mlsanityData to 7 Oct 2026

Regulatory Markets for AI Safety

arXiv 2001.00078 ↗First posted 11 Dec 2019cs.CY econ.GN q-fin.ECcited by 13

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Abstract (arXiv)

We propose a new model for regulation to achieve AI safety: global regulatory markets. We first sketch the model in general terms and provide an overview of the costs and benefits of this approach. We then demonstrate how the model might work in practice: responding to the risk of adversarial attacks on AI models employed in commercial drones.

Key facts. Cited by 13 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Dec 2019.

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Citing papers per year: 2021: 4; 2022: 0; 2023: 3; 2024: 3; 2025: 3.

13 papers.

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  1. 2021Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safetycited by 35
  2. 2025Media and responsible AI governance: a game-theoretic and LLM analysiscited by 11
  3. 2025Do LLMs trust AI regulation? Emerging behaviour of game-theoretic LLM agentscited by 11
  4. 2024Trust AI Regulation? Discerning users are vital to build trust and effective AI regulationcited by 9
  5. 2023Exploring the Relevance of Data Privacy-Enhancing Technologies for AI Governance Use Casescited by 5
  6. 2023An International Consortium for Evaluations of Societal-Scale Risks from Advanced AIcited by 5
  7. 2025Real-World Gaps in AI Governance Researchcited by 5
  8. 2021Beyond Fairness Metrics: Roadblocks and Challenges for Ethical AI in Practicecited by 4
  9. 2024Evolutionary mechanisms that promote cooperation may not promote social welfarecited by 3
  10. 2024Exploring Cross-model Neuronal Correlations in the Context of Predicting Model Performance and Generalizabilitycited by 3
  11. 2023Both eyes open: Vigilant Incentives help Regulatory Markets improve AI Safetycited by 2
  12. 2021A Framework for Understanding AI-Induced Field Change: How AI Technologies are Legitimized and Institutionalizedcited by 1
1 more
  1. 2021Safe Transformative AI via a Windfall Clausecited by 0