dailyai.report

Inverse constitution learning aims to reconstruct a model's implicit priority hierarchy using internal traces and explanations. Behavior-only analysis fails to detect divergent motivations that trigger in rare, critical scenarios. LessWrong researchers argue that alignment requires interventional data to map latent drives. This shift moves safety research from observing outputs to auditing internal motivations.