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Harvester: Why IRCC is Harvesting Your Submitted Application Documents With Their Latest Automation Tool

 

We have re-produced IRCC’s Harvester user guide from 2021 below (with additional redactions added to preserve passwords that were likely erroneously disclosed).

Harvester Program Guide_Redacted 2_Redacted FINAL

 

What is Harvester?

Per page 5 of the PDF, it is an automation tool that downloads eDOCs from GCMS and organizes (read: reorganizes) the file using clear detailed names. The use of Harvester has improved productivity in pre-assessment by over 25% with minimal training.

Like Chinook (and compatible with Chinook), it also uses an Excel interface and Microsoft Access. Documents are harvested in silos, allowing an Officer to secure, control, and monitor access to a file. Reading between the lines, the use of Microsoft Access also allows all documentation to be displayed on one horizontal screen (to be used , alongside GCMS, and Chinook in a streamlined way. 7-zip is used to encrypt the documentation and similar to Chinook there’s a deletion system after use. Importantly, there appears to be added security functions on who can access the documents and also a trail of records for auditing. I suspect that this could come in handy in future litigation with respect to whether documentation was considered or not. Some docs are excluded from Harvester – either purposely by an Officer where the visa officer does not need to review said doc OR if the harvest does not succeed. I was not able to gleam from my reading where harvests are unsuccessful but one must assume there would be some tech explanation.

Much like Chinook, it appears quite innocuous on the face. It speeds up assessment, heck even I could use a Harvester download and saving (automating) the organization of a file before I review – tasks we often leave to legal assistants and case managers.

However, there may me more than meets the eye. We’re getting a clearer picture of what the Officer actually sees in front of them when they render a decision. What the Chinook 3+ Platform looks like, the various tools and prompts that may or may not be providing information to guide a decision being rendered. Harvester is another one.

 

Takeaways

I would love feedback from our readers to see if they have any ideas but at this stage, I am looking at a couple major ones.

  1. Does the way we name and number our files mean anything any more? We often are creative with the way we try and flag specific names or combine documents, but how does Harvester extract or parse this apart? Is Harvester used (usable) on all apps or just select types that are already streamlined online?
  2. How meaningful is the ability to view the documents on Microsoft Access. From my understanding Harvester replaces the need to utilize other applications such as possibly PDF, Word, or an image reviewer. What does that mean for the way an Officer scrolls through various documents. What other tools does Microsoft Access provide in this regard (I’ve only watched a few online videos so maybe some of the tech-minded can advise);
  3. Why are there silos created for multiple applications? I am concerned again about this ability to string together various applications and harvest all at the same time. Is there a purpose to this? It would make very much sense within a family of applicants to be able to do so, but why would multiple applications un-related be harvested unless its simply to get the files ‘set up’ for review.

Would love for some of you to take a look at Harvester and let us know what you think!

 

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Delaying Decisions on Post-Graduate Work Permit Refusals Have Cruel Implications + Creates Backlogs

(First of all – Happy New Year! I might not be very happy in this post, so I’ll get it out of the way first).

For the past month, we have been dealing with several inquiries from folks who have been refused Post-Graduate Work Permits (PGWPs).

These have mostly been for small administrative issues such as a failure to send a proper final transcript, pay appropriate fees, or uploading issues. Some other cases are those where there is one semester that was not a final semester and that was part-time, usually do to some school scheduling or academic issue. Many had increasing mental health challenges due to COVID-19 related issues, such as the passing away of family members and the need to travel back for those arrangements.

The crux of the problem is that these applications are being refused more than 180 days after the Applicant completes studies. Why is this significant? Well, even though an Applicant is able to restore their status within 90 days of losing their status, at 180 days after the completion of studies, the restoration to PGWP option ceases to exist. Applicants are required to apply for a PGWP within 180 days of completing studies.

Restoration, becomes therefore meaningless as an option outside of the 180 day window. This leads to two applications flooding the system.

  1. Reconsiderations –  many of which (time and time again I find) fail to address the legal test for reconsideration as set out by IRCC and as I have discussed in this past blog.
  2. Temporary Resident Permits – we have been retained for several of these of late and unfortunately it is heading to the 8 month + range for a just graduated student to wait which is simply not feasible for most.
  3. Unnecessary Return to Studies with Unclear Implications of Past Studies – many students go back to school – which makes sense from a Diploma to Bachelors level (perhaps) but for many who graduated from a Bachelors or higher, it really makes little sense to force them to take another program. These decisions are being made rushed, finances are being secured urgently (but with huge impact to families) – all to have to remedy a small admin or one part-time semester issue. It truly is overdoing things.

