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National and university science policy in the Netherlands tends to prioritize in various ways computer and computational sciences over the social sciences and humanities. We feel that the oppositions that are produced and reinforced through such policies are both false and unproductive. As scholars working on data and technology-related issues at three Dutch universities, we initiated a conversation about what it would mean to think and work together. Taking our disciplinary background and research fields as starting points, we asked how these produced different conceptions of the same terms, how these differences could be generative or problematic, and how our disciplines become invested in a particular interpretation? The resulting discussions examine the productive and limiting characteristics of scientific disciplines, the boundary objects that allow us to work together, the influence of industry on our collaborations, and the related need to think beyond disciplinary collaborations and interactions.
In this chapter, we bring together three strands of empirical research across three contexts addressing how children are increasingly subject to digitized and datafied monitoring and surveillance of their lives. Our collaborative writing process braids together research on the datafication of childhood across three international contexts: media discourse on ‘sharenting’ in the US, privacy practices in Italian families, and anticipation of pupils’ futures in secondary schools in England (UK). Throughout and between these empirical examples, we explore themes of neoliberalism, subjectification, risk, and decision-making, and highlight how asymmetric power relations become embedded in data flows and practices. By making these commonalities visible across contexts, this chapter contributes towards arguments for adopting a data justice approach as a potential resistance and response to the datafication of childhood. We argue that, while data justice remains a future ideal for most children (and adults) around the world, there is an urgent need for intervention and action, in the form of greater governmental regulation and the inclusion of diverse children’s voices and experiences in decision-making.
Datafied systems require data subjects, but how these subjects are configured is often made invisible. This chapter explores the configuration of individuals as data subjects within datafied systems, highlighting the importance of the historical, contextual, social, and power dynamics that shape and determine datafication processes. The chapter discussions question the assumption of data objectivity, emphasizing the impact of data collection, conceptualization, and design choices on the creation of data subjects. Specific areas of datafication are examined, including power dynamics in self-tracking practices, the configuration of older adults and disabled experiences as data subjects, and the definition of data subjects in autonomous vehicles. These collectively reveal how datafication practices are informed by the interplay of data, society, stereotypes, and the self. In examining the implications of datafication and its impact on both individuals and communities, this chapter highlights the multidimensional nature of datafication and the need for transdisciplinary approaches to comprehend the power dynamics, agency, and historical contexts in configuring data subjects. The authors show how critical explorations of the intricate interplay between data subjects, data experts, and data-driven algorithms can help envision alternative configurations for more comprehensive, inclusive, and responsive data and datafication practices.
In this chapter, the authors critically interrogate the concept of data colonialism developed by Couldry and Mejias. Through their different critiques they bring to the table differing perspectives on the adoption of the concept within the field of critical data studies. Some authors offer fundamental critiques of the concept, arguing for scholarship and research that examines colonization as a tangible and pre-existing system of oppression with a violent data legacy that is continued through computation, as well as questioning the ways in which adoption of the concept can flatten our understanding of how data power works differently in the different contexts of Western consumerism and data production labour markets in post-colonial states. Other contributors identify gaps in the existing conceptualization in relation to environmental justice, and understanding the historical roots of colonialism in feudalist societies which also have their own resonances with contemporary datafied societies.
The chapter traces the contested politics of data, shifting scales from the transnational to the national and local levels: from questions of the (extra-)territoriality of data, the role of jurisdictions and contested ‘technical territories’ to the concrete lived spaces where data are produced, stored, and circulated. The different contributions thus zoom in from global geopolitical struggles over digital sovereignty and hegemony over data infrastructure to local contestations over subsea cable networks and landing stations, data centres, as well as neighbourhood gentrification driven by AI-development. This multiscalar approach to data politics aims to emphasize the tensions between the abstract global logics of data circulation and the local realities of data, between historical state and corporate projects of extending data territories as a form of ‘domination’, and the localized effects of such projects, including gentrification, expropriation, and the colonial erasure of local knowledges and sovereignty. At the micro level, several of the contributors to this volume explore community activism through a case study of Montreal, where local activists oppose processes of gentrification and displacement driven by an emerging AI ecosystem meant to boost Canada’s innovation and platform economies. We home in on instances of community mapping that produce data in a fair and equitable way; data that empower communities to resist gentrification and expropriation and to support situated knowledges.
