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活动的计算机，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表现出洞察与理解的异常失衡：虽然新的、更深层次的洞察已然出现，但人类心智此前为这类活动带来的许多重要品质却完全缺失。因此，关键问题在于：我们已复制了心智的哪些特征，哪些特征仍然缺失，以及这是否重要。当人类面对世界呈现出的模糊性、涌现知识和社会情境时，他们为任务带来的一项核心能力便是反思。然而，这种能力在当前主流AI中完全缺失。本文探讨反思型AI可能呈现的形态，进而借鉴复杂系统、认知科学和智能体中的反思概念，勾勒出反思型AI智能体的架构，并指出前进方向。