[論文レビュー] From Principles to Rules: A Regulatory Approach for Frontier AI

Jonas Schuett, Markus Anderljung+3 more|arXiv (Cornell University)|Jul 10, 2024

Law, AI, and Intellectual Property被引用数 7

ひとこと要約

本論は、フロンティアAIの安全性に関する高レベルの原則から始め、規制能力が拡大するにつれてよりルールベースの要求へと段階的に移行するスペクトラム型の規制アプローチを提唱する。監督、適応性、能力開発を強調する。

ABSTRACT

Several jurisdictions are starting to regulate frontier artificial intelligence (AI) systems, i.e. general-purpose AI systems that match or exceed the capabilities present in the most advanced systems. To reduce risks from these systems, regulators may require frontier AI developers to adopt safety measures. The requirements could be formulated as high-level principles (e.g. 'AI systems should be safe and secure') or specific rules (e.g. 'AI systems must be evaluated for dangerous model capabilities following the protocol set forth in...'). These regulatory approaches, known as 'principle-based' and 'rule-based' regulation, have complementary strengths and weaknesses. While specific rules provide more certainty and are easier to enforce, they can quickly become outdated and lead to box-ticking. Conversely, while high-level principles provide less certainty and are more costly to enforce, they are more adaptable and more appropriate in situations where the regulator is unsure exactly what behavior would best advance a given regulatory objective. However, rule-based and principle-based regulation are not binary options. Policymakers must choose a point on the spectrum between them, recognizing that the right level of specificity may vary between requirements and change over time. We recommend that policymakers should initially (1) mandate adherence to high-level principles for safe frontier AI development and deployment, (2) ensure that regulators closely oversee how developers comply with these principles, and (3) urgently build up regulatory capacity. Over time, the approach should likely become more rule-based. Our recommendations are based on a number of assumptions, including (A) risks from frontier AI systems are poorly understood and rapidly evolving, (B) many safety practices are still nascent, and (C) frontier AI developers are best placed to innovate on safety practices.

研究の動機と目的

• Explain the regulatory challenge of frontier AI systems and the strengths/weaknesses of principle-based versus rule-based regulation.
• Propose a pragmatic, phased regulatory approach combining principles with increasing rule specificity.
• Advocate initial focus on core safety principles, strong regulatory oversight, and building regulatory capacity.
• Highlight assumptions about uncertain risks, nascent safety practices, and the role of developers in innovating safety.

提案手法

• Compare principle-based and rule-based regulatory approaches and identify their trade-offs.
• Argue for a non-binary spectrum and a phased adoption strategy for frontier AI regulation.
• Recommend concrete initial steps: mandate high-level safety principles, enhance regulator oversight of compliance, and invest in capacity building.
• Outline a forward-looking transition plan toward more rule-based regulation over time.

実験結果

リサーチクエスチョン

• RQ1 What are the comparative strengths and weaknesses of principle-based versus rule-based regulation for frontier AI?
• RQ2 How should policymakers sequence regulatory interventions from principles to rules to manage evolving frontier AI risks?
• RQ3 What initial regulatory steps best balance safety with innovation in frontier AI development?
• RQ4 What capacities must regulators develop to effectively oversee adherence to frontier AI safety principles?

主な発見

• Principle-based approaches offer adaptability but less certainty and higher enforcement costs; rule-based approaches provide certainty but risk becoming outdated.
• Regulation should not be binary but positioned on a spectrum with varying specificity across requirements.
• Initial regulation should mandate adherence to high-level safety principles, with strong regulator oversight of compliance and rapid capacity-building.
• Over time, the framework is likely to shift toward more rule-based requirements as safety practices mature and regulatory capacity grows.