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Addressing Uncertainty, Ambiguity and  Ignorance in Sustainability Appraisal Andy Stirling SPRU – science and technology policy research presentation to interdisciplinary workshop on  'Cost‐Benefit Analysis: Uncertainty, Discounting and the Sustainable Future’ Technical University Eindhoven, 12‐13 th  April, 2010
‘ Sound Science’ in Policy Under Uncertainty on chemicals: “ … sound science  will be the basis of the Commission's legislative proposal…”   - EC RTD Commissioner, Philippe Busquin ,[object Object],[object Object],former UK Prime Minister, Tony Blair ,[object Object],[object Object],UK Energy Minister Malcolm Wicks  ,[object Object],  Powerful pressures for ‘decision justification’
0.001 0.1 10 1000 externality’: c US /kWh  (after Sundqvist  et al , 2005) high  SUSTAINABILITY  low CBA delivers precise orderings of options coal oil gas nuclear hydro wind solar biomass ‘ Sound Science’ in CBA?  – the energy sector example
0.001 0.1 10 1000 coal oil gas nuclear hydro 36 wind solar biomass n = ‘ externality’: c US /kWh  (after Sundqvist  et al , 2005) minimum maximum 25%  75% high  SUSTAINABILITY  low CBA delivers precise orderings of options , but is sensitive to ‘framing’ ‘ Sound Science’ in CBA?  – the energy sector example
0.001 0.1 10 1000 coal oil gas nuclear hydro 36 20 wind 18 solar 11 biomass 22 31 21 16 n = ‘ externality’: c US /kWh  (after Sundqvist  et al , 2005) high  SUSTAINABILITY  low CBA delivers precise orderings of options , but is sensitive to ‘framing’ ‘ Sound Science’ in CBA?  – the energy sector example  ,[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Some dimensions of ‘framing’ in sustainability appraisal ,[object Object],[object Object],‘ Framing’ in CBA ,[object Object]
abatement  cost mitigation cost hypothetical markets damage  cost Hohmeyer,  1988 Ottinger et  al, 1990 Externe,  1995 principal  method Tellus,  1991 Framing: divergent methods in CBA ,[object Object]
Hohmeyer,  1988 Ottinger et  al, 1990 FUEL CYCLE STAGE LIFE  CYCLE PHASE extraction processing transport storage conversion residues materials energy construction operation capacity decommissioning DTI,  1992 effect  addressed effect  partly  addressed Framing: ‘system boundaries’ in CBA ,[object Object]
global  warming nuclear  proliferation ecosystem  damage aesthetic  impacts Schuman  et al, 1982 Hohmeyer,  1988 Ottinger et  al, 1990 Externe,  1995 effect  addressed Framing: ‘sustainability’ issues in CBA ,[object Object]
acoustic noise marine debris aerial visibility effects  marine hydrocarbon releases agricultural intensification marine life morbidity air quality  mechanical hazards altered flow rates and patterns micro-climate effects ambient temperature change  mutagenicity or teratogenicity aqueous radioactive pollution  navigational hazards    behavioural interference  nitrogen oxide emissions carbon monoxide emissions occupational health catastrophic dam burst  occupational safety catastrophic pollution potential particulate emissions or community disruption prompt public health impacts drainage disruption  psychological trauma  ecological or habitat disturbance radioactive emissions   electromagnetic interference resource depletion elevated water levels  road traffic  endangered species impacts  rural population impacts enhanced coastal erosion  salinity change enshading or reflection  sedimentation changes  entrainment of aquatic biota  soil acidification  eutrophication  soil erosion explosive or incendiary effects soil sterilisation fisheries interference  soil structure loss chain residues  soil toxification or contamination gaseous waste volume management  solid waste volume management  greenhouse gas emissions  stratospheric ozone depletion  hazard to bird flight  sulphur oxide emissions metal releases  thermal radiation effects  hydrogen sulphide emissions toxic aerial emissions seismicity  tritiated water emissions  induced subsidence  tropospheric ozone enhancement  interference with migration  turbidity changes  land use change visual aesthetic offence  latent human health effects volatile organic emissions liquid waste volume management  water abstraction demand  local ambient CO 2 /O 2  balance water quality effects  Categories of  ‘ environmental impact’ variously addressed  in CBAs in OECD  countries of electricity supply technologies (studies reviewed  earlier)… Framing: ‘sustainability’ issues in CBA …  even greater numbers of non-environmental aspects of sustainability (‘externalities’)
