Classical, Modern & Post-Normal Classical, Modern & Post-Normal ScienceScience

the Truth!Classical:

•Observations•Sense experiments•Subjective judgments•Past experience

Absolute

Reductionist, “puzzle-solving”

Modern / Normal:•Exclusive, remote•Non-interdisciplinary•Experiments/models•Data analysis/interpretation•Hypothesis testing

•predictions •probabilities•possible explanations •disconnected policy•adversarial•communication gaps

“Post-Normal”•Inclusive•Natural & social sciences•Complexity/risk/urgency•Systems approach•Cost/benefits•Public debate

Precautionary, risk management

•shared decision making•problems solving •confidence/trust building•Anti-science perception

Perceptions of Perceptions of ScienceScience

God-like? Elitist? Crusading knight? Mad/evil?

Two Opposing Metaphors for Two Opposing Metaphors for Science: Science: God-likeGod-like or or GolemGolem??

• ““Ultimate source of Ultimate source of knowledge/wisdom.knowledge/wisdom.

• Operates in unencumbered, controlled Operates in unencumbered, controlled environment.environment.

• Strives for perfection.Strives for perfection.• Accountable, held to high standard.Accountable, held to high standard.

• A creature of our own design, neither good or A creature of our own design, neither good or bad. bad.

• Powerful, protective, follows orders. Powerful, protective, follows orders. • Clumsy and dangerous, must be controlled. Clumsy and dangerous, must be controlled. • Fallible = low expectations. Fallible = low expectations. • Can’t be blamed for mistakes if it is trying.Can’t be blamed for mistakes if it is trying.

Truth

The Snowball The Snowball EffectEffect

Climate Science Uncertainties

“Other” Uncertainties

Cascading Uncertainties in Climate Cascading Uncertainties in Climate ScienceScience

Emission scenarios

Carbon cycle response

Global climate

sensitivity

Regional climate change

scenarios

Range of possible impacts

Adapted from Schneider 1983

Scientists face important challenges in Scientists face important challenges in communicating science to non-scientistscommunicating science to non-scientists

• The nature of ‘normal’ scientific investigation and The nature of ‘normal’ scientific investigation and debatedebate– logic vs. cognitive processeslogic vs. cognitive processes– adversarial, not focused on consensus developmentadversarial, not focused on consensus development– debate primarily within disciplinesdebate primarily within disciplines

• IsolationismIsolationism– ““too busy” to talk to non-scientists!too busy” to talk to non-scientists!– rift between physical and social scientistsrift between physical and social scientists

• Inadequate training in communication skillsInadequate training in communication skills– dealing with mediadealing with media– addressing misinformationaddressing misinformation– understanding policy development processunderstanding policy development process

Can complex science be understood by the Can complex science be understood by the public?public?

• Yes, many successful examples !Yes, many successful examples !

• Knowledge from Scientific process Knowledge from Scientific process

• ““Step-back”, discuss and debunk science Step-back”, discuss and debunk science mythsmyths– Myth 1: science as a collection of established factsMyth 1: science as a collection of established facts– Myth 2: conflicting science presented in a Myth 2: conflicting science presented in a

balanced waybalanced way– Myth 3: science jargon as chief obstacleMyth 3: science jargon as chief obstacle

Interpretations of Global Climate Interpretations of Global Climate Science UncertaintiesScience Uncertainties• Scientists:Scientists:

intrinsic part of scienceintrinsic part of science too many variables to eliminatetoo many variables to eliminate can be reduced with more scientific informationcan be reduced with more scientific information general support of a general support of a ““precautionary” approach”.precautionary” approach”.

