Cognitive Biases and Environmental Decision Making
Overarching Proposal Question
How do cognitive biases influence decisions
related to water allocation?
Proposal Foci
Short term choice preferences:
economic vs. ecological impacts
Long tem choice preferences
Group D-M Structure influence individual biases
Human Cognition and Motivation
• Limited attention and processing capacity
• Limited emotional capacity
• Multiple goals and multiple modes of making
decisions
trial & error based system
These limitation can be mediated by controllable
factors…
Information Provision
(type & forms)
Decision making
(structure & process)
Scientific community is extremely concerned about
environmental issues, how about the public?
Worry is a Function of Our Perception of Risk
Dual Processing
Systems
ANALYTIC
(Risk = Probability of Outcome X Consequence)
‘newer’ system
AFFECTIVE
(Risk as Feelings)
Objective Risk ≠ Subjective Risk
Perceived Risk correlated with dread risk and unknown
risk
Vampire Protection Kit, 1897
Low real hazard, high concern for protection
How Close is the Threat? Spatial & Temporal Dimensions
Bruegel the Elder’s “Landscape with the fall of Icarus” (1555)
Related econspeak…
Hyperbolic Discounting
(inconsistent valuation over time)
Loss aversion /Status quo biases
(current baseline taken as optimal refernce point)
Finite Pool of Worry
Ranking of Priorities for US Policymakers
(2008 National Survey – “Very High” Category)
1.Economy
2.Deficit
3.Iraq & Afghanistan Wars
4.Health Care
5.Terrorism
6.Social Security
7.Education
8.Tax Cuts
9.Illegal Migration
10.Global Warming (21%)
11.Abortion
Leiserowitz et al. 2008
Single Action Bias
Weber 1997
Connecting Impacts & Competing Worries
Source: South Florida Water Management District
Lay
Leiserowitz and Broad 2008
If we’re not worried, why all the debate?
Framing & Ideology (not facts) Dominate
Tim Calver photo
Support for Policies
(surcharges for gas, clean energy, air travel)
Carbon TAX vs. Carbon Offset
Mean Support for Regulation
3
2
1
Offset
Tax
0
-1
-2
-3
Democrat
Independent
Republican
Carbon TAX vs. Carbon Offset
Mean Support for Regulation
3
2
1
Offset
Tax
0
-1
-2
-3
Democrat
Independent
Republican
Conflicting Mental Models
Mental Models Differ Dramatically
Climate Expert
-------------------------------------------------------------------------------------------------------------------Farmer
Hansen et al. 2004
Communicating Probabilistic Information
Broad et al. 2007
Risk Communication and Trust in Information Provider
“How much do you trust the following groups to tell
you the truth about global warming?”
(7%)
(83%)
(10%)
Source: Leiserowitz, January 2003 (n = 549)
WSC Groups
Informational Needs
Impacts Info needed by behavioral group:
Interesting
S-B Stuff
-ecological impacts
-environmental impacts
-visualization tools & scenarios
-uncertainty characterizations
Preference
Characterization
Behavioral Experiments, Surveys,
Focus groups, Ethnography
Under different
conditions –
type of info/D-M
structure
What do you need and when?
Stuff that interests us
group versus individual decision dynamics?
how people make decisions that play out over
long timeframes?
How to convey probabilistic information?
How do people tradeoff outcomes that have
different hedonic properties?
Unknown Risk
GW
Controllable
(low dread)
Uncontrollable
(high dread)
CC
water
Well-known Risk
Courtesy of Paul Slovic
Challenges
• Temporal Tradeoffs
• Social Tradeoffs
• Risk and Uncertainty & Risk Perception
Humans are not good at Risk Assessment
Temporal and Spatial Challenge:
Connect to salient emotions – e.g., ocean warming  human health
Complex connections and competing issues:
Connect impacts – e.g., acidification  coral reefs  tourism  economy
Framing & Ideology
Multiple frames and information sources appropriate for different groups
“Checklist for Communication”
•
•
•
•
•
•
•
Balancing Affective vs Analytic
Temporal and Spatial Distance
Mental models
Finite pool of worry
Single action bias
Interpretive Communities (‘know thy audience’)
Intermediary orgs & group processes
– Role models
– Imitation
• Decision Architecture
– Opt in/out, anchor pts.
– Social distance
Limited attention and processing capacity
• Need to attend selectively
– Guided by expectations (values, beliefs) and goals
• Illinois farmers in early 1990s (Weber, 1997)
• Using uncertainty about a future hazard as an excuse to ignore it
• Use of simple emotion- and association-based processes over
effortful analytic processes
– Learning by getting hurt rather than by instruction
• Need to encode and evaluate locally
– Thurber story: “Compared to what?”
Problems with Actions Guided (solely) by Worry
• Single action bias
– Tendency to engage in a single risk reduction or risk
management behavior when action is triggered by concern
(rather than analysis)
• Argentine farmers concerned about climate change engage
in either production, pricing, or policy path to protection,
but not all three (Weber, 1999)
• Finite pool of worry
– Increases in concern about one risk are accompanied by
decreases in another (Weber , 2006)
Lay Person Ranking of Hazards