My research focuses on decision-making under severe uncertainty. I mostly focus on policy decisions, using highly uncertain scientific evidence. I also have broad interests in formal epistemology and the philosophy of scientific models.
Published work is listed first, followed by draft papers organised under three broad research projects: models and climate science, severe uncertainty, and modelling in philosophy. My PhD thesis is also available online: Policymaking under scientific uncertainty.
- Making confident decisions with model ensembles, forthcoming in Philosophy of Science. Co-authors: Richard Bradley and Roman Frigg [preprint]
We apply the “confidence” approach developed by Hill and Bradley to the case of hurricane models, demonstrating a method that can be generalised to decision-making with ensembles of structurally different models
- Following the Science: Pandemic Policy Making and Reasonable Worst-Case Scenarios, (2021), LSE Public Policy Review [link]
The UK has been ‘following the science’ in response to the COVID-19 pandemic in line with the national framework for the use of scientific advice in assessment of risk. We argue that the way in which it does so is unsatisfactory in two important respects. Firstly, pandemic policy making is not based on a comprehensive assessment of policy impacts. And secondly, the focus on reasonable worst-case scenarios as a way of managing uncertainty results in a loss of decision-relevant information and does not provide a coherent basis for policy making.
- Expert deference as a belief revision schema, (2020) Synthese [link]
I criticise two approaches to expert testimony: supra-Bayesianism and deference as a constraint on priors. I develop an alternative model of expert deference: deference as a belief revision schema. Inspired by Richard Jeffrey’s strategy for model uncertain belief revision, I show how deference can be considered as an exogenous constraint on a posterior belief state in a way that does not require any particular priors. I argue that this approach resolves or partially mitigates the problems I raised for the two, more standard, approaches.
Models and climate science
I am interested in a number of questions about how complex simulation models are used in climate science, and in particular to support decision-making using climate science.
- A decision-theoretic account of useful information from climate science (new project)
How can climate scientists contribute to decision-making about climate adaptation? Using a decision table as a framing device, I outline a much wider role for scientists at all stages of the decision process.
- Against aggregation (draft)
I argue against the aggregation of model outputs using a weighted average, looking at the case of hurricane models. I examine various motivations for averaging, and show that they fail to provide a plausible justification for the case of model outputs.
Modelling in philosophy
I am exploring the idea that modelling, as a methodology, is useful in philosophy.
- Do Formal Epistemology and Decision Theory use the scientific method of “modelling”? (under review)
I have developed an analysis of formal philosophy (i.e., using mathematics) as instances of modelling. I argue that they should be analysed and understood in terms of prominent approaches to scientific models in the philosophy of science literature, such as the DEKI account of representation. I discuss how normativity can be incorporated into a theory of modelling.
- Does normative ethics use the scientific method of “modelling”? (under review)
I argue that elements of modelling are widespread in ethics. I propose that we can construe general moral “theories”, like utilitarianism, as models—idealised, domain-specific, workings out of particular rightmakers and goodmakers—and that doing so offers us (1) a plausible interpretation of these theories, (2) an explanation of the diversity of theories on offer, and (3) an explanation of their limitations. There are several consequences to this view. First, we get a new way of understanding what is going on (and going wrong) in the theory/anti-theory debate in ethics. Second, we get a new way of understanding impossibility theorems in population ethics, and their bearing on ethics as a whole. Finally, I claim that the fact that ethicists have (unknowingly) been modelling comes with certain methodological constraints for them. Most notably, models are not sensitive to counterexamples in the way that much of ethical theory is taken to be.
I am interested in developing decision-theoretic and epistemic accounts of and tools for realistic agents, who don’t meet the exacting idealisations of theories like Bayesianism.
- A two-stage model for awareness growth (under review)
I am developing an account of rational awareness growth. It is a two-stage model: (1) The agent becomes aware of new possibilities and determines how they relate to previously known possibilities. Here I propose a simple model using elementary lattice theory. (2) The agent forms attitudes to the new possibilities, constrained by their prior belief state. The second stage is a development of the family of views known as “reverse Bayesianism” and is a direct descendant of Richard Bradley’s proposal in his book Decision theory with a human face.
- Scoring rules, expert disagreement and values (draft )
I examine the problem of expert disagreement, and whether opinion pooling is a viable method for policymakers to resolve such disagreement. I argue that there is significant utility to such methods, but that they require technical and value judgements in the selection of a scoring rule. Policymakers should develop these technical skills, and the discussion on opinion pooling should reflect that it is not a purely epistemic procedure.
My Master’s research was in particle physics.
- (Defunct) Working paper on effective field theories as a method in Weak physics (2014)
- Analysis of the lepton polarisation asymmetries of B¯ → K¯ 2(1430) ℓ+ ℓ− decay, Eur. Phys. J. C (2011) 71: 1751