IRCC needs to urgently render timely decisions on study permit refusals – I would argue 90 days from a student’s completion of studies (i.e. less time if the student applies later) is an absolute maximum time that can be taken (freeing up another 90 for restoration in a feasible time). Given the use of Artificial Intelligence (“AI”) in this space, it should free up Officers to consider some of these cases where there may be admin issue to see if it can be addressed in reconsideration or in applying discretion, rather than having to put students in the loop. Right now, the Courts, are taking a position there is no discretion so litigation is of limited use to force change.

If in fact, the refusal of PGWPs is now a policy directive to try and tackle the backlog or filter the number of PGWP holders perhaps this should be communicated. Students could choose to transition out of classes back home, or return back after graduation, rather than stick around in limbo waiting for a TRP.

Too many mental health issues are being burdened by students who simply are going things that students go through, such as taking part-time classes to better their education outcomes or to save money. Students are making honest mistakes following confusing immigration application instructions. They should not be punished the way they currently are under our Canadian immigration system.

Agree? Disagree? Feel free to engage with me on Twitter or email me at info@heronlaw.ca with your thoughts.

#intled #cdnimm

 

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Five AI-Decision Making Questions We Need Answers To From IRCC

In this short post, I will canvass five relatively urgent questions we need the collective answers to as we represent clients who are now being addressed by artificial-intelligence built decision-making systems. For clarity and to adopt IRCC’s status quo, I will not consider Chinook to be one of those systems, BUT it is clear Chinook interacts with AI and the role of Chinook as it pertains to decisions, especially as advanced analytics skips eligibility assessment become increasingly more important.

1) If IRCC is basing Advanced Analytics decisions of historical data, what historical data is being utilized? Does it represent a reasonable/ideal officer and how can it be re-programmed?

How do we ensure it represents an ideal period (not a stressed officer/overburdened)? IRCC has been overburdened with applications for the last decade having to create systems to shortcut decision-making and has been openly acknowledging their resource crunch. If historical data does not represent what we want for future processing – how can projections be changed. How, in practice, does bias get stripped or de-programmed out of data? We have seen positive impacts (for example Nigerian study permit approval rates) since recent advocacy but is that programmed in manually by a human? and how?

2) How does Advanced Analytics interact with Chinook?

In the past Chinook was utilized for only a portion of cases, we understand to both bulk approve cases and bulk refuse. If Advanced Analytics serves to provide auto-positive eligibility, why is Chinook even needed to sort the Applicant’s information to decide whether to approve or refuse. Is there column in Chinook that allows an Officer to see if Eligibility has already been met (i.e. it was AA’d) and therefore altering their application and use of Chinook? The fear is Chinook becomes just a refusal tool and is no longer needed for approvals.

Furthermore, what does an Officer see when they have to perform eligibility assessment? Are they given any information about data trends/key risk indicators/etc. that Advanced Analytics helped generate presumably during the triage? Is it something the Officer has to dig for in separate module of Chinook or is it displayed right in their face as they render a decision to remind them?

Are Officer’s made aware if a case goes into manual review for example as QA for an Automated Decision? How are those cases tracked?

3) What is the incentive to actually process a non-AA decision if AA decisions can be processed more accurately/quickly?

For those files that are triaged to the non-Green/Human bin, if it becomes a numbers game and the situation is no longer ‘first in, first out’, why even process the complex cases anymore? Why not fill the slots with newer AA/low risk cases that will create less challenges and just let decisions that are complicated or require human intervention to set for one, two years until the Applicant seeks a withdrawal? Other than mandamus, what remedies will Applicants have to resolve their cases. It is simply about complaining hard enough to get pulled out of review and for an eventual refusal? How do we ensure we do not refuse all Tier 2/3 cases as a matter of general practice as we get more Tier 1 applications in the door (likely from visa-exempt, Global North countries).

4) What does counsel for the Department of Justice see in GCMS/Rule 9 Reasons versus what we see?

Usually, the idea of a tribunal record or GCMS is that it a central record of an Applicant’s file but with increasing redactions, it is becoming less and less clear who has access to what information. Client’s are triaged utilizing “bins” but those bins are stripped from the GCMS notes we get. Are they also stripped for DOJ or not? Right now local word flags and risk indicators are stripped for applicants, but are they also stripped for DOJ? What about the audit trail that exists for each applicant that we have not been able to obtain via ATIP?

