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Responsible Reporting for Frontier AI Development

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arxiv 2404.02675 v1 pith:6PO6PEPY submitted 2024-04-03 cs.CY cs.AI

Noam Kolt , Markus Anderljung , Joslyn Barnhart , Asher Brass , Kevin Esvelt , Gillian K. Hadfield , Lennart Heim , Mikel Rodriguez
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Jonas B. Sandbrink Thomas Woodside
This is my paper · ORCID
classification cs.CYcs.AI
keywords frontierinformationsystemsreportingorganizationsresponsiblerisksaccess
verification ladder T0 review T1 audit T2 compute T3 formal
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Mitigating the risks from frontier AI systems requires up-to-date and reliable information about those systems. Organizations that develop and deploy frontier systems have significant access to such information. By reporting safety-critical information to actors in government, industry, and civil society, these organizations could improve visibility into new and emerging risks posed by frontier systems. Equipped with this information, developers could make better informed decisions on risk management, while policymakers could design more targeted and robust regulatory infrastructure. We outline the key features of responsible reporting and propose mechanisms for implementing them in practice.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Towards Responsible Governing AI Proliferation

    cs.CY 2024-12 conditional novelty 6.0 of 10

    The paper proposes a 'Proliferation' paradigm of AI, where small, hidden, augmented, decentralized, and open-weight models challenge compute-centric governance.

  2. Pre-Deployment Information Sharing: A Zoning Taxonomy for Precursory Capabilities

    cs.CY 2024-11 conditional novelty 6.0 of 10

    A zoning taxonomy for precursory AI capabilities underpins four recommendations specifying pre-deployment information sharing under the Frontier AI Safety Commitments.

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