Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Break-out session Uncertainty, assumptions and

value commitments

• Jeroen van der Sluijs (Chair)• Naomi Oreskes (key-note)• Barbara Regeer (young researcher)• Anne Myhr (rapporteur)

Copernicus InstituteInterfaces between Science & Society, Milano, 27-28 November 2003

Towards multi-dimensional uncertainty assessment for

complex environmental problems

Jeroen van der Sluijs (UU Copernicus Institute)

j.p.vandersluijs@chem.uu.nl

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Insights on uncertainty• Uncertainty is partly socially constructed and its

assessment always involves subjective judgement• Omitting uncertainty management can lead to scandals

and crisis; undermines trust in the science• More research does not necessarily reduce uncertainty

– may reveal unforeseen complexities– irreducible uncertainty (intrinsic or practically)

• High quality low uncertainty• Shift in focus needed from reducing uncertainty towards

a systematic management of uncertainty and value loadings

• Uncertainty is a multi-dimensional concept and can manifest itself at different locations

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Locations of uncertainty• Sociopolitical and institutional context• System boundary & problem framing• Model

– Model structure – Assumptions– Parameters

• Inputs– Scenarios– Data

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Dimensions of uncertainty

• Technical (inexactness)• Methodological (unreliability)• Epistemological (ignorance)• Societal (limited social

robustness)

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Code Proxy Empirical Method Validation

4 Exact measure Large sampledirect mmts

Best availablepractice

Compared withindep. mmts ofsame variable

3 Good fit formeasure

Small sampledirect mmts

Reliable methodcommonlyaccepted

Compared withindep. mmts ofclosely relatedvariable

2 Well correlated Modeled/deriveddata

Acceptablemethod limitedconsensus onreliability

Compared withmmts notindependent

1 Weak correlation Educated guesses/ rule of thumb est

Preliminarymethods unknownreliability

Weak / indirectvalidation

0 Not clearlyrelated

Crude speculation No discerniblerigour

No validation

NUSAP: Qualified QuantitiesExample pedigree matrix:

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Sensitivity

Pedigree weakstronglow

high

NUSAP Diagnostic Diagram

Dangerzone

Safezone

Copernicus InstituteInterfaces between Science & Society, Milano, 27-28 November 2003

Method for analysis of assumptions

Applied toEO5 Environmental Indicators

(Penny Kloprogge)

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Calculation chain ozone deaths & hospital admittances

1 Societal/demographical developments2 VOC and NOx emissions in the Netherlands

and abroad 3 Ozone concentrations 4 Potential exposure to ozone5 Number of deaths/hospital admittances

due to exposure

What are key-assumptions in this calculation and what is their pedigree?

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Value loading can be in: practical / disciplinary / epistemic / socio-political sense

Pedigree criteria for reviewing assumptions:• Plausibility• Inter-subjectivity peers• Inter-subjectivity stakeholders• Choice space• Influence of situational restrictions (time, money)• Sensitivity to view and preferences of analyst• Estimated influence on results

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Workshop reviewing assumptions

• Completion of list of key assumptions

• Rank assumptions according to importance

• Elicit pedigree scores

• Evaluate method

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Key assumptions ozonedeaths and hospital admittances

• Uncertainty mainly determined by uncertainty in Relative Risk (RR)

• No differences in emissions abroad between the two scenarios

• Ozone concentration homogeneously distributed in 50 x 50 km grid cells

• Worst case meteo now = worst case future• RR constant over time (while air pollution

mixture may change!)• Linear dose-effect relationship

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

Example “traffic light” graph

Assumption that there is a linear dose-effect relationship

Copernicus InstituteInterfaces between Science & Society, Milano, 27-11-2003 more info: www.nusap.net

ConclusionsNUSAP system Can address all locations and dimensions of uncertainty Provides framework for synthesising qualitative and

quantitative assessments of uncertainty Structures in depth review of strengths and weaknesses

of knowledge bases and of assumptions Helps to focus research efforts on most problematic

model components Can be used interactively in extended peer processes to

structure the critical appraisal of knowledge bases for (sustainability) policies.