Taking it a step further – what constitutes a Tribunal Record anymore? Is it only what was submitted by the Applicant and what is in the Officer’s final decision? I know my colleague, Steven Meurrens has started to get even email records between Officers, but there’s a lack of clarity on what that Tribunal Record consists of and whether it necessarily must include the audit trail, risk indicators, and local word flags. Should it include the algorithms?

How does one even try to make fettering arguments if we do not know what the Officer had access to before rendering a decision (how they were possibly fettered)?

The other question becomes how do we let the judiciary know about these systems? Does it go up as a DOJ-led reference (and who can intervene and be on the other side)? The strategic litigation likely will be implemented again in a weak fact case. How do we ensure counsel on the other side is prepared for this so they can not only fight back but provide a counternarrative to the judiciary on these issues?

5) Will the Triaging Rules ever be Made Public? 

Currently, the AI is quite basic from our understanding. There are key rules inputted and applications that meet the requirements go through a decision-tree that leads to auto-eligibility approvals. However, as these AA programs adopt more machine learning components, allowing them to spot out and sniff out new flags, new rules, new issues – will there be some transparency around what the rules are? Should there be different treatment between rules that are more on the security/intelligence/system integrity side versus more black and white rules such as only individual applicants can get tier one processing, or applicant’s must not have had a previous refusal to benefit from X, or holding a U.S. visa or previous Canadian visa over past ten years is a Tier 1 factor.

If the ultimate goal is also to use these rules to try and affect processing (lower number of applicants and raise approvals), presumably telling the public these factors so they may be dissuaded from applying when they do not have a strong case could be of benefit.

Just some random Monday morning musings as we dig further. Stay tuned.

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How Much More Likely is an SDS Study Permit to Get Approved Than a Non-SDS Study Permit? – A Stats Look

One of the common questions we get asked by applicants (and indeed rumours fly around constantly on) is whether it makes sense to pursue IRCC’s Student Direct Stream or just go the regular route.

I recently obtained data from an IRCC requests that helps contextualize this question a bit. I decided (for interest of trying to make the data easier to understand) to just look at January to August 2022. This sample size necessarily limits our analysis, but I think it gives us a good microcosm to examine. January to August 2022 is not hindered (as much) by the COVID-19 restrictions of 2019-2020 and 2021 was for all intents and purposes a ‘straddle’ year.

This investigation is important because there have been rumours and allegations for example – that India SDS is not worth the effort (and that locally decided non-SDS cases have a higher refusal rate) or that for Philippines applicants, SDS is pretty much a non-effective process.

Without further ado, here is the raw data. Remember I did not (for purposes of visualization) break down the actual numbers of applications and did not do an ‘averaging’ because it depends on actual total numbers, which will take a bit more time to calculate with the way data was presented.

via IRCC CDO Approval % SDS/NSE by Country of Residence/Citizenship
Jan-22 Feb-22 Mar-22 Apr-22 May-22 Jun-22 Jul-22 Aug-22
India 72% 67% 69% 64% 60% 55% 57% 62%
Nigeria 61% 60% 68% 76% 91% 92% 63% 91%
China 86% 61% 58% 77% 83% 83% 76% 88%
Philippines 40% 40% 38% 50% 53% 40% 46% 48%
Vietnam 79% 82% 82% 66% 62% 74% 71% 82%
Pakistan 25% 40% 43% 40% 59% 56% 77% 67%
Approval % of Non-SDS/NSE by Country of Residence/Citizenship
via IRCC CDO Jan-22 Feb-22 Mar-22 Apr-22 May-22 Jun-22 Jul-22 Aug-22
India 12% 25% 24% 20% 36% 38% 35% 42%
Nigeria 44% 34% 26% 30% 31% 34% 69% 63%
China 74% 48% 72% 78% 82% 84% 90% 82%
Philippines 57% 58% 55% 82% 75% 84% 77% 76%
Vietnam 58% 51% 59% 79% 72% 61% 81% 55%
Pakistan 24% 17% 44% 17% 36% 48% 37% 38%

I have a few big takeaways:

  1. Philippines SDS is the only SDS that has an approval rate that is significantly and consistently below Non-SDS. LJ Dangzalan has been talking about this a ton, but numbers back this up;
  2. The India Non-SDS rumour appears just that. It may be select cases or ‘overselling’ local services but numbers don’t back that up;
  3. Pakistan SDS makes a big difference (and the last four months) show it; and
  4. The Nigerian student advocacy (and Nigerian Student Express) is trending well.

 

Anything else interesting you can gather from the data that catches your eye?

