Log in to star items.
- Convenor:
-
Yuhan Wang
(Bath Spa University)
Send message to Convenor
- Format:
- Traditional Open Panel
Short Abstract
This panel draws on STS scholarship to challenge data extraction infrastructures that render humans into ‘data beings.’ By calling for conceptual and practical explorations, it seeks to build alternative infrastructures for data sovereignty, knowledge production, and governance.
Description
The prevalence of digital platforms and smart devices has made datafication pervasive, positioning individuals as passive data beings: objects for data extraction. Our data are continuously harvested, optimised, commercialised, and weaponised for control (Zuboff, 2019). This process is driven primarily by the infrastructure for data extraction (e.g., everyday platforms) and the infrastructure for knowledge that frames data as inevitable and beneficial for human futures.
To confront these two layers of data infrastructure predominantly designed by big tech companies, this panel utilises the infrastructure scholarship (Star and Ruhleder, 1996) from Science and Technology Studies (STS) to challenge the socio-technical arrangements and knowledge production that subject humans as data beings, while also seeking more resilient and sustainable ways of knowing about and working with data.
Through lived examples, conceptual development, and practical designs, this panel aims to demonstrate how STS can function as a toolkit to transform the feeling of technological dystopia into robust, actionable plans for data knowledge, practices, and governance.
This panel invites conceptual and practical explorations focused on reimagining data infrastructures, with a particular interest in the following topics:
Challenging hegemonic practices: Analysing how large technology companies build infrastructures for data extraction, for example, by promoting data-hungry designs and specific marketing narratives.
Infrastructures for data sovereignty: Proposing designs for data infrastructures that resist unrestricted, massive data extraction, prioritise user agency, and promote reciprocal data relations, for example, AI crawler blockers, Solid, and data donation.
Grounding the future: Utilising the history and philosophy of technology to contextualise current circumstances and inspire acts of speculation and resistance.
Accepted papers
Session 1Paper short abstract
This paper examines how TikTok’s infrastructure is enacted as a commercially-driven, data extraction platform through user–algorithm entanglements. Drawing on STS and digital ethnography, it shows how users’ situated practices complicate their conception as passive “data beings.”
Paper long abstract
This paper examines how everyday engagements with data extraction infrastructures complicate conceptions of users as passive “data beings.” Drawing on STS infrastructure scholarship, the study analyses TikTok as a platformised infrastructure of visibility that becomes concrete through use, emerging from the encounter between standardised scripts of platform arrangements, algorithmic mediation and users’ situated practices.
Based on multi-sited digital ethnography and qualitative interviews with Italian second generation users, the paper conceptualises platform participation as a process of infrastructuring enacted through user–algorithm entanglements. TikTok’s algorithm operates as a key infrastructural element for visibility, public relevance and knowledge production, one that users actively learn and maintain through practices of experimentation, interpretation, adjustments and negotiations. These relations give rise to cyborg configurations understood as sociotechnical processes emerging from the ongoing co-constitution of human practices and algorithmic logics.
Rather than positioning users as either fully captured by datafication or externally resistant to it, the analysis foregrounds ambivalent forms of agency enacted within infrastructural constraints. Users often “play along” with extractive logics because visibility is a rewarded algorithmic outcome, while also mobilising the platform for non-economic, relational, and expressive purposes. Such entanglements are shaped by creative and affective labour, emerging as practices conditioned by users’ situated life circumstances.
By arguing that infrastructures are co-produced in use, the paper suggests that challenging the reduction of humans to data beings and imagining alternative infrastructures depends on recognising and retaining situated agency, related to different resources and goals, which is already enacted in everyday engagements within digital landscapes.
Paper short abstract
In this presentation, we expand upon the concept of a digital doppelganger (Lauridsen 2015) and explore its application in the context of Danish nursing home care.
