Hostname: page-component-586b7cd67f-rcrh6 Total loading time: 0 Render date: 2024-12-01T08:58:53.007Z Has data issue: false hasContentIssue false

The policy consequences of cascade blindness

Published online by Cambridge University Press:  15 November 2018

ADAM ELGA*
Affiliation:
Princeton University Department of Philosophy, Princeton, NJ, USA
DANIEL M. OPPENHEIMER
Affiliation:
Carnegie Mellon University, Departments of Psychology and Social and Decision Sciences, Pittsburgh, PA, USA
*
*Correspondence to: Princeton University Department of Philosophy, 1879 Hall, Princeton University, Princeton, NJ 08544-1006, USA. Email: [email protected]

Abstract

One way to reduce waste and to make a system more robust is to allow its components to pool resources. For example, banks might insure each other or share a common capital reserve. Systems whose resources have been pooled in this way are highly prevalent in such diverse domains as finance, infrastructure, health care, emergency response and engineering. However, these systems have a combination of characteristics that leave them vulnerable to poor decision-making: non-linearity of risk; obvious rewards combined with hidden costs; and political and market incentives that encourage inadequate safety margins. Three studies demonstrate a tendency for managers of such systems to underestimate the probability of cascading failures. We describe a series of behaviorally based policy interventions to mitigate the resulting hazards.

Type
Article
Copyright
Copyright © Cambridge University Press 2018

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Boin, A. and Hart, P. (2003), ‘Public leadership in times of crisis: mission impossible?’, Public Administration Review, 63(5): 544553.CrossRefGoogle Scholar
Brunnermeier, Markus K. (2009), ‘Deciphering the liquidity and credit crunch 2007–2008’, Journal of Economic Perspectives, 23, 77100.CrossRefGoogle Scholar
De Bock, D., Van Dooren, W., Janssens, D. and Verschaffel, L. (2002), ‘Improper use of linear reasoning: An in-depth study of the nature and the irresistibility of secondary school students' errors’, Educational Studies in Mathematics, 50(3): 311334.CrossRefGoogle Scholar
Dinner, I., Johnson, E. J., Goldstein, D. G. and Liu, K. (2011), ‘Partitioning default effects: why people choose not to choose’, Journal of Experimental Psychology: Applied, 17(4): 332.Google ScholarPubMed
Dobson, I. (2007), ‘Where is the edge for cascading failure?: challenges and opportunities for quantifying blackout risk’, Paper presented at the IEEE Power Engineering Society General Meeting, Tampa, FL.CrossRefGoogle Scholar
Dobson, I., Carreras, B. A. and Newman, D. E. (2005), ‘A loading dependent model of probabilistic cascading failure’, Probability in the Engineering and Informational Sciences, 19, pp. 1532.CrossRefGoogle Scholar
Elga, A. (2012), ‘How to destroy probabilities and lives by trying to make things safer’, Paper presented at California Institute of Technology, Pasadena, CA.Google Scholar
Gorton, G. and Metrick, A. (2010), ‘Haircuts’, Federal Reserve Bank of St. Louis Review, 507520.Google Scholar
Granovetter, M. (1978), ‘Threshold models of collective behavior’, American Journal of Sociology, 14201443.CrossRefGoogle Scholar
Hines, P., Balasubramaniam, K. and Sanchez, E. (2009), ‘Cascading failures in power grids’, IEEE Potentials, 2430.CrossRefGoogle Scholar
Kindleberger, C. and Aliber, R. (2005), Manias, Panics, and Crashes: A History of Financial Crises. 5th edition. Hoboken, NJ: John Wiley & Sons.CrossRefGoogle Scholar
Lagos, M., Lewis, S. and Pickoff-White, L. (2018, March 8), ‘My world was burning’: The North Bay fires and what went wrong. Reveal. Retrieved from https://www.revealnews.org/article/my-world-was-burning-the-north-bay-fires-and-what-went-wrong/Google Scholar
Nedic, D. P., Dobson, I., Kirschen, D. S., Carreras, B. A. and Lynch, V.E. (2006), ‘Criticality in a cascading failure blackout model’, International Journal of Electrical Power and Energy Systems, 28, 627633.CrossRefGoogle Scholar
Olsson, A. C., Enkvist, T. and Juslin, P. (2006), ‘Go with the flow: How to master a nonlinear multiple-cue judgment task’, Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(6): 1371.Google Scholar
Paolacci, G., Chandler, J., and Ipeirotis, P. G. (2010), ‘Running experiments on Amazon Mechanical Turk’, Judgment and Decision Making, 5, 411419.Google Scholar
Perrow, C. (1999), Normal Accidents: Living with High-Risk Technologies. Princeton, NJ: Princeton University Press.Google Scholar
Perrow, C. (2007), ‘The Next Catastrophe: Reducing our Vulnerabilities to Natural, Industrial, and Terrorist Disasters’, Princeton, NJ: Princeton University Press.Google Scholar
Sachs, J. (2009, January 1), ‘Blackouts and cascading failures of the global markets’, Scientific American. Retrieved from https://www.scientificamerican.com/article/blackouts-and-cascading-failures/CrossRefGoogle Scholar
Sheppard, K. (2014, March 8), ‘New report warns of “cascading system failure” caused by climate change. Huffington Post’, Retrieved from https://grist.org/climate-energy/new-report-warns-of-cascading-system-failure-caused-by-climate-change/Google Scholar
Sterman, J., Fiddaman, T., Frankck, T., Jones, A., McCauley, S., Rice, P., Sawin, E., and Siegel, L. (2013), ‘Management flight simulators to support slimate segotiations: The C-ROADS climate policy model’, Environmental Modeling & Software, 44, 122135.CrossRefGoogle Scholar
Thaler, R. H., Sunstein, C. R., and Balz, J. P. (2013), ‘Choice Architecture’, in Shafir, E. (ed.) The Behavioral Foundations of Public Policy, Princeton, NJ: Princeton University Press.Google Scholar
Thomson, K.S. and Oppenheimer, D.M. (2016), ‘Cognitive Reflection and Non-Linear Thinking’, Paper presented at the International Conference on Thinking, Providence, RI.CrossRefGoogle Scholar
Van Dooren, W., De Bock, D., Depaepe, F., Janssens, D. and Verschaffel, L. (2003), ‘The illusion of linearity: Expanding the evidence towards probabilistic reasoning’, Educational Studies in Mathematics, 53(2): 113138.CrossRefGoogle Scholar
Watts, D. (2002), ‘A simple model of global cascades on random networks’, PNAS, 99, 57665771.CrossRefGoogle ScholarPubMed
Wei, M., Lu, Z., Tang, Y. and Lu, X. (2018, April) ‘How can cyber-physical interdependence affect the mitigation of cascading power failure? IEEE Conference on Computer Communications’, Retrieved from http://csa.eng.usf.edu/getsrc/?n=papers/18wlt-info.pdfCrossRefGoogle Scholar
Yellen, J. (2013), ‘Interconnectedness and systemic risk: Lessons from the financial crisis and policy implications’, Remarks presented at the American Economic Association/American Finance Association Joint Luncheon, San Diego, California.Google Scholar
Zhao, J. (2016), ‘Failures of Non-Linear Thinking’, Paper Presented at the International Conference on Thinking, Providence, RI.Google Scholar
Supplementary material: File

Elga and Oppenheimer supplementary material

Elga and Oppenheimer supplementary material
Download Elga and Oppenheimer supplementary material(File)
File 29.1 KB