 

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[Legal Rant] Addressing “Gaming the System” Concerns – Indian Study Permit Applicants and the SDS Example

 

Perhaps this post is inevitable. The reach of s.91 IRPA might be difficult to both control or manage from here inside Canada. Other than bulk refusing the applicants of certain unauthorized practitioners/agents that are found (and it appears only in egregious cases), it is highly unlikely we will see any enforcement. We will try and cut off the Canadian links, but too often they go under the surface – a quick Use of Rep signed here, a quick portal creation there, and the situation goes unnoticed by the applicant and our system-defending officers.

What is increasingly troublesome, however, is that there appear to be ways the system is being effectively gamed – or at least it is being marketed this way. As part of my work I am quite public on Twitter and Social media, and invite those with tips and leads to tell what is going on – ground level. This is one of those tips I received.

Here is one case that I think should trouble some folks.

Canada’s Student Direct Stream (SDS) has been lauded by many in the policy space for creating a subcategory of ‘ready-to-study’ students with good language scores, funds to pay for first year tuition, and a GIC. While I do not have recent stats and need to obtain them, the benefits of these programs have historically been faster processing and higher (10-12%) approval rates to reward students who did the leg work. One of the unique features of the SDS Application is that the approval (and refusal) is issued at Case Processing Centre (“CPC”) Edmonton in Canada, taking a large weight off the local visa offices and triaging cases more effectively.

I also want to give a bit of a context for writing this piece. A study permit was refused and the individual decided to go to an unauthorized representative for the subsequent follow-up application. That agent told the individual that previous counsel had provided too many explanations and letters and that the key to approval was to ensure the Visa Application Centre (“VAC”), and by extension the local visa office, could flag the file after submission. They recommended against submitting another SDS application.

Based on my credible source, who has canvassed other immigration agents from India, who confirmed same – the on the ground knowledge now is that SDS Applications will now take significant longer than regular applications and that to get approvals, the best thing to do is to get the office processed at the local level, at Delhi.

The way to do this is two fold:

  1. Make sure the language test done is the PTE – so that the file has to be processed locally in Delhi; and
  2. Make sure that only first semester and not first year tuition is paid to avoid SDS processing and keep the file local.

This is not the first time we have heard of a perceived preferential processing for non-SDS applications. Similarly for applicants from Philippines and Pakistan we have heard similar things in the past – along with Applicants that have taken various tips to try and get their cases triaged differently. These seem to be amplified concern of Applicants by the fact September school deadlines are starting and applicants need quicker decisions rendered than the SDS ones that have been taking several months. Agents are telling students (and apparently results are showing) approvals at the local office level.

RANT: I think we have to get to a point now, where we ask ourselves why we would create a stream like SDS only to have it take longer to process and perhaps offer less competitive processing.

Without the stats at this stage, I can only pass over the anecdotes I am hearing, but there is enough of a concern on the ground (I am not going to use the word qualitative this week – it doesn’t work) that applicants are being guided by unauthorized practitioners into ‘gaming the system.’ I believe it is enough of a concern that someone should step in to ensure transparency and proper communication.

Either there should be no discrepancy in processing times (thus removing the incentive of speed) or there should be a clear policy aim to have significantly higher approval rates for SDS than non-SDS streams, as should be the case on the basis of the required documentation to be submitted and obtained prior to application.

As IRCC moves to implement technological changes and institute these rules that will triage applications, it must be very aware of those who may have unauthorized access to or are learning how these rules work so as to want to circumvent them. If the data also comes out (beyond anecdotal) to support certain actions, applicants will adjust their behaviours and will be led to do so by unauthorized reps.

If SDS is the superstar program, worthy of global expansion, it is marketed as – there’s no reason it should take longer and make one’s applicant less likely to succeed. The doors of exploitation open up if there’s not consistency in this.

[End of Rant]

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Ocran v. Thavaratnam and Hoku: How a Chinook Decision is Bootstrapped in Judicial Review and Strategies to Counter

I am writing this post after noticing a troubling trend and pattern. Unfortunately, counsel who are unprepared for how the Department of Justice and IRCC work in tandem on these cases (and to be honest, some Judges have also fallen into the trap of this strategy) can lead to JRs being dismissed at leave.

