Complexity Science as Magic Feather

1. Complexity Science as Magic Feather Institute for Complex Systems Simulation Seth Bullock 2 July 2012

2. About Me Game Theory Neuromodulation Visualization Termites Simulation Modelling Honest Signalling Markets Networks Science Biology Social Processes Cog. Psych. AI Amorphous Computing Me Cog. Phil. Alife Complexity Science Interdisciplinarity Complexity Emergence Philosophy of Science Self-organization Adaptation Methodology

3. “Complexity science explores the emergent behaviourof complex systems by focusing on their interconnections and architecture, rather than on individual components. It represents a novel scientific approach across traditional disciplinary boundaries.” – EPSRC Research Landscape, Cross-Disciplinary Interfaces Programme, June 2009. What is Complexity Science?

4. A Systemic Century 20th Century 21st Century

5. Systemic Questions

6. Emergent Organisation

7. The Synthetic Method ? 

8. ...Perhaps Inside a Computer? • The Southampton Supercomputer: • Fastest at a UK University • Greenest in the UK • 8000 processors • £3m • ...an extremely powerful tool. • But with great power comes great responsibility...

9. Why Complexity Science for You? • The standard (sometimes partially implicit) rhetoric: • 1. Socio-techno-cultural-economic systems are: • large, involved, unfolding, contextual, reflexive, etc. • i.e., they are “complex”. • 2. Social scientists struggle to understand these systems • 3. Complexity Science is the proper study of such systems. •  Complexity Science should be useful to social scientists.

10. An Example? • Lynne Cameron studies second language learning. • I worked with her informally on applying complex systems ideas to the systems she was interested in. • How do the trajectories of language learning experience within a classroom differ from those experienced at home? • We had some extremely interesting conversations, • ...and a sense that the language of dynamical systems theory was very pertinent and potentially productive, • ...but we had problems moving from talking to modelling.

11. Gloom... • What was going wrong? • There was scant theory with which to guide the modelling • The questions to be addressed by the model were unclear • “Complexity Science” seemed unable to fill these gaps... • Since then I have repeatedly encountered a similar impasse. • I have begun to think that it stems from: • limits on what can be discovered through modelling • unhelpful expectations of complexity science

12. Models Aren’t Magic... Consider: Q. How do judges set bail? M is collecting questionnaire data from judges in order to try to understand how they reach their bail judgements... • M: “I’ve got data from five judges, but it’s really hard, could you, like, simulate 20 judges for me?” • S: “Well, we’d need to model their decision-making... ...so, I’d need you to explain how they set bail.” • M: “Umm... but...?”

13. Complexity Science isn’t Physics... Are social scientists “damsels in distress”? Are complexity scientists “white knights”? No. Even Physics rarely delivers the predictive, realistic, explanatory models that solve a problem for a scientific community. The rhetoric surrounding complexity science is wrong – it is not a “saviour”. So what role should we expect complexity science to play?

14. An Example: Reprise What impact did our “modelling” attempts have? A change in mind-set, a sharpening of focus. The development of new empirical tools, new measures, new approaches to visualization. Stelma, J. “Exploring the emergence of activity in language classroom activity”, in preparation. Cameron, L. & Stelma, J. (2004). “The dynamics of metaphor in conciliation talk”, Sociolinguistics Symposium, 1-4 April 2004, Newcastle.

15. A New Rhetoric... • 1. Socio-techno-cultural-economic systems are: • large, involved, unfolding, contextual, reflexive, etc. • i.e., they are “complex” • 2. Social scientists are best placed to understand these systems • 3. But progress at/beyond paradigm boundaries is difficult • 4. Complexity Science is a source of tools for thinking • language, concepts, models, measures, frameworks •  Complexity Science should be useful to social scientists.

16. A “Magic Feather”? Reconceives complexity sci. as empowering social scientists... ...enabling them to transcend a current paradigm.

18. Autopoiesis (for Dumbos) • An autopoietic system • is a self-authoring, self-making system • renews, repairs, replicates or reproduces itself in a flow of matter and energy • generates/maintains it’s own boundary, distinguishing itself from its milieu • is a living system, a normative system • is a sense-making, autonomous system • has agency in the sense that it has its own agenda

20. Autopoietic Habits • Autopoietic systems may be sociological: • Smoking cigarettes reinforces a habit • The habit promotes smoking cigarettes • The habit is self-maintaining • In fact the habit also brings about its own preconditions by financially legitimising cigarette factories, etc • From the perspective of the cigarette: A social-cultural-industrial-economic matrix exists, maintaining its place in an auto-catalytic, self-perpetuating cycle...

21. Autopoietic Families • What would constitute an autopoietic perspective on families and family care? • What are the components of a family? • What processes create/maintain them? • In what sense are families precarious? • In what ways do normal family processes mitigate against insults? • How are families structurally coupled together and to systems of care? How could an autopoietic care system be implemented?

22. Thank you