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）致力于制造能够执行心智活动的计算机，随着这一目标的推进，人类正越来越多地将任务委托给机器。然而，AI系统在完成这些任务时往往表现出洞察力与理解力的异常失衡：它们具备新颖且更深刻的洞见，但人类心智原本在活动中赋予的许多重要特质却完全缺失。因此，关键问题在于：我们复制了心智的哪些特征，遗漏了哪些特征，以及这些缺失是否重要？人类在应对世界呈现的模糊性、涌现性知识及社会情境时，一个核心能力便是反思。然而，当前主流AI完全缺乏这一能力。本文探讨反思型AI可能呈现的样貌。继而，借鉴复杂系统、认知科学及智能体中的反思概念，我们勾勒出反思型AI智能体的架构，并指出未来发展方向。