Here’s the pattern:

  1. Temporary Resident Refusal – template refusal letter, further templated GCMS notes – these refusals are done on template refusal language. The refusal letter contains template grounds, and then the GCMS notes indicates further broad refusal grounds using such grounds as concerns about the applicant being ‘young, single, and mobile’, concerns about the ‘applicant’s family ties in Canada,’ the studies not being a ‘reasonable expense’, or the applicant’s ‘past mark sheets’ being of concern – among many others.
  2. Judicial Review – Applicant’s Record – Filed By Applicant – Usually on grounds that only conclusion statements are made, limited reference to material facts, speculative – therefore not intelligible, transparent or justifiable (Vavilov);
  3. Respondent’s Memorandum – Applicant is trying to relitigate facts – onus is on Applicant to prove they meet requirements, Officer’s not required to consider every fact, decision is reasonable. The DOJ then goes out of their way to usually add some detail or justification (I call this portion bootstrapping or counsel’s speculation) to tie together the pieces of the decision.
  4. Judge renders leave decision (refused) or grants hearing  but renders decision that may actually be seeking to question the Applicant’s efforts to provide evidence or question why not more was not provided – Judge often times stepping into the role of bootstrapping or speculating). Counsel tries to argue back that strong evidence was provided, and case becomes about relitigating and justification based on evidence before decision-maker (Applicant loses, often).

 

Assertions of Facts/Consideration of Evidence Leading to Conclusion or Just Conclusions With No Facts

If I wanted to refuse a study permit application reasonably, I could reasonably do it. Highlight some sort of shortcoming/mis-step/inadequacy of evidence, tie it somehow to a refusal ground, and lead to a conclusion that the Officer was not convinced.

However in this new Chinook world, the conclusions often come first and in fact (unintentional), there are little to no actual facts in decisions. This is because, as we know, decisions are being bulk refused and in other times Officers do not have enough time to properly suss out the facts short of stopping at the first grey area they see.

Very commonly decisions read like this:

The Applicant has a girlfriend in Canada. Therefore the applicant’s family ties and economic ties do not satisfy me they will leave Canada at the end of their authorized stay.

Unfortunately there is no logical leap step between Fact or Finding, or even if there is, there’s some obligation to consider evidence that might lead to an opposite finding, which rarely happens.

 

Reverse Engineering Decision – DOJ’s Position Supported by Ocran v. Canada (Citizenship of Immigration) 2022 FC 175 

I generally love his decisions – and his interpretation and application of Vavilov is top notch, but I would say Justice Little’s decision in Ocran is one where it went beyond a judicial review of the decision (para 24 onwards) to almost a stepping in the shoes of the Officer to re-evaluate the factual record in light of the sparse GCMS notes. In no part of the decision, does Justice Little actually address the flawed nature of analysis based on a ‘reading in’ of justifying evidence. In short, I think Ocran opens up (and maybe I read Vavilov the wrong way) to reverse engineering a refusal decision based on stated conclusions with limited factual reliance by the decision-maker.

The approach taken in Ocran has inspired the same process by Department of Justice in cases, and unsurprisingly the decision is being cited for that preposition now that the Record can be read into the sparse GCMS notes. The harm of this is that template language that never meant to analyze or apply the facts to a reached decision are now retroactively used to justify that decision-made.

While I celebrated (sort of) the decision of Justice Little not to break down/opine on the Chinook system, perhaps having sought to contextualize how Officers render their decision template decision using Chinook would have kept him from stepping in to provide as detailed of a factual analysis as he did.

As a side note, even more worrisome is that I have seen after judicial review (consent), a case go back to IRCC where the Officer refused again and did so by adding one line of fact (citing the Record) between each of their previously templated decisions. In short, it is not difficult to rewrite a Chinook decision to make it reasonable even if it was found unreasonable at first.

 

How to Counter – Thavaratnam v. Canada (MCI) 2022 FC 967 

On the more hopeful side of things, a recent decision by Madam Justice Furlanetto in Thavartnam gives applicant’s more hope.

In this decision, the Officer refused a temporary resident visa for an applicant from Sri Lanka, utilizing what Madam Justice Furlanetto refers to in para 19 as blanket or boilerplate statements and a series of conclusions (para 20).

She notes the gaps in reasoning from the Officer and the attempts of the DOJ to try and explain them, but concludes that this does not cure in inadequacy of the reasons for decision.

She writes:

[24] The Respondent proposes various explanations for the Officer’s conclusions. It asserts that the Applicant’s ties to Sri Lanka are weak when weighed against his family residing in Canada because only his wife is in Sri Lanka and they have no children. The Respondent asserts that the Applicant’s savings equate to $18,000 CAD and his pay for the year $5,000 CAD, which is extremely low by Canadian standards. It suggests that the business activities cannot be verified because they are training activities at a private organization owned by a relative. These explanations, however, were not those given in the GCMS notes. Counsel’s speculation of a plausible explanation cannot cure the inadequacy of the reasons for decision (Asong Alem v Canada (Citizenship and Immigration), 2010 FC 148 [Asong Alem] at para 19).

