Paper short abstract

Based on multimodal analysis of 87 autonomous vehicle left-turn maneuvers recorded by end users as beta testers, this study shows how safety is assessed in real traffic. Rather than inherent in technology, safety emerges as a graded evaluation through practical reasoning and human coordination.

Paper long abstract

Safety is not an inherent property of technology but is produced in situated interaction. This study examines how the safety of autonomous vehicles (AVs) is constituted and assessed by beta testers taking AVs on city rides. Drawing on multimodal conversation analysis (Goodwin, 2000; Mondada, 2014) and a collection of 87 left-turn maneuvers, a hazardous and complex scenario (Choi, 2010), the study analyzes YouTube videos recorded from multiple camera angles by testers themselves.

The findings, based on tests involving at least two end-users with access to Tesla’s autonomous beta software, show that maneuvers are collaboratively evaluated as unsafe, “not safe” or “not unsafe”, revealing a graduated spectrum of safety rather than a binary distinction. The analysis shows how evaluators’ practical reasoning (Garfinkel, 1967) organizes these judgments by attending to the traffic context, the situated spatial and temporal unfolding of vehicle operation, and the projected actions of other road users. In doing so, human actors coordinate with autonomous systems to manage risk and stabilize the technology within a situated sociotechnical framework (Raudaskoski, 2023; Due, 2024).

Although autonomous systems are often framed by media, industry, and some scholarly literature as “disruptive” (e.g., Brynjolfsson & McAfee, 2014; Ford, 2015), real-world performance depends on human judgment and situated action (Suchman, 2007). By foregrounding the “just how” of human-machine interaction, this study highlights the invisible labour and practical accomplishments through which humans make AV systems function reliably, challenging inflated narratives of technology disruption.