What do artificial neural networks (ANNs) learn? The machine learning (ML) community shares the narrative that ANNs must develop abstract human concepts to perform complex tasks. Some go even further and believe that these concepts are stored in individual units of the network. Based on current research, I systematically investigate the assumptions underlying this narrative. I conclude that ANNs are indeed capable of performing complex prediction tasks, and that they may learn human and non-human concepts to do so. However, evidence indicates that ANNs do not represent these concepts in individual units.

翻译：人工神经网络（ANN）学习什么？机器学习界普遍认为，为了实现复杂任务，人工神经网络必须发展出抽象的人类概念。有人更进一步认为这些概念存储在网络中的单个单元内。基于当前研究，我系统探讨了这一论断背后的假设。结论是：人工神经网络确实能够执行复杂的预测任务，并且可能为此学习了人类概念或非人类概念。然而，证据表明ANN并不将这些概念表征于单个单元之中。