynamics increasing network vulnerability to cascading failures. Phys. Rev. Lett. 100, 218701 (2008)

  17. 17.

    Controlling cascading failure: understanding the vulnerabilities of interconnected infrastructures. J. Urban Technol. 9, 109–123 (2002)This is an excellent analysis of the role of interconnectivity in catastrophic failures.

  18. 18.

    , , , & Efficient response to cascading disaster spreading. Phys. Rev. E 75, 056107 (2007)

  19. 19.

    , & Systemic risk in a unifying framework for cascading processes on networks. Eur. Phys. J. B 71, 441–460 (2009)This paper gives a good overview of different classes of cascade effects with a unifying theoretical framework.

  20. 20.

    , , , & Default cascades: when does risk diversification increase stability? J. Financ. Stab. 8, 138–149 (2012)

  21. 21.

    Albeverio S., Jentsch V., Kantz H., eds. Extreme Events in Nature and Society (Springer, 2010)

  22. 22.

    , & Self-organized criticality: an explanation of the 1/f noise. Phys. Rev. Lett. 59, 381–384 (1987)

  23. 23.

    , & Error and attack tolerance of complex networks. Nature 406, 378–382 (2000)

  24. 24.

    , , & Universality behind Basquin’s law of fatigue. Phys. Rev. Lett. 100, 094301 (2008)

  25. 25.

    , & Explosive percolation in random networks. Science 323, 1453–1455 (2009)

  26. 26.

    & Dragon-kings: mechanisms, statistical methods and empirical evidence. Eur. Phys. J. Spec. Top. 205, 1–26 (2012)

  27. 27.

    Introduction to Nonlinear Science (Cambridge Univ. Press, 1995)

  28. 28.

    Nonlinear Dynamics and Chaos (Perseus, 1994)

  29. 29.

    , & Controllability of complex networks. Nature 473, 167–173 (2011)

  30. 30.

    The Logic of Failure (Metropolitan, 1996)This book is a good demonstration that we tend to make wrong decisions when trying to manage complex systems.

  31. 31.

    Evolutionary Dynamics (Belknap, 2006)

  32. 32.

    Social Self-Organization (Springer, 2012)This book offers an integrative approach to agent-based modelling of emergent social phenomena, systemic risks in social and economic systems, and how to manage complexity.

  33. 33.

    , , & From crowd dynamics to crowd safety: a video-based analysis. Adv. Complex Syst. 11, 497–527 (2008)

  34. 34.

    & Crowd disasters as systemic failures: analysis of the Love Parade disaster. Eur. Phys. J. Data Sci. 1, 7 (2012)

  35. 35.

    et al. Growth, innovation, scaling and the pace of life in cities. Proc. Natl Acad. Sci. USA 104, 7301–7306 (2007)

  36. 36.

    Why Society is a Complex Matter (Springer, 2012)

  37. 37.

    Aven T., Vinnem J. E., eds. Risk, Reliability and Societal Safety Vols 1–3 (Taylor and Francis, 2007)This compendium is a comprehensive source of information about risk, reliability, safety and resilience.

  38. 38.

    Rodriguez H., Quarantelli E. L., Dynes R. R., eds. Handbook of Disaster Research (Springer, 2007)

  39. 39.

    Risk Analysis of Complex and Uncertain Systems (Springer, 2009)

  40. 40.

    Normal Accidents. Living with High-Risk Technologies (Princeton Univ. Press, 1999)This eye-opening book shows how catastrophes result from couplings and complexity.

  41. 41.

    & Human Error. Causes and Control (Taylor and Francis, 2006)This book is a good summary of why, how and when people make mistakes.

  42. 42.

    Worst Cases (Univ. Chicago, 2006)

  43. 43.

    & Harnessing Complexity (Basis Books, 2000)This book offers a good introduction into complex social systems and bottom-up management.

  44. 44.

    & Collectives and the Design of Complex Systems (Springer, 2004)

  45. 45.

    & Self-control of traffic lights and vehicle flows in urban road networks. J. Stat. Mech. P04019 (2008)

  46. 46.

    & Ad-hoc on-demand distance vector routing. In Second IEEE Workshop on Mobile Computing Systems and Applications 90–100 (WMCSA Proceedings, 1999)

  47. 47.

    & Toward a smart grid: power delivery for the 21st century. IEEE Power Energy Mag. 3, 34–41 (2005)

  48. 48.

    , , , & Mitigation of malicious attacks on networks. Proc. Natl Acad. Sci. USA 108, 3838–3841 (2011)

  49. 49.

    Comfort L. K., Boin A., Demchak C. C., eds. Designing Resilience. Preparing for Extreme Events (Univ. Pittsburgh, 2010)

  50. 50.

    et al. Early-warning signals for critical transitions. Nature 461, 53–59 (2009)

  51. 51.

    , & Synchronization (Cambridge Univ. Press, 2003)

  52. 52.

    & Systemic risk in banking ecosystems. Nature 469, 351–355 (2011)

  53. 53.

    , , , & DebtRank: too connected to fail? Financial networks, the FED and systemic risks. Sci. Rep. 2, 541 (2012)

  54. 54.

