Central planning is unbeatable as a resource allocation mechanism for small systems. As you attempt to scale it up, it becomes terribly ineffective, to such an extent that decentralized control algorithms wastly outperform it, despite being inherently wasteful
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I think it's a technology problem, not an intrinsic issue. Better cybernetics will enable us to scale efficient central control (while taking into account uncertainty and exploration) to increasingly large systems in the future
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This is tightly related to AI as well: it's the question of local vs. global optimization in a non-differentiable system, open-ended goal-setting, objective propagation from one module to its neighbors, parent, and internal submodules...
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Backprop is a centralized answer, that only applies to differentiable functions where "control" means adjusting some parameters and where the optimization objective is already known. Its range of applicability is minuscule
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May I point you to Hayek's 1952 book The Sensory Order? It's mainly an information processing and signalling problem - short version: individuals and small teams taken collectively are better at timely classification, even though they may make the wrong decisions.
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Haven't read it, thanks for the suggestion!
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"free" markets are ill-defined and have never existed. Perhaps you meant to say "competitive" markets?
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Or just markets. Markers don't emerge naturally, feudalism or oligargy is the natural state when no working (democratic) government exists.
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One of the things I've liked about my area of Google at least is the avoidance of internal competition. Internal competition breeds mistrust, is clearly wasteful and makes it hard to build systems like Borg. You ask for internal competition, you get our messaging apps. Not good.
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That's easy, nothing to do with efficiency everything to do with humanity. Efficient Power brokering is what keeps large organizations alive.
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