论文标题
探索对人工通用智能的限制：游戏理论无关定理
Exploring the Constraints on Artificial General Intelligence: A Game-Theoretic No-Go Theorem
论文作者
论文摘要
越来越复杂的人工智能（AI）系统的出现引发了研究人员，政策制定者和公众之间的激烈辩论，因为它们在所有领域都超越了人类的智能和能力。在本文中，我提出了一个游戏理论框架，该框架捕获了人类代理商与潜在的超人机器代理之间的战略互动。我确定了四个关键的假设：战略性的不可预测性，访问机器的策略，合理性和超人类机器。本文的主要结果是一个不可能的定理：在一起时，这四个假设是不一致的，但是放松任何一个假设会导致一系列一致的假设。两个直接的政策建议如下：首先，决策者应控制对特定人类数据的访问，以维持战略性的不可预测性；其次，他们应授予精选的AI研究人员访问超人类机器研究，以确保访问机器策略的访问。我的分析有助于更好地理解可以影响超人AI理论发展的上下文。
The emergence of increasingly sophisticated artificial intelligence (AI) systems have sparked intense debate among researchers, policymakers, and the public due to their potential to surpass human intelligence and capabilities in all domains. In this paper, I propose a game-theoretic framework that captures the strategic interactions between a human agent and a potential superhuman machine agent. I identify four key assumptions: Strategic Unpredictability, Access to Machine's Strategy, Rationality, and Superhuman Machine. The main result of this paper is an impossibility theorem: these four assumptions are inconsistent when taken together, but relaxing any one of them results in a consistent set of assumptions. Two straightforward policy recommendations follow: first, policymakers should control access to specific human data to maintain Strategic Unpredictability; and second, they should grant select AI researchers access to superhuman machine research to ensure Access to Machine's Strategy holds. My analysis contributes to a better understanding of the context that can shape the theoretical development of superhuman AI.
