David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
J. Richard Gott III (1993) has used the “Copernican principle” to derive a probability density function for the total longevity of any phenomenon, based solely on the phenomenon’s past longevity. John Leslie (1996) and others have used an apparently similar probabilistic argument, the “Doomsday Argument,” to claim that conventional predictions of longevity must be adjusted, based on Bayes’ Theorem, in favor of shorter longevities. Here I show that Gott’s arguments are flawed and contradictory, but that one of his conclusions—his delta t formula—is mathematically equivalent to Laplace’s famous (and notorious) ‘rule of succession’; moreover, Gott’s delta t formula is a plausible worst-case (if one favors greater longevity) bound in some contexts. On the other hand, the Doomsday Argument is fallacious: the argument’s Bayesian formalism is stated in terms of total duration, but all attempted real-life applications of the argument—with one exception, an application by Gott 1994—actually plug in prior probabilities for future duration; moreover, the Self-Sampling Assumption, an essential premise of the Doomsday Argument, is contradicted by the prior information in all known real-life cases. But rejecting the Doomsday Argument does not entail rejecting the possibility of learning about the future from the past. Applying the work of Bruce M. Hill (1968, 1988, 1993) and Frank P.A. Coolen (1998, 2006) in the field of non-parametric predictive inference, I propose and defend an alternative methodology for quantifying how past longevity of any phenomenon does provide evidence for future longevity. In so doing, I identify an objective standard by which to choose among counting time intervals, counting population, or counting any other measure of past longevity in predicting future longevity. This methodology forms the basis of a calculus of induction.
|Keywords||Induction non-parametric predictive inference Doomsday Argument Self-Sampling Assumption Copernican principle Anthropic principle|
|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
No citations found.
Similar books and articles
Ronald Pisaturo (2009). Past Longevity as Evidence for the Future. Philosophy of Science 76 (1):73-100.
Brian Kierland & Bradley Monton (2006). How to Predict Future Duration From Present Age. Philosophical Quarterly 56 (January):16-38.
Bradley Monton & Brian Kierland (2006). How to Predict Future Duration From Present Age. Philosophical Quarterly 56 (222):16 - 38.
Nick Bostrom (2000). Observer-Relative Chances in Anthropic Reasoning? Erkenntnis 52 (1):93-108.
Nick Bostrom (2001). The Doomsday Argument Adam & Eve, UN++, and Quantum Joe. Synthese 127 (3):359 - 387.
E. Sober (2003). An Empirical Critique of Two Versions of the Doomsday Argument – Gott's Line and Leslie's Wedge. Synthese 135 (3):415 - 430.
Bradley Monton (2003). The Doomsday Argument Without Knowledge of Birth Rank. Philosophical Quarterly 53 (210):79–82.
George F. Sowers Jr (2002). The Demise of the Doomsday Argument. Mind 111 (441):37-46.
George F. Sowers Jr (2002). The Demise of the Doomsday Argument. Mind 111 (441):37 - 45.
Mr István A. Aranyosi, The Doomsday Simulation Argument. Or Why Isn't the End Nigh, and You're Not Living in a Simulation.
D. J. Bradley (2005). No Doomsday Argument Without Knowledge of Birth Rank: A Defense of Bostrom. Synthese 144 (1):91 - 100.
Kevin B. Korb & Jonathan J. Oliver (1998). A Refutation of the Doomsday Argument. Mind 107 (426):403-410.
Added to index2011-08-01
Total downloads16 ( #146,415 of 1,696,541 )
Recent downloads (6 months)2 ( #247,412 of 1,696,541 )
How can I increase my downloads?