Richard Bradley| (Project Leader)

I will be working on a number of different topics over the period of the project, including:

(1) The classification of different types of uncertainty and the relationship between them;

(2) How imprecise probabilities and utilities should be revised;

(3) Models of decision making under severe uncertainty both about the state of the world and about how to value the consequences of them.

(4) The treatment of unawareness within theories of attitude revision.

Work relevant to the project:

1. Decision Theory with an Human Face, book manuscript under contract with Cambridge University Press

2. 'Types of Uncertainty,' (with M. Drechsler), currently under review.

3. 'Revising Incomplete Attitudes,' Synthese, 171 (2): 235-256, 2009.

4. 'The Kinematics of Belief and Desire,' Synthese, 56 (3): 513-535, 2007.

5. 'A Unified Bayesian Decision Theory,' Theory and Decision  63:233-263, 2007.


Roman Frigg|

Climate models become ever larger and more complex, the idea being that they provide ever more accurate and useful information. Can these models deliver can as advertised? Together with a group of scientists and philosophers at LSE, I will explore this question. We aim to provide in an in-depth exploration of how model uncertainty affects models' ability to make policy relevant forecasts, and to discuss the consequences of whatever limitations there are.

Work relevant to the project:

1. 'Probabilistic Forecasting: Why Model Imperfection Is a Poison Pill,' (with Seamus Bradley, Reason L. Machete and Leonard A. Smith), in Hanne Anderson, Dennis Dieks, Gregory Wheeler, Wenceslao Gonzalez and Thomas Uebel (eds): New Challenges to Philosophy of Science. Berlin and New York: Springer (forthcoming).

2. 'Laplace's Demon and the Adventures of his Apprentice,' (with Seamus Bradley, Reason L. Machete and Leonard A. Smith), Grantham Discussion Papers, forthcoming.

3. 'UKCP - A Critical Assessment,' (with Dave A. Stainforth and Leonard A. Smith), in progress.


Katie Steele|

Many recognise that climate policy decisions, at the regional level at least, are decisions under severe uncertainty. But what is the best way to formally represent or characterise any such uncertainty? My work will examine the extent to which, for climate models, this depends on i) the evidence at hand and the types of predictions this evidence supports; and  ii) the models for decision-making that are deemed appropriate.

Work relevant to the project:

1. ‘Climate Models, Calibration and Confirmation,’ (with Charlotte Werndl), The British Journal for the Philosophy of Science, forthcoming.

2. ‘What are the minimal requirements of rational choice? Arguments from the sequential-decision setting,’ Theory and Decision 68(4) (2010): 463–487.

3. 'Distinguishing indeterminate belief from ‘risk-averse’ preferences,' Synthese 158(2) (2007): 189–205.


Alex Voorhoeve|

Decision theorists distinguish risky situations in which we can assign probabilities to the outcomes of our actions from decisions under uncertainty, when we cannot. I'm interested how people make decisions under uncertainty and how we ought to make such decisions. In the context of this project, I plan to research these topics in the context of choosing climate policy, which is often regarded as a paradigm example of decision-making under uncertainty. Many studies report that people are averse to uncertainty. Some have also argued that we ought to be uncertainty averse in our decision-making. So far, my work suggests we ought to be sceptical about both these opinions.

Work relevant to the project:

1. 'How Much Ambiguity Aversion? Finding Indifferences between Ellsberg's Risky and Ambiguous bets', (with Ken Binmore and Lisa Stewart), Journal of Risk and Uncertainty, 45 (2012): 215-38.

2. 'Decide as You Would with Full Information!' (with Marc Fleurbaey), in Ole Norheim et al. (eds.) Inequalities in Health: Concepts, Measures, and Ethics. Oxford University Press, forthcoming.


Charlotte Werndl|

Climate models are known to be strongly imperfect in the sense that they only very crudely mirror certain aspects of the real-world target systems. Recent results suggest that for strongly imperfect models there can be a breakdown of probabilistic forecasts. I plan to identify what features of models lead to this breakdown. More generally, I will focus on the question what differences between a model and its real-world target system imply that the predictions of the model are reliable or become useless.

Work relevant to the project:

1.  'Climate Models, Confirmation and Calibration,'  (with Katie Steele), The British Journal for the Philosophy of Science, forthcoming.

2.  'What are the New Implications of Chaos for Unpredictability?' The British Journal for the Philosophy of Science  60 (2009): 195-220.

3.  'On Choosing Between Deterministic and Indeterministic Models: Underdetermination and Indirect Evidence,' Synthese, forthcoming.


Hykel Hosni|

Affiliated researcher on a Marie-Curie Fellowship

Under very specific conditions, probability constitutes a robustly justified model of uncertainty quantification. Yet, real-world decision-making abounds with complex problems in which probability appears to be of little applicability. I will tackle the question as to how we should extend probability to make rational decisions in those cases. This will throw new light on one of the most fundamental problems in the multifaceted field of uncertain reasoning: how to identify a satisfactory trade-off between foundational robustness and expressive power in the quantification of uncertainty.

Work relevant to the project:

1. Fedel, M., Hosni, H., & Montagna, F., "A logical characterization of coherence for imprecise probabilities". International Journal of Approximate Reasoning, 52(8), 1147–1170 (2011).

2. Hosni, H., "Towards a Bayesian theory of second-order uncertainty: Lessons from non-standard logics". In S. O. Hansson (Ed.), David Makinson on Classical Methods for Non-Classical Problems. Trends in Logic, Springer, forthcoming.


Casey Helgeson (Post Doc)

My work on the Managing Severe Uncertainty project aims to better integrate the scientific, ethical, and decision-theoretic aspects of climate policy decision-making. 

Work relevant to the project:

1. "The confirmational significance of agreeing measurements", Philosophy of Science, forthcoming.


Thomas Rowe (PhD Student)

Tom graduated from Manchester University with a BA in Politics, Philosophy and Economics. Before joining the project he studied for a research track MA in Political Theory at the University of Sheffield.


Silvia Milano (PhD Student)

Before coming to the LSE, Silvia studied Philosophy at the Scuola Normale Superiore of Pisa. She is interested in the relationship between group and individual decision making, and problems of ethical uncertainty.