thin and thick complexity: philosophical challenges roger strand senter for vitenskapsteori, uib;...
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Thin and Thick Complexity:Philosophical Challenges
Roger StrandSenter for vitenskapsteori, UiB;
Institut de Ciència i Tecnologia Ambientals, UAB
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The Challenge
• We need a better understanding of– complex systems– different kinds and layers of complexity– the relationship between knowledge, action and
reality in a complex world
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• D. Gross & R. Strand (2000): “Can Agent-Based Models Assist Decisions on Large-Scale Practical Problems? A Philosophical Analysis,” Complexity, 5:26-33.
• R. Strand (2002): “Complexity, Ideology and Governance,” Emergence, 4:164-183.
• D. Chu, R. Strand & R. Fjelland (2003): “Theories of Complexity,” Complexity, 8:19-30.
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Matthias’ Questions
• How does this relate to issues of ethics of science, technology and environment?
• It might be that– the simplifying dimension of science is important in its
creation of environmental and social problems
– a better understanding of such a relationship could help us to learn how to produce fewer such problems
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Matthias’ Questions
• What would be a worthy topic for a follow-up?• Several. For example, we are in need of positive
theoretical accounts of– the interaction between the complexity of systems and
the complexity of scientific practice-and-knowledge
– scientific principles of emergent simplicity and their environmental and societal costs
• Why?• I will try to get to that.
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The Talk
• simplicity, thin complexity, thick complexity
• an outline of a positive theoretical account (work in slow progress)
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Thin Complexity
• Non-linearity– Chaos: The Strong Law of Causality does not hold– Bifurcations and catastrophes
• Complexity as an intermediate phenomenon– Self-organisation “on the border of chaos”– Not small and isolated, not big and fully connected
• Metaphorical use of mathematical methods– Fractals, scaling (power) laws
• The “paradigm” of CAS and Agent-Based Models
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The Simple View
• “Clearly, modern societies are characterized by a belief in the strategy of reducing practical problems to a set of technical problems to be handled by the appropriate institutions and expertise. This belief, however, has been accused of implying a nonchalant attitude toward uncertainty and complexity (Funtowicz & Ravetz, 1993, 1994b).”
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The Simple View
• “Imagine a person who believes firmly in the excellence of modernity, Enlightenment, natural science, and in general western traditions of (secular) thinking. We might picture him as being male; jokingly we may say this is a person who believes that there is a rational and objective answer to most questions, and that he knows quite a few of these answers himself. I suggest the following fiction to be a possible worldview of this person: ”
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The Simple View
• objectivist, mechanicist-materialist metaphysics• weak and strong laws of causality; reductionism• the world is a sparsely connected system
– science should cut Nature at the seams
• knowledge as representation– knowledge cannot be the object of moral blame
• facts//values, reason//passion• the human condition is to be an individual mind• reflexivity: the simple view warrants and is the truth
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Thin Complexity
• objectivist, mechanicist-materialist metaphysics• weak and strong laws of causality; reductionism• the world is a sparsely connected system
– the seams are finer, intertwined and not in straight lines
• knowledge as representation– knowledge cannot be the object of moral blame
• facts//values, reason//passion• the human condition is to be an individual mind• reflexivity: the simple view warrants and is the truth
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Reflecting upon Thin Complexity
• objectivist, mechanicist-materialist metaphysics• weak and strong laws of causality; reductionism• the world is a sparsely connected system
– the seams are finer, intertwined and not in straight lines
• knowledge as representation– knowledge cannot be the object of moral blame
• facts//values, reason//passion• the human condition is to be an individual mind• reflexivity: the simple view warrants and is the truth
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Thick Complexity
• objectivist, mechanicist-materialist metaphysics• weak and strong laws of causality; reductionism• the world is a sparsely connected system• knowledge as representation
– knowledge cannot be the object of moral blame
• facts//values, reason//passion• the human condition is to be an individual mind• reflexivity: the simple view warrants and is the truth
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To know is to simplify
• .. extending the network, but at what cost? for whom?