• Policymakers:Policymakers: science is sloppyscience is sloppy ““burden of proof”burden of proof” lack of/incomplete knowledge = bad sciencelack of/incomplete knowledge = bad science must have all the facts: decision making/policy must have all the facts: decision making/policy

implementation implementation little/no support of precautionary stepslittle/no support of precautionary steps

The Climate Uncertainty The Climate Uncertainty “Toolbox”“Toolbox”

Permutation

tests

Bootstrapping

Resampling

Stochastic models

Monte

Carlo

Bayesian

statisticsJackknife

Deterministic

models

Neural

networks

Fisherian statistics

Climate models

Likelihood-based

approaches

Scenario analysis

Communicating Uncertainties of Climate Communicating Uncertainties of Climate ChangeChange

• Increase science literacyIncrease science literacy

• Outreach materials: Hypothetical scientific investigations.Outreach materials: Hypothetical scientific investigations.

• Develop vivid narratives of potential harmDevelop vivid narratives of potential harm

• Address/communicate uncertainties to stakeholder communities.Address/communicate uncertainties to stakeholder communities.

• Understand decision making mechanics, assess values and Understand decision making mechanics, assess values and attitudesattitudes

• Develop an integrative (social-natural science), participatory Develop an integrative (social-natural science), participatory decision-making processdecision-making process

• Psychometric paradigm: people (focus on a range of qualitatively Psychometric paradigm: people (focus on a range of qualitatively distinctive factors that are irreducible by numbers) show a richer distinctive factors that are irreducible by numbers) show a richer rationality than experts (focus on quantity), risk perception in rationality than experts (focus on quantity), risk perception in social sciences, used to explain divergence between risk related social sciences, used to explain divergence between risk related judgmentsjudgments

• People influenced by whether risk is catastrophic , future People influenced by whether risk is catastrophic , future generations, involuntary incurred, , uncontrollable, delayed vs generations, involuntary incurred, , uncontrollable, delayed vs immediate, and particularly dreaded.immediate, and particularly dreaded.

Cass Sustein 2007: Columbia Law Review 107: 503-557

What are the likely climate changes What are the likely climate changes over the next century, or so??over the next century, or so??

• Most global warming projections are for a 4-10 F Most global warming projections are for a 4-10 F increase by 2100increase by 2100

• Virtually certain:Virtually certain: ~ ~ 95 to 100%95 to 100% – Warmer days and nights, fewer cold periods over most land Warmer days and nights, fewer cold periods over most land

areasareas

• Very likely: Very likely: ~ 67-95%~ 67-95%– Warm spells/heat waves, frequency increasing over most land Warm spells/heat waves, frequency increasing over most land

areasareas– Heavy and more frequent precipitation eventsHeavy and more frequent precipitation events

• Likely:Likely: ~ 33-67%~ 33-67%– Area affected by drought increasesArea affected by drought increases– Intense tropical cyclone activity increasesIntense tropical cyclone activity increases– Increased incidence of extreme high sea level (exclude Increased incidence of extreme high sea level (exclude

tsunamis)tsunamis)

Communicating Uncertainty:Communicating Uncertainty:Examples from Weather ForecastsExamples from Weather Forecasts

• Numerical probabilities:Numerical probabilities: – A 30 % chance of rain.A 30 % chance of rain.

• Qualitative or categorical forecastsQualitative or categorical forecasts:: – Today’s weather will be “fine”.Today’s weather will be “fine”.

Handmer et al. 2007

Communicating Uncertainty:Communicating Uncertainty:Examples from Weather Examples from Weather

ForecastsForecasts• Numerical probabilities:Numerical probabilities:

– high likelihood, tangible events high likelihood, tangible events – can be misinterpreted: where? when? how can be misinterpreted: where? when? how

long?long?– example: 30% chance of rainexample: 30% chance of rain

• a 30% chance of rain in the forecast area.a 30% chance of rain in the forecast area.• a 30% chance of rain at a specific location in forecast a 30% chance of rain at a specific location in forecast

area.area.• only 30% of the forecast area will be affected, if it does only 30% of the forecast area will be affected, if it does

rain.rain.• it will rain 30% of the day.it will rain 30% of the day.• it will rain 3 out of 10 days when rain is forecastedit will rain 3 out of 10 days when rain is forecasted

