1. Risk, Uncertainty, and the Precautionary Principle
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. 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. 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. 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. 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. 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. 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. 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. 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. Applications for Climate Policy
12. The Cascade of Uncertainty
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. Iterative Risk Management Process
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. 7 Criteria for evaluating approaches to acceptable-risk
Comprehensive Logically sound Practical Open to evaluation
Politically acceptable Compatible with institutions Conducive to
learning