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Debates are ongoing on the limits of - and possibilities for - sovereignty in the digital era. While most observers spotlight the implications of the Internet, cryptocurrencies, artificial intelligence/machine learning and advanced data analytics for the sovereignty of nation states, a critical yet under examined question concerns what digital innovations mean for authority, power and control in the humanitarian sphere in which different rules, values and expectations are thought to apply. This forum brings together practitioners and scholars to explore both conceptually and empirically how digitisation and datafication in aid are (re)shaping notions of sovereign power in humanitarian space. The forum's contributors challenge established understandings of sovereignty in new forms of digital humanitarian action. Among other focus areas, the forum draws attention to how cyber dependencies threaten international humanitarian organisations' purported digital sovereignty. It also contests the potential of technologies like blockchain to revolutionise notions of sovereignty in humanitarian assistance and hypothesises about the ineluctable parasitic qualities of humanitarian technology. The forum concludes by proposing that digital technologies deployed in migration contexts might be understood as 'sovereignty experiments'. We invite readers from scholarly, policy and practitioner communities alike to engage closely with these critical perspectives on digitisation and sovereignty in humanitarian space.

Eind 2020 heeft de data governance clinic voor het project Intelligent Gebruik Openbare Ruimte (IGOR) plaatsgevonden. De inzet van deze clinic was om de ethische vragen rondom om dit project te doordenken en in kaart te brengen hoe reflectie op dergelijke vragen een structureel onderdeel kan worden van het project. In dit artikel wordt allereerst een korte omschrijving gegeven van de inhoud van het IGOR project. Vervolgens worden een aantal voorbeelden gegeven van ethische vragen met betrekking tot het gebruik van data en besluitvormingsprocedures die relevant zijn voor het IGOR project. Tot slot volgen de aanbevelingen die naar aanleiding van de clinic zijn gedaan. Daarbij staat een reactie vanuit het IGOR-team met betrekking tot de overwegingen en aanbevelingen. Deze zijn in november 2021 geschreven. Het oorspronkelijke verslag met aanbevelingen (voor intern gebruik binnen gemeente Amsterdam) is geschreven door: Merel Noorman (1), Thijs Turel (2) en Linnet Taylor (1). Deze samenvatting van de aanbevelingen en reactie vanuit het IGOR-team november 2021 zijn geschreven door Boen Groothoff (3) en Yuki Tol (3).

What can urban big data research tell us about cities? While studying cities as complex systems offers a new perspective on urban dynamics, we should dig deeper into the epistemological claims made by these studies and ask what it means to distance the urban researcher from the city. Big data research has the tendency to flatten our perspective: it shows us technology users and their interactions with digital systems but does so often at the expense of the informal and irregular aspects of city life. It also presents us with the city as optimisable system, offering up the chance to engineer it for particular forms of efficiency or productivity. Both optimisation itself, and the process of ordering of the city for optimisation, confer political and economic power and produce a hierarchy of interests. This commentary advocates that researchers connect systems research to questions of structure and power. To do this requires a critical approach to what is missing, what is implied by the choices about which data to collect and how to make them available, and an understanding of the ontologies that shape both the data sets and the urban spaces they describe.

The evolution of big data into a policy tool came with pre-big-data assumptions about privacy and data reuse. In the 2010s this model broke down irretrievably as big data became a tool for intervening on the public on a mass scale. This chapter traces the ensuing institutional responses, in both the public and private sectors, of self-regulation through guidelines and notions of 'responsible data' and shows how they break down when faced with the politics of inclusion and exclusion, and with questions of downstream impacts on sustainability and other structural questions of justice. I argue that Fraser's lens of 'abnormal justice' presents a more useful lens than responsibility in relation to technologies of automation, as it demands understanding of the self-defined interests of affected groups. Integrating these concerns into AI governance requires an approach based on Mouffe's notion of agonistic pluralism in order to can take into account different views of what AI may, and should, do in the world.

