The document discusses complex adaptive systems (CAS) and how they apply to both natural and human systems. It explains that CAS cannot be understood by analyzing separate components and that their dynamics are nonlinear. The presentation examines how human behaviors and interventions can change CAS dynamics in unexpected ways and influence outcomes. It emphasizes that modeling CAS requires accounting for surprises, phase changes, and reorganizations. The document also addresses innovation as a CAS, noting the need to operate on slow-moving variables using fast-moving instruments to achieve impact at scale.

1. Analysis of Trade-offs in Agricultural
Systems: Achieving impact
Javier Ekboir
Institutional Learning & Change Initiative of the CGIAR 1

2. Content of the presentation
• Complex adaptive systems (CAS)
• Human and natural CAS
• Modeling CAS
• Innovations as CAS
• Achieving impact at scale
Institutional Learning & Change Initiative of the CGIAR 2

3. Famous phrases
There is no likelihood that humans will ever tap the
power of atom (Robert Millikan1923)
The atom bomb will never go off and I speak as an
expert (Admiral W. Leahy1945)
I think there will be a world market for five computers
(Thomas Watson 1958)
The internet will never take off (Bill Gates 1988)
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4. What is a CAS?
A systems that cannot be understood by
analyzing its separate components
Complex is not complicated
Two types of CAS: transportation systems and
climate change
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5. Dynamics of a natural CAS
5
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6. How do humans change these dynamics?
They have foresight and purpose (they plan)
They learn (make sense) and adapt
They respond to incentives, not always for the
general good
They interact (fads, externalities, herd
effects, bubbles)
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7. How do humans change these dynamics?
Collective action is an instrument and a restriction
for achieving impact at scale
Human dynamics are much faster than natural
dynamics
Human decision-making processes change fast
and involve multiple goals and influences
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8. Coupled dynamics in CAS
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9. The dynamics of CAS
Interventions can have unexpected
results
The same outcome may result
from different interventions
Different outcomes may result
from the same intervention
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10. The dynamics of CAS
Path dependence
Complex processes cannot be predicted, but
futures can be explored as possibilities
Minimal changes in the initial conditions have
great consequences
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11. Modeling change in CAS
Complex behavior can emerge from very simple
rules
In a CAS there is no optimization but evolutionary
processes (rugged landscapes, networked
genes, quantum tunneling)
Modeling has to deal with surprises, phase changes
and reorganizations
Tradeoff analysis should be complemented with
coordination and diffusion
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12. Innovation as a CAS
Successful innovations are long adaptive processes
Innovations combine
technical, business, organizational and
institutional dimensions
Distribution of resources and capabilities (power
laws, what are the right indicators?)
Socioeconomic landscapes are changed by
successful innovations
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13. Operating on a CAS
CAS cannot be managed but can be harnessed
All strategies were developed for fast moving
variables (firms)
That’s why we have a better idea of how to improve
value chain
We do not know how to operate on slow moving
variables with fast moving instruments
What is the role of science in innovation processes?
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14. Achieving impact
Develop a theory of change across scales (but not
any ToC)
Review the theory of change often (but not too
often)
How will rural areas look after the impact?
How do we do adaptive management of research?
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15. References on complex systems
Axelrod, R. and M.D. Cohen. 1999, Harnessing Complexity.
Organizational Implications of a Scientific Frontier. NY: The
Free Press
Crutchfield, J.P. and P. Schuster (eds.). 2003. Evolutionary
Dynamics. Exploring the Interplay of
Selection, Accident, Neutrality and Function. Santa Fe Institute in
the Sciences of Complexity, Oxford University Press Inc
Gunderson, L.H. and C.S. Holling (eds.). 2002. Panarchy.
Understanding Transformations in Human and Natural Systems.
Washington, D.C.: Island Press
Miller, A.I. 2000. Insights of Genius. Imagery and Creativity in
Science and Art. 1st edition, Cambridge, Mass.: MIT Press
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