Cognitive Biases and Environmental Decision Making Overarching Proposal
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
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: -ecological impacts -environmental impacts -visualization tools & scenarios -uncertainty characterizations Behavioral Experiments, Surveys, Focus groups, Ethnography Interesting S-B Stuff Preference Characterization 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 Slovi
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
“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 1990 s (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
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