机器理解：如何更精确地提问与断言 AI 系统的理解能力
Machine understanding
研究者借鉴哲学与认知科学，提出一个把“理解”概念化为系统（S）与理解对象（T）之间关系的框架，用于更精确地提问和断言机器理解。该框架讨论了如何界定这一关系、系统与对象，并为每种情况给出可选方案。作者表示目标不是为某种理解理论辩护，而是为评估或推进机器理解的工作者提供概念工具。
What do artificial intelligence (AI) systems “understand”? This question arises not only in assessing a system’s intelligence but also in evaluation practices to ensure the safe and responsible deployment of AI. Drawing on scholarship from philosophy and cognitive science, and informed by current practices in AI, we develop a framework for asking more precise questions and making more precise claims about machine understanding. We conceptualize understanding as a relation between a system (S) and a target of understanding (T), and we discuss how to specify the relation, the system, and the target, offering a landscape of options in each case. Our goal is not to defend a particular account of understanding, but to provide conceptual tools for those working to assess or advance machine understanding.
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来源：Trends in Cognitive Sciences · cell.com