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Putting Policy Makers First. Moving Beyond the Complexity Sciences to Complexity Engineering www.synthesisips.net greg.fisher@synthesisips.net. Introduction. Bank of England for 9 years Hedge Fund for 4 years Synthesis - with Paul Ormerod & Bridget Rosewell in 2011.
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Putting Policy Makers First • Moving Beyond the Complexity Sciences to Complexity Engineering • www.synthesisips.net • greg.fisher@synthesisips.net
Introduction • Bank of England for 9 years • Hedge Fund for 4 years • Synthesis - with Paul Ormerod & Bridget Rosewell in 2011 • Think Tank (policy intermediary) • Centred around Complexity Theory • Emerging Theme: Complexity Engineering
Why we are here...? • Introducing: Sharon
Complexity & Policy:How it works at the moment Well, pattern recognition helps because life seems to be a mix of evolving patterns, global cascades, black swans, and things like that. Angela! I want to tell you about complex systems! They’re amazing! Did you know that the future of a social systems is inherently unknowable?! There are these things called emergent phenomena. They’re terribly important and It’s all a bit technical Ah well, you should be aware when deciding things that the world is not deterministic Please leave now via that window and wave goodbye to your funding! *shrugs*, and? That’s a pity. So what? ok, I’m listening What does that mean for me? Complexity Boffin Policy Maker
How It could Work Angela, could you tell me what your problems are? Of course! Where do I begin?!... I would like to help by using some new approaches to social systems. Complexity Boffin Policy Maker
Science & Engineering Complexity Engineering Complexity Sciences Policy Maker Policy Maker Sharon Intermediaries (like Think Tanks)
Scientists & Engineers Scientific Principles Rigorous Thinking Funky Tools like ABM Internal dialogue: jargon mostly ok Engineering Principles Empathy with policymakers Imaginative Thinking to marry science & policy Clear articulation to layman
Some Engineering Principles? • Old Paradigm: one expert, correct model, add data = endogenous policy choice • But: society evolving, idiosyncrasies matter, & no-one can know whole terrain in wicked problem • Key principles: • Crowd source views of policy space from multiple stakeholders • Pattern recognition of “policy space” • Repeat back to test pattern recognition • Consider policy options
Example: Multiple & Severe Disadvantages • Round-Table Discussion: policy makers first • UK Care delivery is silo-based • People = Sum of care requirements • Sharon: 8 application forms for unemployment, childcare, drug abuse, homelessness, psychologist, etc. • Idea: tailored care for 5% of care cases - devolved authority
Moving Forward: Project Idea Mature Tools Prototype Tools Learn from examples Apply to multiple Policy Terrains Publish on web as a “wiki”: additions & Evolution Use in Policy Learn from Complexity Consultants Learning Feedback Loop