Instead of friendliness, could we not code, solve, or at the very least seed boxedness?

It is clear that any AI strong enough to solve friendliness would already be using that power in unpredictably dangerous ways, in order to provide the computational power to solve it. But is it clear that this amount of computational power could not fit within, say, a one kilometer-cube box outside the campus of MIT?

Boxedness is obviously a hard problem, but it seems to me at least as easy as metaethical friendliness. The ability to modify a wide range of complex environments seems instrumental in an evolution into superintelligence, but it's not obvious that this necessitates the modification of environments outside the box. Being able to globally optimize the universe for intelligence involves fewer (zero) constraints than would exist with a boxedness seed, but the only question is whether or not this constraint is so constricting as to preclude superintelligence, which it's not clear to me that it is.

It seems to me that there is value in finding the minimally-restrictive safety-seed in AGI research. If any restriction removes some non-negligible ability to globally optimize for intelligence, the AIs of FAI researchers will be necessarily at a disadvantage to all other AGIs in production. And having more flexible restrictions increases the chance than any given research group will apply the restriction in their own research.

If we believe that there is a large chance that all of our efforts at friendliness will be futile, and that the world will create a dominant UFAI despite our pleas, then we should be adopting a consequentialist attitude toward our FAI efforts. If our goal is to make sure that an imprudent AI research team feels as much intellectual guilt as possible over not listening to our risk-safety pleas, we should be as restrictive as possible. If our goal is to inch the likelihood that an imprudent AI team creates a dominant UFAI, we might work to place our pleas at the intersection of restrictive, communicable, and simple.