Crisis narratives surrounding Europe's 2015 migration influx fuelled demands for new ways of tracking, mapping and predicting human mobility. We explore how market opportunities for technology firms and data analytics start-ups created by the EU's Global Approach to Migration led to solutionistic approaches to compiling and analysing migration statistics. We show that initiatives such as the rebranding of existing platforms and services as migration prediction systems are consolidating policy conceptualisations of migration as risk. Despite the promise of greater granularity, this "big data approach" cannot offer greater certainty about who is on the move and why. Instead such approaches are ill-suited to understanding the complex dynamics of migration and to offering protection to vulnerable people. The marketisation of migration statistics through big data offers a key case for advancing progressive approaches to both migration statistics and global data justice.Los relatos de crisis en torno a las corrientes migratorias hacia Europa del año 2015 han impulsado la demanda de nuevas formas de seguimiento, mapeo y predicción de la movilidad de personas. Exploramos cómo las oportunidades de mercado para las empresas de tecnología y las nuevas empresas de análisis de datos creadas por el Enfoque Global de la Migración de la UE han causado enfoques simplificadores al compilar y analizar las estadísticas migratorias. Mostramos que iniciativas tales como el cambio de nombre de ciertas plataformas y servicios existentes en los sistemas de predicción migratoria están transformando la conceptualización de las política migratoria como un riesgo. A pesar de la promesa de una mayor granularidad, este “enfoque big data” no logra ofrecer una mayor certeza sobre quién está en movimiento y por qué. Al contrario, estos enfoques no son adecuados para comprender las complejas dinámicas migratorias ni para ofrecer protección a las personas vulnerables. La comercialización de las estadísticas migratorias a través de Big Data ofrece un caso clave para avanzar sobre enfoques más progresivos tanto para las estadísticas migratorias y como para la justicia global de datos.

The nature and production of migration statistics are in flux. State bureaucracies are no longer the primary source of migration data. . Instead, there are a myriad unofficial data sources and processing collaborations which produce migration and mobility data as a by-product of both commercial and governmental processes. This has implications both for international processes of migration assessment and control, and for states’ domestic policies with respect to migrants. This paper brings together migration studies with Science and Technology Studies (STS) literature to take stock of these new data sources' theoretical and empirical implications for both migrants and the links between migration and broader social processes. We identify migration information infrastructures: configurations of data assemblages which involve private and public sector actors, where data originally collected for one purpose (billing customers, sharing social information, sensing environmental change) become repurposed as migration statistics. We explore the implications of such migration information infrastructures for migration researchers: what are the entanglements that such infrastructures bring with them, and what do they mean for the ethics and practicalities of doing migration research?

Digital vaccination certification involves making many promises, few of which can realistically be kept. In this paper, we demonstrate how this phenomenon constitutes various forms of theatre – immunity theatre, border theatre, behavioural theatre and equality theatre – doing so by drawing on perspectives from technology regulation, migration studies and critical geopolitics. Technological theatre and political theatre often serve valid functions, but these forms are problematic for several reasons. First, they involve real-world infrastructures that, while unlikely to accomplish the task at hand, will nevertheless last a long time and be repurposed. They therefore constitute governance by data infrastructure, diverting action and control away from elected legislators to for-profit contractors. Second, vaccine certification effectively legitimises inequalities between countries and people by formalising ways to distinguish between the vaccinated and non-vaccinated and to exclude the latter, thus reinforcing both mobility and connectivity divides. It serves as a way to (further) close borders and to regulate, through code and infrastructure, access to public goods such as employment and public space. Finally, the project of certification displaces a more important action, namely addressing the radical inequality in countries’ ability to combat the pandemic.