   THE FORM OF EFFECTS   eg:  death / injury / disease routine marginal / novel catastrophic reversible / irreversible    DISTRIBUTIONAL ISSUES   eg:  concentrated / dispersed public / workers  benefits / burdens future / present human / non-human    AUTONOMY OF AFFECTED   eg:  voluntary / controllable / familiar institutional trust  Framing: ‘sustainability’ issues in CBA ,[object Object],[object Object]
Incommensurability: ‘apples & oranges’ ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Arrow: axiomatic rationality to explore  ordinal  social choice Much discussed, but not refuted within rational choice paradigm economics is curiously reticent to highlight this Nobel-winning work Subjectivity of utility means no  cardinal  preference orderings
SALIENT POSSIBILITIES DEFINED  POSSIBILITIES UNDERDEFINED  Aspects of Incertitude  – a heuristic framework
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],SALIENT POSSIBILITIES DEFINED  RISK all relevant  probabilities are known UNCERTAINTY not all relevant  probabilities  are known Aspects of Incertitude  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… POSSIBILITIES UNDERDEFINED
  …  many analytic schemes for problems    deriving probabilities – in terms of: -  source:  context; data; model; expertise; -  levels:  statistical; scenarios; scientific; -  nature:  epistemic; ontological, normative; -  technical:  inputs; structure; parameters; - practical:  variability; sensitivity; precision - locus:  institutional, moral, legal, situation;    …  RIVM, van Asselt, de Marchi SALIENT POSSIBILITIES DEFINED  RISK EMPIRICAL UNCERTAINTY intrinsic  to data THEORETICAL UNCERTANTY inherent in science or models after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… UNCERTAINTY not all relevant  probabilities  are known Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
RISK UNCERTAINTY AMBIGUITY constituting, bounding,  partitioning or ordering of  salient possibilities is  unclear or contested   POSSIBILITIES UNDERDEFINED  empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… Aspects of Incertitude  IGNORANCE at least some salient  possibilities are  indeterminate or  indeterminable
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],RISK UNCERTAINTY IGNORANCE empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… AMBIGUITY salient possibilities are unclear or contested Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
RISK UNCERTAINTY IGNORANCE AMBIGUITY empirical uncertainty theoretical uncertainty UNCHARACTERISABILITY problematic definition, bounding or partitioning NONCOMPARABILITY problematic basis for comparison INCOMMENSURABILITY problematic aggregate relative orderings UNQUANTIFIABILITY   problematic aggregate  cardinal ratios &increments SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
[object Object],[object Object],[object Object],[object Object],RISK UNCERTAINTY OPEN IGNORANCE acknowledged IGNORANCE CLOSED IGNORANCE unacknowledged AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
only rarely discussed…  but then tends to be in terms of ‘reducibility’. This assumes that knowledge is  always additive and increased by research. But this not always true (eg: CFCs, TSEs, EDCs) RISK UNCERTAINTY IGNORANCE AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed ACCESSIBLE INACCESSIBLE Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
eg: CFCs eg: TSEs; EDCs RISK UNCERTAINTY IGNORANCE AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty INSTITUTIONAL IGNORANCE salient knowledges available, but not accounted for in policy SOCIETAL IGNORANCE knowledges accessible, but not yet available SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed ACCESSIBLE INACCESSIBLE Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
RISK UNCERTAINTY institutional ignorance societal ignorance AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty PHENOMENOLOGICAL IGNORANCE intrinsic to nature of world EPISTEMIC  IGNORANCE intrinsic to nature of understanding SALIENT POSSIBILITIES DEFINED  after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… IGNORANCE INACCESSIBLE OPEN closed ACCESSIBLE Aspects of Incertitude  POSSIBILITIES UNDERDEFINED
