Communicating scientific uncertainty

TLDR

Scientific uncertainty is inherent, and its effective communication is crucial because the information required varies with the type of decision—whether seeking a signal, choosing among options, or creating new options. The study aims to improve decision‑making, science quality, and support for science by examining how to characterize, assess, and convey uncertainties across three decision types. The authors propose a minimal‑burden protocol that summarizes multiple uncertainty sources in standard terms to gradually educate decision‑makers.

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.