arXiv:2603.05175v2 Announce Type: replace Abstract: The rapid proliferation of AI applications has intensified debate on effective regulation of these black-box services. Effective regulation must balance two competing goals: (1) deterring non-compliant providers from entering the market, while (2) retaining compliant ones. We call this ideal the perfect market outcome (PMO). Regulators face two compounding obstacles that make PMO difficult to achieve: providers hold private information and can act strategically to evade compliance, while any evidence drawn or derived from a finite sample carr
The increasing deployment of advanced AI applications necessitates robust regulatory frameworks, making this an immediate and critical area of focus.
This paper highlights the complex challenges regulators face in fostering innovation while mitigating risks associated with black-box AI, directly impacting future market structures and national competitiveness.
Regulatory approaches will evolve to incorporate incentive-aware mechanisms, moving beyond simple deterrence to strategic market shaping.
- · Governments with strong regulatory capabilities
- · Ethical AI developers
- · AI assurance providers
- · Non-compliant AI providers
- · Nations with weak regulatory frameworks
- · AI companies reliant on opacity
Regulators will develop more sophisticated tools to monitor and enforce AI compliance, accounting for strategic behavior.
Increased transparency requirements or explainability mandates for AI systems become standard, influencing AI development lifecycles.
A global divergence in AI regulatory effectiveness could emerge, impacting international AI competition and market access.
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Read at arXiv cs.LG