Communicating Uncertainty Karen Akerlof Ph D Research Assistant

Communicating Uncertainty Karen Akerlof, Ph. D Research Assistant Professor Center for Climate Change Communication George Mason University

What are the social science fields that study decision-making under uncertainty? Mostconditions of theseofsocial • Decision sciences scientists are psychologists, • Risk or are in perception fields that use • Human dimensions psychological theories • Communication (science communication, health communication) • Public policy

Risk technical The field risk perception • Risk equalsof probability times magnitude (psychometrics) has been driven by the question of • Risk is a situation or event where why technical experts and something of human value (including humans themselves) non-experts view riskshas so been put at stake and where the differently outcome is uncertain • Risk equals hazard times outrage emotional, value-based

Baruch Fischhoff Paul Slovic Decision Research Carnegie Mellon University of Oregon Daniel Kahneman Princeton

These fields are heavily quantitative: modeling; experimental research Van der Linden, S. (2015). The social-psychological determinants of climate change risk perceptions: Towards a comprehensive model. Journal of Environmental Psychology, 41, 112– 124.

Social science frequently follows government priorities: nanotechnology, disaster recovery (Hurricane Sandy), climate change … fisheries?

Goal To communicate the information that people need to make choices. * Social science can be used to inform decisions about WHAT to communicate and HOW to communicate it.

People Can View Physical Reality Very Differently

Factors that influence communication about uncertainty 1) Social context (trust; values; what is at “risk”? ) 2) Type of decision being informed (what types of technical information about uncertainty are needed) 3) “Curse” of expert knowledge 4) Heuristics and biases (that we all have)

Social context 1) Risk is socially constructed by different groups. Facilitate stakeholder selfidentification with the decision-making group. 2) Trust highly influences how people process risk. Instead of asking for trust, demonstrate accountability: transparency, external oversight, audits, advisory panels, contractual agreements.

Type of decision: how good are the predictions of outcomes? 1) Which option is best? Portray varied sources of uncertainty—not just variability in data but biases from judgement, assumptions, and methodological practices. Develop protocols for reporting these sources.

Fischhoff, B. , & Davis, A. L. (2014). Communicating scientific uncertainty. Proceedings of the National Academy of Sciences, 111(Supplement 4), 13664– 13671.

Type of decision: how well known are the scientific processes shaping outcomes? 2) What options are possible? Decision makers need to understand scientific processes, and related uncertainties, in order to consider their options. Lay and expert mental models of scientific processes frequently differ. Identify problem areas and shape communication accordingly.

Curse of expert knowledge 1) Lay interpretations of scientific terms may differ from experts. Use terms that are less likely to be confused. Instead of uncertainty use “range”; instead of error use “difference from the estimate. ” 2) Members of the public may not have pre-existing cognitive frameworks that allow them to easily understand highly technical information. Use analogies, visualizations, diagrams, summaries of most important points.

Heuristics and biases (that we all have) People use “heuristics” to make decisions quickly and easily. Heuristics like “availability, ” the examples we can easily recall, can strongly influence subsequent choices. If intuitions based on lay theories are wrong, recognize the reasonableness of the intuition, provide examples that are inconsistent with that view, and then explain the scientific evidence.

People Can View Physical Reality Very Differently But if we understand why, we may be able to move closer to agreement.

Citations: Trust Akerlof, K. , Rowan, K. E. , Fitzgerald, D. , & Cedeno, A. Y. (2012). Communication of climate projections in US media amid politicization of model science. Nature Climate Change, 2(9), 648– 654. Priest, S. H. , Bonfadelli, H. , & Rusanen, M. (2003). The “Trust Gap” Hypothesis: Predicting Support for Biotechnology Across National Cultures as a Function of Trust in Actors. Risk Analysis, 23(4), 751– 766. Sandman, P. M. (1993). Responding to Community Outrage: Strategies for Effective Risk Communication. AIHA.

Communicating uncertainty for decision-making Fischhoff, B. , & Davis, A. L. (2014). Communicating scientific uncertainty. Proceedings of the National Academy of Sciences, 111(Supplement 4), 13664– 13671. Rowan, K. E. , Botan, C. H. , Kreps, G. L. , Samoilenko, S. , & Farnsworth, K. (2009). Risk communication education for local emergency managers: Using the CAUSE model for research, education, and outreach. Handbook of Risk and Crisis Communication, 168– 191. Sterman, J. D. (2008). Risk communication on climate: mental models and mass balance. Science, 322(5901), 532– 533.

Communication barriers Budescu, D. V. , Broomell, S. , & Por, H. -H. (2009). Improving Communication of Uncertainty in the Reports of the Intergovernmental Panel on Climate Change. Psychological Science, 20(3), 299– 308. Morss, R. E. , Demuth, J. L. , & Lazo, J. K. (2008). Communicating Uncertainty in Weather Forecasts: A Survey of the U. S. Public. Weather and Forecasting, 23(5), 974– 991. Somerville, R. C. J. , & Hassol, S. J. (2011). Communicating the science of climate change. Physics Today, 64(10), 48– 53.

Contact: kakerlof@gmu. edu 703 993 6667