This article showcases a speculative methodology for recreating interactions between a human and Google Search’s Auto-Predict interface as conversations, to explore how AI-based systems are both persuasive and deeply personal. Using ethnomethodology tools and a symbolic interactionist lens, the paper presents three versions of a single Google search, each variation building a slightly different angle on the plausible utterances and interpersonal dynamics of the human and nonhuman partners. This thought experiment emerges from a decade of classroom-based digital literacy exercises with young adults, training them to analyze their lived experiences with digital media, algorithms, and devices. Transforming information exchanges into personal conversations provides a creative method for analyzing how relations are co-constructed in the granular processes of interaction, through which mutual intelligibility is built, meaning about the world is made, and identities are formed. This critical analysis extends methods for human–machine communication studies and elaborates notions of algorithmic identity.

中文翻译：

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算法作为对话伙伴：从符号交互的角度看谷歌自动预测


本文展示了一种推测方法，用于将人类与 Google 搜索的自动预测界面之间的交互重新创建为对话，以探索基于人工智能的系统如何既具有说服力又具有深度个性化。使用民族方法论工具和象征性互动主义视角，本文提出了单个谷歌搜索的三个版本，每个版本都对人类和非人类伙伴的合理话语和人际动态建立了略有不同的角度。这个思想实验源于十年来针对年轻人进行的基于课堂的数字素养练习，训练他们分析他们使用数字媒体、算法和设备的生活经验。将信息交换转化为个人对话提供了一种创造性的方法，用于分析在交互的细粒度过程中如何共同构建关系，通过这种方法建立相互的可理解性，创造关于世界的意义，并形成身份。这一批判性分析扩展了人机通信研究的方法，并阐述了算法身份的概念。