When you try to make predictions, use a philosophy that performs predictions well. Bayesian rationality provides many useful tools to determine what the expected results are, but no tools to determine which expected result to choose. Trivialism provides tools more well suited for deciding in the absence of information.
[...] tools to determine which expected result to choose. Trivialism provides tools more well suited for deciding in the absence of information.
Whoa whoa whoa. Too much inferential distance. I don't even have the slightest remote idea of where to begin imagining how trivialism could possibly be used or imply anything even remotely like a tool for "choosing" anything.
Is there a "Learn Trivialism the Hard Way" thing somewhere that would help me bridge the gap between "X is true for all X" and actually choosing an action, a ...
Straight from Wikipedia.
I just had to stare at this a while. We can have papers published about this, we really ought to be able to get papers published about Friendly AI subproblems.
My favorite part is at the very end.
Trivialism is the theory that every proposition is true. A consequence of trivialism is that all statements, including all contradictions of the form "p and not p" (that something both 'is' and 'isn't' at the same time), are true.[1]
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