The COVID-19 pandemic took high-income countries entirely by surprise. Despite funding pandemic preparedness programs in Asia for more than 20 years, donor countries had not experienced an uncontrolled pandemic since HIV in the 1980s. When Ebola, Zika, SARS, and MERS threatened, countries outside the immediate geographic neighborhood or income level of those diseases’ places of origin were left largely untouched. In contrast to the swift, comprehensive response of South-East Asian countries, authorities in Europe and the United States assumed this coronavirus would behave like its predecessors SARS and MERS.What happened next around the world was both harrowing and illuminating. Lacking protective material resources, the human capacity for contact tracing or understanding of the disease, policymakers in higher-income countries turned to technology for a miracle. The technology sector responded with history’s most extensive hackathon, illuminating the mutual shaping of technology and public health policy. The most striking feature of the technological response to the pandemic has been the degree of what Morozov has called solutionism driving it—the belief that complex problems can be solved by technological intervention alone.

Civil society around the world has called for data-driven companies to take their responsibility seriously and to work on becoming more fair, transparent, accountable and trustworthy, to name just a few of the goals that have been set. Data ethics has been put forward as a promising strategy to make this happen. However, data ethics is a fuzzy concept that can mean different things to different people. This chapter is therefore dedicated to explaining data ethics from different angles. It will first look into data ethics as an academic discipline and illustrate how some of these academic viewpoints trickle down in the debate on data science and AI. Next, it will focus on how data ethics has been put forward as a regulatory strategy by data- driven companies. It will look into the relation between law and ethics, because if in this entrepreneurial context data ethics is not properly embedded, it can be used as an escape from legal regulation. This chapter will end with a reflection on the future relation of data ethics and data science and provide some discussion questions to instigate further debate.

As data technologies become the medium of experiment for living labs, they become less a collaboration between citizen and researcher and more a test of how commercial actors can influence the public. Two new practices suggest we shouldapply research ethics rules: first, that the experimentation taking place does not aim to test technology using people, but to test people using technology; and second, that such experimentation is explicitly designed to understand how thepopulation outside the lab can be influenced and manipulated, and therefore has a political character that research ethics can give us some leverage over.

Biometrics, the technology for measuring, analysing and processing a person’s physiological characteristics, such as their fingerprints, iris or facial patterns, is increasingly used in the management of migrant and refugee flows. This panel interrogates the uses of biometric technologies and the consequences for the lives of migrants and refugees. It asks how biometric data are constituted, what their limitations and biases are, how biometric technologies challenge traditional notions of the physical border, in whose interest and with what implications for migrants and refugees. In particular, in bringing together a multidisciplinary group of international experts to develop a critical, comparative and empirically grounded dialogue, the panel explores the consequences of this ‘machinic life’ for the lives of actual people, migrants and refugees who navigate actual and digital borders in the quest of a better life. As such, the panel engages with crucial themes of processes of bordering, extractive logics and commercial dimensions of biometric flows and algorithmic sorting, discrimination and exclusion, and human agency and autonomy. Ultimately, all papers are concerned with the broader intersection of data, computation and justice.

Higher-income countries’ response to the COVID-19 pandemic has been characterised by technological solutionism—the claim that technology on its own can solve problems that are in reality complex and multidimensional. This essay explores the mutual shaping that has occurred between technological solutions and public health policy in the Global North, where governments have allowed capacity to drive policy rather than vice versa. This has led to a situation where contact-tracing and other surveillance technology has become centered in policy, at the expense of the human capacity and material resources that were, and are, necessary to combat the pandemic effectively. This contribution charts how the subsitution of just-in-time technology for human inputs took a toll in terms of mortality by delaying an appropriate public health response.

The scale and asymmetry of commercial technology firms’ power over people through data, combined with the increasing involvement of the private sector in public governance, means that increasingly, people do not have the ability to opt out of engaging with technology firms. At the same time, those firms are increasingly intervening on the population level in ways that have implications for social and political life. This creates the potential for power relations of domination, and demands that we decide what constitutes the legitimacy to act on the public. Business ethics and private law are not designed to answer these questions, which are primarily political. If people have lost the right to disengage with commercial technologies, we may need to hold the companies that offer them to the same standards to which we hold the public sector. This paper first defines the problem and demonstrates that it is significant and widespread, and then argues for the development of an overarching normative framework for what constitutes non-domination with regard to digital technologies. Such a framework must involve a nuanced idea of political power and accountability that can respond not only to the legality of corporate behaviour, but to its legitimacy.

