
… and free association. Here are my notes and ruminations from Scott Page’s talk at the SFI Overview on Complex Adaptive Systems.
“Perspective is a way to encode the world. There is a perspective from which any problem is easy.”
“Bee hives must stay at 96 degrees for bees to reach maturity. Bees can cool with their wings or huddle together for warmth. Genetically homogenous bees all move together, and the temperature fluctuates widely. Genetically diverse bees keep the hive at a constant temperature.”
Page’s conclusion that diversity is as important as ability seems pretty profound.
His argument for diversity in complex adaptive systems seems to be to be the underpinning of that popular book by Surowiecki, The Wisdom of Crowds.
I’d posit that diverse group performance comes not from convergence to the mean on a single parameter scale, but the factoring of diverse and orthogonal perspectives. Diversity brings more variables into the multivariate regression of teams.
According to Scott Page, “People in diverse groups are less happy. Their views are challenged, and they feel like the outcomes were manipulated. Based on their experiences, they will self-report that it was not better than when they were on a homogenous team.”
As you increase diversity, complexity goes up, but then it drops and you get the central limit theorem. There is a sweet spot with just the right interplay between agents. Also, there is not one dimension that perspectives lie along. Diversity captures orthogonal perspectives and more adjacencies. The better the perspective, the less rugged the landscape (in terms of finding the global optimum and not getting trapped in local optima). Consultants can hop across local peaks without being any smarter or more experienced in their client’s business. The goal is not regression to the mean.
Thinking about the wisdom of crowds as an emergence, this is the question I have been wrestling with:
Does the minimal threshold complexity for interesting emergent phenomena necessitate inscrutability of results by members of the system?
For example, if a group of diverse people routinely beats the experts, where does the learning occur? It seems to be at the system level, and not the individual level. The decision may make no sense to the individual members, but the decision making process does. The “wisdom” of the process could be taught to others, but not the outcomes.
This generalization about emergence seems to hold for evolution, brains & neural networks, hives, and cultural memetic drift (more on this). In interesting systems, the emergent phenomena are at a different layer of abstraction, and may only be recognized by “in-process” or nodal members by pattern or proxy.

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