Transcript the Presentation Here.

Communicating Uncertainty
Karen Akerlof, PhD
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:
[email protected]
703 993 6667