immigrate, ingratiate, inebriate

Canada's Auditor General issued a report yesterday about how the Immigration, Refugees and Citizenship Canada (IRCC) has done a very poor job of tracking foreign students among other groups. I won't go into the detail of the report as it is widely available; below is my proposal to solve the interminable backlog of IRCC and to make our IRCC the best in the world.

The tl;dr is to use algorithms that are designed based on the already existing processes and flowcharts that go from applicant to permanent resident, and, have an agentic AI that interfaces with the applicant, uses those algorithms, and reports to the IRCC Officer to make a decision, eventually to gradually automate the simplest and clearest of cases.

This is another idea that if I had 100M$CAD I would implement, though probably I wouldn't need the full amount. With a 12-15 person team of technicians, one of which would be a security expert to  require strong encryption, strict access controls, and transparent audit logs to protect applicants’ data, we would proceed as follows. 

Month 0-2 - get a meeting with the minister, propose the plan, enlist an IRCC manager to work with, hire my team of technicians and explain the plan to the technicians and the project manager I hire to manage this project.

Month 3-6 - the technicians would work on building the agentic core, a technician would meet with the IRCC manager to obtain in detail the process for international students so as to translate that into an algorithm that can be programmed. 

Additionally, the technicians would build a staff interface, a web based desktop interface that allows interaction with the agentic AI, where the AI would deliver cases that need human intervention. This interface would also allow the human staffer to search on any applicant, run reports on the different streams of applicants, and to drill down on any case to see all of the applicant information that was supplied.

Next would be an applicant mobile application, that for any of the streams, asks the appropriate questions based on the algorithm, and supply a method to upload documents and images and so on. It would be in the form of an AI that simply and conversationally asks questions, it would be highly multi-lingual, and it would be trauma aware for those refugees coming from war torn places or persecuted groups. The applicant ought to be able to fulfill all of their IRCC application through this interface.

Finally a representative portal would be created for immigration lawyers, NGOs and other community groups, that, if the representative obtains a 'represent me' authorization, can then look up the specific case of the person they are representing in the IRCC platform, and can send in a comment, a document or fill in anything that might be missing for this applicant's case. Obviously the representative would be able to check the status of a case as well.

Month 7-9 - working with only the international student stream, we would integrate the document pipeline, run internal tests with IRCC staff, fix edge cases, and do run throughs of test student applications from all of the interfaces we've built, starting with the simplest student application to more complex ones. At this stage every student application would pass through the agentic AI and algorithms but would stop at the IRCC officer to do the approval.

During the last quarter of the first year, the lead technician and the IIRC manager assigned to this project would formulate the algorithms for the TFWs and Refugees, each of which could have multiple unique streams within them. 

Month 10-12 - pilot launch where real applicants are onboarded, perhaps manually at first, and then eventually onboarded automatically. The backlog of student applications could begin to get reduced. Once this system is in place there would only be two bottlenecks, either the student is unresponsive, or, the IRCC staffer is over worked with 10,000+ cases to address. For the former, we could have the agentic AI send emails, SMS, try phone calls, mail letters, and also, flag CBSA so that if that applicant leaves the country, if they re-enter the country the CBSA agent can pull them aside, have them fill out an IRCC  questionnaire on a tablet (connected to the IRCC platform) that is witnessed by the CBSA agent and then the applicant is free to continue their travel. 

For the case where the IRCC staff have 10,000+ cases to deal with, eventually we would find a very small subset of student applications that time after time they meet every condition faithfully, and so we first fully automate to approval of these cases that meet that criteria. Now, going forward, all of the backlog, and all new applications can happen extremely quickly as the agentic AI using the algorithms runs through the correct applications in minutes, rather than months. Gradually we add a few more very specific cases that can be fully automated from receipt of application to instantaneous approval. We continue doing this so that really only the edge cases have to go to the IRCC officers. Note that no automated system would ever refuse an applicant; auto-approval only happens for the clean cases; complex or sensitive cases go to the IRCC officer.

By the end of this period, the IRCC minister will have their own access to the IRCC platform to see backlog reports, processing times, bottlenecks, auto-progress rates and would be able to ask the agentic AI specific questions like how many students have been flagged with incomplete documents, or, what are students most often forgetting to include, and things like that.

Once it is proven that the student backlog has been dealt with and that the student processing time that has been automated is so quick, it will be easy to convince the IRCC minister that we are to continue expanding the IRCC agentic AI platform.

We would follow the same development, testing and production steps to implement the TFW and the Refugee immigration streams. The TFW applicant interface would also have an easy way for the applicant to report being mistreated that would eventually get to an IRCC agent who can send someone to do an inspection. As the interface is simply a chatbot in the language of the application, the applicant can simply state that he or she has very poor living conditions, for example, the AI could ask some clarifying questions, and then produce a report.

For refugees that have trouble understanding, or need help, using the 'represent me' at a commuty refugee organization or with an immigration lawyer, the helper there could gently help the refugee to get all of the required documents entered and questions answered, and can then see what the status is of the application which ought to be much faster given this new IRCC platform.

In the third year the remaining immigration streams (Family reunification, Express Entry, caregivers, and provincial nominees) would be added in the same piecemeal way.

In the fourth year we start some value added development, first is a spot for immigration numbers to be reported that is public facing. For example, a map of Canada shows at the top that 123443/500000 immigrants have entered during the current government year. When clicking into a province, it could show 48221/150000 which includes 21000 students, 12500 workers, 6200 refugees and family reunification of 8521 and a small note below these statistics that says that Ontario has indicated it can support 150k newcomers this year. Once within a province, cities that have provided their readiness for immigrants can be clicked, and so municpal data can be shown, for example, Kingston, ON 1588/3412, housing availability: green, school capacity: yellow, healthcare load: green, labour demand: strong in healthcare, trades, IT

This public facing dashboard will be available all of the time and updated in real time as the agentic AI approves (or as IRCC Officers approve) cases.

Once a year the federal government would need to work with the provinces and to set immigration level for the different types of immigrants, and the municipalites would need to report how many they can receive, in line with the province and Canada's plan. So once a year the totals on the publc facing site would get updated, and, the data would be stored within the IRCC platform to fulfill what comes in the next paragraph.

At the beginning of the government year when the immigration numbers are reset, new applicants coming in can move to pretty much anywhere that a city indicates that the immigrants are welcome. Municipalites can also specify what kinds of workers are needed so that the applicants can know where they will get a job in their industry. As the year progresses, some municipalites will reach their quota, and when they do, they will continue to be visible on the IRCC webpage, but no longer available to be chosen by the applicant - so now their pathway to permanent residency can only go forward if they pick an available city to move to.

Once all of the backlogs are taken care of for all of the immigration streams, the approval process ought to be much quicker. Any that have been automated due to having only green flags and meeting all requirements, would get approved within minutes. Any that require an IRCC officer to do further research can be addressed much more quickly with the help of the agentic AI and the case file that the agentic AI built.

On Power & Politics today JP mentioned that recent polls show that support for immigration has dropped to around 1/3 of Canadians. I hope that having a transparent and efficient IRCC platform would help to raise again the support for immigration in our country. As a country we are much stronger with our new immigrants coming in.

Canada could become the first country in the world with a humane, transparent, real‑time immigration operating system — one that treats newcomers not as files, but as future neighbours. We could set an example for other countries.