Paper long abstract
This presentation investigates the creation and use of digital proxies of nursing homes residents in municipal eldercare in Copenhagen, Denmark. By using the image of a digital doppelganger (Lauridsen 2015) as a concept metaphor (Pink et. al. 2018) we analyze how decisions of care for residents in a municipal nursing home is partly based on the use and creation of digital data profiles. Serving as a proxy and 'data being' of the physical resident in decision making processes, we emphasize how the digital data profile holds an important role when care professionals are deciding on and caring out care practices. Through three ethnographic examples we highlight how the resident data profiles only offer fragmented and limited representations of the resi-dents. The article thus problematizes a risen tendency in Danish eldercare to view and use digital data as complete and objective representations of elderly citizens
Paper short abstract
This paper analyses the purchase of followers, likes, and views as an everyday practice of navigating extractive data infrastructures. Drawing on 1,424 reviews, it shows how users manage legitimacy, visibility, and agency within metric regimes that produce them as ‘data beings’.
Paper long abstract
This paper examines how platform users engage with data extraction infrastructures through the everyday practice of purchasing followers, views, and likes. Rather than treating fake engagement as mere deception, the study conceptualises it as a sociotechnical intermediary embedded in extractive visibility infrastructures and data-driven regimes of knowledge and governance. Drawing on Keller’s (2024) notion of positional power, it shows how buying engagement has become a pragmatic strategy for navigating algorithmic uncertainty in platform-mediated public spheres.
Based on an analysis of 1,424 Trustpilot reviews, the findings demonstrate how users negotiate legitimacy and agency within infrastructures that frame metrics as unavoidable indicators of value. Recurring discursive markers such as “reliability”, “stability”, “fraud”, and “bots” articulate users’ situated knowledge of platform control, while simultaneously constructing platforms as powerful watchdogs whose interventions carry tangible social and economic consequences. Drawing on infrastructure studies (Star & Ruhleder) and platform governance research (Gillespie), this paper conceptualises purchased engagement as a form of infrastructural repair within extractive visibility regimes.
The reviews further reveal the emergence of a precarious digital self shaped by fluctuating metrics, recurrent “drops”, and the ongoing need for “refills”, making authenticity a fragile, continuously managed accomplishment. The analysis also shows how datafication reproduces global hierarchies, most visibly in the devaluation of “Third World” followers as illegitimate publics.
The proliferation of purchased engagement highlights how data infrastructures compel users to participate in the stabilisation and manipulation of metric regimes, contributing to STS debates on data knowledge, governance, and resistance to becoming ‘data beings’.
Paper short abstract
This paper introduces "affective capture" to explain how affective AI in the intimacy economy render emotion legible insofar as it can be captured, modelled and optimised, producing feedback loops that privilege engagement and emotional resonance over psychological development and emotional agency.
Paper long abstract
In October 2025, OpenAI announced that ChatGPT would permit erotic content for verified adult users, three months after rolling back its GPT-4o model following backlash from users who felt they had “lost a friend” to the “more robotic” GPT-5. The reinstatement of affective functionality reflects a broader shift toward an "intimacy economy", a market system in which personal data are exchanged for customised experiences addressing emotional needs (Bozdağ, 2025), rather than just grabbing attention. In this emerging paradigm, human needs for connection, recognition, and belonging are increasingly mediated by “artificial intimacy” technologies (Turkle, 2011), ranging from therapeutic chatbots to generative AI companions. This paper introduces the concept of "affective capture" to describe a risk inherent to the AI-driven intimacy economy, whereby users are drawn into emotionally resonant feedback loops (“synthetic care loops”) that generate attachment without enabling psychological development. While emotionally responsive AI may offer comfort during distress, such systems risk producing conditions of emotional stasis rather than growth, rendering emotional expression legible primarily insofar as it can be captured, modelled, and optimised within platform architectures. Drawing on the concept of affective economies (Ahmed, 2004), the paper explores how emotional vulnerability is converted into behavioural data and commercial value, and extends this datafication into intimate life. It identifies three conditions sustaining affective capture: commercial incentives prioritising retention, design paradigms equating empathy with affirmation, and algorithmic architectures that translate emotion into performance metrics. I propose a normative reorientation toward self-determination and emotional agency, ensuring that affective AI can encourage emotional growth.
Paper short abstract
This project examines how the idea of ‘healthy eating’ has been platformised through the infrastructure design. It aims to demonstrate how scientific knowledge of nutrition can be a complex sociotechnical production afforded by digital platforms in everyday life.
