Care-ful data studies: or, what do we see, when we look at datafied societies through the lens of care?

ABSTRACT

In this special issue, we ask: What do we see when we look at datafied societies through the lens of care? Following the footsteps of feminist writers, activists, and academics who take care as a vantage point for scrutinising and reimaging technoscientific societies, this special issue brings together scholars from critical data studies who explore what we might learn (and see) when we apply care ethics to the study of datafication. To develop a view on datafied societies informed by ethics, concepts, and practices of care, we propose a move from critique to care in social studies of data-driven technologies. We specifically identify five moves in which a care lens provides a new perspective when studying datafication and datafied societies: (1) a move from data-driven technologies to socio-digital care arrangements, (2) a move from data science to data work and care, (3) a move from technical to situated modes of knowledge production, (4) a move from studying harms of datafication to the politics of vulnerability, and (5) a move towards building communities of care. Discussing how critical data studies and care ethics can mutually contribute to each other, this collection explores how this way of thinking can inform new ways of seeing datafied societies and imagine living and being well in more than human worlds nurtured by care.

KEYWORDS:

• Care-ful data studies
• critical data studies
• datafication
• data feminism
• ethics of care

In this special issue, we ask: What do we see¹ when we look at datafied societies through the lens of care? Seeing and reimagining the world through care is a feminist move that has a long tradition. It encourages others to question the status quo and work towards more equitable, inclusive, and sustainable futures. One example of such a feminist reimagination of technoscientific progress was published in 1905 by Bengali Muslim writer and social reformer Rokeya Sahkawat Hossain. In her essay Sultana’s Dream, Hossain encourages readers to dream with technoscience on how to do life, gender, science, and society differently. The protagonist of the story is a Bengali woman who dreams of a world radically different to the patriarchal, colonised, and highly segregated society in which Hossain lived. A world in which women engineers and scientists create technoscientific innovations to further environmental and social justice rather than advance warfare, oppression, and economic competition. Their innovations include solar-powered watering and cooking technologies, which nurture a society centered around human and more than human care relations. Hossain’s dreaming protagonist challenges the status-quo, it allows readers to see that there are other ways of doing things and other ways of being in the world, ‘even if improbable, for both women and science’ (Murphy, 2015).

Following the footsteps of Hossain and other feminist writers, activists, and academics who take care as a vantage point for scrutinising and reimaging technoscientific societies, this special issue brings together scholars from critical data studies who explore what we might learn (and see) when we apply care ethics to the study of datafication. Drawing on a rich interdisciplinary literature on care ethics and critical data studies, we acknowledge that the collective ‘we’ used in the title and throughout this editorial essentially refers to its two authors, Irina and Juliane, and our view and experiences of research in and about datafied societies. As guest editors based at European universities, we strived to bring together perspectives on care and datafied societies from different countries, societal domains, and theoretical stances. The idea for this special issue started with Irina’s doctoral dissertation that elaborated on the role of critique in the field of critical data studies (Zakharova, 2022), it was further developed in an open panel on ‘Care-ful datafied futures and technopolitics of care’ which Irina convened at the EASST 2022 conference and in which some of the contributors of this special issue already presented. Collectively, the authors in this special issue share our preoccupation with developing a view on datafied societies informed by ethics, concepts, and practices of care and lay the groundwork for a move from critique to care in social studies of data-driven technologies.

In the remainder of this editorial, we first introduce the field of critical data studies as well as different concepts and approaches to care ethics. We subsequently identify five moves in which a care lens provides a new perspective when studying datafication and datafied societies: (1) from data-driven technologies to socio-digital care arrangements, (2) from data science to data work and care, (3) from technical to situated modes of knowledge production, (4) from studying harms of datafication to the politics of vulnerability, and (5) towards building communities of care. In conclusion we discuss how critical data studies and care ethics can mutually contribute to each other, inform new ways of seeing datafied societies, and imagine more than human worlds nurtured by care.

