Academic journal article Environment and Planning D: Society and Space

Data Colonialism through Accumulation by Dispossession: New Metaphors for Daily Data

Academic journal article Environment and Planning D: Society and Space

Data Colonialism through Accumulation by Dispossession: New Metaphors for Daily Data

Article excerpt

Abstract

In recent years, much has been written on 'big data' in both the popular and academic press. After the hubristic declaration of the 'end of theory' more nuanced arguments have emerged, suggesting that increasingly pervasive data collection and quantification may have significant implications for the social sciences, even if the social, scientific, political, and economic agendas behind big data are less new than they are often portrayed. Compared to the boosterish tone of much of its press, academic critiques of big data have been relatively muted, often focusing on the continued importance of more traditional forms of domain knowledge and expertise. Indeed, many academic responses to big data enthusiastically celebrate the availability of new data sources and the potential for new insights and perspectives they may enable. Undermining many of these critiques is a lack of attention to the role of technology in society, particularly with respect to the labor process, the continued extension of labor relations into previously private times and places, and the commoditization of more and more aspects of everyday life. In this article, we parse a variety of big data definitions to argue that it is only when individual datums by the million, billion, or more are linked together algorithmically that 'big data' emerges as a commodity. Such decisions do not occur in a vacuum but as part of an asymmetric power relationship in which individuals are dispossessed of the data they generate in their day-to-day lives. We argue that the asymmetry of this data capture process is a means of capitalist 'accumulation by dispossession' that colonizes and commodifies everyday life in ways previously impossible. Situating the promises of 'big data' within the utopian imaginaries of digital frontierism, we suggest processes of data colonialism are actually unfolding behind these utopic promises. Amid private corporate and academic excitement over new forms of data analysis and visualization, situating big data as a form of capitalist expropriation and dispossession stresses the urgent need for critical, theoretical understandings of data and society.

Keywords

Data colonialism, 'big data', everyday life, accumulation by dispossession, commodification, critical data studies

Introduction: The Shape of 'big data' (1)

In recent years, data--be they Big (Lohr, 2012), big (Boellstorff, 2013), 'big' (Dalton and Thatcher, 2014), small (Kitchin and Lauriault, 2014), or raw (Gitelman, 2013)--have moved to center stage in both popular and academic presses. As with other technological developments, such as e-commerce (Leyshon et al., 2005), initial boosterish claims have been followed by more nuanced critiques. In the popular press, critiques have tended to focus on the limitations or failures of big data to produce the promised results (Glanz, 2013; Marcus and Davis, 2014) or on the limitations of both current theory and statistics to interpret data (The Economist, 2014). In academic discussions, while concerns over the utility of big data remain, critiques have emphasized a variety of questions including its role in surveillance (Crampton et al., 2014), its epistemologies (boyd and Crawford, 2012), and its paradigms (Kitchin, 2014). However, even as aspects of big data are pulled apart and questioned in these and other venues, new regimes of data generation, acquisition, and analysis slip into normalcy--as even the most profound technologies recede from view as they transform into unquestioned amenities of the everyday (Brown et al., 2011; Weiser, 1991).

This article engages specific asymmetries of the relations between data producers and owners--end-users and app developers--that have become a focal point of value generation in the technology industry. Often self-presented as perpetually 'new' (Leszczynski, 2014), the social, scientific, political, and economic agendas behind big data clearly follow longer historical trends such as social physics (Barnes and Wilson, 2014; Wyly, 2014), geodemographic marketing (Dalton and Thatcher, 2015), self-entrepreneurialism (Levenda et al. …

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