عنوان

Scientific uncertainty and decision making

Number

TLets571150

Title Proper

Scientific uncertainty and decision making

General Material Designation

[Thesis]

First Statement of Responsibility

Bradley, Seamus

Name of Publisher, Distributor, etc.

London School of Economics and Political Science (University of London)

Date of Publication, Distribution, etc.

2012

Dissertation or thesis details and type of degree

Ph.D.

Body granting the degree

London School of Economics and Political Science (University of London)

Text preceding or following the note

2012

Text of Note

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

B Philosophy (General)

Bradley, Seamus

London School of Economics and Political Science (University of London)

Electronic name

p

[Thesis]

276903

a

Y