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Managing Uncertainty in science for suSTainability future research challenges for Europe

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Title: Managing Uncertainty in science for suSTainability future research challenges for Europe


1
Managing Uncertainty in science for
suSTainability future research challenges for
Europe
  • Jeroen van der Sluijs (UU Copernicus Institute)
  • j.p.vandersluijs_at_chem.uu.nl

2
Uncertainty in knowledge based society the
problem
  • 1984 Keepin Wynne
  • Despite the appearance of analytical rigour,
    IIASAs widely acclaimed global energy
    projections are highly unstable and based on
    informal guesswork. This results from inadequate
    peer review and quality control, raising
    questions about political bias in scientific
    analysis.

3
RIVM / De Kwaadsteniet (1999)
  • RIVM over-exact prognoses based on virtual
    reality of computer models
  • Newspaper headlines
  • Environmental institute lies and deceits
  • Fuss in parliament after criticism on
    environmental numbers
  • The bankruptcy of the environmental numbers
  • Society has a right on fair information, RIVM
    does not provide it

4
Harremoes et al. 2001 EEA report Late lessons
from early warnings the precautionary principle
1896-2000
  • 12 lessons, amongst which
  • Acknowledge and respond to ignorance, as well as
    uncertainty and risk
  • Identify and work to reduce blind spots and gaps
    in scientific knowledge
  • Ensure use of 'lay' and local knowledge
  • Take full account of the assumptions and values
    of different social groups

5
Crossing the disciplinary boundaries
  • Once environmental numbers are thrown over the
    disciplinary fence, important caveats tend to be
    ignored, uncertainties compressed and numbers
    used at face value
  • e.g. Climate Sensitivity, see Van der Sluijs,
    Wynne, Shackley, 1998

?
!
Resulting misconception Worst case 4.5C
1.5-4.5 C
6
The certainty trough (McKenzie, 1990)
7
Developments
  • Funtowicz and Ravetz book (1990) / Morgan and
    Henrion book (1990)
  • Good Practice Guidance (IPCC, 1999 CLRTAP, 2001)
  • RIVM Leidraad uncertainty management (2001-2002)
  • www.nusap.net
  • MUST-EoI
  • Ph.D. theses devoted to uncertainty management
  • Jeroen van der Sluijs (1997)
  • Serafin Corral (2000)
  • Marjolein van Asselt (2000)
  • John van Aardenne (2002)
  • Jos Olivier (2002)
  • Penny Kloprogge (2003)
  • Simône Huijs (2003)
  • Matthieu Craye (2004)

8
Conferences and workshops
  • EFIEA Uncertainty workshop (Baden, 10-18 July
    1999)
  • NUSAP-TIMER workshop (Loosdrecht, June 2001)
  • Expert workshop RIVM leidraad Uncertainty
    Management (Utrecht, 25-10-2001) User workshop
    (Bilthoven, 22-11-2001)
  • UN/ECE Uncertainty Treatment in Integrated
    Assessment Modelling (Laxenburg, January 24,
    2002)
  • FP6-MUST workshop (Brussels, November 11, 2002)
  • JRC IPSC EEA workshop Interfaces between
    science society (Autumn 2003)
  • International Symposium Uncertainty and
    Precaution in Environmental Management
    (Copenhagen, June 7-9, 2004 Poul Harremoës, DTU)

9
Insights on uncertainty
  • Uncertainty is partly socially constructed and
    its assessment always involves subjective
    judgement
  • Omitting uncertainty management leads to scandals
    and crisis
  • More research does not necessarily reduce
    uncertainty
  • may reveal unforeseen complexities
  • irreducible uncertainty (intrinsic or
    practically)
  • Quality relates to fitness for function
  • High quality ? low uncertainty
  • Shift in focus needed from reducing uncertainty
    towards a systematic management of uncertainty

10
Sorts of uncertainty
  • Technical (inexactness)
  • Methodological (unreliability)
  • Epistemological (ignorance)
  • NUSAP Qualified Quantities
  • (Funtowicz and Ravetz, 1990)

11
Locations of uncertainty
  • Sociopolitical and institutional context
  • System boundary problem framing
  • System boundary
  • Problem framing
  • Scenario framing (storylines)
  • Model/instrument
  • Indicators
  • Conceptual model structure / assumptions
  • Technical model structure
  • Parameters
  • Inputs
  • Scenarios
  • Data

12
Aim of a FP6 MUST Network of Excellence
  • Increase Europe's capacity to manage and surmount
    uncertainties surrounding knowledge production
    and use in designing and implementing
    precautionary policies and sustainable
    development.

13
Challenges for MUST
  • Dissemination of state of the art
  • Facilitate fruitful utilisation of
    complementarity of formal, participatory,
    deliberative and institutional approaches to
    assess and manage uncertainty?towards a new
    strategy for uncertainty management
  • Enhanced conceptualisation of uncertainty
  • Analysis of knowledge utilisation under
    uncertainty
  • Address institutional changes required for full
    fledged uncertainty management

14
Workshop Program
  • 1430 Jeroen van der Sluijs MUST research
    challenges
  • 1450 Jerry Ravetz Policy critical ignorance
  • 1510 Andrea Saltelli Quantitative methods
  • 1530 Jacquie Burgess Deliberative methods
  • 1550 Break
  • 1600 Joachim Spangenberg Extended peer
    processes
  • 1620 Penny Kloprogge Coping with
    value-ladenness
  • 1640 Ângela Pereira Communication of
    uncertainty
  • 1700 Matthias Kaiser Uncertainty and
    precaution
  • 1720 Discussion
  • 18.00 End
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