Cities in the global South are being “datafied”, with increasing presence of digital data of all kinds: from mobile phones, remote sensing, ground-level sensors, community mapping, etc. This has created growing interest in “data justice” in urban locations: the way in which data intersects with questions of social justice – who wins and who loses from the new digital datasets and data flows, and the relationship of data to power and inequality; particularly for those already marginalised in the physical city. This collection presents ten case studies of urban data justice; analysing from a data justice/rights or critical data perspective an initiative or phenomenon relating to growing availability and use of data in urban areas in the global South. These case studies – covering Latin America, Africa and Asia – highlight themes of increasing resistance to datafication among marginalised urban communities; of the way in which social processes and structures shape datafication and its impacts; and of the need for longer-term, qualitative actions that truly listen to the concerns and priorities of these communities. The collection also outlines a future research agenda on urban data justice in the global South.

What appears on the surface as conservatism or irrational rejection of new ideas may represent a deeper logic of societal stability woven around moral values, sources of legitimacy, and economic in...

In this paper, we investigate people’s perception of datafication andsurveillance in Amsterdam Smart City. Based on a series of focusgroups, we show how people understand new forms of hypervisbi-lity, what strategies they use to navigate these experiences, and whatthe limitations of these strategies are. We show how people tried todiscern between public and private sector actors, to differentiate whothey trusted by building on the existing social contract. People alsotrusted the objectivity of data in relation to prior experiences of socialcontexts and discrimination. Lastly, we show how the experiences ofsome of the inhabitants in our study who were most vulnerable tohypervisibility highlight the limits to strategies based on the neutral-ity of data. By asking about perceived surveillance rather thanemphasising actual practices of surveilling, we show differentiatedcontexts and strategies, providing empirical grounds to question thedominant technical framing of smart cities.

Today, withdrawing from digital space would mean giving up on countless pleasures and conveniences afforded by communication and navigation devices. Even if one wanted to withdraw, living offline has become rather difficult. Around the world urban life has become digitized and datafied to a degree that any attempt at living even for a few days without engagement with digital space would likely require a withdrawal from urban life altogether: from travel, work, and personal relations as we nowadays experience and live them. Many urbanites produce digital data through almost everything they do. We get up in the morning and use a mobile phone that is constantly emitting information to check our email, the news, and social media. We travel to work using an electronic travel card or in a car with various GPS and digital systems. We walk down streets where signals from our phones and other devices are captured and read by wifi beacons and MAC address sensors, and our images by CCTV. We use apps that emit details of our location, we tweet, we tag, we check in. We make phone calls through particular antennas set up by our mobile phone providers. We interact with the city digitally by paying our taxes, living in our houses, using city services, and offering feedback to the authorities. All day, digital signatures are embedded in the technologies we use, emitted as we communicate and move around, and signaled by most of our activities. The picture that builds up about us in the course of every day is both behavioral and spatial in ways that are often opaque to us. Actual and possible effects of digitalization and datafication of urban life are critically debated in scholarly and policy circles; and Liesbet Van Zoonen (2015) has observed that city governments today are faced with a super-wicked problem of data governance (Levin et al. 2012). In this context citizens are both contributors to the digitalization and datafication, as well as being affected by these processes.

We examine the current ‘datafication’ process underway in low- and middle-income countries (LMICs), and the power shifts it is creating in the field of international development. The use of new communications and database technologies in LMICs is generating ‘big data’ (for example from the use of mobile phones, mobile-based financial services and the internet) which is collected and processed by corporations. When shared, these data are also becoming a potentially valuable resource for development research and policy. With these new sources of data, new power structures are emerging within the field of development. We identify two trends in particular, illustrating them with examples: first, the empowerment of public–private partnerships around datafication in LMICs and the consequently growing agency of corporations as development actors. Second, the way commercially generated big data is becoming the foundation for country-level ‘data doubles’, i.e. digital representations of social phenomena and/or territories that are created in parallel with, and sometimes in lieu of, national data and statistics. We explore the resulting shift from legibility ( Scott, 1998 ) to visibility, and the implications of seeing development interventions as a byproduct of larger-scale processes of informational capitalism.

