Alignment Compilers

Sharing the right values does not determine the right actions. Even a benevolent AI faces an implementation problem: higher-level goals underdetermine what to do in particular local circumstances. Complex alignment problems often cannot be solved by specifying the behavior of every component. Across biological, behavioral, and economic systems, higher-scale conditions can instead be translated into intermediate control landscapes that let competent components work out detailed implementations locally. I identify alignment compilation as a recurring architecture in which a comparatively sparse interface makes higher-scale conditions locally actionable while competent components supply detailed implementation. The framework clarifies when such delegation is advantageous, where it can fail, and how alignment interfaces can participate in bidirectional adaptation between humans and AI systems.