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. Scientific research can reduce both kinds of uncertainty. Research directed at clarifying facts can provide imperfect answers to questions such as how well an oil pipeline will be maintained and monitored, how long the recovery period will be after bariatric surgery, and how much protection bicycle helmets afford. Research directed at clarifying values can provide imperfect answers to questions such as which charitable contributions give donors the greatest satisfaction, what happens when people commit to long-term goals, how much pleasure people can expect from windfalls (e.g., lottery winnings) and how much pain from misfortunes (e.g., severe accidents) (1, 2).Taking full advantage of scientific research requires knowing how much uncertainty surrounds it. Decision makers who place too much confidence in science can face unexpected problems, not realizing how wary they should have been. Decision makers who place too little confidence in science can miss opportunities, while wasting time and resources gathering information with no practical value. As a result, conveying uncertainty is essential to science communication.