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At a session of the World Economic Forum in Davos, Switzerland, SFI scientists described ways the latest research in complex systems might enhance the resilience and control of economic, social, and cyber systems.

During the January 25 session, "Managing complexity with the Santa Fe Institute," panelists, through example, showed how control of a complex system need not mean the control of all its individual elements but only of a select number of key nodes.

They included SFI External Professor W. Brian Arthur; Albert-Laszlo Barabasi (Northeastern University); SFI Science Board Co-Chair and External Professor Stephanie Forrest (University of New Mexico); and SFI External Professor Scott Page (University of Michigan). SFI Distinguished Fellow Murray Gell-Mann introduced the panel.

The discussion focused on complex systems approaches to four kinds of systems:

Economic systems: Complexity economics views the economy as a system within which the elements (banks, corporations, governments, etc.) react and re-react with each other in complex and unpredictable ways. Small events can ricochet through the system, having considerable impact. The euro crisis illustrates how the differing economic theories can paint distinct pictures of a single economic event -- with different responses to economic challenges. Complexity economics gives an arguably more realistic view of how economies work, they said.

Social systems: The nature of the complexity that pervades society is seen in the billions connected to the Internet, or the connectivity that is our shared genetic network. But the control of a complex system need not mean the control of all its individual elements. Understanding control points in social systems can help manage the complex as the epidemiology of cancer or communications networks in large organizations. In an organization, knowing who the control nodes or influencers are may be the key to communicating effectively, creating change, and influencing culture. Complexity research helps model and reveal such control nodes.

Cyber systems: Complexity theory offers new insights into how to protect computer systems from malicious agents, using ideas from immunology, epidemiology, and ecology. In nature, there is an ever-raging arms race between attackers and defenders, with the constant evolution of weapons and defense. The development of cyberinfrastructure can learn from nature. It is a monoculture, built to face and manage a series of similar risks. It does a poor job detecting and defending against novel forms of attack. One way that cyberinfrastructure can replicate nature in its digital immune system is to ensure that all copies of software are unique, while underlying functionality remains the same. Unique differences protect from replicated attacks.  Another challenge for cybersecurity is creating agile regulatory policies that allow cyberdefence to stand up against ever-evolving and unpredictable predators.

Human systems: The study of complexity offers insights into how to create better performance at a macro level. It is well understood that performance can be improved by adding numbers to increase output, or by specializing. But simply adding more of the same skills will ultimately achieve more of the same output. The study of complexity suggests that to truly improve performance in our complex world, diversity is super-additive. Diversity speaks to how people think, their models, causal networks, and the tools they acquire during life. In mathematical terms: the wisdom of the crowd = the intelligence of the individuals + the diversity of the crowd Diversity is also a powerful tool for problem-solving. Diverse thinkers bring different types of solutions to any problem. 

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