As a transformative general-purpose technology, AI has empowered various industries and will continue to shape our lives through ubiquitous applications. Despite the enormous benefits from wide-spread AI deployment, it is crucial to address associated downside risks and therefore ensure AI advances are safe, fair, responsible, and aligned with human values. To do so, we need to establish effective AI governance. In this work, we show that the strategic interaction between the regulatory agencies and AI firms has an intrinsic structure reminiscent of a Stackelberg game, which motivates us to propose a game-theoretic modeling framework for AI governance. In particular, we formulate such interaction as a Stackelberg game composed of a leader and a follower, which captures the underlying game structure compared to its simultaneous play counterparts. Furthermore, the choice of the leader naturally gives rise to two settings. And we demonstrate that our proposed model can serves as a unified AI governance framework from two aspects: firstly we can map one setting to the AI governance of civil domains and the other to the safety-critical and military domains, secondly, the two settings of governance could be chosen contingent on the capability of the intelligent systems. To the best of our knowledge, this work is the first to use game theory for analyzing and structuring AI governance. We also discuss promising directions and hope this can help stimulate research interest in this interdisciplinary area. On a high, we hope this work would contribute to develop a new paradigm for technology policy: the quantitative and AI-driven methods for the technology policy field, which holds significant promise for overcoming many shortcomings of existing qualitative approaches.

翻译：作为一项变革性通用技术，人工智能已赋能多个行业，并将通过无处不在的应用持续塑造我们的生活。尽管广泛部署AI带来了巨大收益，但解决相关风险、确保AI发展安全、公平、负责任且符合人类价值观至关重要。为此，我们需要建立有效的AI治理机制。在本研究中，我们表明监管机构与AI企业之间的战略互动具有类似Stackelberg博弈的内在结构，这促使我们提出一个基于博弈论的AI治理建模框架。具体而言，我们将此类互动建模为由领导者和追随者构成的Stackelberg博弈，相较于同步博弈模型，该框架能够捕捉潜在博弈结构。此外，领导者的选择自然衍生出两种设定。我们证明所提出模型可从两方面充当统一AI治理框架：一方面，可将一种设定映射至民用领域AI治理，另一种映射至安全关键及军事领域；另一方面，两种治理设定可根据智能系统能力进行选择。据我们所知，本研究首次运用博弈论分析和构建AI治理结构。我们还探讨了有前景的研究方向，期望能激发这一跨学科领域的研究兴趣。从宏观层面而言，希望本研究有助于开创技术政策新范式：即采用定量与AI驱动方法解决技术政策领域问题，这对于克服现有定性方法的诸多局限性具有重要潜力。