Surveying the landscape of advanced digital technologies in migration management
CERC Migration Research Affiliate Lucia Nalbandian and Research Assistant Nick Dreher build on a previously published (PDF file) CERC Working Paper with a new open access publication (external link) on the results of their study into the uses of Advanced Digital Technologies (ADTs) in migration management around the world.
Lucia and Nick, what initially motivated you to work together on this topic?
LN: There has been considerable discussion about how the Government of Canada employs artificial intelligence in immigration processes. This led us to consider the broader landscape of advanced digital technologies (ADTs) used by governments worldwide and other predictive technologies that are being recommended for use by agencies and organizations working with immigrants. Our original research question emerged from a place of curiosity: If these technologies are being employed by governments and non-governmental organizations, how are scholars, practitioners and community members engaging with and questioning their use?
ND: The paper builds partly on Lucia’s initial work, which focused on the Canadian experience. We decided to expand it to examine other countries. To our knowledge, there was no systematic evaluation of how ADTs were used across different countries in immigration processes. We aimed to fill this gap through the literature review and the Migration Tech Tracker.
Speaking of the Tech Tracker, in the paper, you highlight that it is an interactive tool consolidating information from the literature review. How do you envision researchers, practitioners, and community organizations will use this tool?
ND: The Tech Tracker provides an overview of where ADTs are used, serving as a starting point for in-depth research by scholars, activists and civil society actors. It was designed as a collaborative tool that others can build on and contribute to.
LN: On the Migration Tech Tracker’s website, we invite those familiar with or involved in examining other ADTs used in migration management to contribute new data. We want to continue updating it based on their suggestions. Looking ahead, I hope the Tech Tracker becomes a source of transparency and information, even for individuals undergoing migration or immigration processes themselves. It could offer insights into how technologies like machine learning are utilized in different stages of the migration process.
Why do you think your literature review uncovered the prevalence of a negative perception regarding the uses of ADTs for migration management?
ND: Most literature discusses ADTs either as a mechanism for migrant control or migrant support. It’s important to keep in mind that our focus was on technologies deployed by states or international organizations;, we did not delve into the literature of technologies adopted by civil society or migrants. Other scholarship has highlighted more positive benefits to the application of ADTs. When we look at how ADTs are used by governments, we find they are justified using the same paradigms that are discussed in other areas of migration literature, namely migration as a risk to the state and the desire for safe, orderly and regular migration called upon by the Global Compact.
LN: Even when governments adhere to the ideals of the Global Compact, their policy decisions might have different effects than what was intended. For example, governments often pursue technologies to increase efficiency, yet research is showing that not all new technology results in faster, streamlined processes, but may instead be resulting in breaches of data privacy and over-collection of information that may not be relevant for migration decision-making.
ND: Our analysis also identifies instances where governments collaborate with non-profit organizations, using ADT-collected data to help migrants settle in the right place. Promising refugee placement programs like Annie MOORE, GeoMatch Algorithm and Pairity, for example, use technology to assist refugees in settling where they have the highest chances of finding employment and community.
Your literature review spans 2010 to 2022. How has the landscape of ADTs in migration management evolved over this period, and how do you think research on the topic will progress in the future?
ND: Initially, the widely used ADTs discussed in literature were biometrics and, to some extent, Internet of things with tools like drones used for border surveillance.
LN: As we approach the future, artificial intelligence (AI) and machine learning technologies become more prominent in their role in managing large quantities of data. From Immigration, Refugees and Citizenship Canada’s immigration application processing to the complex ecosystem of AI-supported, data-driven monitoring technologies in the United States, these initiatives reflect a shift in the government’s interest toward using machine learning to enhance migration management efficiency. It seems now there’s a desire to make migrants more “readable.”.
ND: Our project also identifies technologies not yet well covered in the literature, like blockchain and cloud computing, pointing researchers to possibilities for further inquiry. That doesn’t necessarily mean that these technologies have not been deployed; rather, scholarly research has still to explore them in detail.
Reflecting on the complexity of actors involved in these processes, another emerging area of interest is the role of international organizations in facilitating the deployment of ADTs, but also of technology companies that are developing these tools. What is their responsibility as actors in this space? Those are interesting directions for future research.
LN: Outside the social sciences, other fields are starting to fill some of the knowledge gaps on the use of experimental methodologies, like AI. Being a very data-heavy field, migration provides many opportunities for interdisciplinary connections. Think of statisticians looking at ADTs and immigration to make inferences about migration rates, or urban planning researchers making predictions about what an area will look like in terms of population density and the necessary infrastructure to support growth over the next 10 years. I’m excited to see how other fields outside the social sciences deploy experimental technologies to mine the data collected in migration research and unlock insights we wouldn’t otherwise have. I just hope we can all be proactive in considering what is ‘right’ and how to do our work ethically.
