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Our courses offer excellent training for a career in international development or for advanced study, and attract students of the highest calibre from across the world.
“I had waited for 10 years before my dream to study in Oxford became a reality and the experience was truly beyond expectation”
Our courses offer excellent training for a career in international development or for advanced study, and attract students of the highest calibre from across the world.
“I had waited for 10 years before my dream to study in Oxford became a reality and the experience was truly beyond expectation”
Our students are taught to develop as critical and independent thinkers and when they leave us they are equipped with the knowledge and skills they need to bring about real change.
“My time at Oxford strengthened my critical analysis and provided me with a unique interdisciplinary grounding in history, politics and economics that has equipped me well in dealing with public policy issues and program development strategy.”
Our students are taught to develop as critical and independent thinkers and when they leave us they are equipped with the knowledge and skills they need to bring about real change.
“My time at Oxford strengthened my critical analysis and provided me with a unique interdisciplinary grounding in history, politics and economics that has equipped me well in dealing with public policy issues and program development strategy.”
Use of new technologies across European immigration and asylum systems can expedite some decision-making processes, but also increase vulnerabilities for migrants, meaning new governance frameworks are needed.
From dialect recognition systems to matching tools, the use of new technologies is gradually rising in the migration and asylum fields across Europe. Several states have started using or testing such technologies to control who enters their borders or gains access to their protection mechanisms. These technologies, especially automated decision-making systems, can expedite decision-making processes, benefitting governments and some applicants.
Yet they also involve inherent risks of bias, discrimination and potential “machine mistakes”, which pose a significant threat to migrants and asylum seekers – often already disenfranchised and facing challenges in seeking remedies. Their use can also lead to new relationships between the public and private sectors, requiring new governance structures and legislative frameworks to regulate who is responsible for data protection, possible machine mistakes, and related inaccurate or discriminatory outcomes.
As the EU Artificial Intelligence (AI) Act proposal categorises AI uses for immigration, asylum and border control as “high-risk”, there is a need for systemic investigation of current practices and their use across Europe. In a new report, Automating Immigration and Asylum: The Uses of New Technologies in Migration and Asylum Governance in Europe, I map out the existing uses of new technologies across European immigration and asylum systems at both national and EU levels.
The report explores the technologies used prior to arrival, at the border and within European territories. The term “border” here refers to the physical borders of states and the location where migrants, asylum seekers and refugees are when they are subject to a particular technology used by an authority. This is not to deny that “digital borders” function on and beyond territorial borders. Rather, the temporal approach shows that migrants, asylum seekers and refugees are subject to various technologies at each different stage of their mobility around and inside Europe.
The practices I explore in the report include specifically:
Other technologies are under development, including risk assessments and profiling through interoperability between large EU information systems; document verification in Belgium and France, and categorisation of appeal cases in the Netherlands. An EU-funded research project tested controversial lie detection technologies in Hungary, Latvia and Greece. Another project explored the feasibility of behaviour analysis, including emotion recognition for border control. Although currently not implemented, these projects’ findings are available to inform future product development. A number of matching tools are also being tested to optimise migrants’ and asylum seekers’ settlement outcomes.
Some technologies have been tested or implemented, but then terminated. For example, speech and dialect recognition to identify asylum seekers’ countries of origin was tested in Turkey, but not used due to poor accuracy. In the UK, between 2015 and 2020, the Home Office used a potentially discriminatory algorithm to process visitor visa applications, but stopped following civil society campaigning. The Netherlands used risk assessment between 2014 and 2021 to evaluate potential sponsors of highly skilled migrants, storing companies’ details, including the ethnic composition of their boards – a practice halted thanks to internal and external pressures. The country is currently developing a new model to assess sponsors without storing information on ethnicity.
This wide range of applications for new technologies implies that each should be investigated independently, including its context and unique stakeholder requirements. The report, therefore, debunks a black-and-white perception of technology uses. Some technologies, such as those that prioritise migrants’ preferences in their settlement processes, can benefit applicants by giving them a say in their settlement trajectory. Others, such as profiling people through risk assessments or monitoring them through invasive electronic tools, can be extremely harmful. This makes it crucial to examine each use of new technology in its own right, including its design and implementation processes, and legal and social impacts.
Transparency over whether a decision-making process involves automation and, if so, its technical details, is also vital to understanding technology’s impact, yet these details are not always made public or are too difficult for outsiders to comprehend. Yet without transparency, migrants lack access to justifications for decisions affecting their lives and cannot pursue effective remedies.
Transparency is also important for decision-makers. While human caseworkers are involved in each practice I examined, the extent of their involvement and their knowledge of the entire decision-making process varies. For example, some new technologies, such as mobile phone data and speech or dialect recognition tools, are used to produce evidence for decision-makers in the asylum process. These automated reports cannot be a reason to reject an applicant’s claim, but they can impact the process if decision-makers over-rely on reports prepared by these sophisticated tools.
Many of the technologies I explore in the report are designed to benefit, first and foremost, state authorities. Migrants’ interests and voices are generally not included in their design and implementation. Some technologies aim to benefit migrants above anyone else, such as speech recognition in Latvia to help them with their citizenship applications. However, most are designed to support migration controls or benefit state needs rather than those of migrants. I therefore argue that who benefits from these technologies, who has access to their details, and who is included and excluded remain crucial questions to inform appropriate governance structures for AI use in migration processes.
Ozkul, Derya (2023) Automating Immigration and Asylum: The Uses of New Technologies in Migration and Asylum Governance in Europe. Oxford: Refugee Studies Centre, University of Oxford.
The report was prepared for the Algorithmic Fairness for Asylum Seekers and Refugees Project, funded by the Volkswagen Foundation.
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AI-generated image of mobility and migration. Credit: DALL·E 2 / OpenAI