My research focuses on policy decision-making about highly uncertain sciences. I have done a lot of work with one case study: insurance against damage from hurricanes in the North Atlantic. I am also interested in formal epistemology more broadly, and in the philosophy of scientific models.

My blog contains a section of research-related posts. You can find more formal examples of my work below.


  • 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

Work in progress

  • Modelling and Formal Epistemology (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.

  • 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.

    • Deference and belief revision (under review)

    I criticise two approaches to expert testimony: supra-Bayesianism and deference as a constraint on priors (DC). 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. 

    • Scoring rules, expert disagreement and values (draft available)

    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. 

    • Against aggregation

    I argue against the aggregation of model outputs using a weighted average, looking at the case of hurricane model


    Physics research

    My Master’s research was in particle physics.