This article provides an ethnomethodologically informed ethnographic investigation of visually recognisable aspects of shared work spots in co-working office rooms. We focus on the phenomenon of holding a place in such environments, and document the participants’ practices which constitute distinguishing between empty and taken places. Our investigation leads to a conceptualisation of designed andad hocplaces, noting that objective assessments of rooms’ occupation status are problematic. We propose the notion of markers of presence, i.e. the material objects and their configurations, which participants use to indicate to others that a certain place is taken. Finally, we identify an observation area within the office space which participants recurrently use to assess the availability of work spots. We conclude by pointing out that rather than being tied to static features of material objects, the evidently visible occupational status of shared work spots is dynamically re-produced in participants’ ongoing courses of action.

Social sciences have been always formed and influenced by the development of society, adjusting the conceptual, methodological, and theoretical frameworks to emerging social phenomena. In recent years, with the leap in the advancement of Artificial Intelligence (AI) and the proliferation of its everyday applications, “non-human intelligent actors” are increasingly becoming part of the society. This is manifested in the evolving realms of smart home systems, autonomous vehicles, chatbots, intelligent public displays, etc. In this paper, we present a prospective research project that takes one of the pioneering steps towards establishing a “distinctively sociological” conception
of AI. Its first objective is to extract the existing conceptions of AI as perceived by its technological developers and (possibly differently) by its users. In the
second part, capitalizing on a set of interviews with experts from social science domains, we will explore the new imaginable conceptions of AI that do not originate from its technological possibilities but rather from societal necessities. The current formal ways of defining AI are grounded in the technological possibilities, namely machine learning methods and neural network models. Butwhat exactly is AI as a social phenomenon, which may act on its own, can be blamed responsible for ethically problematic behavior, or even endanger people’s employment? We argue that such conceptual investigation is a crucial step for further empirical studies of phenomena related to AI’s position in
current societies, but also will open up ways for critiques of new technological advancements with social consequences in mind from the outset.