Cognitive Biases and Environmental Decision Making

1. Cognitive Biases and Environmental Decision Making

2. 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

3. Human Cognition and Motivation • Limited attention and processing capacity • Limited emotional capacity • Multiple goals and multiple modes of making decisions trial & error based system

4. These limitation can be mediated by controllable factors… Information Provision (type & forms) Decision making (structure & process)

5. Worry is a Function of Our Perception of Risk Scientific community is extremely concerned about environmental issues, how about the public? ANALYTIC (Risk = Probability of Outcome X Consequence) ‘newer’ system Dual Processing Systems AFFECTIVE (Risk as Feelings)

6. Objective Risk ≠ Subjective Risk Perceived Risk correlated with dreadriskand unknown risk

7. Vampire Protection Kit, 1897 Low real hazard, high concern for protection

8. How Close is the Threat? Spatial & Temporal Dimensions Bruegel the Elder’s “Landscape with the fall of Icarus” (1555)

9. Related econspeak… Hyperbolic Discounting (inconsistent valuation over time) Loss aversion /Status quo biases (current baseline taken as optimal refernce point)

10. Finite Pool of Worry Ranking of Priorities for US Policymakers (2008 National Survey – “Very High” Category) Economy Deficit Iraq & Afghanistan Wars Health Care Terrorism Social Security Education Tax Cuts Illegal Migration Global Warming (21%) Abortion Leiserowitz et al. 2008

11. Single Action Bias Weber 1997

12. Connecting Impacts & Competing Worries Source: South Florida Water Management District

13. Lay Leiserowitz and Broad 2008

14. If we’re not worried, why all the debate?

15. Framing & Ideology (not facts) Dominate Tim Calver photo

16. Support for Policies (surcharges for gas, clean energy, air travel) Carbon TAX vs. Carbon Offset 3 2 1 Mean Support for Regulation Offset 0 Tax -1 -2 Democrat Independent Republican -3

17. Carbon TAX vs. Carbon Offset 3 2 1 Mean Support for Regulation Offset 0 Tax -1 -2 Democrat Independent Republican -3

18. Conflicting Mental Models

19. Mental Models Differ Dramatically Climate Expert --------------------------------------------------------------------------------------------------------------------- Farmer Hansen et al. 2004

20. Communicating Probabilistic Information Broad et al. 2007

21. Risk Communication and Trust in Information Provider “How much do you trust the following groups to tell you the truth about global warming?” (83%) (10%) (7%) Source: Leiserowitz, January 2003 (n = 549)

22. WSC Groups Informational Needs Interesting S-B Stuff Impacts Info needed by behavioral group: -ecological impacts -environmental impacts -visualization tools & scenarios -uncertainty characterizations Preference Characterization Under different conditions – type of info/D-M structure Behavioral Experiments, Surveys, Focus groups, Ethnography

23. 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?

24. Unknown Risk GW Uncontrollable (high dread) Controllable (low dread) CC water Courtesy of Paul Slovic Well-known Risk

25. Challenges • Temporal Tradeoffs • Social Tradeoffs • Risk and Uncertainty & Risk Perception

26. 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

27. “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

28. 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?”

29. 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)

30. Lay Person Ranking of Hazards