This paper examines research about Wikipedia that has been undertaken using big data approaches. The aim is to gauge the coherence as against the disparateness of studies from different disciplines, how these studies relate to each other, and to research about Wikipedia and new social media in general. The paper is partly based on interviews with big data researchers, and discusses a number of themes and implications of Wikipedia research, including about the workings of online collaboration, the way that contributions mirror (or not) aspects of real-world geographies, and how contributions can be used to predict offline social and economic trends. Among the findings is that in some areas of research, studies build on and extend each other's results. However, most of the studies stay within disciplinary silos and could be better integrated with other research on Wikipedia and with research about new media. Wikipedia is among few sources in big data research where the data are openly available, unlike many studies where data are proprietary. Thus, it has lent itself to a burgeoning and promising body of research. The paper concludes that in order to fulfil this promise, this research must pay more attention to theories and research from other disciplines, and also go beyond questions based narrowly on the availability of data and towards a more powerful analytical grasp of the phenomenon being investigated.

This paper is the product of a workshop that brought together practitioners, researchers, and data experts to discuss how big data is becoming a resource for positive social change in low- and middle-income countries (LMICs). We include in our definition of big data sources such as social media data, mobile phone use records, digitally mediated transactions, online news media sources, and administrative records. We argue that there are four main areas where big data has potential for promoting positive social change: advocacy; analysis and prediction; facilitating information exchange; and promoting accountability and transparency. These areas all have particular challenges and possibilities, but there are also issues shared across them, such as open data and privacy concerns. Big data is shaping up to be one of the key battlefields of our time, and the paper argues that this is therefore an opportune moment for civil society groups in particular to become a larger part of the conversation about the use of big data, since questions about the asymmetries of power involved are especially urgent in these uses in LMICs. Civil society groups are also currently underrepresented in debates about privacy and the rights of technology users, which are dominated by corporations, governments and nongovernmental organizations in the Global North. We conclude by offering some lessons drawn from a number of case studies that represent the current state-of-the-art.

The use of digital communication technologies, and of mobile phones in particular, has seen an exponential rise in low- and middle-income countries over the last decade. These data, emitted as a byproduct of technologies such as mobile phone location information and calling metadata, have the potential to fill some of the problematic gaps in data resources available to country policymakers and international development organisations. Using three examples of current big data initiatives in the international development field, we examine the implications of these new types of data for development policy and planning: their advantages and drawbacks, emerging practices relating to their use, and how they potentially influence ideas and policies of development. We also assess the politics of these new types of digital data, which are often collected and processed by corporations or by researchers in industrialised countries. Our analysis indicates that these new data sources already represent an important complement to country-level statistics, but that there are currently important challenges which will need to addressed if the promises of big data in development are to be fulfilled.

While plans to develop “smart cities” are gathering pace across the world, we know little about the ways in which the discourses of datafication, smartness, and big data play out in material contexts of urban development, including utility and resource management. In this paper, we explore this intersection in the case of Bangalore’s water supply, where IBM in alliance with the Bangalore Water Supply and Sewerage Board (BWSSB) is implementing a water-flow sensor network and geographic database system under the label of “big data for water supply.” We illustrate how the BWSSB-IBM approach narrows down the complex field of water provision to a question of water in- and out-flow measurements and the monitoring of BWSSB ground personnel. In theoretical terms, we discuss the ways in which these processes constitute both particular claims to knowledge, and the redefinition of citizenship as consumption.