RISK UNCERTAINTY IGNORANCE institutional ignorance societal ignorance AMBIGUITY EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty INDETERMINACY  eg: genotypic change after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… INACCESSIBLE OPEN closed ACCESSIBLE Aspects of Incertitude  DETERMISTIC CHAOS eg: butterfly effect SALIENT POSSIBILITIES DEFINED  POSSIBILITIES UNDERDEFINED
RISK UNCERTAINTY IGNORANCE institutional ignorance societal ignorance indeter-minacy deterministic chaos AMBIGUITY EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty HERMENEUTIC IGNORANCE  intrinsic to language AXIOMATIC IGNORANCE  inherent in assumptions LOGICAL IGNORANCE  incomplete logic system after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed INACCESSIBLE ACCESSIBLE Aspects of Incertitude  SALIENT POSSIBILITIES DEFINED  POSSIBILITIES UNDERDEFINED
after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… UNCERTAINTY IGNORANCE institutional ignorance societal ignorance indeter-minacy deterministic chaos hermeneutic ignorance axiomatic ignorance logical ignorance AMBIGUITY POSSIBILITIES UNDERDEFINED  EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED  CBA TENDS TO TREAT ALL INCERTITUDE (IF AT ALL) AS RISK RISK INACCESSIBLE ACCESSIBLE OPEN closed Aspects of Incertitude
POSSIBILITIES UNDERDEFINED  SALIENT POSSIBILITIES DEFINED  IGNORANCE after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… BUT NEGLECTED ASPECTS CAN ALSO BE EFFECTIVELY ADDRESSED inaccessible ACCESSIBLE OPEN RISK UNCERTAINTY AMBIGUITY humility and transparency closed institutional ignorance societal ignorance research and monitoring transdisciplinary learning precautionary appraisal participatory deliberation Aspects of Incertitude  reductive aggregation
unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities some specific, concrete practical lessons for CBA Responses to Incertitude
unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities RISK UNCERTAINTY AMBIGUITY IGNORANCE risk assessment ,  cost-benefit analysis decision theory optimising models some specific, concrete practical lessons for CBA Responses to Incertitude
unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment ,  cost-benefit analysis decision theory optimising models uncertainty heuristics  interval analysis sensitivity testing some specific, concrete practical lessons for CBA Responses to Incertitude  knowledge about possibilities
scenarios / backcasting  interactive modeling mapping / Q-methods participatory deliberation unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment ,  cost-benefit analysis decision theory optimising models uncertainty heuristics  interval analysis sensitivity testing some specific, concrete practical lessons for CBA Responses to Incertitude  knowledge about possibilities
unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment ,  cost-benefit analysis decision theory optimising models uncertainty heuristics  interval analysis sensitivity testing scenarios / backcasting  interactive modeling mapping / Q-methods inclusive engagement monitor,   surveil, research diversity, flexibility, learning resilience, adaptability some specific, concrete practical lessons for CBA Responses to Incertitude  knowledge about possibilities
unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities RISK UNCERTAINTY AMBIGUITY decision rules aggregative analysis deliberative process political closure reductive modeling stochastic reasoning rules of thumb insurance ` evidence-basing  agenda-setting   horizon scanning transdisciplinarity liability   law harm definitions   indicators / metrics   institutional remits  ‘ Reductive aggregation’ presents powerful means to justify decisions  This ‘closing down’ around risk is Beck’s “organised irresponsibility” Institutional Pressures for Closure IGNORANCE
unproblematic problematic unproblematic problematic knowledge about likelihoods Precaution and Participation as Analytical Rigour PRECAUTIONARY APPRAISAL PARTICIPATORY DELIBERATION REDUCTIVE  AGGREGATION RISK UNCERTAINTY AMBIGUITY IGNORANCE knowledge about possibilities HUMILITY, LEARNING, ENQUIRY TRANSDISCIPLINARY  REFLEXIVITY AND RIGOUR
