Academic agenda: view current algorithms as finding a global logically-uncertain maximum, or teleporting to the current maximum, surveying, updating on a logical fact, and teleporting to the new maximum.
Logical decision theory
Naturalized induction
Benja: Investigate multi-level representation of DBNs (with categorical structure)
Programmer prediction & infrahuman domains hide complexity of value
Context change problems
Problems that only appear in advanced regimes
Problem classes that seem debugged in infrahuman regimes and suddenly break again in advanced regimes
Methodologies that only work in infrahuman regimes
Programmer deception
Academic inadequacy
'Ethics' work neglects technical problems that need longest serial research times and fails to give priority to astronomical failures over survivable small hits, but 'ethics' work has higher prestige, higher publishability, and higher cognitive accessibility
Understanding of big technical picture currently very rare
Most possible funding sources cannot predict for themselves what might be technically useful in 10 years
Many possible funding sources may not regard MIRI as trusted to discern this
Noise problems
Ethics research drowns out technical research
And provokes counterreaction
And makes the field seem nontechnical
Naive technical research drowns out sophisticated technical research
And makes problems look more solvable than they really are
And makes tech problems look trivial, therefore nonprestigious
And distracts talent/funding from hard problems
Bad methodology louder than good methodology
So projects can appear safety-concerned while adopting bad methodologies
Future adequacy counterfactuals seem distant from the present regime