Saurabh Arora - The advantages of uncertainty - toward new principles for coo...
S12h tokyo 29 august nistep
1. Ambiguous Evidence:
implications of uncertainty for science policy
seminar given at National Institute of Science and Technology Policy (NISTEP),
Ministry of Education, Culture, Sports, Science and Technology (MEXT),
Tokyo, 29th August 2012
Andy Stirling
SPRU & STEPS Centre
2. Conventional Technology Policy
“you can’t stop progress” …
- The Economist
PROGRESS
“we'll restore science to its rightful place”…
` - President Obama
“Our hope … relies on scientific and
technological progress” - Premier Wen Jiabao
“One can not impede scientific progress.”
- President Ahmadinejad
TECHNOLOGY
all innovation is progress…
Lisbon Strategy for: “pro-innovation action”
- EU Council of Ministers
“we need more pro-innovation policies”
- PM Gordon Brown
“… the Government’s strategy is …
pro-innovation” - PM David Cameron
3. Conventional Technology Policy
Lord Alec Broers, President, RAEng PROGRESS
…“history is a race to advance technology”
Technology:
“will determine the future of the human race’”
The challenge of government:
TECHNOLOGY
“to strive to stay in the race”…
The role of the public:
“to give technology the status it deserves”…
5. Conventional Technology Policy
PROGRESS
TECHNOLOGY
Treats innovation as homogeneous: no distinctions … no
alternatives… no politics … no choice
!
6. Conventional Technology Policy
PROGRESS
TECHNOLOGY
Treats innovation as homogeneous: no distinctions … no alternatives …
no politics … no choice !
Scope for debate restricted to: yes or no? … how much?
how fast? … who leads?
7. Conventional Technology Policy
PROGRESS
TECHNOLOGY
Treats innovation as homogeneous: no distinctions … no alternatives …
no politics … no choice !
Scope for debate restricted to: yes or no? … how much?
how fast?’ … who leads?
Seriously neglects questions over: which way? …what alternatives?
says who? …why?
8. Technological Progress is Evolutionary
For instance... “sustainable energy”
Not all that is conceivable, feasible, viable – will be fully realisable
9. Technological Progress
Intended and unintended processes and power ‘close down’ pathways
social shaping (Bijker, 85) co-construction (Misa, 03)
studies: expectations (Brown, 03) imaginations (Jasanoff, 05)
10. Technological Progress
Intended and unintended processes and power ‘close down’ pathways
history: contingency (Mokyr, 92) momentum (Hughes 83)
path-dependence (David, 85) path creation
(Karnoe, 01)
11. Technological Progress
Intended and unintended processes and power ‘close down’ pathways
philosophy: autonomy (Winner, 77) closure (Feenberg, 91)
/politics entrapment (Walker, 01) alignment (Geels, 02)
12. Technological Progress
Intended and unintended processes and power ‘close down’ pathways
economics: homeostasis (Sahal, 85) lock-in (Arthur, 89)
regimes (Nelson & Winter, 77) trajectories (Dosi,
82)
13. ‘Sound Science’ in Policy and Regulation
on public health:
“… sound science … science-based decisions”
- UN WHO DG Margaret Chan
on genetic modification:
“… this government's approach is to make
decisions … on the basis of sound science”
- former UK Prime Minister, Tony Blair
on chemicals:
“ …sound science will be the basis of the
Commission's legislative proposal…”
- EC RTD Commissioner, Philippe Busquin
on energy:
“[n]ow is the right time for a cool-headed,
evidence based assessment … I want to
sweep away historic prejudice and put in its
place evidence and science”
former UK Energy Minister Malcolm Wicks
Justification: from political ‘problems’ to technical ‘puzzles’
19. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores, (often) denies radical openness of ‘incertitude’:
- insufficiency: knowledge efficacy is not normative basis for action
. Aristotle, Kant, Habermas know-how is less important than know-why
– eg: how to apply neuroscience?
20. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge enabling utility is limited on wider effects
. Lao Tzu, Socrates, Keynes ‘unknowns’ as important as ‘knowns’
– eg: unexpected
mechanisms
in nanohealth
technologies
21. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge enabling utility is limited on wider effects
- indeterminacy: effective knowledge does not preclude surprise
. Gödel, Dosi, Collingridge ”known knowns” foster hubris
– eg: dangers of thinking we know
halogenated hydrocarbons,
CFCs and the ozone hole
endocrine disruptors
methyl tertbutyl ether
22. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge is always limited as a basis for action
- indeterminacy: effective knowledge does not preclude surprise
- ‘inversity’: increased knowledge can increase
ignorance . Einstein, Ravetz, Beck… area / perimeter of known
– nonlinear
dynamics
of climate
and oceans
23. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge is always limited as a basis for action
- indeterminacy : effective knowledge does not preclude surprise
- ‘inversity’: increased knowledge can increase ignorance
- intractability: knowledge-commitments compound vulnerability
. Ellul, Wynne, Tenner not existence but exposure to unknown
eg: nuclear
dependency
24. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge is always limited as a basis for action
- indeterminacy : effective knowledge does not preclude surprise
- ‘inversity’: increased knowledge can increase ignorance
- intractability: knowledge-commitments compound vulnerability
- incommensurability: knowledges are plural and often
conflicting . Kuhn, Arrow, Jasanoff… knowledge often not linear / additive
- eg: agronomy, ecology, soil science,
molecular biology on GM
25. Knowing Knowledge
Conventional expert practices suppress our ‘knowledge about knowledge’
marginalises, elides, ignores and (often) denies realities of knowledge:
- insufficiency: knowledge efficacy is not normative basis for action
- incompleteness: knowledge is always limited as a basis for action
- indeterminacy: effective knowledge does not preclude surprise
- ‘inversity’: increased knowledge can increase ignorance
- intractability: knowledge-commitments compound vulnerability
- incommensurability: knowledges are plural and often conflicting
representing incomplete knowledge as expert ‘risk’ is deeply problematic
26. Beyond Risk
contrasting aspects of ‘incertitude’
unproblematic RISK
engineered components
closed deterministic
systems high frequency
knowledge incidents familiar contexts
about
INCERTITUDE
likelihoods
open dynamic systems
low frequency events
human factors
changing contexts
problematic UNCERTAINTY
- Socrates, Lao Tzu, Knight, Keynes, Shackle, Collingridge, Smithson, Ravetz, Wynne ...
