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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
You don't need to look at country-scale economies to observe this effect (obviously free markets >> central planning), it applies even to large companies. Past a certain scale you need teams that compete against each other with overlapping products. But why?
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
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...
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
So essentially what's good for Singapore cannot be good for the United Kingdom. (The USA is a bad example because that was a case of colonies coming together followed by annexations & agreements. More centripetal.)
(India is a worse example because it was scattered [ancient & medieval], then colonised [The Raj], then centripetal [Independence], converted to centrifugal [Constitution], then centralised [Congress] & now in the midst of chaos [BJP]). New Congress needed!
What about borg? It's a large centrally planned system that you probably use everyday https://ai.google/research/pubs/pub43438 …
"We are not sure where the ultimate scalability limit to Borg’s centralized architecture will come from; so far, every time we have approached a limit, we’ve managed to eliminate it."
centralized planning, as an optimizing tool per goal, falls into an optimization pit, from which it can then never escape, as the environment evolves. Perfection is death
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