What do we want from machine intelligence? We envision machines that are not just tools for thought but partners in thought: reasonable, insightful, knowledgeable, reliable and trustworthy systems that think with us. Current artificial intelligence systems satisfy some of these criteria, some of the time. In this Perspective, we show how the science of collaborative cognition can be put to work to engineer systems that really can be called ‘thought partners’, systems built to meet our expectations and complement our limitations. We lay out several modes of collaborative thought in which humans and artificial intelligence thought partners can engage, and we propose desiderata for human-compatible thought partnerships. Drawing on motifs from computational cognitive science, we motivate an alternative scaling path for the design of thought partners and ecosystems around their use through a Bayesian lens, whereby the partners we construct actively build and reason over models of the human and world.

我们希望机器智能能提供什么？我们设想的机器不仅是思考的工具，而且是思想的伙伴：与我们一起思考的合理、有洞察力、知识渊博、可靠和值得信赖的系统。当前的人工智能系统在某些时候满足其中一些标准。在这个视角中，我们展示了如何将协作认知科学用于设计真正可以称为“思想伙伴”的系统，这些系统旨在满足我们的期望并补充我们的局限性。我们列出了人类和人工智能思想伙伴可以参与的几种协作思维模式，并提出了人类兼容的思维伙伴关系的 desiderata。借鉴计算认知科学的主题，我们通过贝叶斯镜头为围绕其使用的思想伙伴和生态系统的设计开辟了一条替代的扩展路径，我们构建的合作伙伴可以积极构建和推理人类和世界的模型。