Scientific uncertainty and decision making

مرکز و کتابخانه مطالعات اسلامی به زبان های اروپایی

منو

" Scientific uncertainty and decision making "
Bradley, Seamus

Document Type	:	Latin Dissertation
Record Number	:	1099361
Doc. No	:	TLets571150
Main Entry	:	Bradley, Seamus
Title & Author	:	Scientific uncertainty and decision making\ Bradley, Seamus
College	:	London School of Economics and Political Science (University of London)
Date	:	2012
student score	:	2012
Degree	:	Ph.D.
Abstract	:	It is important to have an adequate model of uncertainty, since decisions must be made before the uncertainty can be resolved. For instance, flood defenses must be designed before we know the future distribution of flood events. It is standardly assumed that probability theory offers the best model of uncertain information. I think there are reasons to be sceptical of this claim. I criticise some arguments for the claim that probability theory is the only adequate model of uncertainty. In particular I critique Dutch book arguments, representation theorems, and accuracy based arguments. Then I put forward my preferred model: imprecise probabilities. These are sets of probability measures. I offer several motivations for this model of uncertain belief, and suggest a number of interpretations of the framework. I also defend the model against some criticisms, including the so-called problem of dilation. I apply this framework to decision problems in the abstract. I discuss some decision rules from the literature including Levi's E-admissibility and the more permissive rule favoured by Walley, among others. I then point towards some applications to climate decisions. My conclusions are largely negative: decision making under such severe uncertainty is inevitably difficult. I finish with a case study of scientific uncertainty. Climate modellers attempt to offer probabilistic forecasts of future climate change. There is reason to be sceptical that the model probabilities offered really do reflect the chances of future climate change, at least at regional scales and long lead times. Indeed, scientific uncertainty is multi-dimensional, and difficult to quantify. I argue that probability theory is not an adequate representation of the kinds of severe uncertainty that arise in some areas in science. I claim that this requires that we look for a better framework for modelling uncertainty
Subject	:	B Philosophy (General)
Added Entry	:	London School of Economics and Political Science (University of London)