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Instead of assuming agents were perfectly rational, we allowed there were limits to how smart they were. Instead of assuming the economy displayed diminishing returns (negative feedbacks), we allowed that it might also contain increasing returns (positive feedbacks). Instead of assuming the economy was a mechanistic system operating at equilibrium,
... See moreJessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
The answer derives from the fact that what is good for groups is not always good for the individuals comprising them. For example, both multicellular organisms and social insect colonies are functionally specialized and hierarchically organized collectives that are highly successful in maintaining and transmitting accumulated knowledge, in the form
... See moreJessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
Value is subjective, which means uncertainty governs all economic phenomena.
Sacha Meyers • Bitcoin Is Venice: Essays on the Past and Future of Capitalism
Naked Economics: Undressing the Dismal Science (Fully Revised and Updated)
Charles Wheelan • 1 highlight
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le Donut économie intégrée des humains sociaux et adaptables complexité dynamique distributif par dessein régénératif par dessein agnostique en matière de croissance
Kate RAWORTH • La Théorie du donut
The take-home message from Schelling’s story—that incentives sometimes backfire—is familiar to psychologists.
Jessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
They appear to want some of the same things most of us want: recognition from their peers and communities and better lives for the people they care about. Being
Jessica C. Flack • Worlds Hidden in Plain Sight: The Evolving Idea of Complexity at the Santa Fe Institute, 1984–2019 (Compass)
There is no Newtonian law of markets; they are all ephemeral relationships in a sea of noise and the only way you can do that and capture non-linearity and complexity is with a system that is rich enough to be able to contain all the models, so a universal approximator—that’s what neural nets are—and allows you to do that.