Probability as Possibility Spaces: Communicating Uncertainty to Policymakers

Abstract:

One problem facing the sciences is communicating results and recommendations to policymakers. This is perhaps particularly difficult in the geosciences where results are often based on probabilistic models, as probability is often and unduly equated with a specific kind of uncertainty or unreliability in the results. This leads to a great deal of miscommunication and misguided policy decisions. It is, then, valid to ask how scientists should talk about probability, uncertainty, and models in a way that correctly conveys what the users of these models intend. What I propose is a new way to think and, importantly, talk about probability which will hopefully make this much more transparent to both users and policy makers. Rather than using a frequentist (prior percentages) or Bayesian (observer uncertainty) framework, we should talk about probability as a tool for defining a possibility space for measurements. This model is conceptually simple and makes probability a tool of refinement rather than a source of inaccuracy. A similar possibility-space model has proven useful in the climate sciences and there is good reason to believe it will have similar applications in hydrology.