Central to our argument is the separation between two notions of understanding: interactional and dispositional. We will also inspect practices deployed to maintain the distinction between human and artificial interlocutors and the conditions under which this separation becomes strained. More specifically, we aim to expand prior work in CSCW by examining circumstances in which suspicion, deception, and disbelief are occasioned as natural phenomena. Our purpose in what follows is to address the question of what it means to act together, to cooperate, in a landscape potentially permeated by fake or artificial actors-that is, in what sense is interaction with the artificial itself contrived as a mere simulacrum? As articulated by McDermott, ‘When we can talk to machines, will we understand each other?’ (McDermott, 2007, p. As we aim to demonstrate further, this carefulness becomes especially important when bringing agentive technologies within the analytic scope. ( 2021) have characterized by its ‘careful examination of the nature of concept use and some scepticism about representational views of the mind’ (p. In pursuing our goal, we draw on the works of Wittgenstein, Garfinkel, and Sacks to align ourselves with an empirical and conceptual approach to CSCW that Randall et al. However, any detailed examination of understanding or intersubjectivity is bound to confront a wealth of thorny theoretical and methodological issues. Stahl ( 2016) argued that the question of how people can understand each other is a foundational issue for the social sciences with particular relevance to CSCW, as studies in the field continuously contribute analyses of how intersubjectivity is established in specific work practices. Understanding one another is perhaps not a prerequisite for cooperation, but it is deeply intertwined with the effectiveness of concerted action and the entailed intersubjectivity structures of our sense of reality (Schutz, 1976). The ability to ‘go on’ has been connected to understanding, most notably by Wittgenstein ( 1953). The keystone for the lyrics then picks up on suspicion as the very obstacle to a shared project. By shifting the focus to these parahuman relations, the paper aims to highlight the profound philosophical question of what acting in concert with others means-to ‘go on together’, as the song describes it. We will expand the scope of the implied relationship from lovers to persons interacting with digital agents or chatbots. An examination of the first line of the chorus allows us to elaborate on the aims of this essay. As with any good pop song, much meaning is contained in a few select words. Mark James wrote the song, which depicts a couple caught in a mistrusting and dysfunctional relationship, from which we borrowed our title. Therefore, this study concludes that the proliferation of conversational systems, fueled by artificial intelligence, may have unintended consequences, including impacts on human–human interactions. When suspicion is roused, shared understanding is disrupted. Furthermore, outside of experimental settings, any problems in identifying and categorizing an interactional partner raise concerns regarding trust and suspicion. The interplay between these forms of analysis shapes the developing sense of interactional exchanges and is crucial for established relations.
By departing from ethnomethodology and conversation analysis, we illustrate how parties in a conversation regularly deploy two forms of analysis (categorial and sequential) to understand their interactional partners. When interactions are successful but the artificial agent has not been identified as such, can it also be said that the interlocutors have understood each other? In what ways does understanding figure in real-world human–computer interactions? Based on empirical observations, this study shows how we need two parallel conceptions of understanding to address these questions. The passage from the theoretical to the practical domain also accentuates understanding as a topic of continued inquiry. Consequently, the ‘Turing test’ has moved from the laboratory into the wild. Thus, discerning whether an interactional partner is a human or an artificial agent is no longer merely a theoretical question but a practical problem society faces. The quality of the voice and interactivity are sometimes so good that the artificial can no longer be differentiated from real persons. In recent years, the field of natural language processing has seen substantial developments, resulting in powerful voice-based interactive services.
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