The power of algorithms has become a familiar topic in society, media, and the social sciences. It is increasingly common to argue that, for instance, algorithms automate inequality, that they are biased black boxes that reproduce racism, or that they control our money and information. Implicit in many of these discussions is that algorithms are permeated with normativities, and that these normativities shape society. The aim of this editorial is double: First, it contributes to a more nuanced discussion about algorithms (...) by discussing how we, as social scientists, think about algorithms in relation to five theoretical ideal types. For instance, what does it mean to go under the hood of the algorithm and what does it mean to stay above it? Second, it introduces the contributions to this special theme by situating them in relation to these five ideal types. By doing this, the editorial aims to contribute to an increased analytical awareness of how algorithms are theorized in society and culture. The articles in the special theme deal with algorithms in different settings, ranging from farming, schools, and self-tracking to AIDS, nuclear power plants, and surveillance. The contributions thus explore, both theoretically and empirically, different settings where algorithms are intertwined with normativities. (shrink)

As states increasingly use algorithms to improve the legibility of society, particularly during the COVID-19 pandemic, it is common for concerns about the expanding power of the algorithm or the state to be raised in a deterministic manner. However, how are the algorithms for states’ legibility projects enacted, contested, and reconfigured? Drawing on interviews and media data, this study fills this gap by examining Health Code, the Chinese contact tracing and risk assessment algorithmic system that serves as the COVID-19 health (...) passport. I first explore the intensive and invisible work and infrastructures that enact and stabilize Health Code’s sociotechnical assemblage. I then show how this assemblage is frequently challenged and destabilized by errors, breakdowns, and exclusions. Facing unintended engagements from heterogeneous social actors, local interests, and power hierarchies, Health Code reassembles into multiple and contradictory assemblages at different periods and social localities. Finally, I examine how people game and bypass the algorithm’s surveillance with their agencies. Recognizing this messiness and heterogeneity contributes to a more nuanced and realistic understanding of states’ use of algorithms, including the risks. Doing so also urges us to rethink the politics of citizenship and inequality in the digital age beyond inclusion. (shrink)

The Central American migrant caravans of 2018 are best understood as having been precipitated by entangled multi-scalar geopolitical histories among the United States, Mexico, Guatemala, Honduras, and El Salvador. Unsurprisingly, the migrants traveling north to the United States garnered widespread attention on social media. So much so that the reaction to the caravan accelerated plans to deploy troops to the US southern border and deny Central Americans the opportunity to seek asylum. This example showcases how the digital world can have (...) exponential material effects. While coverage on border security and migration has been extensive, within political geography, such concerns have rarely been paired with social media. In this article, we take as our object of analysis the digitality or “digital life” of the migrant caravan. Mapping the patterns of migrant caravan-related tweeting paired with the exploration of Twitter’s networked dimensions reveals the platform to be a fundamentally spatial technology. Rather than reflect, refract or distort, Twitter produces and is in turn produced through spatial mechanisms. We present multiple cartographic visualizations in support of this claim and highlight the ways in which a contextual knowledge of the subject under study—the migrant caravan—can further inform analyses of Big Data. (shrink)

How do digital platforms govern their users? Existing studies, with their focus on impersonal and procedural modes of governance, have largely neglected to examine the human labor through which platform companies attempt to elicit the consent of their users. This study describes the relationship labor that is systematically excised from many platforms’ accounts of what they do and missing from much of the scholarship on platform governance. Relationship labor is carried out by agents of platform companies who engage in interpersonal (...) communications with a platform’s users in an effort to align diverse users’ activities and preferences with the company’s interests. The authors draw on ethnographic research conducted at AllDone (a for-profit startup that built an online market for local services) and edX (a non-profit startup that partnered with institutions to offer Massive Open Online Courses). The findings leverage variation in organizational contexts to elaborate the common practices and divergent strategies of relationship labor deployed by each platform. Both platforms relied on relationship workers to engage in account management practices aimed at addressing the particular concerns of individual users through interpersonal communications. Relationship workers in each setting also engaged in community management practices that facilitated contact and collaboration among users in pursuit of shared goals. However, our findings show that the relative frequency of relationship workers’ use of account management and community management practices varies with organizational conditions. This difference in strategies also corresponded to different ways of valuing relationship workers and incorporating them into organizational processes. The article demonstrates how variation in organizational context accounts for divergent strategies for governing user participation in digital platforms and for the particular processes through which governance is accomplished and contested. (shrink)