Journal of Risk Research 13:191-205 (2010)
Authors |
|
Abstract |
Some risks have extremely high stakes. For example, a worldwide pandemic or asteroid impact could potentially kill more than a billion people. Comfortingly, scientific calculations often put very low probabilities on the occurrence of such catastrophes. In this paper, we argue that there are important new methodological problems which arise when assessing global catastrophic risks and we focus on a problem regarding probability estimation. When an expert provides a calculation of the probability of an outcome, they are really providing the probability of the outcome occurring, given that their argument is watertight. However, their argument may fail for a number of reasons such as a flaw in the underlying theory, a flaw in the modeling of the problem, or a mistake in the calculations. If the probability estimate given by an argument is dwarfed by the chance that the argument itself is flawed, then the estimate is suspect. We develop this idea formally, explaining how it differs from the related distinctions of model and parameter uncertainty. Using the risk estimates from the Large Hadron Collider as a test case, we show how serious the problem can be when it comes to catastrophic risks and how best to address it.
|
Keywords | No keywords specified (fix it) |
Categories | (categorize this paper) |
Options |
![]() ![]() ![]() ![]() |
Download options
References found in this work BETA
The Dappled World: A Study of the Boundaries of Science.Nancy Cartwright - 1999 - Cambridge University Press.
Experience and Prediction: An Analysis of the Foundations and the Structure of Knowledge.Hans Reichenbach - 1938 - Chicago, IL, USA: University of Chicago Press.
The Logic of Scientific Discovery.K. Popper - 1959 - British Journal for the Philosophy of Science 10 (37):55-57.
View all 16 references / Add more references
Citations of this work BETA
Climate Uncertainty, Real Possibilities and the Precautionary Principle.Jeroen Hopster - forthcoming - Erkenntnis:1-17.
Thinking Inside the Box: Controlling and Using an Oracle AI.Stuart Armstrong, Anders Sandberg & Nick Bostrom - 2012 - Minds and Machines 22 (4):299-324.
Thinking Inside the Box: Using and Controlling an Oracle AI.Stuart Armstrong, Anders Sandberg & Nick Bostrom - forthcoming - Minds and Machines.
Epistemic Uncertainties in Climate Predictions: A Challenge for Practical Decision Making.Rafaela Hillerbrand - 2009 - Intergenerational Justice Review 3 (3).
Similar books and articles
Epistemic Anxiety and Adaptive Invariantism.Jennifer Nagel - 2010 - Philosophical Perspectives 24 (1):407-435.
Technological Risk and Small Probabilities.Kristin Shrader-Frechette - 1985 - Journal of Business Ethics 4 (6):431 - 445.
Probabilities and the Fine-Tuning Argument: A Sceptical View.Timothy McGrew, Lydia McGrew & and Eric Vestrup - 2001 - Mind 110 (440):1027-1038.
Evaluating the Source of the Risks Associated with Natural Events.Colleen Murphy & Paolo Gardoni - 2011 - Res Publica 17 (2):125-140.
Outcome-Desirability Bias in Resource Management Problems.Mathias Gustafsson, Anders Biel & Tommy Garling - 1999 - Thinking and Reasoning 5 (4):327 – 337.
High Stakes and Acceptance Behavior in Ultimatum Bargaining.Bertrand Munier & Costin Zaharia - 2002 - Theory and Decision 53 (3):187-207.
Commonalities in Time and Ambiguity Aversion for Long-Term Risks.Harrell W. Chesson & W. Kip Viscusi - 2003 - Theory and Decision 54 (1):57-71.
Analytics
Added to PP index
2009-01-28
Total views
39 ( #288,782 of 2,498,775 )
Recent downloads (6 months)
5 ( #139,668 of 2,498,775 )
2009-01-28
Total views
39 ( #288,782 of 2,498,775 )
Recent downloads (6 months)
5 ( #139,668 of 2,498,775 )
How can I increase my downloads?
Downloads