The immigration hall at Toronto Pearson International Airport frequently has the atmosphere of a space between two futures. In long lines, travelers stand silently, shifting their weight from one foot to the other while holding their passports. Soft glows from overhead screens indicate that decisions are increasingly being made behind the scenes rather than by individuals.
Canada has invested years in developing artificial intelligence tools that will assist immigration officers in processing applications more quickly and distinguishing between simple and complex cases. Chinook and other AI assistants, according to officials, are triage tools that help handle an excessive volume of applications. There’s reasoning behind it. Human officers can only read so many files in a day due to the increase in immigration volumes.
| Category | Details |
|---|---|
| Country | Canada |
| Agency | Canada Border Services Agency |
| Key Technology | AI-driven risk assessment and screening tools |
| Known Systems | Chinook, Automated Decision Assistant |
| Pilot Launch | Began pilots in 2018; expanded testing through 2023–2027 |
| Purpose | Speed up visa processing and identify high-risk travelers |
| Key Concern | Allegations of racial bias and profiling |
| Official Reference | https://www.canada.ca/en/border-services-agency.html |
It turns out, however, that speed is accompanied by tension.
Civil liberties organizations and experts have begun to warn that these systems might be subtly introducing bias, especially against applicants from specific nations. As this is happening, it seems like something fundamental is changing, not only in the way decisions are made but also in the definition of fairness.
The issue isn’t purely theoretical. Because historical data by definition reflects past human decisions, researchers have noted that AI systems learn from historical data. If there was bias in those earlier decisions, the algorithm may have absorbed it and repeated patterns without realizing them. The machine might not be purposefully discriminating. It’s just digitally inheriting human prejudice.
The change at airports is subtle but discernible.
Cameras scan the faces of travelers as they approach kiosks rather than officers. The procedure is rapid, effective, and nearly frictionless. However, some travelers report feeling uneasy, as though an unseen force is assessing them before anyone speaks.
Standing in a quiet side room as others passed freely, one traveler recalled being arbitrarily referred for further screening. It was an oddly impersonal experience. There was only a silent wait under fluorescent lights, no opportunity for explanation or conversation.
Officials maintain that AI does not make choices. That authority is still held by human officers. They claim that the system only highlights cases for additional examination. The extent of those flags’ influence is still unknown, though. After all, when systems are portrayed as intelligent, humans are more likely to believe their recommendations.
The recommendations made by algorithms carry psychological weight.
Scholars and immigration attorneys have expressed a deeper concern that some nationalities or demographic groups may be flagged disproportionately. A professor likened the situation to risk-assessment instruments utilized in the American legal system, where research revealed notable racial differences in forecasts. Although the system in Canada is different, the pattern seems familiar enough to cause concern.
Policymakers in Ottawa’s government offices must strike a challenging balance. A key component of Canada’s economic and cultural identity is its immigration system. In order to maintain its workforce and growth, the nation is dependent on skilled immigrants. Efficiency is important. Trust, however, does as well. And it’s hard to rebuild trust once it’s been damaged.
Although their attention occasionally veers toward jobs, union representatives have also voiced concerns. Some border guards are concerned that automation may gradually diminish their role by substituting automated recommendations for human judgment. When they speak, they use language that conveys caution rather than outright hostility.
The contradiction is difficult to overlook.
One of the most individualized decisions a government can make is immigration. They decide where people build their lives, live, and work. Giving machines a portion of that process feels, at the very least, emotionally taxing. However, the demand for automation keeps rising.
Similar tools are being adopted by governments all over the world, from Australia’s border screening to Europe’s visa processing. Canada is not by itself. It’s a component of a larger trend toward digital governance, where effectiveness frequently outpaces oversight. For some immigrants, it is unavoidable. Some people are still very skeptics.
Underlying the debate is a more subdued question. What happens if people think the AI doesn’t work as intended, even if it does? Reality can be shaped by perception just as much as by policy, particularly in the context of immigration.
The system’s existence is more apparent when strolling through Pearson Airport late at night, when there are fewer people and the lighting is harsher. Cameras silently observe. The screens move.
Nobody makes the algorithm’s decisions public. They just occur. People wait in lines across polished floors somewhere, hoping the machine can see them clearly.