• New (positive) attempt: Let us try to describe scientific practice as a simplification process, complexifying various aspects
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Two conceptual partitions
We The external world
EnvironmentSystem
The external worldInteraction;
conceptual partition
Interaction
Conceptual partition
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Theoretical models defining the partition
We The external world
EnvironmentSystem
The external worldInteraction
Interaction
Model
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Scientific practice:Temporarily forgetting the external world
We The external world
EnvironmentSystem
The external world
Model
?
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Galileo: primary and secondary qualities
… a piece of paper or a feather, when gently rubbed over any part of our body whatsoever, will in itself act
everywhere in an identical way; it will, namely, move and contact. But we, should we be touched between the
eyes, on the tip of the nose, or under the nostrils, will feel an almost intolerable titillation – while if touched in
other places, we will scarcely feel anything at all. Now this titillation is completely ours and not the feather's, so
that if the living, sensing body were removed, nothing would remain of the titillation but an empty name. And I
believe that many other qualities, such as taste, odour, colour, and so on, often predicated of natural bodies,
have a similar and no greater existence than this.
Galileo Galilei (1623): The Assayer
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Galileo: The Book of the Universe is written in the language of mathematics
WePerceptions
Secondary Qualities
The external world
EnvironmentSystem
The external worldQuantifiable Primary Qualities
Mathematical Relationships
Conceptual analysis and synthesis in terms of linear components
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“ .. is written in the language of mathematics and the characters are triangles, circles and other geometrical shapes without the means of which it is humanly impossible to decipher a single word; without which we are wandering in vain
through a dark labyrinth.”
WePerceptions
Secondary Qualities
The external world
EnvironmentSystem
The external worldQuantifiable Primary Qualities
Mathematical Relationships
ModelLinear equations
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The modelling relationRobert Rosen (1991): Life Itself
F A formal system
– Ex.: A finite set of finite state vectors
– (x,y,z,vx,vy,vz)
NThe real system
encoding
decodingINFERENTIAL
CAUSAL
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Galilean simplicity
• Primary qualities: objectivity
• Linearity: analytico-synthetic method
• Causality– The Weak Law: No arbitrariness– The Strong Law: No chaos
• Universality
• Where does one find such systems??
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We The external world
EnvironmentSystem
The external world
Model
?
Laboratory Systems
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We
System
Model
Laboratory Systems
The external world
Phenomeno-technique
Gaston Bachelard, H.-J. Rheinberger
Construction
Effects
Reification
Prediction
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Complexity in natural systems
• Primary and secondary qualities• Non-linear or non-quantitative relationships• Apparent lack of striking causal patterns• Uniqueness and apparent historicity• What is system and what is environment?• What is the appropriate coding and decoding??
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Giving up the modelling relation: Natural history
F The formal system
– Ex.: A finite set of finite state vectors
– (x,y,z,vx,vy,vz)
NThe real system
encoding
decodingINFERENTIAL
CAUSAL
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Giving up the modelling relation: Natural history
F The formal system
– A rich description of things, events and progressions
NThe real system
encoding
CAUSAL
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Giving up the modelling relation: Metaphor
F The formal system
– F.ex. States given in terms of wave functions
NThe real system
decodingINFERENTIAL
CAUSAL??
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We
System
Model
The working of a metaphorical model
The external world
Phenomeno-technique
Construction
Success
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We
System
Model
The problem with a metaphorical model
The external world
Prediction ??
Playing
Success ??
Decoding as scientific success criterion
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Non-literal principlesof emergent simplicity?
• The rational agent
• Claude Bernard’s “inner environment” and physiological concept of disease
• Darwin and evolutionary stable strategies
• The diversity-stability debate
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The scientist
System
Model
Epistemological Complexity
The external world
Phenomeno-technique
Construction
Effects
Reification
Prediction
Framing of the policy process
What is important to save? To do? To know?