1. 1. Risk, Uncertainty, and the Precautionary Principle
2. 2. Types of Probability a priori probability: known outcomes. ex. rolling a dice, roulette wheel Statistical probability: Observed frequencies used to predict outcomes. ex. odds of being killed on a single airline flight are 1/29 million Estimated probability (uncertainty) Most common, demands judgment
3. 3. Risk vs Uncertainty Risk: possible outcomes are known, as are their probabilities of occurring. Tangible and quantified. Uncertainty: outcomes and/or probabilities are either unknown or are estimated with low precision
4. 4. Risk vs Uncertainty cont'd... Whether a decision is made under risk or uncertainty depends on your confidence in the reliability of the probability estimate. Real-life situations usually involve uncertainty without exact probabilities available. So strictly speaking, almost all decisions are made under uncertainty. There are methods for trying to turn uncertainty into risk and manage that risk.
5. 5. Bayesian Probability Assigns a definite probability value to every statement about the world. Almost nothing (apart from axioms) is fully believed. Unfeasible: Doesn't help us achieve a practical belief system because we have limited cognitive capacities. In order to grasp complex situations (and make decisions), we need to reduce uncertainty to de facto belief rather than just probabilities.
6. 6. Unknown Possibilities Sometimes we don't have a complete list of the alternatives or consequences that should be taken into account. Creators of first atomic bomb worried that detonation might consume the atmosphere, kill all life on Earth. Still, no scientific calculation can remove apprehension about the possibility of something that nobody has been able to think of. But taking this logic to extreme paralyzes decision- making.
7. 7. Unknown Possibilities cont'd... When to account for unknown possibilities, when to ignore them? Novelty: new and untested phenomena should be treated with special care. System limitations: cautiousness important when potential impacts may have unlimited or very long lasting consequences. Complex systems: ecosystems and the atmospheric system may be impossible to restore after a major disturbance.
8. 8. Responding to Risk and Uncertainty Expected utility can be used to make decisions ex. betting $10 on red in Roulette pays 1:1 [($10)*(0.47)] + [(- $10)*(0.53)] = - $0.60 EV But the morally relevant aspects of situations of risk and uncertainty go far beyond the impersonal sets of consequences that expected utility operates on Proponents of nuclear energy emphasize how small the risks are (noun), whereas opponents question the very act of risking (verb) improbable but potentially devastating accidents.
9. 9. The Precautionary Principle Designed to ensure that the absence of scientific certainty isn't used as a reason for postponing actions that could protect people and environment when there's a credible threat of serious or irreversible harm. Maximin approach: choose the alternative that maximizes the minimum possible outcome. Useful when the negative outcome is ruinous. But ignores the probability of the ruinous outcome as well as potentially forsaken benefits.
10. 10. Principle of Bounded Subadditivity An event has more psychological impact when it turns impossibility into possibility, or possibility into certainty, than when it merely makes a possibility more likely. ex. Greater impact of changing from 0.9 to 1 or from 0 to 0.1 than changing the probability from 0.3 to 0.4 Biopsy example People value the elimination of a hazard more than a comparable reduction in its likelihood
11. 11. Applications for Climate Policy
12. 12. The Cascade of Uncertainty
13. 13. Approaches to acceptable-risk decisions Formal Analysis: cost-benefit analysis and decision analysis Formalized prescriptive procedure Complex problems decomposed into more manageable components to be studied Bootstrapping: use tried and tested methods Historical experience and standards prescribe future action Professional Judgment: alternatives emerge from decisions of qualified experts They may use formal analysis, but their own best judgment is final arbiter of whether or not to accept a given risk
14. 14. Iterative Risk Management Process
15. 15. Framing and Decision Processes Predict-then-act (aka top-down, science-first, scenario approach) Impact uncertainty described independently of other parts of the decision problem Probability estimates followed by impact projections Assess-risk-of-policy (aka bottom-up, context- first, vulnerability approach) Starts with decision-making context Uncertainty description customized to focus on key factors and goals as decided by policy-makers
16. 16. 7 Criteria for evaluating approaches to acceptable-risk Comprehensive Logically sound Practical Open to evaluation Politically acceptable Compatible with institutions Conducive to learning