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Once we train models on the chain of thought outputs, next token prediction can solve the halting problem for us (eg, this chain of thinking matches this other chain of thinking).

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I think that is how human brains work. When we practice, at first we have to be deliberate (thinking slow). Then we “learn” from our own experience and it becomes muscle memory (thinking fast). Of course, it increases the odds we are wrong.

Or worse, we incorrectly overweight the wrong chain of thinking to an irrelevant output (but pragmatically useful output), at scale.

For example, xenophobia as a response to economic hardship is the wrong chain of thinking embedded in the larger zeitgeist.

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