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Precaution as ‘Broadening Out’ Appraisal  (cf: EEA, 2001) Deliberative process  (not just ‘decision rule’) transcends CBA ,[object Object]
organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls low  sustainability   high ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example
organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls low  sustainability   high ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example GOVERNMENT
organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example low  sustainability   high GOVERNMENT INDUSTRY
organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls GOVERNMENT INDUSTRY organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls PUBLIC INTEREST ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example low  sustainability   high
[object Object],[object Object],Conclusions Address uncertainty, ambiguity & ignorance in appraisal ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
 

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Addressing Uncertainty, Ambiguity and Ignorance in Sustainability

  • 1. Addressing Uncertainty, Ambiguity and Ignorance in Sustainability Appraisal Andy Stirling SPRU – science and technology policy research presentation to interdisciplinary workshop on 'Cost‐Benefit Analysis: Uncertainty, Discounting and the Sustainable Future’ Technical University Eindhoven, 12‐13 th April, 2010
  • 2.
  • 3. 0.001 0.1 10 1000 externality’: c US /kWh (after Sundqvist et al , 2005) high SUSTAINABILITY low CBA delivers precise orderings of options coal oil gas nuclear hydro wind solar biomass ‘ Sound Science’ in CBA? – the energy sector example
  • 4. 0.001 0.1 10 1000 coal oil gas nuclear hydro 36 wind solar biomass n = ‘ externality’: c US /kWh (after Sundqvist et al , 2005) minimum maximum 25% 75% high SUSTAINABILITY low CBA delivers precise orderings of options , but is sensitive to ‘framing’ ‘ Sound Science’ in CBA? – the energy sector example
  • 5.
  • 6.
  • 7.
  • 8.
  • 9.
  • 10. acoustic noise marine debris aerial visibility effects marine hydrocarbon releases agricultural intensification marine life morbidity air quality mechanical hazards altered flow rates and patterns micro-climate effects ambient temperature change mutagenicity or teratogenicity aqueous radioactive pollution navigational hazards behavioural interference nitrogen oxide emissions carbon monoxide emissions occupational health catastrophic dam burst occupational safety catastrophic pollution potential particulate emissions or community disruption prompt public health impacts drainage disruption psychological trauma ecological or habitat disturbance radioactive emissions electromagnetic interference resource depletion elevated water levels road traffic endangered species impacts rural population impacts enhanced coastal erosion salinity change enshading or reflection sedimentation changes entrainment of aquatic biota soil acidification eutrophication soil erosion explosive or incendiary effects soil sterilisation fisheries interference soil structure loss chain residues soil toxification or contamination gaseous waste volume management solid waste volume management greenhouse gas emissions stratospheric ozone depletion hazard to bird flight sulphur oxide emissions metal releases thermal radiation effects hydrogen sulphide emissions toxic aerial emissions seismicity tritiated water emissions induced subsidence tropospheric ozone enhancement interference with migration turbidity changes land use change visual aesthetic offence latent human health effects volatile organic emissions liquid waste volume management water abstraction demand local ambient CO 2 /O 2 balance water quality effects Categories of ‘ environmental impact’ variously addressed in CBAs in OECD countries of electricity supply technologies (studies reviewed earlier)… Framing: ‘sustainability’ issues in CBA … even greater numbers of non-environmental aspects of sustainability (‘externalities’)
  • 11.
  • 12.
  • 13. SALIENT POSSIBILITIES DEFINED POSSIBILITIES UNDERDEFINED Aspects of Incertitude – a heuristic framework
  • 14.