This is a paragraph that needs to be commonplace in responses where the DOJ seeks to try and take the reasons beyond what is written to piece together, what are gaps on the page. (Recall: Komolafe v Canada (Minister of Citizenship and Immigration), 2013 FC 431, 16 Imm. L.R. (4th) 267, at para 11.)

 

Contexualizing Bootstrapping for the Federal Court – Hoku v. Canada (Citizenship and Immigration), 2019 FC 362

I often start my contexualizing my reply’s with the DOJ’s practice. Again, Ilike to use the language of bootstrapping borrowing from wording of Justice Ahmed.

Respondent’s Position re: Family Ties Bootstraps the Officer’s Decision and Commits the Same Error as the Officer of Failing to Analyze Family Ties

3. With respect, the Respondent’s submissions regarding family ties bootstraps the decision of the Officer in this matter. Justice Ahmed writes in Hoku v. Canada (Citizenship and Immigration), 2019 FC 362 [“Hoku”] at para 13 about the practice of bootstrapping.

[13] The Applicant also submits that her detailed submissions and supporting documents were not considered. The Applicant explains that this evidence included her immigration history, personal background, bona fides about her spiritual healing, the nature of her criminal conviction, and indicia of rehabilitation. The Applicant points out that the Minister’s Policy Manual states that all of these factors must be considered, and argued that the Respondent’s submissions bootstrap the actual decision and the reasons discernable from the GCMS notes.

[14] The Respondent submits that the Applicant simply failed to establish that her circumstances justify issuing an ARC, which is not intended to routinely allow persons to overcome a deportation order (Andujo at para 26). The Respondent also submits that it is unclear if the Applicant explained to the Decision-Maker that she exited Canada to comply with her probation order and objects to any inclusion of information not before the Decision-Maker.

[15] First, I agree with the Applicant that the Respondent’s submissions bootstrap the actual Decision-Maker’s reasoning. For example, there is nothing to support the Respondent’s Memorandum at paragraph 16 which states that the Decision-Maker found that the Applicant’s reasons for requesting an ARC were not compelling.
(emphasis added)

Hoku at para 13.

I often then apply and highlight what the DOJ says and respond as follows:

The reality is that the Officer does not offer any justification for the templated reasons they have provided. The Officer merely states that the Applicant “is single, mobile, is not well established and has no dependents.” The Respondent is attempting to fill in the gaps on the page with their own analysis, which is not the purpose of judicial review and represents the very process of bootstrapping.

I hope this piece was helpful. Again, I love the judicial review practice and am excited to make an announcement in September (so soon!) about our further shift towards this direction and this work. I hope young counsel interested in the work slow down and do their research, before engaging DOJ on a Chinook refusal JR.

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The High Refusal Rate for C42 Spousal Applicants at the Abu Dhabi VO: A Closer Look

I recently received some very interesting data from IRCC for a conference I am presenting at in October.

While I will be assembling a team to break down this data (with the help of a trained data scientist), I wanted to write a short piece following a long blog hiatus on probably the data statistic that on the face stands out the most from my first glance.

This stat is the high refusal rate of C42 (spouse of FT study permit holder) applicants who apply at the Abu Dhabi Visa Office in the UAE.

I have extracted the data below.

 

he benefit of doing both Country of Citizenship and Country of Residence disaggregations is it not only shows the major discrepancies on the face (that only 17%/18% of Abu Dhabi VO applicants are getting approved versus 64%/62% as a global rate* – excluding in Canada + Extension apps) but also to see who makes up the large majority of applicants and where do they live. While in my practice I have been quite attuned to the challenges of Indian and Pakistan applicants living in the UAE, I am definitely surprised by the number of Philippines applicants being decided in Abu Dhabi UAE.

The broader implications of this of course means that either initial applications are being refused alongside but possibly that also several families are being separated with a Principal Applicant being approved and the spouse refused. These cases have appeared on my desk quite often recently.

