debate

**Debate** is an **AI alignment approach where two AI agents argue opposing sides of a question, and a human judge selects the most compelling argument** — the key insight is that even if the judge can't solve the problem directly, they can evaluate which argument is more convincing, enabling scalable oversight of superhuman AI. **Debate Framework** - **Two Agents**: Agent A and Agent B take opposing positions on a question. - **Arguments**: Agents alternately present arguments, evidence, and counterarguments. - **Judge**: A human (or simpler AI) evaluates the debate and selects the winner. - **Training**: Agents are trained to win debates — incentivized to find and present truthful, compelling arguments. **Why It Matters** - **Scalable Oversight**: The judge doesn't need to know the answer — just evaluate arguments. Enables oversight of superhuman AI. - **Truth-Seeking**: In a zero-sum debate, the optimal strategy is to present truth — lies can be exposed by the opponent. - **Alignment**: If debate incentivizes truth-telling, it provides a scalable mechanism for aligning AI with human values. **Debate** is **adversarial truth-finding** — using competitive argumentation to elicit truthful AI outputs that human judges can verify.