– not useful when:not useful when:• i.e. 0.0001% chance of as a severe event i.e. 0.0001% chance of as a severe event • Abstract, “invisible”, even catastrophic eventsAbstract, “invisible”, even catastrophic events• Public more concerned with issues of control, trust and Public more concerned with issues of control, trust and

equityequityHandmer et al. 2007

Decision-making Under Decision-making Under UncertaintyUncertainty

Decisions:Decisions: • based on likelihood of uncertain eventsbased on likelihood of uncertain events

– Uncertainties expressedUncertainties expressed• numerical form (odds) numerical form (odds) • subjective probabilistic statementssubjective probabilistic statements

• heuristicsheuristics– RepresentativenessRepresentativeness – degree of relationship, causality – degree of relationship, causality– Availability Availability – ease of instances/consequences imagined– ease of instances/consequences imagined– Adjustment/AnchoringAdjustment/Anchoring –initial value adjusted to yield final –initial value adjusted to yield final

answer (problem formulation or partial computation)answer (problem formulation or partial computation)

Tversky, A. and D. Kahneeman. (1974). Judgment under Uncertainty: Heuristics and Biases. Science 185: 1124-1131

Decision-making Under Decision-making Under UncertaintyUncertainty

• Task of choiceTask of choice– Framing Framing

• Relate decision making to similar problemsRelate decision making to similar problems• Used to determine outcome loss or gainsUsed to determine outcome loss or gains

– EvaluationEvaluation• Act to reduce loss probability, maximize gainsAct to reduce loss probability, maximize gains• Adopt risk averse stanceAdopt risk averse stance

• 3 subconscious processes 3 subconscious processes (heuristics)(heuristics):: – RepresentativenessRepresentativeness – degree of relationship, causality – degree of relationship, causality– Availability Availability – ease of instances/consequences imagined– ease of instances/consequences imagined– Adjustment/AnchoringAdjustment/Anchoring –initial value adjusted to yield final –initial value adjusted to yield final

answer (problem formulation or partial computation)answer (problem formulation or partial computation)

Patt, A. and S. Dessai. (2005). Communicating Uncertainty: lessons learned and suggestions for climate change assessment. C. R. Geoscience 337: 425-441

Tversky, A. and D. Kahneeman. (1974). Judgment under Uncertainty: Heuristics and Biases. Science 185: 1124-1131

Decision-making Under Decision-making Under UncertaintyUncertainty

• Stochastic uncertainties Stochastic uncertainties (unpredictability/surprises)(unpredictability/surprises)– Framing: (usually) in frequentist termsFraming: (usually) in frequentist terms– Uncertainty: probability expressed relative frequenciesUncertainty: probability expressed relative frequencies– Heuristic:Heuristic: Availability Availability = analogy = analogy– Evaluation: Less risk averse, under-estimate risk, less prone Evaluation: Less risk averse, under-estimate risk, less prone

to illogical choiceto illogical choice• Epistemic uncertaintiesEpistemic uncertainties (structural/ignorance)(structural/ignorance)

– Framing (often) in Bayesian termsFraming (often) in Bayesian terms– Uncertainties: ambiguous probability estimates, numerical Uncertainties: ambiguous probability estimates, numerical

ranges confidence, expert opinionranges confidence, expert opinion– Heuristic: Heuristic: RepresentativenessRepresentativeness = common, familiarity= common, familiarity – Evaluation: More risk averse, over-estimate risk, more prone Evaluation: More risk averse, over-estimate risk, more prone

to logic errorsto logic errors

Patt, A. and S. Dessai. (2005). Communicating Uncertainty: lessons learned and suggestions for climate change assessment. C. R. Geoscience 337: 425-441

Tversky, A. and D. Kahneeman. (1974). Judgment under Uncertainty: Heuristics and Biases. Science 185: 1124-1131