27. Beyond Risk
contrasting aspects of ‘incertitude’
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
engineered components defining pros & cons
closed deterministic contrasting impacts
systems high frequency diverse perspectives
knowledge incidents familiar contexts alternative options
about
INCERTITUDE
likelihoods
open dynamic systems novel agents or vectors
low frequency events surprising conditions
human factors new alternatives
changing contexts wilful blinkers
problematic UNCERTAINTY IGNORANCE
- Socrates, Lao Tzu, Knight, Keynes, Shackle, Collingridge, Smithson, Ravetz, Wynne ...
28. Pressures for Closure
institutional drivers of risk assessment
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
aggregative analysis
patronage, pressure
political closure
knowledge
about
insurance limits ` science-based
reductive models policy
likelihoods stochastic reasoning institutional
remits
political
liability protection culture
harm definitions
indicators / metrics
problematic UNCERTAINTY IGNORANCE
risk focus is shaped by power – Beck’s “organised irresponsibility”
29. Methods for ‘Opening Up’
precaution and participation are about rigour
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
aggregated probabilities
optimisation algorithms
synthetic decision trees
Delphi / Foresight
knowledge predictive modelling
about
likelihoods
problematic UNCERTAINTY IGNORANCE
precautionary methods ‘open up’ appreciation of incertitude
30. Methods for ‘Opening Up’
precaution and participation are about rigour
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
aggregated probabilities
optimisation algorithms
synthetic decision trees
Delphi / Foresight
knowledge predictive modelling
about
likelihoods
burden of evidence
onus of persuasion
uncertainty factors
decision heuristics
interval analysis
sensitivity testing
problematic UNCERTAINTY IGNORANCE
precautionary methods ‘open up’ appreciation of incertitude
31. Methods for ‘Opening Up’
precaution and participation are about rigour
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
aggregated probabilities scenarios / backcasting
optimisation algorithms interactive modelling
synthetic decision trees mapping / Q-methods
Delphi / Foresight participatory deliberation
knowledge predictive modelling democratic procedures
about
likelihoods
burden of evidence
onus of persuasion
uncertainty factors
decision heuristics
interval analysis
sensitivity testing
problematic UNCERTAINTY IGNORANCE
precautionary methods ‘open up’ appreciation of incertitude
32. Methods for ‘Opening Up’
precaution and participation are about rigour
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
aggregated probabilities scenarios / backcasting
optimisation algorithms interactive modelling
synthetic decision trees mapping / Q-methods
Delphi / Foresight participatory deliberation
knowledge predictive modelling democratic procedures
about
likelihoods
burden of evidence responsive civic research
onus of persuasion curiosity monitoring,
uncertainty factors evidentiary presumptions
decision heuristics flexibility, reversibility
interval analysis diversity, resilience,
sensitivity testing agility, adaptability
problematic UNCERTAINTY IGNORANCE
precautionary methods ‘open up’ appreciation of incertitude
33. ‘Opening Up’ Incertitude
precaution and participation are about rigour
knowledge about possibilities
unproblematic problematic
unproblematic RISK AMBIGUITY
definitive participatory
prescription deliberation
knowledge
Options
about
likelihoods safety humility
Options
reflexivity
precautionary adaptive
sustainability
appraisal learning
problematic UNCERTAINTY IGNORANCE
‘opening up’: options, issues, approaches, possibilities, perspectives
34. Plural Conditional Advice
erent agricultural strategies
ptions of selection of UK expert policy advisers
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
35. Plural Conditional Advice
erent agricultural strategies
ptions of selection of UK expert policy advisers
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
high risk low
36. Plural Conditional Advice
erent agricultural strategies
ptions of selection of UK expert policy advisers
GOVERNMENT
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
high risk low
37. Plural Conditional Advice
erent agricultural strategies
ptions of selection of UK expert policy advisers
GOVERNMENT INDUSTRY
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
high risk low
38. Plural Conditional Advice
erent agricultural strategies
ptions of selection of UK expert policy advisers
GOVERNMENT INDUSTRY PUBLIC INTEREST
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
organic
environmental
intensive
GM + labelling
GM + monitoring
GM + voluntary controls
high risk low