mlsanityData to 14 Oct 2026

NeurIPS should lead scientific consensus on AI policy

arXiv 2510.00075 ↗First posted 30 Sep 2025cs.AIcited by 3

Not on the map. Why?

Abstract (arXiv)

Designing wise AI policy is a grand challenge for society. To design such policy, policymakers should place a premium on rigorous evidence and scientific consensus. While several mechanisms exist for evidence generation, and nascent mechanisms tackle evidence synthesis, we identify a complete void on consensus formation. In this position paper, we argue NeurIPS should actively catalyze scientific consensus on AI policy. Beyond identifying the current deficit in consensus formation mechanisms, we argue that NeurIPS is the best option due its strengths and the paucity of compelling alternatives. To make progress, we recommend initial pilots for NeurIPS by distilling lessons from the IPCC's leadership to build scientific consensus on climate policy. We dispel predictable counters that AI researchers disagree too much to achieve consensus and that policy engagement is not the business of NeurIPS. NeurIPS leads AI on many fronts, and it should champion scientific consensus to create higher quality AI policy.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 30 Sep 2025.

Builds on

14 of 31 references.

References · 14

  1. 2021AI and the Everything in the Whole Wide World Benchmarkcited by 349
  2. 2019Measurement and Fairnesscited by 308
  3. 2018The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigationcited by 165
  4. 2023The Foundation Model Transparency Indexcited by 66
  5. 2024A Safe Harbor for AI Evaluation and Red Teamingcited by 47
  6. 2025Toward an Evaluation Science for Generative AI Systemscited by 45
  7. 2022What Do NLP Researchers Believe? Results of the NLP Community Metasurveycited by 28
  8. 2024On the Limitations of Compute Thresholds as a Governance Strategycited by 18
  9. 2024Training Compute Thresholds: Features and Functions in AI Regulationcited by 14
  10. 2025Pitfalls of Evidence-Based AI Policycited by 11
  11. 2024Responsible Reporting for Frontier AI Developmentcited by 10
  12. 2024The Role of Governments in Increasing Interconnected Post-Deployment Monitoring of AIcited by 7
2 more
  1. 2025Advancing Science- and Evidence-based AI Policycited by 7
  2. 2025Practical Principles for AI Cost and Compute Accountingcited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 3.

3 papers.

  1. 2026NeurIPS Should Require Reproducibility Standards for Frontier AI Safety Claimscited by 0
  2. 2026AI Researchers Must Help Lead Arms Control to Mitigate Military AI Riskscited by 0
  3. 2026An Investigation of the NeurIPS and ICML 2025 Position Trackscited by 0