Moving from critique to care in studies of datafied societies

Critical data studies is a growing interdisciplinary research field concerned with the recursive relations between digital data and society (Dalton et al., 2016; Hepp et al., 2022; Iliadis & Russo, 2016; Kennedy & Bates, 2017; Kitchin & Lauriault, 2014). It emerged as a response to the data-utopian views on society which gained traction with advancements in data-driven technologies processing big data. This critical response was initiated amongst others by boyd and Crawford (2012) who formulated ‘critical questions’ to the imaginaries of big data envisioning new possibilities for datafied knowledge production. Central to critical data studies is its critique of technological determinism, techno-solutionism, and ‘data-intensive and positivistic approaches’ (Iliadis & Russo, 2016, p. 1). As an interdisciplinary research field, critical data studies commits to understanding data as relational and historically situated in time and space, rather than a ‘raw’ material and resource (Gitelman, 2013). The term ‘critical data studies’, coined by Craig Dalton and Jim Thatcher (2014) served to distinguish this scholarship from other research interested in advancing computational techniques of big data analysis and also as a new way of conceptualising datafication: as data-induced transformation processes and their implications for societies (Schäfer & van Es, 2017; van Dijck, 2014).

A critical approach has been without doubt an important response to big data and subsequent iterations of data-driven technologies with the most recent incarnation in the form of generative AI. However, as Yanni Loukissas (2019) argues ‘critical reflection has its own limits; it can be detached rather than responsible, analytic rather than affective or conceptual rather than hands-on’ (p.19). Hence, critical data studies scholars increasingly argue that a response to the ever intensifying datafication of social life needs to move beyond critique and consider new ‘response-abilities’ (Haraway, 2016), affections, and care relations in research and practice (Jarke & Bates, forthcoming; Powell et al., 2022; Ruckenstein, 2023). Loukissas (2019) describes his engagement with data-driven technology as emerging from a care ethics:

Unlike critical reflection, care embraces affect, material engagement, and a host of concerns sometimes invisible in conventional work with technology. Care is critical in that it calls attention to neglected things. But it is more than critical reflection; it is a doing practice. In pursuing opportunities not only for critical reflection on data but in support of care too, I hope to bring largely unrecognized and unrewarded local sensibilities into efforts to understand data. (p. 19)

Science and technology studies (STS) scholar Maria Puig de la Bellacasa (2017) proposed a similar analytical move from critique to care by drawing on Bruno Latour’s (2004) provocative essay about practices of academic critique. For Latour, academic critique was focused on dismantling individual aspects of technoscientific reality which he addressed as matters of fact. Instead, Latour (2004) argued, researchers should critically attend to how ‘highly complex, historically situated, richly diverse’ (p. 237) matters of concern are assembled and shed light on the contingencies and associations of practices and actors. Puig de la Bellacasa, in turn, proposes to take this analytical move further by shifting the analytical focus to matters of care. In her posthumanist approach, she expanded the concept of care by redefining ‘the meanings of care for knowing and thinking with more than human worlds in technoscience and naturecultures’ (p.12).

Much of the current work on care ethics in STS and critical data studies builds on the ideas of political scientist Joan Tronto. In her joint work with Berenice Fisher, she defined care as

a species activity that includes everything we do to maintain, continue, and repair our world so that we may live in it as well as possible. That world includes our bodies, our selves, and our environment, all of which we seek to interweave in a complex, life-sustaining web. (Fisher & Tronto, 1990, p. 34, original emphasis)

Importantly, Fisher and Tronto understand care primarily as a normative disposition: an obligation to care that materialises in decision-making about who deserves and ought to receive care, the distribution of resources required for care, and the giving and receiving of care. As Nancy Fraser (2016) points out, care work, or care-giving tasks (such as rearing children, tending to the sick, maintaining households and relations within communities of people) have historically been allocated to women. Early concepts of care argued that the reason for this gendered care work was women’s ‘“different voice” attuned to relational well-being (‘care’) rather than abstract rule-following’ (Martin et al., 2015, p. 628 with reference to Gilligan 1982). Despite the criticism that emerged as a response to such a conceptualisation of care, it laid the foundation for understanding affective, gendered, and invisible aspects of care. Subsequent feminist research and activism focused on unequal power distributions for an analysis of care work (Fisher & Tronto, 1990; Narayan, 1995). Black feminist scholarship addressed intersectionality revealing further dimensions of inequalities (e.g., Collins, 1990).

