By Stuart Kerr, Technology Correspondent
Published: 2025-07-16 | Last updated: 2025-07-16Contact: liveaiwire@gmail.com | Follow @LiveAIWire
Author Bio: https://www.liveaiwire.com/p/to-liveaiwire-where-artificial.html
What happens when your visa is denied, not by a human, but by an algorithm? As artificial intelligence expands into public administration, immigration systems worldwide are quietly adopting machine learning models to sort, score, and select human lives. The age of the algorithmic border has arrived.
Borderlines Drawn by Code
In immigration systems from Canada to the EU, governments are piloting or already deploying artificial intelligence to automate decisions traditionally made by caseworkers. These systems screen visa applications, flag high-risk individuals, and even recommend deportations. The aim is clear: process more cases, faster. But the consequences of outsourcing human judgment are anything but straightforward.
The International Bar Association has documented how Canada's immigration authority has experimented with AI to triage temporary resident visa applications. Applicants deemed "low risk" are processed quickly, while others face deeper scrutiny. The model’s criteria? Proprietary and opaque. Meanwhile, critics argue that such algorithms embed historical bias and offer no recourse when errors occur.
Predicting the Unpredictable
In the United States, tools powered by predictive analytics are used to assess the likelihood of visa overstays or security risks. As reported in The Regulatory Review, ICE and CBP have increasingly relied on AI for behavioural analysis, automated surveillance, and watchlist creation.
Such systems don’t just make decisions—they predict future behaviour. The danger lies in their certainty. Algorithms trained on historical data risk reinforcing structural injustices. Asylum seekers, for example, may be denied due to risk scores derived from nationality or travel history rather than individual merit.
Emotionless Empires
In AI and the Gig Economy, we explored how platform workers are judged by emotionless systems. Now, border tech is following suit. These decisions lack context, empathy, or appeal. Even worse, they are often hidden behind the myth of neutrality—that data doesn’t discriminate.
But as the Chatham House report (PDF) explains, asylum decisions are inherently complex, relying on cultural nuance and personal storytelling. AI systems trained to "screen out fraud" may instead screen out the vulnerable.
Biometric Borders and Automated Surveillance
Beyond paperwork, AI is also patrolling physical and digital borders. Governments now deploy facial recognition at airports, predictive modelling at visa centres, and AI-powered drones for land surveillance. The Access Now report (PDF) details how automated border systems are built on biometric data that can be incomplete, racially skewed, or misinterpreted.
As discussed in Emotional Intelligence, machines can simulate empathy—but they cannot live it. The emotional toll of being screened by systems you cannot question is rising, particularly among already-marginalised communities.
Accountability in the Black Box
Transparency is a recurring issue. Applicants are rarely told what data was used, how it was weighed, or how to challenge outcomes. Even regulators struggle to audit AI models embedded deep within government infrastructure. As we saw in AI in Mental Health, opaque systems in sensitive domains often lead to underreported harms.
There is growing international pressure for algorithmic accountability in migration. Civil rights groups, legal experts, and ethicists are calling for bans on predictive deportation, full disclosure of risk models, and the right to a human appeal.
The Future of Fair Movement
Automation may have a role to play in making immigration faster and more consistent. But it must not come at the cost of fairness, compassion, and human dignity. The border of tomorrow isn’t just a physical checkpoint—it’s a decision tree, a risk score, a training set.
As more lives are sorted by silicon, we must ask: who programmed the rules? Who audits the outcomes? And most critically—can an algorithm ever truly understand the human journey?
About the Author
Stuart Kerr is the Technology Correspondent at LiveAIWire. He writes about AI’s impact on infrastructure, governance, creativity, and power.
Contact: liveaiwire@gmail.com | Follow @LiveAIWire
References:
IBA – Artificial Intelligence and Canada’s Immigration System
The Regulatory Review – Rise of AI in Immigration Enforcement
Fair Observer – AI Programs and Migrant Rights
Refugee Protection in the AI Era – Chatham House (PDF)
Uses of AI in Migration and Border Control – Access Now (PDF)