Empirical and robust over theoretical and perfect

For AI alignment, an empirical, practical approach is preferable to chasing utopian theoretical perfection (whose values, what alignment means), because perfect systems are often brittle; the goal should be to make models good enough and robust enough that nothing terrible happens and we can keep iterating — raising the floor matters more than reaching the ceiling.