Sigrid Keydana, in her post Plus/minus what? Let’s talk about uncertainty (talk) — recurrent null, said
What’s the most important thing about communicating uncertainty? You’re doing it
Really?
Here, for example, a graph from a blog post
The graph clearly “communicates” the uncertainty but does it really convey it? Would you consider the lines and their corresponding confidence intervals very uncertain had you not seen the points?
What if I tell you that there’s a 30% Chance of Rain Tomorrow? Will you know what it means? Will a person who doesn’t operate on numbers know what it means? The answer, to both these questions, is “no”, as is shown by Gigerenzer and his collaborators in a 2005 paper.
Communicating uncertainty is not a new problem. Until recently, the biggest “clients” of uncertainty communication research were the weather forecasters. However, the recent “data era” introduced uncertainty to every aspect of our personal and professional lives. From credit risk to insurance premiums, from user classification to content recommendation, the uncertainty is everywhere. Simply “doing” uncertainty communication, as Sigrid Keydana from the Recurrent Null blog suggested isn’t enough. The huge public surprise caused by the 2016 US presidential election is the best evidence for that. Proper uncertainty communication is a complex topic. A good starting point to this complex topic is a paper Visualizing Uncertainty About the Future by David Spiegelhalter.
Boris Gorelik 