(Un)certainty, Expertise, & Media

Description

Key Questions:

  • How do various types of people -- like scientists, journalists, etc. -- communicate about the uncertainty inherent in all science?
  • Who gets to be an expert?
  • How do people collaborate in conversation to establish certain people as experts or not?

Science is a way of building knowledge about the world, and building knowledge requires us to communicate about the things we do not and cannot know, and the things we are more and less certain about.

One useful way of carving up the notion of uncertainty is the distinction between probabilistic and epistemic uncertainty (e.g., Peters & Dunwoody, 2016). Probabilistic uncertainty is due to randomness, even if that randomness is known: it’s impossible to know the outcome of a roll of fair dice until you actually roll them, but you can quantify the likelihood of all possible outcomes in advance. Epistemic uncertainty is due to lack of knowledge: what if you rolled what you thought was a pair of dice, but it was actually a pair of alphabet blocks or ice cubes?

Both of these are key to science communication. Margins of error, p-values, and other statistical terms are all ways of communicating probabilistic uncertainty. Meanwhile, consensus about the boundaries of what we do and don’t know is a prerequisite for meaningful scholarly contribution.

We’re interested in how experts from different fields, journalists, and educators, communicate and understand both types of uncertainty in a range of contexts. We’re also interested in different ways to carve up uncertainty – are there other types that are particularly meaningful? We’re interested in how all this looks different in various contexts. Finally, we’re also interested in the connection between uncertainty and expertise: How does being clear about what you don’t know affect the construction of expertise?