Despite sharing a core view on care work as social reproduction necessary to sustain social order, care ethics is not a uniform theory and also encompasses post-ANT, relational views on care as a practice (e.g., Mol, 2008). In addition, the care lens includes postcolonial feminist understandings of care relations, for instance paternalistic/maternalistic care arrangements, invisibility and lack of monetary compensation in certain sectors of the labour market, or colonial extractivism through presumed care (Graham, 2007; Mooten, 2015; Narayan, 1995). The political move to use care as legitimation of uncaring actions has been addressed as the ‘darker side’ of care (Martin et al., 2015, p. 627). Particularly de- and postcolonial care lenses, however, address care not only as a tedious task or a potentially toxic relation, but also as acts of self-determination, community support, and joy (Graham, 2007).

In working on this special issue we, however, came to notice how these perspectives are yet to take life in datafied societies into view. In the following, we present five moves in which a care lens enables us to look differently at datafied social worlds. We do this by presenting and discussing current work on care in data studies vis-a-vis the nine contributions to this special issue.

From data-driven technologies to socio-digital care arrangements

A first move considers how data-driven technologies and data become part of care arrangements in different social domains, e.g., in healthcare, education, or welfare. The concept of sociomaterial care arrangements was proposed by Tomás Sánchez Criado and Israel Rodríguez Giralt (2016) who argued to not only understand care from a ‘bodywork perspective’ usually associated with the invisible labour of care, but to conceive of care as distributed amongst human and more than human actors.

With datafication, sociomaterial care relations transform because data-driven technologies have become an integral part of almost all aspects of our social lives. A first move in care-ful data studies is hence to analyse how care practices and dispositions are enacted in relation to data-driven technologies, for example alongside, by, through, or in opposition to them. For example, ‘caring-through-data’ describes a complex set of social relations and emotional concerns whereas ‘data-as-care’ implies that care ‘as a problem … can be solved by data granularity and management’ (Kaziunas et al., 2017, p. 2269). The authors of this introduction (Zakharova & Jarke, 2022) considered how data-driven technologies can function as antagonists, intermediaries, recipients, or means to receive care. Advancing this research, we contend that data studies can contribute to care theories by attending to the socio-digital care arrangements explicitly encompassing the materialities, affectivities, and normativities of datafication across many social domains. For example, in this special issue, Vera Gallistl and Roger von Laufenberg (2023) explore how data-driven technologies such as AI-based fall detection systems enter care homes and reconfigure the provision of care for older residents. Michela Cozza (2023) reflects the introduction of data-driven technologies as a response to the so-called ‘care crisis’ triggered (amongst others) by demographic ageing. This vantage point hence allows us to consider how the datafication of care practices leads to a reconfiguration and redistribution of care in socio-digital care arrangements.

From data science to data work and data care: invisibilities and valorisation

A second way in which a care lens offers a new perspective, is through the analysis of data work; that is work related to the production, processing, and use of data which makes up some of the more mundane tasks preceding any ‘advanced’ data analysis. As data science becomes more and more widespread, this data work is often decoupled from the more prestigious data modelling. For example, Mary Gray and Siddharth Suri (2019) have made an important contribution with their book Ghost Work in which they uncover the emotionally challenging, highly invisible, and undervalued data-related labour by workers in the Global South. Similarly, Nithja Sambasivan and colleagues (2021) argue that this kind of invisibility and devaluation is built into the hierarchies of how data science operates: ‘Everyone wants to do the model work, not the data work’. How this plays out in data science has been critiqued (Neff et al., 2017) and researched through a care lens (Baker & Karasti, 2018; J. Gray & Witt, 2021) to demonstrate that additional data work (beyond an application of formally correct analytical methods) is required for sense-making about data. In this sense, one vantage point to study care in datafied societies is by looking at the care work that sustains and enables the production, processing, circulation, and use of data. At the same time, the ‘valorization through care’ (Pinel et al., 2020, p. 185) encompasses tasks valued differently within the organisational structure. In this special issue almost all contributions deal with data work in one form or another. In the three contributions by Preeti Mudliar (2024), Sarah Davis and Constantin Holmer (2024), and Juliane Jarke and Stefanie Büchner (2024) there is a particular focus on the invisibilities of data work and value production associated with care work.

