472. How to communicate uncertainty?
Invited abstract in session TA-61: Addressing behavioral issues of real-world problems 1, stream Behavioural OR.
Tuesday, 8:30-10:00Room: Maurice Keyworth G.31
Authors (first author is the speaker)
| 1. | Anna Cajochen
|
| Environmental Social Sciences (ESS), Eawag: Swiss Federal Institute of Aquatic Science and Technology | |
| 2. | Michael Siegrist
|
| D-USYS, ETH Zürich | |
| 3. | Judit Lienert
|
| Environmental Social Sciences (ESS), Eawag: Swiss Federal Institute of Aquatic Science and Technology |
Abstract
Environmental challenges such as water pollution must be addressed through effective strategies based on reliable information. However, information can be uncertain. Uncertainties stem from measurement inaccuracies, unknown causality, disagreement among experts, and unpredictable events. Uncertainty is unavoidable but should be considered for effective strategic decision-making. To date, little is known about how to best communicate uncertainty to stakeholders and the public. Reasons include the complexity of uncertainty itself and the interplay between communication formats, individual responses, and individual factors. This study examines the impact of different uncertainty communication formats on, for example, the understanding, and perception of uncertainty information. In an online survey, we randomly assign participants to experimental groups, which receive uncertain information about the effectiveness of wastewater infrastructure in preventing combined sewer overflows. We examine different uncertainty communication formats recommended in existing guidelines. This research aims to provide empirical evidence to support and refine the guidelines. It also seeks to identify straightforward ways for effectively communicating uncertainty to lay people. Developing effective and straightforward approaches can help ensure that uncertainty communication reaches a broad audience, enabling more inclusive decision-making on shared challenges like environmental issues.
Keywords
- Risk Analysis and Management
- Decision Analysis
Status: accepted
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