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Algorithmic Borders: How Artificial Intelligence Is Rewriting Refugee Polic

  • Writer: theconvergencys
    theconvergencys
  • Nov 7, 2025
  • 4 min read

By Alex Wang Oct. 28, 2025



Artificial intelligence (AI) is rapidly transforming how governments manage migration. What was once a domain of humanitarian discretion and legal review is now increasingly filtered through algorithms and predictive models. While policymakers promote AI as a solution to backlog and inefficiency, this technological shift risks redefining who deserves protection—and on what basis. By embedding automation into asylum processing, border surveillance, and risk assessment, states may be outsourcing human judgment to systems that reproduce bias and conceal accountability. The challenge ahead is not merely technological, but ethical and economic: how to balance efficiency with fundamental rights in an age of algorithmic governance.



I — Digitizing the Border: The Global Expansion of AI Systems

Over the past five years, governments have deployed AI-driven tools to accelerate migration management. In the European Union, the forthcoming European Travel Information and Authorization System (ETIAS) and the Entry/Exit System (EES) integrate facial-recognition, risk-profiling, and biometric databases across 27 member states. The European Parliamentary Research Service reports that these systems will handle data from more than 400 million travelers annually, creating one of the largest cross-border information architectures in the world.

Beyond Europe, similar digitization efforts have emerged. The United Nations High Commissioner for Refugees (UNHCR) operates PRIMES, a biometric database storing information on over 13 million displaced persons worldwide. In the United States, Customs and Border Protection uses predictive analytics to determine “inadmissibility risks,” while Australia’s Department of Home Affairs has tested automated “risk scoring” for visa applications. These systems promise faster processing and cost efficiency, but they also entrench a data-driven logic that may prioritize security and administrative convenience over individual protection.



II — Efficiency Versus Equity

The core appeal of AI in refugee management lies in efficiency. Governments facing rising asylum claims view automation as a path to reduce costs and shorten waiting times. The United Kingdom’s Home Office, for instance, cited algorithmic tools as a means to address its record-high asylum backlog exceeding 215,000 cases in mid-2023.

Yet efficiency comes at a moral price. Algorithms learn from historical data, meaning that any bias embedded in previous asylum decisions—based on nationality, language, or perceived credibility—is replicated at scale. A 2024 study by the Helen Bamber Foundation found that AI systems used in asylum triage disproportionately flagged applicants from majority-Muslim countries as “high risk.” The Council of Europe warned in a 2025 report that such systems can “undermine the principle of non-refoulement” by generating de-facto denials without human oversight.

This tension exposes the paradox of “digital humanitarianism”: the belief that technology can fix structural inequities that it may, in fact, deepen. When asylum decisions are partially or fully automated, refugees cease to be seen as individuals with narratives and become datasets to be sorted and scored.



III — Economic and Political Incentives

Adopting AI in refugee policy is not just a governance choice—it is an economic one. Automated systems reduce staffing costs, streamline resource allocation, and attract private-sector contracts worth billions. The European Commission’s 2023 Digital Border Strategy projected annual savings of €220 million through automation of screening and identity verification. However, these savings are often offset by long-term costs in litigation, data breaches, and human-rights compliance.

The involvement of private firms compounds accountability challenges. Companies such as Palantir Technologies and Accenture have secured major contracts to develop biometric and risk-analysis systems for governments. Because these tools are proprietary, their internal algorithms remain opaque—even to the agencies that rely on them. The result is a privatization of public responsibility: governments make life-altering decisions using systems they neither fully understand nor control.



IV — Humanitarian Consequences of Automation

The humanitarian risks are immediate and tangible. Errors in biometric identification have already led to wrongful detentions and delays in aid distribution. In Bangladesh, AI-powered verification errors in the Rohingya refugee registration system temporarily suspended food assistance for thousands. Similar failures have been reported in Greece’s asylum screening, where algorithmic flagging produced inconsistent interview outcomes.

Moreover, the expansion of predictive analytics transforms the notion of “risk” itself. Instead of evaluating claims based on past persecution, AI models predict the likelihood of “future compliance,” turning protection into a behavioral forecast. This predictive logic undermines the 1951 Refugee Convention, which defines asylum as a right, not a privilege contingent on algorithmic approval.



V — Toward Ethical and Transparent Governance

Reforming this system requires embedding human-rights safeguards into every stage of AI deployment. The Council of Europe and the OECD recommend three policy principles:

  1. Transparency and explainability: Asylum applicants must be informed when AI tools are used in their assessment, and governments must disclose the criteria underlying automated decisions.

  2. Human oversight and appealability: No refugee determination should occur without the possibility of full human review and legal challenge.

  3. Algorithmic accountability: Independent audits must evaluate datasets for bias and ensure that efficiency gains do not erode protection standards.

Some positive models already exist. Canada’s Immigration and Refugee Board introduced a hybrid system that uses AI to categorize claims but requires every decision to undergo manual verification. The European Commission’s Ethics Guidelines for Trustworthy AI establish “fundamental rights impact assessments” as mandatory for border-management technologies. These measures demonstrate that ethical oversight is possible when political will aligns with technological capacity.



VI — Conclusion

The digital transformation of refugee policy is not inherently harmful, but it is profoundly consequential. Artificial intelligence offers governments unprecedented analytical power, yet its uncritical adoption risks converting humanitarian protection into an exercise in data management. The moral test of technology lies not in its efficiency, but in whom it empowers. If AI is to redefine global migration governance, it must do so in service of dignity, fairness, and transparency—not expediency. The world stands at a crossroads where the architecture of asylum could become either smarter or colder. The decision, as always, remains human.



Works Cited

“Artificial Intelligence (AI) and Migration.” Council of Europe Committee on Migration, Refugees and Displaced Persons, 2025, https://rm.coe.int/report-artificial-intelligence-and-migration/1680b67b8a.

“Artificial Intelligence in Asylum Procedures in the EU.” European Parliamentary Research Service, 2025, https://www.europarl.europa.eu/RegData/etudes/BRIE/2025/775861/EPRS_BRI%282025%29775861_EN.pdf.

“Digitalisation of EU Borders.” European Commission Digital Border Strategy Report, 2023, https://home-affairs.ec.europa.eu/digitalisation-eu-borders_en.

Forster, Madeleine. “Refugee Protection in the Artificial Intelligence Era: A Test Case for Rights.” Chatham House, The Royal Institute of International Affairs, 2022, https://www.chathamhouse.org/sites/default/files/2022-09/2022-09-07-refugee-protection-artificial-intelligence-era-forster.pdf.

“Global Trends: Forced Displacement in 2024.” United Nations High Commissioner for Refugees (UNHCR), 2024, https://www.unhcr.org/global-trends-report-2024.html.

“Integrating Refugee Protection with Responsible AI Governance.” Organisation for Economic Co-operation and Development (OECD), 2024,

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