Diversity and neocolonialism in Big Data research: Avoiding extractivism while struggling with paternalism

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Paula Helm, Amalia de Götzen, Luca Cernuzzi, Alethia Hume, Shyam Diwakar, Salvador Ruiz Correa, Daniel Gatica-Perez
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引用次数: 0

Abstract

The extractive logic of Big Data-driven technology and knowledge production has raised serious concerns. While most criticism initially focused on the impacts on Western societies, attention is now increasingly turning to the consequences for communities in the Global South. To date, debates have focused on private-sector activities. In this article, we start from the conviction that publicly funded knowledge and technology production must also be scrutinized for their potential neocolonial entanglements. To this end, we analyze the dynamics of collaboration in an European Union-funded research project that collects data for developing a social platform focused on diversity. The project includes pilot sites in China, Denmark, the United Kingdom, India, Italy, Mexico, Mongolia, and Paraguay. We present the experience at four field sites and reflect on the project’s initial conception, our collaboration, challenges, progress, and results. We then analyze the different experiences in comparison. We conclude that while we have succeeded in finding viable strategies to avoid contributing to the dynamics of unilateral data extraction as one side of the neocolonial circle, it has been infinitely more difficult to break through the much more subtle but no less powerful mechanisms of paternalism that we find to be prevalent in data-driven North–South relations. These mechanisms, however, can be identified as the other side of the neocolonial circle.
大数据研究中的多样性和新殖民主义:在与家长式主义斗争的同时避免榨取主义
大数据驱动的技术和知识生产的抽取逻辑引发了严重的担忧。虽然大多数批评最初集中在对西方社会的影响上,但现在越来越多的注意力转向对全球南方社区的影响。迄今为止,辩论主要集中在私营部门的活动上。在本文中,我们从这样一个信念开始,即公共资助的知识和技术生产也必须仔细审查它们潜在的新殖民主义纠缠。为此,我们在一个欧盟资助的研究项目中分析了合作的动态,该项目收集数据,用于开发一个专注于多样性的社交平台。该项目的试点地点包括中国、丹麦、英国、印度、意大利、墨西哥、蒙古和巴拉圭。我们介绍了四个实地站点的经验,并反思了项目的初始概念、我们的合作、挑战、进展和结果。然后,我们分析不同的经验进行比较。我们的结论是,虽然我们成功地找到了可行的战略,以避免助长作为新殖民主义圈子一方的单方面数据提取的动态,但要突破我们发现在数据驱动的北南关系中普遍存在的更为微妙但同样强大的家长制机制,难度要大得多。然而,这些机制可以被认为是新殖民主义圈子的另一面。
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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