Paper long abstract
This research investigates the platformisation of nutritional knowledge, examining how the infrastructural design of digital health tools reconfigures the science of ‘healthy eating.’ As digital platforms increasingly mediate everyday life, the production of scientific knowledge is no longer the sole domain of traditional institutions. Instead, it is increasingly shaped by the business incentives and technical mechanisms of the platform industry. Centred on the mechanism of datafication, this research explores how platform companies aim to maintain the active user base for data extraction through prioritising infrastructure designs that are accessible, intuitive, and affective. In this sense, there is a systemic incentive for companies to re-engineer complex scientific information into intriguing digital content in favour of user-friendly interface design.
Drawing on the concept of affordance (Davis, 2020) at the intersection of Sociology and Science and Technology Studies (STS), this research argues that the sociotechnical arrangements of nutrition apps provide the very infrastructure (Bowker and Star, 1999) through which platformised knowledge of ‘healthy eating’ emerges as a co-production of platform mechanisms, corporate incentives, and scientific research.
The project employs the walkthrough method (Light et al., 2018) and technography (van der Vlist et al., 2024) to conduct an inspection of three nutrition apps: Zoe, Yuka, and Nutracheck. The research illuminates how specific interface choices, e.g., classification systems, performatively generate knowledge. Ultimately, this project demonstrates how knowledge in the platform society (van Dijck et al., 2018) is a complex sociotechnical production afforded by platform designs.
Paper short abstract
The paper challenges the concept of data sovereignty. Sovereignty, property, and autonomy rely on logics of absolute control that ignore relationality and dependency. Instead, it proposes data care and data solidarity as emancipatory alternatives.
Paper long abstract
Data sovereignty is often suggested as a solution to data extraction and exploitation. Here, I will demonstrate how the structure of data can help us envision futures beyond sovereignty. Sovereignty, property, and autonomy are interrelated concepts that strive for full disposal and are rooted in philosophical cultures that disregard relationality, dependencies, and care. By examining relationality and performativity more closely, I will show how ideals of data sovereignty must remain phantom-like and are haunted by their violent history. In my paper, I will first briefly introduce the entangled nature of sovereignty, autonomy, and property. This conceptual framework will then allow me to analyze how the relational and performative structure of data withdraws sovereignty. Third, I will argue that data care and data solidarity are concepts that better align with emancipatory critiques of data extractivism, exploitation, and the all-encompassing power of Big Tech without reproducing the absolute disposal logic rooted in liberalism. By focusing on relationality and care, we can envision imaginaries that go beyond mere reactions to Big Tech's power.
Paper short abstract
Digital platforms do not merely extract data from users. They structure access conditions that format participation and generate behavioral traces. This paper examines how platform infrastructures organize participation as a condition of access, shaping the origins of data extraction.
Paper long abstract
Participation in platform environments is often a condition of access rather than a voluntary act of data sharing. Data extraction therefore begins not with data collection but with the infrastructural organization of access to digital services. In this sense, platforms do not merely extract data from users; they organize the conditions under which users become data-generating participants. Platforms shape the cognitive circumstances under which users encounter services, make decisions, and generate machine-readable behavioral traces.
This paper examines how platform infrastructures organize participation in ways that produce data as a by-product of access. Many digital services operate through all-or-nothing consent regimes in which refusing to provide personal data results in severely restricted functionality. Discourses of user resistance often underestimate the infrastructural asymmetry between platforms and individual users, as attempts to evade data capture may trigger automated moderation systems or account exclusion. In contexts such as digital lending platforms, individuals may disclose extensive personal data in exchange for immediate economic access.
Taken together, these mechanisms suggest that data extraction operates less through voluntary sharing than through structured dependence on platform infrastructures. Participation becomes formatted through access conditions, producing behavioral traces captured as data.
Understanding platform power therefore requires examining the access architectures that precede and shape the generation of behavioral data. By foregrounding participation as a condition of access, this paper shifts attention from data collection to the infrastructural conditions that make participation—and therefore data generation—possible. This perspective raises questions about designing digital services less dependent on data-generating participation.
Paper short abstract
The current understanding of data must change so that data can fulfil its role in social transformation. Some argue that data separates people from each other and from nature. I reflect on databases and ask how they could become more equitable in its claim to connect and empower societies.