If I were to chalk the C42 refusals to a central reason (and again, even our refusal grounds data – isn’t disaggregated properly right now), I think the lack of citizenship and instability of residency in the UAE is a contributing factor. Many residency permits are tied to work or study in UAE by the Principal Applicant, and there are many non-Emirates in the UAE who go whole lives and generations without ever getting full citizenship. Another factor could be also the deciding of cases of non-citizens of a country at that country’s visa office. We’re increasingly learning of triaging that involves visa offices in Europe handling backlogs from Asia/Africa, and this may be a very similar case particularly for the study permits from the Philippines.

This data set was not easy to get. I had to push to get the data disaggregated and after it was received it had several mistakes. It took two months of back and forths just to get to this point.

This is probably just 0.01% of the work will need to be done. Again, I am not even a data analyst which is why I have put out the call to others in the field and am really impressed by all the responses of offers to help.

I look forward to presenting this data in October. Thanks for tuning in (as always)!

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Coach Will: New Vocabulary Words Tomorrow’s Immigration Practitioners Will Need To Know

As a resource, and to buy time as I am writing more substantive blogs, I wanted to share a #CoachWill blog on new vocabulary, terminology that tomorrow’s immigration practitioners will need to know, learn, advise their clients on, and spend time with. I am still very much learning these terms and their impact, but it gives us a mutual starting point to grow our knowledge of how Canadian immigration law will be impacted moving forward:

 

Advanced Analytics: which is composed of both Predictive and Prescriptive components, consists of using computer technology to analyze past behaviours, with the goal of discovering patterns that enable predictions of future behaviours. With the aid of a team of computer science, data, IT, and program specialists, AA may result in the creation of a model that can perform risk triage and enable automated approvals on a portion of cases, thereby achieving significant productivity gains and reducing processing times. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

Artificial Intelligence: Encompassing a broad range of technologies and approaches, Al is essentially the field of computer science dedicated to solving cognitive problems commonly associated with human intelligence, such as learning, problem solving, and pattern recognition. [As defined in IRCC’s Policy Playbook on Automation]

 

Automated decision support system: Includes any information technology designed to directly support a human decision-maker on an administrative decision (for example, by providing a recommendation), and/or designed to make an administrative decision in lieu of a human decision-maker. This includes systems like eTA or Visitor Record and Study Permit Extension automation in GCMS. [As defined in IRCC’s Policy Playbook on Automation]

 

Black Box: Opaque software tools working outside the scope of meaningful scrutiny and accountability. Usually deep learning systems. Their behaviour can be difficult to interpret and explain, raising concerns over explainability, transparency, and human control. [As defined in IRCC’s Policy Playbook on Automation]

 

Deep learning/neural network is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. While a neural network with a single layer can still make approximate predictions, additional hidden layers can help to optimize and refine for accuracy. [As defined by IBM: https://www.ibm.com/cloud/learn/deep-learning#:~:text=Deep%20learning%20is%20a%20subset,from%20large%20amounts%20of%20data

 

Exploration zone: The exploration zone – also referred to as a “sandbox” – is the environment used for
research, experimentation and testing related to advanced analytics and Al. Data, codes and software
are isolated from those in production so that they can be tested securely.
“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

“Fettering” of a decision-maker’s discretion: Fettering occurs when a decision-maker does not
genuinely exercise independent judgment in a matter. This can occur when a decision-maker binds
him/herself to a fixed rule of policy, another person’s opinion, or the outputs of a decision support
system. Although an administrative decision-maker may properly be influenced by policy considerations
and other factors, he or she must put his or her mind to the specific circumstances of the case and not
focus blindly on one input (e.g. a risk score provided by an algorithmic system) to the exclusion of other
relevant factors. [As defined in IRCC’s Policy Playbook on Automation]

 

Machine learning: A sub-category of artificial intelligence, machine learning refers to algorithms and statistical models that learn and improve from examples, data, and experience, rather than following pre-programmed rules. Machine learning systems effectively perform a specific task without using explicit instructions, relying on models and inference instead. [As defined in IRCC’s Policy Playbook on Automation]

 

A minimum viable product (MVP) is a development technique in which a new product or website is developed with sufficient features to satisfy early adopters. The final, complete set of features is only designed and developed after considering feedback from the product’s initial users. [As defined by Techopedia – https://www.techopedia.com/definition/27809/minimum-viable-product-mvp

 

Predictive Analytics: brings together advanced analytics capabilities spanning ad-hoc statistical analysis, predictive modeling, data mining, text analysis, optimization, real-time scoring and machine learning. These tools help organizations discover patterns in data and go beyond knowing what has happened to anticipating what is likely to happen next. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Prescriptive Analytics: Prescriptive Analytics is an advanced analytics technology that can provide recommendations to decision-makers and help them achieve business goals by solving complicated optimization problems. [As defined in IRCC’s China-Advanced Analytics TRV Privacy Impact Assessment]

