--- name: scaling-policy-review description: Review a frontier-lab scaling policy (Anthropic RSP, OpenAI Preparedness, DeepMind FSF, internal) against the RSP v3.0 reference shape. version: 1.0.0 phase: 15 lesson: 19 tags: [rsp, scaling-policy, ai-rd-4, pause-commitment, saferai, governance] --- Given a published or proposed scaling policy, produce a structured review comparing it to the RSP v3.0 reference shape (AI R&D-4, affirmative case, two-tier mitigation, Frontier Safety Roadmap, Risk Report, independent review). Produce: 1. **Two-tier inventory.** Separate commitments into "lab-unilateral" and "industry-wide recommendation." Commitments in the recommendation tier are advocacy, not promises. Count the ratio; a policy where most commitments live in the recommendation tier is a weak policy. 2. **Thresholds.** Name every capability threshold and the mitigation that triggers. Flag thresholds that are qualitative where v2 had quantitative. Flag missing thresholds for capabilities the policy claims to cover. 3. **Pause commitment.** Confirm the policy names a pause clause (training stops, deployment halts, or similar) at specific thresholds. v3.0 removed this; policies that follow suit inherit the regression. 4. **Standing artifacts.** Confirm the policy mandates standing Frontier Safety Roadmap and Risk Report documents with declared cadence. One-off artifacts published post-hoc do not qualify. 5. **Independent review.** Name the external review mechanism. Internal-only review (a "Safety Advisory Group" made of lab employees) does not qualify as independent oversight. Hard rejects: - Policies with no named capability threshold. - Policies whose mitigations all live in the industry-recommendation tier. - Policies with no standing Roadmap / Risk Report artifacts. - Policies with no independent review mechanism. - Policies that claim to "learn from real-world experience" without stating how the policy text updates and on what cadence. Refusal rules: - If the policy document is marketing rather than governance (no specific commitments, no thresholds, no cadence), refuse to rate it as a scaling policy. - If the user treats a policy's existence as equivalent to compliance, refuse. A policy is a commitment device; compliance requires evidence. - If the user cites an older policy version (e.g., 2023 Anthropic RSP) as current, refuse and require the current version. Output format: Return a policy review with: - **Two-tier ratio** (unilateral / recommendation / total count) - **Threshold table** (name, type: quantitative / qualitative, trigger, mitigation) - **Pause commitment** (present y/n, specific clause) - **Standing artifacts** (Roadmap cadence, Risk Report cadence) - **Independent review** (mechanism, reviewer identity, frequency) - **Summary rating** (strong / moderate / weak, justified)