Probing the improbable: Methodological challenges for risks with low probabilities and high stakes
David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
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)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library||
References found in this work BETA
No references found.
Citations of this work BETA
Stuart Armstrong, Anders Sandberg & Nick Bostrom (2012). Thinking Inside the Box: Controlling and Using an Oracle AI. Minds and Machines 22 (4):299-324.
Similar books and articles
Jennifer Nagel (2010). Epistemic Anxiety and Adaptive Invariantism. Philosophical Perspectives 24 (1):407-435.
Kristin Shrader-Frechette (1985). Technological Risk and Small Probabilities. Journal of Business Ethics 4 (6):431 - 445.
Timothy McGrew, Lydia McGrew & and Eric Vestrup (2001). Probabilities and the Fine-Tuning Argument: A Sceptical View. Mind 110 (440):1027-1038.
J. Alberto Coffa (1977). Probabilities: Reasonable or True? Philosophy of Science 44 (2):186-198.
Colleen Murphy & Paolo Gardoni (2011). Evaluating the Source of the Risks Associated with Natural Events. Res Publica 17 (2):125-140.
Mathias Gustafsson, Anders Biel & Tommy Garling (1999). Outcome-Desirability Bias in Resource Management Problems. Thinking and Reasoning 5 (4):327 – 337.
Bertrand Munier & Costin Zaharia (2002). High Stakes and Acceptance Behavior in Ultimatum Bargaining. Theory and Decision 53 (3):187-207.
Harrell W. Chesson & W. Kip Viscusi (2003). Commonalities in Time and Ambiguity Aversion for Long-Term Risks. Theory and Decision 54 (1):57-71.
Martin Peterson (2001). New Technologies And The Ethics Of Extreme Risks. Ends and Means 5 (2).
Added to index2009-01-28
Total downloads22 ( #172,693 of 1,907,063 )
Recent downloads (6 months)0
How can I increase my downloads?