Putting Trust to the Test: Making Sense of Human–Machine Interactions on TikTok

People’s interaction with online content is increasingly facilitated by intelligent user interfaces and artificial agents. In this article, I explore this shift by drawing on ethnographic fieldwork with users of the TikTok app. More specifically, I write on their interactions with the TikTok algorithm as a form of human–machine interaction and through the lens of trust. Along concrete ethnographic data, this article lays out the multifaceted process in which participants negotiated trust in the TikTok algorithm as an interaction partner in their everyday pursuits for relaxation and entertainment. Understanding trust as something deeply relational, mediating the position that one takes to another, this article outlines the constitutive embodied and affective dimensions of trust. It shows how participants dealt with feelings of their trust in the TikTok algorithm being put to the test, as well as how they negotiated their distance and closeness to it accordingly. By doing so, this article will demonstrate how trust functions a key mediator of meaningful human–machine interaction – shaping not just meaningful outcomes but also meaningful processes of interaction. From this angle, this article closes with an argument for research on the foundational role of trust in human–machine interaction, specifically in ways that look beyond the cognitive processes of judging trust and broadening the scope towards the material and cultural contexts in which people trust others.