The optimism gap: lay prescriptions for characterizing, estimating, and communicating about uncertainty

Being able to accurately estimate the likelihood of critical events is crucial for wise decision making both at the individual and public-policy levels. However, is accuracy always what people want? More generally, when faced when an uncertain outcome, what do people believe is the best outlook—an optimistic, pessimistic, or realistic one—that others should employ to make the best judgment?

In this thesis, I explain how different ways of asking people their recommended levels of optimism can have a dramatic influence on whether people seem to support having optimistically-biased expectations for uncertain events. I found that people do not generally recommend being overly optimistic, meaning they do not recommend that people overestimate the likelihood of desirable events. I also examined if people supposed having optimistically or pessimistically-biased expectations about future COVID-19 and weather-related events. For those events, people did not systematically prescribe optimistic estimations of key events. In fact, for both estimating likelihoods about potential, immediate problems such as contracting COVID-19 and distant, in the future problems, such as a sea-level rise, people thought other people should be pessimistic about crisis-related outcomes.

Knowing if people endorse being optimistic or pessimistic about future events is ultimately important for practical applications, such as the communication between policy makers and laypeople. Generally, a more nuanced understanding of how people estimate and think about prescriptions under uncertainty is ultimately critical for improving decisions about, and preparations for, important life events.