In the first contribution, Mudliar (2024) analyses how children in underprivileged Indian families partake in the care work for their families’ food security by performing biometric authentication to state authorities. By moving children's role in socio-digital care arrangements of food security into focus, Mudliar troubles ‘the biometric assemblage of the welfare state to care for its citizens’. The care-ful data studies lens allows her analysis to highlight multiple invisibilities of children’s care work performed in datafied societies. She demonstrates that it is predominantly underprivileged children who are expected to take over care responsibility for their families’ biometric authentication. In this datafied welfare system, the children are further disadvantaged and marginalised.

Davies and Holmer (2024) analyse academic data work as care work. The paper explores the largely invisible work of biocurators who manage vast amounts of data produced in contemporary biosciences. The authors’ concern is with the framing of such data work as care service that elides professional recognition and valuation of the tasks accomplished by biocurators. While the biocurators in Davies’ and Holmes’ contribution are specifically employed to care for data (quality), Jarke and Büchner (2024) look at work contexts in which the data work required by employees stands in competition to other care obligations. Drawing on two case studies about mundane data work in the domains of youth welfare services and public education, they introduce the concept of data care arrangements to discuss how care becomes enacted in mundane data work in organisational settings. Using care ethics and the concept of data valences they reason that data become matters of care only when organisational and individual expectations assign value to data. This provides a new perspective on the ‘multiple and often conflicting views of betterment, especially of (datafied) optimisation in organisations’.

Taken together the three papers’ care lenses consider the values ascribed to data and to data work. In the case of Jarke and Büchner, it is the value ascribed to data that makes them a matter of care and promotes careful engagement towards data quality. In the case of Davies and Holmer it is the data work of biocurators which adds value to data. In all three papers, tensions emerge from the invisibility of the respective data care work and the unwillingness of those in charge of data infrastructures to acknowledge the ‘petty doings’ (Puig de la Bellacasa, 2011, p. 92) or ‘petty aspects’ (Jarke & Büchner, 2024) of data work. Hence, this vantage point draws attention to invisibilities and the valorisation of different types of data work in socio-digital care arrangements. Defining certain tasks as care, however, might render these tasks outside the formally acknowledged and paid labour.

From technical to situated modes of knowledge production: responsibilities and accountabilities

What further discerns data care in datafied societies is highly situated, practice-informed, and affective knowledge about technologies and data. Against this backdrop, we suggest exploring modes of knowledge production in datafied societies as a third analytical vantage point. What is seen as ‘good’ data is often described in terms of data quality and related practices of data cleaning (Ratner & Ruppert, 2019) and oscillates between affective, practical experiences and techno-political dimensions of knowledge production. For example, affect and personal experiences can help understand evidence production and sense-making of scientific data (Lindén, 2021). Deborah Lupton (2020b) proposes ‘thinking with care’ as an epistemological approach that helps to ‘generate awareness of and attentiveness to the affective as well as social, cultural, and political dimensions’ (Lupton, 2020b, p. 3169) of datafied societies. This raises questions such as: What data are good and what are these data good for? These questions shift focus from techno-political issues such as data quality discussed by data scientists (Dimas et al., 2023) or in context of technology and data interoperability (Edwards et al., 2011), to the situated, affective, lived experiences and practically informed assessments of those affected by data-driven technologies.

Such a focus responds to Puig de la Bellacasa’s (2017) engagement with Fisher’s and Tronto’s assertion that care is directed at making ‘our world’ as good to live in as possible. Puig de la Bellacasa asks what is included in the ‘our’ and argues that ‘good care’ is never neutral. This normative stance raises a pressing issue concerning the responsibilities and accountabilities of different social actors in datafied societies, where power and agency are distributed across socio-digital care arrangements. For example, a recent study by Laura Kocksch and colleagues (2018) illustrates how a care lens embraces the ‘intertwined and distributed responsibilities, often crossing organizational, professional or even legal boundaries’ (p. 92:14). Catherine D’Ignazio and Lauren Klein (2020) have pointed at the increasing responsibilisation of individuals and communities to provide missing data sets. They also encourage readers of their Data Feminism book to ‘elevate emotion and embodiment’ over supposedly neutral and objective forms of data science (visualisations). In this special issue, the contributions by Marthe Stevens and Anne Beaulieu (2023), Natalia Avlona and Irina Shklovski (2024), and Bartosz Ślosarski (2024) focus more closely on care, knowledge production, and questions of responsibility in the datafied societies.

