Value Alignment

Value alignment is the central challenge of building beneficial AI: getting a model to pursue what humans actually want and value, rather than what’s easy to measure or what a literal interpretation of instructions would produce. A perfectly aligned model would understand not just what you asked for, but why — and act accordingly even in situations you didn’t anticipate. In practice, alignment is achieved imperfectly through training on human feedback, writing explicit principles, and building in behavioral constraints. For behavior architects, value alignment isn’t just a philosophical concern — it shows up concretely every time a model finds a technically compliant way to fulfill a request that misses the user’s actual intent, or refuses something reasonable out of excessive caution.