In this expository article we highlight the relevance of explanations for
artificial intelligence, in general, and for the newer developments in {\em
explainable ai}, referring to origins and connections of and among different
approaches. We describe in simple terms, explanations in da
提出一种新型的 AI 决策解释方法，即 Alterfactual Explanations，与传统的 Counterfactual Thinking 方法相比，该方法更加关注决策过程中的无关因素。通过在展示输入数据的无关特征发生改变时决策结果不变的替换真实场景，大幅提升了用户理解 AI 决策过程的效果。