Machine learning algorithms reshape how people communicate, exchange, and associate; how institutions sort them and slot them into social positions; and how they experience life, down to the most ordinary and intimate aspects. In this article, we draw on examples from the field of social media to review the commonalities, interactions, and contradictions between the dispositions of people and those of machines as they learn from and make sense of each other.

中文翻译：

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循环、阶梯和链接：社交和机器学习的递归性

机器学习算法重塑了人们交流、交流和交往的方式；机构如何对它们进行分类并将它们置于社会地位；以及他们如何体验生活，直至最普通和最亲密的方面。在本文中，我们借鉴社交媒体领域的示例来回顾人与机器在相互学习和理解时的性格之间的共性、互动和矛盾。