Datafication and Return Migration: The Case of the International Organization for Migration
by: Younes Ahouga, Toronto Metropolitan University
Datafication has become a mainstay of migration governance. This is epitomized by the very first of the 23 objectives of the Global Compact for Migration (GCM) which encouraged states to ‘Collect and utilize accurate and disaggregated data as a basis for evidence-based policies’. To this end, states had to build digital systems of data collection, analysis, and dissemination; enhance national data capacities through financial and technical assistance; and explore new data sources. Despite the contentious negotiations of the GCM throughout 2017 and 2018, the quantification of migration through digital technology and data consistently garnered widespread support from states. This consensus rests upon the belief that datafication constitutes a panacea for the perennial knowledge gaps, dearth of resources, bureaucratic red tape, and politicized bargaining-hampering policy-making. Indeed, datafication promises an affordable, efficient, timely, and objective monitoring, analysis, and prediction of hitherto invisible and unknowable processes, practices, and vulnerable populations. To achieve success, policy-making must then leverage the latest advances in digital technology and the numerous sources of data generated by the increase in the world’s internet, mobile and social media users.
Accordingly, the datafication of migration championed by the GCM creates an insatiable demand for digital technology and data. Migration policy practitioners regularly deplore the scarcity and insufficient availability, use, and sharing of data. For example, both the outcome document of the 2nd International Forum on Migration Statistics held in 2020 and the UN Secretary General's report on the GCM's implementation published in 2021 criticized the persistence of significant data gaps in regards to the stock, flow, age, gender, status, health, well-being, and trafficking of migrants. Against this backdrop, international organizations are particularly engaged in resolving the seemingly urgent and far-reaching problem of data scarcity facing migration governance. In line with their role as providers of expert and technical knowledge unavailable to (some) states, they actively collect, analyse, and disseminate the largest possible volume and variety of data on migration and migrants.
This is notably the case of the International Organization for Migration (IOM). Since 2004, it has designed, implemented, and expanded its flagship digital system: the Displacement Tracking Matrix (DTM). The DTM quantifies and monitors the mobility of IDPs, refugees, and migrants in crisis situations by routinely collecting biometric data and data regarding the name, gender, nationality, ethnic origin, education, employment, phone number, etc. of hundreds of thousands of vulnerable individuals in countries of the Global South and along migration routes into Europe. This extensive data collection is not only intended to better assess migration flows and inform humanitarian interventions, it also supports relocation and return operations conducted by the IOM.
Although the DTM bolstered the authority of the IOM in the forced migration regime, it also collected data regardless of their policy relevance or operational usefulness. Speaking during a UN policy event on migration data held in 2016, one prominent IOM official stated that his organization had lots of data in most circumstances and that it needed to figure out what to do with them. One can then surmise that parts of the DTM’s data remained on the cloud and that a continuous stream of data overwhelmed the IOM staff. Moreover, some critics argued that IOM has done nothing to prevent DTM’s data from being used for policing purposes, which could marginalize displaced populations that may benefit from being able to remain under the radar.[1]
The organizational and human rights challenges generated by the propensity of international organizations such as the IOM to engage in massive data collection raise the question of whether it is time for migration governance to abide by the principle of data minimization. Brought to the fore by the European Union’s General Data Protection Regulation, this principle requires organizations to collect only the minimum amount of data necessary to achieve a specified goal. Data minimization has the benefit of better protecting the human rights of vulnerable populations. But it also helps organizations tackle the increasingly unwieldy and dysfunctional proliferation of data, which diminishes its value and usefulness and generates additional data management costs and risks. Recognizing the relevance of data minimization is crucial, especially in view of the continually expanding volume and variety of available and collected migration data.
[1] Megan Bradley, The International Organization for Migration: Challenges, Commitments, Complexities (Abingdon, Oxon: Routledge, 2020), 59.
Contact:
Younes Ahouga, Canada Excellence Research Chair in Migration and Integration Program | Toronto Metropolitan University | younes.ahouga@ryerson.ca