Regarding the links, I really find the two first links quite interesting. The timelines are reasonable (15 years is only 10% probability). What I find unreasonable is to regulate when we are still working on brain tissue. We need more integrative and volitive AI to have anything to regulate.
I am very skeptical of any use of development, growth, and other historical and classic economics tools for AI. At the end, the classic Popper arguments (in “the Poverty of historicism”) that science cannot be predicted are strong.
Economics is mainly about “equilibrium” results given preferences and technology. Economics is sound in turning (preferences, technolgy) as input and provide “goods allocations” as output. The evolution of preferences and technologies is exogenous to Economics. The landscape of still unknown production possibility frontiers is radically unknown.
On the other hand find Economics (=applied game theory) as an extremely useful tool to think and create the training world for Artificial Intelligence. As an economist, I find that enviroment is the most legible part of AI programming. Bulding interesting a games and tasks to train AIs is main part its development. Mechanism design (incidentally my current main interest), algorithmic game theory, or agent based economics is directly related to AI in a way no other “classical economics” branch.
Regarding the links, I really find the two first links quite interesting. The timelines are reasonable (15 years is only 10% probability). What I find unreasonable is to regulate when we are still working on brain tissue. We need more integrative and volitive AI to have anything to regulate.
I am very skeptical of any use of development, growth, and other historical and classic economics tools for AI. At the end, the classic Popper arguments (in “the Poverty of historicism”) that science cannot be predicted are strong.
Economics is mainly about “equilibrium” results given preferences and technology. Economics is sound in turning (preferences, technolgy) as input and provide “goods allocations” as output. The evolution of preferences and technologies is exogenous to Economics. The landscape of still unknown production possibility frontiers is radically unknown.
On the other hand find Economics (=applied game theory) as an extremely useful tool to think and create the training world for Artificial Intelligence. As an economist, I find that enviroment is the most legible part of AI programming. Bulding interesting a games and tasks to train AIs is main part its development. Mechanism design (incidentally my current main interest), algorithmic game theory, or agent based economics is directly related to AI in a way no other “classical economics” branch.