Migration Multiple? Big Data, Knowledge Practices and the Governability of Migration (original) (raw)
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2021
Moving from the large debate concerning the role of innovative data sources for social policies and official statistics on the one side, and the ethical concerns involving the use of big data for social research on the other side, this study aims at investigating the evolution of migration research in the big data era. It presents findings from a thematic analysis of transcripts obtained from semi-structured in-depth interviews exploring the experiences and perspectives of seven research and data experts involved in different levels on initiatives that aim to employ innovative data sources and techniques for social good projects unfolding in the field of migration. Interviews had a focus on questions of data quality, regarding both "old" and "new" data sources. Findings from the current study suggest that, in the datafied world, research is invested with an operational role oriented towards the formulation of politically relevant insights for which more timely and granular data are demanded, and current official statistics are consequently considered inadequate. The ethical risks associated with the use of big data in a field as sensitive as the one of migration and the necessary involvement of private companies (that hold the greatest part of such a digital knowledge) not only as data providers but, more importantly, as statistics makers, raises concerns about the risks of big data (mis)use, distribution of responsibilities between the public and private sector, and what role is left to official statistics, traditionally entrusted with providing society with a solid, accessible, and enduring complex of knowledge on its wellness.
Big data for whose sake? Governing migration through artificial intelligence
Humanities and Social Sciences Communications
Although human activity constantly generates massive amounts of data, these data can only be analysed by mainly the private sector and governmental institutes due to data accessibility restrictions. However, neither migrants (as the producers of this data) nor migration scholars (as scientific experts on the topic) are in a position to monitor or control how governments and corporations use such data. Big Data analytics and Artificial Intelligence (AI) technologies are promoted as cutting-edge solutions to ongoing and emerging social, economic and governance challenges. Meanwhile, states increasingly rely on digital and frontier technologies to manage borders and control migratory movements, and the defence industry and military–intelligence sectors provide high-tech tools to support these efforts. Worryingly, during the design and testing of algorithmic tools, migrants are often portrayed as a security threat instead of human beings with fundamental rights and liberties. Thus, priv...
Key opportunities and challenges for the use of big data inmigration research and policy
2020
Migration is one of the defining issues of the 21st century. Better data is required to improve understanding about how and why people are moving, target interventions and support evidence-based migration policy. Big data, defined as large, complex data from diverse sources, has been proposed as a solution to help address current gaps in knowledge. The authors participated in a workshop held in London, UK, in July 2019, that brought together experts from the UN, humanitarian NGOs, policy and academia to develop a better understanding of how big data could be used for migration research and policy. We identified six key areas regarding the application of big data in migration research and policy: accessing and utilising data; integrating data sources and knowledge; understanding environmental drivers of migration; improving healthcare access for migrant populations; ethical and security concerns; and addressing political narratives. We advocate the need for increased cross-disciplina...
Research Methodologies and Ethical Challenges in Digital Migration Studies
Digital technologies present new methodological and ethical challenges for migration studies: from ensuring data access in ethically viable ways to privacy protection, ensuring autonomy, and security of research participants. This Introductory chapter argues that the growing field of digital migration research requires new modes of caring for (big) data. Besides from methodological and ethical reflexivity such care work implies the establishing of analytically sustainable and viable environments for the respective data sets—from large-scale data sets (“big data”) to ethnographic materials. Further, it is argued that approaching migrants’ digital data “with care” means pursuing a critical approach to the use of big data in migration research where the data is not an unquestionable proxy for social activity but rather a complex construct of which the underlying social practices (and vulnerabilities) need to be fully understood. Finally, it is presented how the contributions of this bo...
Migration Governance and Data Saturation: Is Less More?
CERC Policy Brief, 2022
The conventional wisdom among migration policy practitioners is that migration governance faces a problem of data scarcity. Against this backdrop, various stakeholders such as international organizations emphasize the need to leverage the latest advances in digital technology and the numerous sources of digital data to quantify, monitor and predict previously invisible processes, practices and vulnerable populations. In other words, the datafication of migration appears as a panacea which promises an affordable, efficient, timely and objective collection, analysis and dissemination of an ever-increasing volume and variety of data relevant to migration. Yet this approach of data maximization overwhelms policy practitioners with conflicting information. It also sustains an increasingly costly arms race for information which burdens international organizations and threatens the human rights of vulnerable populations. This brief addresses the policy problem of data saturation and recommends the implementation of data minimization. This principle requires to collect only the minimum amount of data necessary to accomplish a carefully predetermined goal. Data minimization would not solely protect the rights of migrants, refugees, asylum seekers and internally displaced persons. It would also tackle the increasingly unwieldy and dysfunctional data saturation which diminishes the value and usefulness of data and generates additional data management costs and risks. With the support of the private sector and academia, the international organizations comprising the UN Network on Migration could effectively implement and showcase data minimization.
Big Data, Big Promises: Revisiting Migration Statistics in Context of the Datafication of Everything
This blog post argues that innovative methods based on varying sources Big data will not solve some of the known core issues and problems of migration statistics - as it is often claimed by policy makers and data scientists. To substantiate this position the post identifies three kinds of politics that influence attempts to quantify migration: the politics of numbers, the politics of method and, finally, a politics of (national) distinction.