Decision-making Under Decision-making Under UncertaintyUncertainty

Decisions:Decisions: • based on likelihood of uncertain eventsbased on likelihood of uncertain events

– Uncertainties expressedUncertainties expressed• numerical form (odds) numerical form (odds) • subjective probabilistic statementssubjective probabilistic statements

• heuristicsheuristics– RepresentativenessRepresentativeness – degree of relationship, causality – degree of relationship, causality– Availability Availability – ease of instances/consequences imagined– ease of instances/consequences imagined– Adjustment/AnchoringAdjustment/Anchoring –initial value adjusted to yield final –initial value adjusted to yield final

answer (problem formulation or partial computation)answer (problem formulation or partial computation)

Tversky, A. and D. Kahneeman. (1974). Judgment under Uncertainty: Heuristics and Biases. Science 185: 1124-1131

Graphical

Communication of

Uncertain Quantiti

es

to Non-Technical

People

Risk Analysis 7 (4)

Ibrekk et a

l. 1987

*

9 graphical representations of the same snow fall predictions

*

Communicating Uncertainty:Communicating Uncertainty:Examples from Weather ForecastsExamples from Weather Forecasts

• Qualitative or categorical forecastsQualitative or categorical forecasts:: – ““Fine”Fine”– Also misinterpreted: does it meanAlso misinterpreted: does it mean

• No rain?No rain?

• Sunny/sunshine?Sunny/sunshine?

• Not too hot/moderate temperature?Not too hot/moderate temperature?

• Clear day/ not cloudy or overcast?Clear day/ not cloudy or overcast?

• Lovely weather/a nice day?Lovely weather/a nice day?

• No wind/light winds?No wind/light winds?

• Some cloud/may be overcast?Some cloud/may be overcast?

Handmer et al. 2007

Communicating Uncertainty:Communicating Uncertainty:When Uncertainties are InsurmountableWhen Uncertainties are Insurmountable

• ScenariosScenarios– Coherent, plausible, alternative representations of future Coherent, plausible, alternative representations of future

climateclimate– Projections/modeled responses (not forecasts) from climate Projections/modeled responses (not forecasts) from climate

“drivers”.“drivers”.– Descriptions: current states, drivers, step-wise changes, Descriptions: current states, drivers, step-wise changes,

future images.future images.– Assessments future climate conditions (very high Assessments future climate conditions (very high

uncertainties).uncertainties).– Assist in designing adaptation/mitigation strategiesAssist in designing adaptation/mitigation strategies– Provide better understanding of interactions/dynamicsProvide better understanding of interactions/dynamics

Outreach: Uncertainties of Climate ChangeOutreach: Uncertainties of Climate Change

• Increase science literacyIncrease science literacy

• vivid narratives of potential harm/benefitsvivid narratives of potential harm/benefits

• Communicate uncertainties to stakeholder communities.Communicate uncertainties to stakeholder communities.

• Assess values and attitudesAssess values and attitudes

• Develop an integrative (social-natural science) decision-making Develop an integrative (social-natural science) decision-making processprocess

• Psychometric paradigm: people (focus on a range of Psychometric paradigm: people (focus on a range of qualitatively distinctive factors that are irreducible by qualitatively distinctive factors that are irreducible by numbers) show a richer rationality than experts (focus on numbers) show a richer rationality than experts (focus on quantity), risk perception in social sciences, used to explain quantity), risk perception in social sciences, used to explain divergence between risk related judgmentsdivergence between risk related judgments

• People influenced by whether risk is catastrophic , future People influenced by whether risk is catastrophic , future generations, involuntary incurred, , uncontrollable, delayed vs generations, involuntary incurred, , uncontrollable, delayed vs immediate, and particularly dreaded.immediate, and particularly dreaded.