Stevens and Beaulieu (2023) explore epistemic responsibility, drawing on an empirical analysis of Dutch mental healthcare professionals learning to apply techniques of supervised machine learning (ML) in their professional practice. The authors apply a relational understanding of more than human care work to make an analytical move from individuals bearing responsibility towards situations that have ‘responsibility as an effect’. Stevens’ and Beaulieu’s study taps into the uncertainties of knowledge production through ML models and highlights the care work required to situate data in the context of its production to make decisions about which ML techniques fit the analysis of which data in which medical contexts.

Avlona and Shklovski (2024) elaborate on the modes of knowledge production which, putting patients in the centre of a data-intensive healthcare setting, are enacted and evaluated through the negotiations of expertise and data quality. In an empirical study of a start-up providing matchmaking of patients to clinical trials, the authors reconstruct how data quality requirements of the matchmaking system reconstruct the data professionals’ understanding of the patients’ medical records and histories and lead to ‘torquing’ of patients’ data to fit into the system. Mobilising the ethics of care to discuss domain expertise of actors handling patients’ data, Avlona and Shklovski explore the affective and material elements of knowledge production in data-intensive work settings.

In a study about the handling of air quality data in Poland, Ślosarski (2024) uses the concept of data phronesis to describe ‘situated and context-dependent practical wisdom of various actors that determines how definitions of ‘good’ data-mediated care for air quality are created’ (p. 2). The contribution provides an epistemological exploration of knowledge production about air quality data that is sensitive to the dynamics of power between different actors involved in the definition of good practices of air quality data handling. This contribution is a detailed example of epistemic dynamics of data-mediated care moving between highly situated practices and materialities of data production on site of air quality measurement and nationally established value judgements about good air data.

All three care lenses oppose a technical view on knowledge production in data-intensive settings, which primarily addresses the functional capabilities of data-driven systems and their human operators to clean, process, and combine vast amounts of data. Ślosarski (2024) illustrates how care as an affective and practical engagement with data allows producing highly contextual rather than generalised knowledge. Stevens and Beaulieu (2023) as well as Avlona and Shklovski (2024) further demonstrate how incorporation of contextual knowledge into data work through care requires a re-evaluation of professional expertise and redistribution of responsibilities between all relevant actors including those who are described through data and typically have no say in what these data ought to mean and represent. From this vantage point, researchers can attend to the normative questions of how data can be understood differently, what data are ‘good’ for understanding and gaining knowledge, and who is responsible for such decisions.

From studying harms to the politics of vulnerability and minoritisation

Practices of data-driven knowledge production have been shown to potentially exert harm in particular on already minoritised communities (Benjamin, 2019; Noble, 2018). For example, in the welfare sector, data are used for decision-making to determine answers to existential questions of who is entitled to public services, healthcare, and liveable futures. In care ethics, these practices of decision-making about a redistribution of resources constitute one of the steps of care provision (Fisher & Tronto, 1990) and follow certain schemata addressing various levels of vulnerability. In datafied societies, multiple vulnerabilities stem from the availability or the lack of certain data (Browne, 2015; D’Ignazio & Klein, 2020). Communities and individuals subjected to extensive datafication experience unproportional surveillance, for example from the government (Eubanks, 2017). Rendering these data visible puts surveilled communities under particular scrutiny and creates dependencies or new harms through visibility; the lack of data, in contrast, might render them as not valuable or non-existent (Crooks & Currie, 2021). As data determine vulnerabilities and redistribute care in datafied societies, attending to vulnerabilities provides a fourth analytical vantage point for care-ful data studies.

In this special issue, Vera Gallistl and Roger von Laufenberg (2023) employ a care perspective to analyse how vulnerabilities associated with old age are defined, configured, and produced through data-driven systems. Drawing on an empirical study of AI-supported fall detectors in a long-term care facility, the contribution turns to the perspectives of older adults on the datafication of their surroundings. Gallistl and von Laufenberg illustrate how situating care around stereotypical views of vulnerabilities of older bodies fails to establish reciprocity in the design and application of the fall detection system and leads to unaccomplished acts of care. In her commentary to this special issue, Michela Cozza (2023) also discusses how various practices of older adults’ welfare care datafication such as ‘classification’, ‘categorisation’, and ‘taskification’ enact stereotypical depictions of ageing inscribed in the design of digital technologies for older adults. She argues that these stereotypical depictions subsequently materialise in different modes of practical organisation of health care provision.

