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)
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.