title: Communicating scientific uncertainty.
abstract: All science has uncertainty. Unless that uncertainty is communicated effectively, decision makers may put too much or too little faith in it. The information that needs to be communicated depends on the decisions that people face. Are they (i) looking for a signal (e.g., whether to evacuate before a hurricane), (ii) choosing among fixed options (e.g., which medical treatment is best), or (iii) learning to create options (e.g., how to regulate nanotechnology)? We examine these three classes of decisions in terms of how to characterize, assess, and convey the uncertainties relevant to each. We then offer a protocol for summarizing the many possible sources of uncertainty in standard terms, designed to impose a minimal burden on scientists, while gradually educating those whose decisions depend on their work. Its goals are better decisions, better science, and better support for science.
authors.affiliation: Departments of Engineering and Public Policy and Social and Decision Sciences, Carnegie Mellon University, Pittsburgh, PA 15213-3890 baruch@cmu.edu.
authors.forename: Baruch
authors.initials: B
authors.lastname: Fischhoff
authors.affiliation: Departments of Engineering and Public Policy and.
authors.forename: Alex L
authors.initials: AL
authors.lastname: Davis
mesh_terms: D003142:Communication; D003657:Decision Making / Q000502:physiology*; D006801:Humans; D033181:Information Dissemination / Q000379:methods*; D008962:Models, Theoretical; D012586:Science; D035501:Uncertainty
keywords: expert elicitation; expert judgment; mental models; risk; science communication