DIGITAL TRACKS BEYOND BORDERS: A SYSTEMATIC REVIEW ON THE MIGRATION CRISIS
This study aimed to systematically examine the studies conducted and published on immigrants, asylum seekers, and refugees by using big data written in English. Articles were searched on Scholar, The Web of Science, ProQuest, Science Direct, PubMed and Scopus databases. The concept set centered around the concepts of immigration and big data was used in the surveys. In accordance with the PRISMA protocol principles, 49 articles were examined according to the inclusion and exclusion criteria among 258 articles obtained from the relevant databases until the end of December 2022. The reviewed articles were categorized under the headings of "topics examined", "dataset", "analyses", "software used" and "key findings". The studies provide indications on how to obtain information about this population, which is difficult to reach group especially due to its massiveness, using big data tools. In the findings, it has been seen that studies based on big data on immigrants, asylum seekers and refugees contribute to facilitating the integration of these groups into the target country. Also, it has been revealed that these studies may lead to undesirable results in terms of violating the confidentiality of research groups, producing labeling, and increasing surveillance for these groups. In addition to these, it has been found that these studies have methodological handicaps in terms of representativeness, accuracy, excessive homogenization, and easy generalization. It is thought that the findings of the study will shed light on the international migration and refugee policies to be carried out using big data analysis tools.
Article, 2022
This paper discusses how new information technologies will change the inquiry of social processes, particularly regarding migration studies. Modern innovations in the sphere of collection and processing of information, like digitalisation, analysis of Big data, and the development of data science, might transform theoretical approaches to migration studies. Applying Babbie’s (2021) macro and micro theory of social process inquiry, the intention in the current article is to add a nano level, which will be increasingly utilised in the coming years, particularly in the sphere of inquiry of population migration using personal biological (fingerprints, eye features, and even DNA) characteristics. The paper underlines that modern information technologies will not only allow for a deeper understanding, but also for a broader capture of social processes. Moreover, these technologies will facilitate the use of mixed method research, i.e. incorporating quantitative and qualitative approaches....
To be published as: Broeders, D. and H. Dijstelbloem (2016) 'The Datafication of Mobility and Migration Management: the Mediating State and its Consequences', pp. 242-260 in: I. Van der Ploeg and J. Pridmore (eds.) Digitizing Identities: Doing Identity in a Networked World. London: Routledge 12 The datafication of mobility and migration management: the mediating state and its consequences Dennis Broeders and Huub Dijstelbloem MONITORING AND DATAFYING HUMAN MOBILITY Modern technologies have increased the possibilities of governments to gather and process data and this has increased the variety and the depth of governmental observation and monitoring. This variety includes the data from new technologies such as radar, infrared and satellite technology ('the eye in the sky') that allow for different forms of observation and detection, while depth can be added through technologies such as ICT, biometrics, GIS technology and statistical risk calculation. The more recent development of big data analysis is now also finding its way into public policy making. The state's perception of reality thus becomes more technologically and statistically mediated and 'datafied'. Data of various types and sources are processed, combined and connected though networked databases. Even though policymakers often claim that technology merely does the same job faster and better, technology also changes both the substance and the nature of policy. For one thing, it brings new actors to the scene. Baker (2008) described the work of what he calls a new class of 'Numerati' that data mine vast databases for correlations and use these to plan for the future. He primarily emphasized the commercial brand of this class, but there are public counterparts in ever larger numbers in, for example, counterterrorism (Balzacq 2008; Monahan and Palmer 2009) and youth care (Schinkel 2011; Keymolen and Broeders 2013), international development (Taylor 2015; Taylor and Broeders 2015) and crisis management (see Adey in this volume) . For another, the use of ever bigger datasets necessitates policy thinking in terms of risks and increasingly favours correlations over causalities (Mayer-Schönberger and Cukier 2013).
Technology, knowledge and the governing of migration
Handbook on the Governance and Politics of Migration, 2021
The chapter offers a selected review of the literature on technology and migration governance. It critically examines the sites of inquiry that the literature has privileged in investigating technology and migration governance. Two concrete features of the imbrication of technological processes and migration governing stand out here: first, the involvement of and reliance on large-scale information systems that collect, circulate and make the electronic data of persons on the move available for analysis by asylum, consular, migration, law enforcement or security authorities, and second, the involvement of and reliance on biometrics (fingerprinting, face or iris recognition in particular) for purposes of identification. In the process, I draw attention here to the literature’s common focus on practices of policy formation and formulation rather than on the enacting of policy, and to the privileging of studies on contexts of the global North rather than of the global South. The chapter subsequently identifies the politics of knowledge as the core matter raised by the imbrication of technology and migration governance. A key issue emphasized in the literature concerns the knowledge practices underpinning the identification and sorting of persons on the move. The literature here argues that the main issue is not how technology can improve migration governance but how shifts within socio-technical settings within migration governance and beyond lead to transformations in the way persons on the move are known to governmental authorities, and therefore acted upon.