Cranky Uncle - a multi-lingual critical thinking game to build resilience against climate misinformation
Abstract
Inoculation theory provides a framework for responding to misinformation about climate change. This involves explaining the misleading rhetorical techniques and logical fallacies used to mislead. Inoculation has been found to be effective in neutralizing misinformation casting doubt on the scientific consensus on human-caused global warming. However, there are many misinformation techniques and inoculating people against them all is a communication and education challenge. Games offer engaging tools for incentivizing people to repeatedly perform misinformation-spotting tasks in order to build up their critical thinking skills. Games that are fun to engage with while serving a useful educational purpose are known as serious games, and are already being explored as a tool for building resilience against misinformation, using an approach known as active inoculation. Typically, inoculation interventions are passive, with messages received in a one-way direction from communicator to audience. In contrast, active inoculation involves participants in an interactive inoculation process - having them learn the techniques of science denial by ironically learning to use the misleading techniques themselves. The Cranky Uncle game adopts an active inoculation approach, where a "cranky uncle" cartoon character mentors players to learn the techniques of science denial. Cranky Uncle is a free game available on iPhone (sks.to/crankyiphone) and Android (sks.to/crankyandroid) smartphones as well as web browsers (sks.to/crankybrowser). The player's aim is to become a "cranky uncle" who skillfully applies a variety of logically flawed argumentation techniques to reject the conclusions of scientific communities. By adopting the mindset of a cranky uncle, the player develops a deeper understanding of science denial techniques, thus acquiring the knowledge to resist misleading persuasion attempts in the future.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2022
- Bibcode:
- 2022AGUFMED11A..02W