  • 15. many analytic schemes for problems deriving probabilities – in terms of: - source: context; data; model; expertise; - levels: statistical; scenarios; scientific; - nature: epistemic; ontological, normative; - technical: inputs; structure; parameters; - practical: variability; sensitivity; precision - locus: institutional, moral, legal, situation; … RIVM, van Asselt, de Marchi SALIENT POSSIBILITIES DEFINED RISK EMPIRICAL UNCERTAINTY intrinsic to data THEORETICAL UNCERTANTY inherent in science or models after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… UNCERTAINTY not all relevant probabilities are known Aspects of Incertitude POSSIBILITIES UNDERDEFINED
  • 16. RISK UNCERTAINTY AMBIGUITY constituting, bounding, partitioning or ordering of salient possibilities is unclear or contested POSSIBILITIES UNDERDEFINED empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… Aspects of Incertitude IGNORANCE at least some salient possibilities are indeterminate or indeterminable
  • 17.
  • 18. RISK UNCERTAINTY IGNORANCE AMBIGUITY empirical uncertainty theoretical uncertainty UNCHARACTERISABILITY problematic definition, bounding or partitioning NONCOMPARABILITY problematic basis for comparison INCOMMENSURABILITY problematic aggregate relative orderings UNQUANTIFIABILITY problematic aggregate cardinal ratios &increments SALIENT POSSIBILITIES DEFINED after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… Aspects of Incertitude POSSIBILITIES UNDERDEFINED
  • 19.
  • 20. only rarely discussed… but then tends to be in terms of ‘reducibility’. This assumes that knowledge is always additive and increased by research. But this not always true (eg: CFCs, TSEs, EDCs) RISK UNCERTAINTY IGNORANCE AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed ACCESSIBLE INACCESSIBLE Aspects of Incertitude POSSIBILITIES UNDERDEFINED
  • 21. eg: CFCs eg: TSEs; EDCs RISK UNCERTAINTY IGNORANCE AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty INSTITUTIONAL IGNORANCE salient knowledges available, but not accounted for in policy SOCIETAL IGNORANCE knowledges accessible, but not yet available SALIENT POSSIBILITIES DEFINED after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed ACCESSIBLE INACCESSIBLE Aspects of Incertitude POSSIBILITIES UNDERDEFINED
  • 22. RISK UNCERTAINTY institutional ignorance societal ignorance AMBIGUITY uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty PHENOMENOLOGICAL IGNORANCE intrinsic to nature of world EPISTEMIC IGNORANCE intrinsic to nature of understanding SALIENT POSSIBILITIES DEFINED after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… IGNORANCE INACCESSIBLE OPEN closed ACCESSIBLE Aspects of Incertitude POSSIBILITIES UNDERDEFINED
  • 23. RISK UNCERTAINTY IGNORANCE institutional ignorance societal ignorance AMBIGUITY EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty INDETERMINACY eg: genotypic change after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… INACCESSIBLE OPEN closed ACCESSIBLE Aspects of Incertitude DETERMISTIC CHAOS eg: butterfly effect SALIENT POSSIBILITIES DEFINED POSSIBILITIES UNDERDEFINED
  • 24. RISK UNCERTAINTY IGNORANCE institutional ignorance societal ignorance indeter-minacy deterministic chaos AMBIGUITY EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty HERMENEUTIC IGNORANCE intrinsic to language AXIOMATIC IGNORANCE inherent in assumptions LOGICAL IGNORANCE incomplete logic system after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… OPEN closed INACCESSIBLE ACCESSIBLE Aspects of Incertitude SALIENT POSSIBILITIES DEFINED POSSIBILITIES UNDERDEFINED
  • 25. after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… UNCERTAINTY IGNORANCE institutional ignorance societal ignorance indeter-minacy deterministic chaos hermeneutic ignorance axiomatic ignorance logical ignorance AMBIGUITY POSSIBILITIES UNDERDEFINED EPISTEMIC PHENOMENOLOGICAL uncharact-erisability noncom-parability ordinal inco-mensurability cardinal un-quantifiability empirical uncertainty theoretical uncertainty SALIENT POSSIBILITIES DEFINED CBA TENDS TO TREAT ALL INCERTITUDE (IF AT ALL) AS RISK RISK INACCESSIBLE ACCESSIBLE OPEN closed Aspects of Incertitude
