Tinker highlights training objectives for legible chain-of-thought and interpretability evals

Tinker says Hase & Potts convert a model's chain-of-thought into a training objective so a monitor can read it more easily. Karvonen et al. use tested counterfactual outputs to build an interpretability eval. The post notes that counterfactuals do not explain the underlying mechanism, but their predictability is a useful foundation.