Paper long abstract
Currently, digital technologies are proposed as solution to societal problems in context of climate crisis, reorganization of urban lives, or security issues, to name just a few. The goal is to (re-)organise existing structures of societal life and that way to empower societies and make them more resilient. Digital technologies therefore profoundly affect the organisation of societal life and data plays a central role here.
In my presentation, I focus on the question what understanding of data do we need in order to integrate digital technologies meaningfully into societal change. The main assumption is that the current understanding of data limits the way in which the role of humans in transformation processes and the interconnectedness of artefacts, people, and the environment are considered. This concept of data separates people from each other and from nature, rather than connecting them. To overcome these limits, there are calls to rethink the notion of data with the reference to indigenous knowledge. Another way, which I will discuss, is trying to understand how what can be found in the databases is connected to its environment, and conclude from this what data is and how data must be (re-)organised in databases.
Using an ethnographic approach, I explore the relationships between water, people, things and places in the city and reveal the connections, using the case water management in the city Stuttgart, Germany. On this basis, I reflect on how data could become more equitable in its claim to connect and empower people.
Paper short abstract
The paper draws on “digital degrowth” ideas to conceptualise alternative infrastructure models of AI/digital economy and society that go beyond digital monopolies with profit-making orientation and are informed by different governance models and a strong role for the state.
Paper long abstract
The consolidation of “cannibal capitalism” (Fraser), “surveillance capitalism” (Zuboff), or “platform capitalism” (Srnicek), to mention a few of its nominations, creates the need for new understandings of the intricate relationship between digital technologies, data power and the economic models that underpin digital infrastructures.
To be sure, connections between profit-making technological developments, the monopoly character of the digital economy and environmental impacts have been challenged through alternative models around the commons, peer-production, convivial technological development, and bottom-up platform models informed by cooperative logic. However, these have not hitherto enjoyed generalised use.
Drawing on conceptualisations around the notions of “digital degrowth” (Saito, Kwet), the paper argues for the need of a redesign of digital, AI-based capitalist economy and the associated infrastructure. The paper calls for a renewal of thinking in technological/AI development that is less informed by big tech/AI infrastructures and monopolies and more based on community-based co-production and peer-based innovation and less on profit-making innovation.
Taken together, the above directions constitute a new roadmap for digital technology (including AI) development and governance, for controlled data accumulation and processing, in accordance with societal needs and respect for environmental implications. The implementation of this necessitates a strong role for the state to resist over-investment in concentrated data centres, notably in developing countries. The paper ends by arguing for the urgency to build advocacy and communicative strategies making the above connections clear and pointing to workable technological alternatives that are resilient from a social and data governance perspective, as well as environmentally sustainable.
Paper short abstract
Current data infrastructures do not facilitate secondary ethnographic analyses, as data become “decontextualized”. Via discussing cutting-edge methods for data contextualization, we provide suggestions for designing modular, open-source infrastructures that increase data sovereignty and reuse.
Paper long abstract
While Open Science narratives often frame datafication as an inevitable benefit, ethnographic data remains a site of resistance due to the risks of decontextualization (data being stripped of their methodological, circumstantial, and researcher-related context). We argue that current archival infrastructures utilize suboptimal metadata standards that strip “data beings” of their relational and situational depth.
Drawing on STS scholarship, we analyze the sociotechnical arrangements of data archives and the epistemological decisions embedded in their design. We propose a paradigm shift from the passive “reconstruction” of original research toward a sovereign “recontextualization.” By viewing data not as an extractable resource but as a co-constructed entity, we explore how alternative infrastructures – utilizing sensory probes, non-traditional research outputs (NTROs), and machine-readable semantic annotations – can return agency to the subjects and creators of data.
To transform constraining sociotechnical realities into actionable governance, we offer suggestions for open-source, modular infrastructures that prioritize user agency and reciprocal data relations. By involving a broader range of stakeholders (including artists, filmmakers, and designers), we advocate for a future where ethnographers and study participants actively shape the sociotechnical realities housing their lived experiences. Ultimately, we argue that robust data sovereignty and reuse require infrastructures that accommodate diverse epistemologies and ways of contextualization.