In an increasingly technological world, it comes as no surprise that the processing of immigration applications would move towards an automated system. In fact, this is precisely what Ottawa has been developing. Since 2014, a “predictive analytics” system that will provide evaluations for applications has been in the works from Canada’s Immigration Department. While review of applications will still be performed manually, the computerized system would eventually assist in making some of the decisions currently made by immigration officers.
According to officials, the idea behind the automated system is to not only help alleviate the current system from its backlogs and processing delays, but to detect fraudulent information or possible red flags in an application. The computer analysis would then assist in determining the acceptance or refusal of an individual’s application.
The focal point in developing the automated system is to determine whether an application is considered high or low risk. With the use of computers, predictive analytics can assess thousands of applications that have already been processed, including the application’s outcome. The patterns found in the data are “learned” by computers and similar to methods used by immigration officials.
According to department spokesperson, Lindsay Wemp, the ultimate goal of the project “is to improve client service and increase operational efficiency by reducing processing times while strengthening program integrity.”
Although the project received government backing in early 2013, computerized decision-making is a long way from being implemented. The option to use such a system, once fully developed, must first undergo comprehensive testing to guarantee accuracy.
Using predictive analytics for immigration applications would be the greatest change for processing since the advent of the Internet. What normally takes weeks, even months in processing times, would take mere days using an automated system. Even more, the system would offer a more economical scheme for processing immigration applications.
Ottawa would not be the first government service to utilize artificial intelligence to detect red flags. Currently, the Canada Revenue Agency uses a decision-making model operated by machines, which has proven to be time and cost-efficient. However, Wemp has emphasized that Ottawa’s project has limits to the involvement of artificial intelligence, citing that human judgment will always remain integral to evaluation processes.
For the future of application processing, Wemp prefers to use terms like “phased approach” when discussing department plans. Likewise, Andrew Griffith, former director general for the Immigration Department, describes the use of technology as evolutionary, and one that can benefit immigration processing. However, Griffith expressed concern over the types of algorithms that will be used for the automated system and whether or not embedded biases will create additional obstacles for applicants. Griffith stated, “Two officers look at an application in different ways. A machine is going to miss things that an officer picks up. I still feel better to have an officer look at every immigration file. Public confidence is important. If Canadians lose confidence in the system, their support for immigration goes down.”
Support for investment immigration to Canada remains the linchpin for the country’s future in business growth and development. With a native population reaching retirement age, Canada cannot afford to miss out on opportunities attracting foreign capital and qualified entrepreneurs due to arbitrary errors within an automated system. Getting the numbers right, then, is key to the project’s success. Wemp has not specified the budgeted amount for its development, other than “modest amounts” allocated to analysts working on the project.
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