Constitutional AI: Harmlessness from AI Feedback

Maya and Leo dig into Constitutional AI, the Anthropic paper that swaps many human harmlessness labels for a short written constitution: the model critiques and rewrites its own risky answers, then an AI judge compares candidate replies against the principles to drive reinforcement learning from AI feedback. Using a healthcare scheduling assistant, they show why critique-before-revision matters, what 'harmless without going mute' looks like in a product, and then argue the paper's central bet on air — Leo backing AI feedback as the road to scalable supervision, Maya pressing the worry that model feedback can launder a model's own blind spots through a cleaner-looking pipeline. Sources: • Constitutional AI: Harmlessness from AI Feedback: https://arxiv.org/pdf/2212.08073 • ConstitutionalHarmlessnessPaper supplementary repository: https://github.com/anthropics/ConstitutionalHarmlessnessPaper