Moving into focus how care fails, Gallistl and von Laufenberg illuminate that a care lens advances analysis beyond studying harmful implications of data-driven technologies and towards explorations of the politics of vulnerability that underlie technology design and utilisation. By defining or rendering in/visible certain vulnerabilities, data-driven systems configure identity positions ascribed to data subjects (Klostermann et al., 2022). Critical data studies and related disciplines widely focus on the interrelation between identities of people and their experiences with and imaginaries of data (Kennedy, 2018; Lupton, 2020a; Newman-Griffis et al., 2023; Pink et al., 2022). The lens of care draws attention to the authorising mechanisms (e.g., paternalism) which move individual vulnerabilities and care for them into focus. Care provision then might legitimise structural issues leading to these vulnerabilities in the first place (Bennett et al., 2020; Narayan, 1995).

Moving forward and building more than human communities of care

The fifth vantage point we want to propose considers community building around existing or lacking socio-digital care arrangements. Research of existing more than human communities, for example hackerspaces, focused on highlighting the community’s human members’ normative patterns of this labour: ‘values of collaboration, cooperation, interpersonal support – in a word, care’ (Toombs et al., 2015, p. 629). Within critical data studies, scholars have also engaged with actions taken by various communities in the wake of lack or surplus of data about them (e.g., D’Ignazio et al., 2022) or the need to create regulations for data sovereignty (Taylor & Kukutai, 2016).

McQuillan (2022, p. 6) reminds us that the “violent separations of ‘us and them’” rather than community-building are inherent to the mechanisms of classification and categorisation underlying datafication. This became apparent during the Covid-19 pandemic which demonstrated how important data are to people’s ‘visibility, survival, and care’ (Milan & Treré, 2020). Assuming a care perspective sensitises to practices, patterns, and power dynamics of othering in datafied societies. Therefore (and perhaps not surprisingly for feminist scholars and activists) the UK-based Care Collective encourages the readers of their Care Manifesto to imagine what would happen ‘if we were to begin […] to put care in the very centre of life’ (The Care Collective et al., 2020, p. 5).

Many data scholars understand building more than human communities of care as an interventionist move and are either closely related to the grassroot data activist initiatives or identify as data activists themselves. In this special issue, Daniel López-Gómez and Israel Rodríguez-Giralt (2024) describe their careful intervention of online community building as volunteer facilitators of a public social networking app for older adults during the Covid-19 pandemic in Spain. The authors highlight the emotional, relational, and infrastructural work of such a digital intervention, reflecting on their own work as facilitators and the older people's agency in configuring digital communities of care. Reporting on the active role of older women in organising digital support and companionship during the pandemic, López-Gómez and Rodríguez-Giralt challenge ageist assumptions underlying the design of the analysed social networking app.

Community building is also an important aspect in Davies’ and Holmer’s (2024) contribution to this special issue. They discuss the dark side of academic data care work performed by biocurators in that this work is quite invisible and generally receives little recognition. However, Davies and Holmer also demonstrate how a care lens not only reconstructs these dark dynamics but allows to see and reimagine a different academy (or ‘academia otherwise’) which values the data care work of biocurators (and other highly specialised professionals) on the same level as it values the publication in high impact journals or the award of huge grants. ‘Academica otherwise’ is a reimagination that centers around care, collaboration, and service, presenting it as a different kind of academic space to the mainstream. It also acknowledges the joy and professional satisfaction that care work might warrant. While such research and activism apply the care lens alongside other powerful concepts, we argue that a care lens allows to foreground how communities and their collective responses to datafication aim to shift power and care relations.

Conclusion

In the introduction of this editorial we asked: What do we see when we look at datafied societies through the lens of care? The seeing we invoke in this editorial is a perspective of ‘a thought collective’ Fleck (1980 [1935]) sensitive to the ethics of care. As we bring together different voices, concepts, and standpoints, we aim to open up a space for new explorations into socio-digital care arrangements. The contributions to this issue demonstrate that looking at datafied societies through the lens of care, positions researchers of datafication at different vantage points.

