NBER Working Papers · 2026 · Joshua S. Gans
中文摘要
监管者应如何将双重用途人工智能模型的分阶段访问与开发者责任相结合？本文构建了一个防御者与一个对手搜寻同一软件漏洞的模型。模型发布后，责任机制会促使防御者投入更多搜寻努力，但也会使对手的搜寻变得更加费力，从而限制了责任机制对损害的影响。独占访问消除了这种策略性反应，因此分阶段访问与责任机制在保护方面具有互补性。防御性搜寻努力会随着发布日期临近而增加，使进一步推迟发布所带来的收益逐渐降低。因此，最优评估窗口存在上限，其对损害加剧的响应也会趋于饱和。由于防御性搜寻需要耗费实际资源，有效率的责任比例可能低于损害的完全内部化水平。该比例通常无法促使开发者选择监管者所偏好的发布日期，因此在发布时点上仍有必要单独施加强制性规定。
Abstract
How should regulators combine staged access to a dual-use AI model with developer liability? I model a defender and an adversary searching for the same software flaws. After release, liability induces more defensive search but also makes the adversary search harder, limiting its effect on harm. Exclusive access removes this strategic response, so staged access and liability are complements in protection. Defensive effort rises towards the release date, making additional delay progressively less productive. Optimal evaluation windows are therefore bounded, and their response to greater harm saturates. Because defensive search uses real resources, the efficient liability rate can be below full internalisation of harm. That rate generally cannot induce the developer to choose the regulator's preferred release date, leaving a distinct role for a timing mandate.