    Freefall: America, Free Markets, and the Sinking of the World Economy (Norton & Company, 2010)

  55. 55.

    Business Dynamics: Systems Thinking and Modeling for a Complex World (McGraw-Hill/Irwin, 2000)

  56. 56.

    & in Networks of Interacting Machines: Production Organization in Complex Industrial Systems and Biological Cells (eds Armbruster, D., Mikhailov, A. S. & Kaneko, K.) 33–66 (World Scientific, 2005)

  57. 57.

    Innovation diffusion in heterogeneous populations: contagion, social influence, and social learning. Am. Econ. Rev. 99, 1899–1924 (2009)

  58. 58.

    & The spread of innovations in social networks. Proc. Natl Acad. Sci. USA 107, 20196–20201 (2010)

  59. 59.

    , & How natural selection can create both self- and other-regarding preferences, and networked minds. Sci. Rep. 72 1480 (2013)

  60. 60.

    et al. Computational social science. Science 323, 721–723 (2009)

  61. 61.

    & Growing Artificial Societies: Social Science from the Bottom Up (Brookings Institution, 1996)This is a groundbreaking book on agent-based modelling.

  62. 62.

    & Platforms and methods for agent-based modeling. Proc. Natl Acad. Sci. USA 99 (S3). 7197–7198 (2002)

  63. 63.

    & The economy needs agent-based modeling. Nature 460, 685–686 (2009)

  64. 64.

    , , , & Understanding mobility in a social petri dish. Sci. Rep. 2, 457 (2012)

  65. 65.

    Game for change. Nature 470, 330–331 (2011)

  66. 66.

    , & Quantitative Risk Management (Princeton Univ. Press, 2005)

  67. 67.

    , , , & Quantifying the behaviour of stock correlations under market stress. Sci. Rep. 2, 752 (2012)

  68. 68.

    & Bio-Inspired Artificial Intelligence (MIT Press, 2008)

  69. 69.

    Society’s nervous system: building effective government, energy, and public health systems. IEEE Computer 45, 31–38 (2012)

  70. 70.

    , , & Adaptive cruise control design for active congestion avoidance. Transp. Res. C 16, 668–683 (2008)

  71. 71.

    & Dynamic spread of happiness in a large social network. Br. Med. J. 337, a2338 (2008)

  72. 72.

    & Cooperation, norms, and revolutions: a unified game-theoretical approach. PLoS ONE 5, e12530 (2010)

  73. 73.

    Practical Bifurcation and Stability Analysis (Springer, 2009)

  74. 74.

    , , & Unified scaling law for earthquakes. Phys. Rev. Lett. 88, 178501 (2002)

  75. 75.

    Traffic and related self-driven many-particle systems. Rev. Mod. Phys. 73, 1067–1141 (2001)

  76. 76.

    , & Role of network topology in the synchronization of power systems. Eur. Phys. J. B 85, 231–238 (2012)

  77. 77.

    & Deterministic Chaos (Wiley-VCH, 2005)

  78. 78.

    Cybernetics (MIT Press, 1965)

  79. 79.

    et al. Individual versus systemic risk and the regulator’s dilemma. Proc. Natl Acad. Sci. USA 108, 12647–12652 (2011)

  80. 80.

    Evolution, population dynamics, and stability. Proc. Natl Acad. Sci. USA 73, 665–668 (1976)

  81. 81.

    The Collapse of Complex Societies (Cambridge Univ. Press, 1988)

  82. 82.

    The World Economic Forum, Global Risks 2011 6th edn (WEF, 2011); .

  83. 83.

    The clash of civilisations? Foreign Aff. 72, 22–49 (1993)

  84. 84.

    Endogenizing geopolitical boundaries with agent-based modeling. Proc. Natl Acad. Sci. USA 99 (suppl. 3). 7296–7303 (2002)

  85. 85.

    et al. Pattern in escalations in insurgent and terrorist activity. Science 333, 81–84 (2011)

  86. 86.

    Risk Society (Sage, 1992)

  87. 87.

    Social Capital (Routeledge, 2010)

  88. 88.

    & Vulnerable Systems (Springer, 2011)

Download references

Acknowledgements

This work has been supported partially by the FET Flagship Pilot Project FuturICT (grant number 284709) and the ETH project “Systemic Risks—Systemic Solutions” (CHIRP II project ETH 48 12-1). I thank L. Böttcher, T. Grund, M. Kaninia, S. Rustler and C. Waloszek for producing the cascade spreading movies and figures. I also thank the FuturICT community for many inspiring discussions.

Author information

Affiliations

  1. ETH Zurich, Clausiusstrasse 50, 8092 Zurich, Switzerland

    • Dirk Helbing
  2. Risk Center, ETH Zurich, Swiss Federal Institute of Technology, Scheuchzerstrasse 7, 8092 Zurich, Switzerland

    • Dirk Helbing

Authors

  1. Search for Dirk Helbing in:

Competing interests

The author declares no competing financial interests.

Corresponding author

Correspondence to Dirk Helbing.

About this article

Publication history

Received

Accepted

Published

DOI

https://doi.org/10.1038/nature12047

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.