Available open access digitally under CC-BY-NC-ND licence.
This book presents emerging themes and future directions in the interdisciplinary field of critical data studies, loosely themed around the notion of shifting response-abilities in a datafied world.
In each chapter an interdisciplinary group of scholars discuss a specific theme, ranging from questions around data power and the configuring of data subjects to the intersection of technology and the environment.
The book is an invaluable dialogue between disciplines that introduces readers to cutting edge arguments within the field. It will be a key resource for scholars and students who require a guide to this rapidly evolving area of research.
This introduction offers a diffractive reading across the chapters of this book by considering shifting response-abilities in a datafied world through five cross-cutting concerns: (1) the responsibilization of individuals and communities through processes of datafication, (2) the abilities of individuals and communities to respond to data power, (3) the endeavour to design responsible data-driven systems, (4) questions around what responsible data studies research may look like, and (5) how we as critical data studies scholars can become response-able to each other. The introduction embraces the concept of ‘response-ability’ as articulated by Donna Haraway, seeking shared agency and mutual responsiveness beyond individual interests, and encompassing the well-being of communities and more-than-human worlds. We highlight the importance of response-ability in fostering collaboration and understanding across our diverse disciplines, geographies and modes of engagement with data power.
Data practices are at the heart of contemporary understandings of environmental change, yet the infrastructures that underpin them are also increasingly understood to have their own significant environmental impacts. In this chapter, contributors address the relationship between data and the environment, by exploring environmental sensing practices, data-driven representations of climate change, and the environmental impacts of data centres. In the contributions, we are interested in the different entanglements of data and the environment, and how power dynamics come into play along the journey from environmental sensing practices, through to data modelling and representation, and data storage and processing in data centres. Across each of the chapter sections, co-authors variously engage with the contours of data, their diverse physical manifestations, their representations, their affects, and the epistemologies they materialize, reproduce, and map onto in environmental and planetary contexts. We ask: how does ‘environmental data power’ as a concept that encompasses all of these practices and contexts operate across each of these registers? To answer this question, we articulate not only how data power takes shape in relation to and via environmental contexts, but also how data technologies, economies, and practices organize and make legible the planetary through these particular affects, epistemologies, and geographies.
This chapter highlights the intricate nature of data and their profound social implications. It examines the acts of rendering data visible and the inherent power dynamics and imbalances that accompany such processes. Our dialogue unfolds in three interconnected parts, each focusing on the intersection of in/visibility and power. Part 1 attends to the challenges of producing knowledge about and with data, emphasizing the relativity, fluidity, and instability inherent in data. It explores frameworks that uncover the often invisible infrastructures of algorithms, rendering visible the actors, technologies, and divergent values involved in data manipulation. Part 2 presents empirical case studies that analyse the consequences of data visibility while contemplating the methodological opportunities and challenges of foregrounding the embedded values and norms within data. Part 3 discusses tool-based interventions aimed at bringing alternative data framings and narratives to the fore. It examines the complexities of tracing data across various contexts and the value, utility, and obstacles associated with creating visual representations of data and their flows. By critically engaging with the complexities of data in/visibility, this chapter challenges existing gatekeepers and fosters a deeper understanding of the multifaceted nature of data and its socio-political ramifications.
The shift towards big data-driven decision-making and algorithmic automation across many aspects of everyday life remains a contentious subject of debate and critique. Critical social scientists and media scholars assert that this shift alters the nexus and power relations between state, citizens, and industry. Individuals and communities have little control over how their data are collected and have little to no influence on the algorithmically informed decisions that govern their lives. This chapter addresses power asymmetries that are emerging at this contemporary juncture. The chapter points to possibilities to agency in the data practices, including consent practices, refusal practices, citizen participation (including citizen juries and citizen assemblies), as well as other forms of data activism. In doing so, we aim to contribute to reshaping data power from the bottom up and propose people-centred and radically contextualized approaches to imagining alternative data futures.