  • 26. POSSIBILITIES UNDERDEFINED SALIENT POSSIBILITIES DEFINED IGNORANCE after: Collingridge, Faber, Funtowicz Keynes, Knight, O’Neill, Proops, Ravetz, Wynne… BUT NEGLECTED ASPECTS CAN ALSO BE EFFECTIVELY ADDRESSED inaccessible ACCESSIBLE OPEN RISK UNCERTAINTY AMBIGUITY humility and transparency closed institutional ignorance societal ignorance research and monitoring transdisciplinary learning precautionary appraisal participatory deliberation Aspects of Incertitude reductive aggregation
  • 27. unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities some specific, concrete practical lessons for CBA Responses to Incertitude
  • 28. unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities RISK UNCERTAINTY AMBIGUITY IGNORANCE risk assessment , cost-benefit analysis decision theory optimising models some specific, concrete practical lessons for CBA Responses to Incertitude
  • 29. unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment , cost-benefit analysis decision theory optimising models uncertainty heuristics interval analysis sensitivity testing some specific, concrete practical lessons for CBA Responses to Incertitude knowledge about possibilities
  • 30. scenarios / backcasting interactive modeling mapping / Q-methods participatory deliberation unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment , cost-benefit analysis decision theory optimising models uncertainty heuristics interval analysis sensitivity testing some specific, concrete practical lessons for CBA Responses to Incertitude knowledge about possibilities
  • 31. unproblematic problematic unproblematic problematic knowledge about likelihoods AMBIGUITY IGNORANCE RISK UNCERTAINTY risk assessment , cost-benefit analysis decision theory optimising models uncertainty heuristics interval analysis sensitivity testing scenarios / backcasting interactive modeling mapping / Q-methods inclusive engagement monitor, surveil, research diversity, flexibility, learning resilience, adaptability some specific, concrete practical lessons for CBA Responses to Incertitude knowledge about possibilities
  • 32. unproblematic problematic unproblematic problematic knowledge about likelihoods knowledge about possibilities RISK UNCERTAINTY AMBIGUITY decision rules aggregative analysis deliberative process political closure reductive modeling stochastic reasoning rules of thumb insurance ` evidence-basing agenda-setting horizon scanning transdisciplinarity liability law harm definitions indicators / metrics institutional remits ‘ Reductive aggregation’ presents powerful means to justify decisions This ‘closing down’ around risk is Beck’s “organised irresponsibility” Institutional Pressures for Closure IGNORANCE
  • 33. unproblematic problematic unproblematic problematic knowledge about likelihoods Precaution and Participation as Analytical Rigour PRECAUTIONARY APPRAISAL PARTICIPATORY DELIBERATION REDUCTIVE AGGREGATION RISK UNCERTAINTY AMBIGUITY IGNORANCE knowledge about possibilities HUMILITY, LEARNING, ENQUIRY TRANSDISCIPLINARY REFLEXIVITY AND RIGOUR
  • 34.
  • 35. organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls low sustainability high ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example
  • 36. organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls low sustainability high ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example GOVERNMENT
  • 37. organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example low sustainability high GOVERNMENT INDUSTRY
  • 38. organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls GOVERNMENT INDUSTRY organic environmental intensive GM + labelling GM + monitoring GM + voluntary controls PUBLIC INTEREST ‘ Mapping’ Key Uncertainties in Sustainability Appraisal Divergent expert views of risks and benefits of different agricultural strategies elicited using multicriteria mapping method in Unillever-sponsored research (2003) A Practical Example low sustainability high
  • 39.
  • 40.  

Notas do Editor

  1.