Existing strategies for managing risks from advanced AI systems often focus on affecting what AI systems are developed and how they diffuse. However, this approach becomes less feasible as the number of developers of advanced AI grows, and impedes beneficial use-cases as well as harmful ones. In response, we urge a complementary approach: increasing societal adaptation to advanced AI, that is, reducing the expected negative impacts from a given level of diffusion of a given AI capability. We introduce a conceptual framework which helps identify adaptive interventions that avoid, defend against and remedy potentially harmful uses of AI systems, illustrated with examples in election manipulation, cyberterrorism, and loss of control to AI decision-makers. We discuss a three-step cycle that society can implement to adapt to AI. Increasing society's ability to implement this cycle builds its resilience to advanced AI. We conclude with concrete recommendations for governments, industry, and third-parties.

存在的管理高级人工智能系统风险的策略通常关注于影响开发什么样的人工智能系统以及它们如何扩散。然而，随着高级人工智能开发者数量的增加，这种方法变得越来越不可行，并且阻碍了有益的和有害的用例。我们呼吁采用一种补充方法：提高社会对高级人工智能的适应能力，即减少特定级别的人工智能能力扩散所带来的预期负面影响。我们引入了一个概念框架，用于识别避免、防范和纠正潜在有害的人工智能系统使用的适应性干预措施，并结合选举操纵、网络恐怖主义和人工智能决策者失控的示例进行说明。我们讨论了社会可以实施的适应人工智能的三个步骤循环。增强社会实施这一循环的能力将提高社会对高级人工智能的韧性。最后，我们为政府、行业和第三方提出具体建议。

先进人工智能的社会适应