Artificial Intelligence (AI) is about making computers that do the sorts of things that minds can do, and as we progress towards this goal, we tend to increasingly delegate human tasks to machines. However, AI systems usually do these tasks with an unusual imbalance of insight and understanding: new, deeper insights are present, yet many important qualities that a human mind would have previously brought to the activity are utterly absent. Therefore, it is crucial to ask which features of minds have we replicated, which are missing, and if that matters. One core feature that humans bring to tasks, when dealing with the ambiguity, emergent knowledge, and social context presented by the world, is reflection. Yet this capability is utterly missing from current mainstream AI. In this paper we ask what reflective AI might look like. Then, drawing on notions of reflection in complex systems, cognitive science, and agents, we sketch an architecture for reflective AI agents, and highlight ways forward.

翻译：人工智能（AI）旨在制造能够执行心智所能完成的各类任务的计算机。随着我们向这一目标迈进，人类任务正日益被委托给机器。然而，AI系统在执行这些任务时，通常呈现出一种洞察与理解之间异常失衡的状态：一方面涌现出全新且更深刻的洞见，另一方面，人类心智此前在此类活动中所具备的许多重要特质却完全缺失。因此，厘清我们已复现了心智的哪些特征、缺失了哪些特征，以及这些缺失是否重要，显得至关重要。当人类在应对世界呈现的模糊性、涌现性知识及社会背景时，其带入任务的核心能力之一便是反思。然而，当前主流AI系统完全缺乏这种能力。本文探讨反思型AI可能的形态，进而借鉴复杂系统、认知科学及智能体领域中关于反思的概念，勾勒出反思型AI智能体的架构雏形，并指出未来发展方向。