First, a care lens illuminates how through datafication, care in socio-digital care arrangements is reconfigured and redistributed. Secondly, a care lens sensitises us to invisibilities and valorisation of different types of data work in socio-digital care arrangements. From this vantage point Davies and Holmer (2024) and Jarke and Büchner (2024) demonstrate how practices of data science like data handling acquire value through a continuous re-evaluation in the contexts of data production and use. Mudliar (2024), in turn, illustrates the implications of viewing data work as an obligation to care. The third vantage point we propose takes this argument to highlight how data care allows alternative modes of knowledge production and encourages the inclusion of communities affected by data. Contributions by Stevens and Beaulieu (2023), Avlona and Shklovski (2024), and Ślosarski (2024) demonstrate how this plays out in a range of data-intensive professional settings. All three studies additionally explore the reconfigurations of responsibilities emerging in socio-digital care arrangements. The fourth vantage point exemplifies how knowledge in datafied societies often concerns subject identities and vulnerabilities. Gallistl and von Laufenberg (2023) in this issue exemplify empirically how care based on data about vulnerabilities fails those subjected to this form of datafied care. The fifth vantage point we propose here promotes a view on datafied societies that is hopeful and imagines more than human communities of care. In contributions by López-Gómez and Rodríguez-Giralt (2024) and Davies and Holmer (2024) such communities are sketched out as datafied societies otherwise.

Overall, this collection illustrates how critical data studies and care ethics can mutually contribute to each other and inform new ways of understanding the ambivalences of data power in datafied societies. On the one hand, they address care as an empirical setting and focus on the role of data in socio-digital care arrangements, e.g., in the healthcare sector (Gallistl & von Laufenberg, 2023; Stevens & Beaulieu, 2023; Avlona & Shklovski, 2024; López-Gómez & Rodríguez-Giralt, 2024; Cozza, 2023). On the other hand, the authors in this special issue employ care ethics as an analytical concept to study the datafication of different social arenas (Mudliar, 2024; Davies & Holmer, 2024; Jarke & Büchner, 2024; Ślosarski, 2024). They attribute care with both its darker and its joyful sides to practices of sustaining, amplifying, and resisting datafication.

Hence, looking at datafication and datafied societies through the lens of care may bring epistemic injustices and violence to the fore. Feminists have argued that if the lived experiences of minoritised communities are not seen and not heard, it’s not their fault but it is structural and built into existing power hierarchies. A care lens facilitates a shift in perspective, and a reflection on one's own standpoint (e.g., McQuillan, 2022). Following feminist writers, scholars, and activists like Rokeya Sahkawat Hossain, a care-ful approach to data studies also facilitates a shifting of perspectives and reimagining of how a datafied world could be otherwise. By looking at the world through care, we may dream and reimagine technoscience as a way to nurture living and being well in more than human worlds.

Acknowledgements

The production of this special issue, too, has been a work of care. We wish to thank the journal editors, the authors, and the reviewers for their respective contributions to this collection. Acknowledging how some of this work takes place under conditions of precarity, it is important for us to stress that academic knowledge production within and outside of the field of critical and care-ful data studies requires care, humility, and solidarity.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article

Additional information

Notes on contributors

Irina Zakharova

Irina Zakharova is postdoctoral researcher at the Leibniz University Hannover, Germany. Her research is in the fields of data studies and feminist science and technology studies. Irina is interested in data practices in public welfare services provision, datafication of public education, and academic knowledge production in the datafied world. She received her doctoral degree in media and communication studies from the University of Bremen.

Juliane Jarke

Juliane Jarke is Professor of Digital Societies at the University of Graz, Austria. Her research attends to the increasing importance of digital data and algorithmic systems in the public sector, education and for ageing populations. She received her PhD in Organisation, Work and Technology from Lancaster University and has a background in computer science, philosophy and STS. Her latest book is Algorithmic Regimes: Methods, Interactions and Politics (Amsterdam University Press). Email: [email protected]

Notes

1 The metaphor of ‘vision’ for describing knowledge production has been widely discussed in (feminist) Science and Technology Studies e.g. Barad (2007). It also has been critically addressed in relation to disabilities and ableism (livingstone, 2018). In this editorial, we use the metaphor of vision in its feminist sense.