Artificial intelligence systems exhibit many useful capabilities, but they appear to lack understanding. This essay describes how we could go about constructing a machine capable of understanding. As John Locke (1689) pointed out words are signs for ideas, which we can paraphrase as thoughts and concepts. To understand a word is to know and be able to work with the underlying concepts for which it is an indicator. Understanding between a speaker and a listener occurs when the speaker casts his or her concepts into words and the listener recovers approximately those same concepts. Current models rely on the listener to construct any potential meaning. The diminution of behaviorism as a psychological paradigm and the rise of cognitivism provide examples of many experimental methods that can be used to determine whether and to what extent a machine might understand and to make suggestions about how that understanding might be instantiated.

翻译：人工智能系统展现出许多实用的能力，但似乎缺乏真正的理解。本文探讨了如何构建具备理解能力的机器。正如约翰·洛克（1689年）所指出的：词语是观念的符号（我们可将其转述为思想与概念）。理解一个词，意味着知晓并能够运用该词所标识的底层概念。当说话者将其概念转化为词语，而听者能大致复现这些概念时，说者与听者之间便产生了理解。当前的模型依赖听者自行构建潜在意义。行为主义作为心理学范式的式微与认知主义的兴起，为我们提供了多种实验方法：既可判断机器是否理解以及理解到何种程度，也可为如何实现这种理解提供启示。