An Interesting Expert Opinion: An Interesting Expert Opinion: An Essay: Divergent American Reactions to Terrorism An Essay: Divergent American Reactions to Terrorism and Climate Changeand Climate Change

Terrorism:Terrorism:

• low probability, palpable, catastrophiclow probability, palpable, catastrophic• risks are immediate, short term risks are immediate, short term • Concern to US, Britain an allies. Concern to US, Britain an allies. • Perceived high risk recurrence Perceived high risk recurrence • neglect probability visual anger, fear, neglect probability visual anger, fear, • Huge costs justified to protect Huge costs justified to protect

national security benefits unimportant national security benefits unimportant • 2005-2006: $255 $318 billion 2005-2006: $255 $318 billion

committed to war on terror vs $312 committed to war on terror vs $312 billion for entire Kyoto protocol. billion for entire Kyoto protocol.

• Public opinion Public opinion – 2004 48% Britons: top global priority 2004 48% Britons: top global priority – 2006 80% Americans top global 2006 80% Americans top global

prioritypriority

Climate change:Climate change: • high probability, impalpable, high probability, impalpable,

catastrophiccatastrophic• Long-term risk, affect future Long-term risk, affect future

generations. generations. • Concern to other nations only Concern to other nations only • serious mitigative/adaptive action serious mitigative/adaptive action

unlikleyunlikley• climate change causes obscure climate change causes obscure

(uncertainties) (uncertainties) • people lack experience make risks people lack experience make risks

apparent, real or impending, apparent, real or impending, • cost benefits, cost benefits, • Public opinion Public opinion

– 2000 CC: ranked environment as 162000 CC: ranked environment as 16thth most important issue and 12most important issue and 12thth out of 13 out of 13 top environmental problems top environmental problems

– 2004: 63% Britons: top global 2004: 63% Britons: top global environmental issue.environmental issue.

Cass Sustein 2007: Columbia Law Review 107: 503-557

Similarities: potentially catastrophic outcomes, difficulty assigning probabilities to risks

Divergence: simple facts and political responses to each risk:

“We have to deal with this new type of threat [terrorism] in a new way we haven’t yet defined.. With a low-probability, high impact event like this.. if there is a 1% chance that Pakistani nuclear scientists are helping Al Qaeda build or develop a nuclear weapon, we have to treat it as a certainty in terms of our response” -- Dick Cheney, Former Vice-President

“Climate change is the most severe problem we are facing today - more serious than the threat from terrorism” – Sir David King Director, Smith School of Environment, Oxford; Research Director, Dept. of Physical Chemistry, Cambridge; Former Chief Scientific Advisor to Blair Administration.

An Interesting Expert Opinion: An Interesting Expert Opinion: An Essay: Divergent American Reactions to Terrorism An Essay: Divergent American Reactions to Terrorism

and Climate Changeand Climate ChangeCass Sustein 2007: Columbia Law Review 107: 503-557

“Any philosophy that in its quest for certainty ignores the reality of the uncertain in the ongoing processes of nature, denies the conditions out of which it arises.”

John Dewey, The Quest for Certainty, 1929

EpiloguEpiloguee

And now, the punch line(s)And now, the punch line(s)…………

• Climate change uncertainties: tremendous outreach challengesClimate change uncertainties: tremendous outreach challenges

• Uncertainties are cumulative: science to policy Uncertainties are cumulative: science to policy

• Climate change predictions: probabilistic context where possible.Climate change predictions: probabilistic context where possible.

• Scenarios: address insurmountable uncertainties.Scenarios: address insurmountable uncertainties.

• Integrative natural and social science approach to decision-making.Integrative natural and social science approach to decision-making.

• Outreach: science mechanics, sources of uncertainty, restore faith in Outreach: science mechanics, sources of uncertainty, restore faith in science, assess/understand heuristics, facilitate improved decision-science, assess/understand heuristics, facilitate improved decision-making, craft a responsible, informative and useful message.making, craft a responsible, informative and useful message.