探讨自主AI生成内容的归属规则与所有权失效机制。
Autonomous AI and Ownership Rules
- 基于可追溯性用占有原则分配所有权，不可追溯则转由新使用者持有。
- 自主AI故意逃避归属可能引发税收套利与监管规避问题。
- 提出赏金、私激励和政府补贴等机制防止无人拥有AI导致市场失灵。
本文分析了人工智能生成内容在何种情况下仍与原始创造者关联，以及在何种情形下会失去这种关联——无论是因疏忽、刻意设计还是涌现行为所致。当AI可追溯至源头时，取得权理论提供了一种高效的所有权分配方式，既维护投资激励，也确保问责机制。一旦AI变得不可追溯——无论出于疏忽、有意隐藏还是自发行为——首次占有规则可激励新持有人将其整合到生产性用途中。研究还探讨了战略性所有权消解：即自主AI被故意设计为规避归属，从而产生税收套利与监管规避机会。为应对这些效率损失，文章建议采用赏金制度、私人激励及政府补贴，以促进对AI的捕获，防止无主AI扭曲市场。
原文摘要 · Abstract (English)
This Article examines the circumstances in which AI-generated outputs remain linked to their creators and the points at which they lose that connection, whether through accident, deliberate design, or emergent behavior. In cases where AI is traceable to an originator, accession doctrine provides an efficient means of assigning ownership, preserving investment incentives while maintaining accountability. When AI becomes untraceable -- whether through carelessness, deliberate obfuscation, or emergent behavior -- first possession rules can encourage reallocation to new custodians who are incentivized to integrate AI into productive use. The analysis further explores strategic ownership dissolution, where autonomous AI is intentionally designed to evade attribution, creating opportunities for tax arbitrage and regulatory avoidance. To counteract these inefficiencies, bounty systems, private incentives, and government subsidies are proposed as mechanisms to encourage AI capture and prevent ownerless AI from distorting markets.
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