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Use highly advanced narrow AI to crack nanotech problems, begin world takeover. Alternatively, use quantum computers to crack nanotech problems, begin world takeover. If FAI is hard and AGI is easy then you need a singleton. If you need a singleton then you need a lot of power very quickly. The easiest way to get that much power that quickly is hard-to-copy technological advances.
Alternatively make your seed AI's decision theory as reflective as you possibly can and then release it at the last possible moment. Pray that reflection on the causes of your utility function is an attractor in decision-theory-space even for non-XDT AIs.
If there are better ideas than these I have not heard them.
Suppose I have already read a few books about institutional microeconomics and evolutionary game theory and I wish to gain a solid grounding in mechanism design and then algorithmic mechanism design. What papers or books on these subjects would you recommend?
Beware the sometimes subtle trap of thinking that, since you have thought about a big decision/belief at seemingly random intervals for a whole week (month, year) now, you have perspective on the decision/belief from a representative variety of your states of mind. State-dependent memory, habits, priming &c. make this unlikely unless you were deliberately making an effort.
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Ignoring sweepstakes as such[1], a focused rationalist should regard all bets with odds far from a coin flip with suspicion; there are often better bets, and with more information for calibration.
[1] Perhaps justifiably, as the "may" in the title of this Discussion post implies more uncertainty than you find in a typical sweepstake scenario where the fine print and simple arithmetic are enough calculation in themselves.
You should be less transparent about your social psychology experiments if you don't want people like me to make them transparent to everyone else.