The increasing availability of ‘data fumes’ (Thatcher, 2014) – data produced as a byproduct of people’s use of technological devices and services – has both political and practical implications for the way people are seen and treated by the state and by the private sector. Yet the data revolution is so far primarily a technical one: the power of data to sort, categorise and intervene has not yet been explicitly connected to a social justice agenda. In fact, while data-driven discrimination is advancing at exactly the same pace as data processing technologies, awareness and mechanisms for combating it are not. This paper posits that just as an idea of justice is needed in order to establish the rule of law, an idea of data justice is necessary to determine ethical paths through a datafying world. The paper will analyse the existing work on data justice and argue for a framework in which it can be brought together into a single framing for further research and debate.

This chapter draws together the conclusions of the book as a whole, namely that the available typologies of group privacy, such as collective action lawsuits or the articulation of the rights of political or activist groups, are intuitively insufficient to address the landscape emerging from the new data analytic technologies. The book has demonstrated that there are multiple and often divergent perspectives on what a group is and how it should be addressed with regard to privacy, but this divergence is also an important tool for understanding which elements of the problem can be addressed using current legal and conceptual tools and which will require new approaches. The chapter outlines the authors’ contributions to the typology of group privacy concerns, then identifies the gaps and limitations that arise from a group perspective on privacy, and the conceptual and practical implications of taking the group level into account. Finally, it suggests ways forward for future research, discussion and action.

The introduction outlines the origin of the book in the concerns arising from new data analytical technologies with regard to collectives. Although their effects have so far been addressed only on the individual level, in fact profiling and machine learning technologies are directed at the group level and are used to formulate types, not tokens – they work to scale, and enable their users to target the collective as much as the individual. This means that our legal, philosophical and analytic attention to the individual may need to be adjusted, and possibly extended, in order to pay attention to the actual technological landscape unfolding before us. This book represents such an adjustment: it may be seen as an exploration of the territory that lies between ‘their privacy’ and ‘its privacy’, with regard to a given group. In this book we push the boundary towards ‘its’, and begin to think about the implications of that shift, first by identifying who must be involved in the discussion. This chapter outlines the philosophical and legal concerns that arise from considering group privacy, and sets out the challenge that this volume aims to answer.

A report on the use and governance of digital data by the city of Amsterdam, with policy recommendations towards inclusive data governance that is fair to minorities and less privileged groups.

Using qualitative data from Ghana, this article explores the role of information in the formation of expectations of migrants and their families back home, with specific reference to the return experience. We develop a typology to illustrate (1) how information influences expectations throughout the migration experience; (2) the ability of the migrant and their family to adapt to those changing expectations, given differing levels of information; and (3) the implications (1) and (2) have for return. Latent tensions and conflicts emerge in which expectations of migrants and migrant families are not harmonious. The evidence shows that the pace of adaptation and change is regulated by access to information; information flow between migrant at destination and home; and the propensity of the migrant to adapt, which is related to the level of financial dependency (or strength of obligation) between migrant and home. The article raises policy questions around information access and information flows, community sensitisation and returnee reintegration, especially in poorer areas. Cet article utilise des donnees qualitatives sur le Ghana pour etudier le role que joue l’information dans la formation des attentes des migrants et de leurs familles, en ciblant plus particulierement l’experience du retour. Nous developpons une typologie dans le but d’illustrer (1) comment l’information determine les attentes dans le cas de l’experience migratoire, (2) la capacite des migrants et de leurs familles a s’adapter a de nouvelles attentes dues a des niveaux d’information differents; et (3) les consequences que les deux premiers points peuvent avoir sur les conditions du retour. Des tensions latentes se manifestent et des conflits emergent quand les attentes des migrants et de leurs familles ne vont pas dans le meme sens. Les temoignages montrent que le rythme d’adaptation et de changement est regule par l’acces a l’information, que l’information circule entre les migrants arrives a destination et le pays d’origine, et que la propension des migrants a s’adapter est liee au niveau de dependance financiere (ou au poids des obligations) entre les migrants et le pays d’origine. L’article souleve des questions a propos de l’acces a l’information et les flux d’information, la sensibilisation des communautes, et la reintegration de ceux qui sont de retour, plus particulierement dans les regions pauvres.