 

Process automation: Also called “business automation” (and sometimes even “digital transformation”), process automation is the use of digital technology to perform routine business processes in a workflow. Process automation can streamline a business for simplicity and improve productivity by taking mundane repetitive tasks from humans and giving them to machines that can do them faster. A wide variety of activities can be automated, or more often, partially automated, with human intervention maintained at strategic points within workflows. In the domain of administrative decision-making at IRCC, “process automation” is used in contrast with “automated decision support,” the former referring to straightforward administrative tasks and the latter reserved for activities involving some degree of judgment. [As defined in IRCC’s Policy Playbook on Automation]

[Last Updated: 19 April 2022 – we will continue to update as new terms get updated]

 

 

 

 

 

 

 

 

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Why the Need for Permissive Conditions Adds Unnecessary Burden for Canadian International Students

Context of the Problem – Unclear Instructions

In March 2022, IRCC amended the study permit instructions for Study Permits: Working on Campus to add clarity to ability to work without a work permit while as a student.

Unfortunately, because of the nature of the oversimplification of how R.186(f) IRPR is presented in the instructions and as well as the obligation to obtain permissive conditions one one’s study permits allowing for the ability to work, this creates a major problem for international students.

For reference, R.186(f) is quoted below:

No permit required

 A foreign national may work in Canada without a work permit

  • (f) if they are a full-time student, on the campus of the university or college at which they are a full-time student, for the period for which they hold a study permit to study at that university or college;

Rather than the need for permissive conditions, conditions which as of right now are not uniformly understood or applied by decision-makers in granting study permits (let alone CBSA border officers when printing them) I believe we should ideally be operating where only the absence of restrictive conditions is needed.

This is of course the old way things have been done, where students who are not able to work while studying (perhaps those who have been approved to study only part-time or in ESL programs) are restricted and need to apply to amend their study permits by way of a new extension applicatoin.

Consequentially, as a result of these policy changes, a student without this language (perhaps in a final semester where they are exempt from the need to be in full-time studies to work part-time) has to apply to IRCC to change conditions of their study permit. This process at least takes a few months if not more, if other issues were to arise or concerns flagged, not related to the change request. All of this additional labour is needed, because of the lack of permissive conditions. Given IRCC has just changed this (with apparently no reference to the way things used to be done), this will create unnecessary further backlogs and apply retrospectively to confuse both potential employers and students affected.

Importantly, risk adverse educational institutions are already considering restricting students from being able to work without this language on their study permits. This jeopardizes many students who rely on the ability to work 20 hours to perform tasks as a teaching assistant/research assistant or who wish to levy their experiences in their final semester – by taking a part time job, pending graduation/PGWP application.

Not to mention not all students in Canada are working under the authority of R.186(f) IRPR. On strict interpretation, this is what IRCC is making it appear as – but many will be working on the basis of R. 186(u) – on implied status, or even R. 186(p), (v) or (w) IRPR.

For reference below:

  • (p) as a student in a health field, including as a medical elective or clinical clerk at a medical teaching institution in Canada, for the primary purpose of acquiring training, if they have written approval from the body that regulates that field;

  • (u) until a decision is made on an application made by them under subsection 201(1), if they have remained in Canada after the expiry of their work permit and they have continued to comply with the conditions set out on the expired work permit, other than the expiry date;

  • (v) if they are the holder of a study permit and

    • (i) they are a full-time student enrolled at a designated learning institution as defined in section 211.1,

    • (ii) the program in which they are enrolled is a post-secondary academic, vocational or professional training program, or a vocational training program at the secondary level offered in Quebec, in each case, of a duration of six months or more that leads to a degree, diploma or certificate, and

    • (iii) although they are permitted to engage in full-time work during a regularly scheduled break between academic sessions, they work no more than 20 hours per week during a regular academic session;

Indeed, and more specifically, R.186(v) (iii) for final semester exemption seems to tie directly to the implied nature of R.186(f), but arguably now requires that language because of – again – the change to a required permissive condition. 

If this seems confusing to us as practitioners, imagine an on-campus employer who is concerned about hiring an international student without authorization. This has the further impact of stigmatizing international students in the hiring process. From my perspective, the Regs should override the lack of permissive conditions, but for Employers who are looking at websites only for policy guidance, that may not be abundantly clear.

Interim Solution : Make it Easier – Issue a Letter via Automated Portal

While I believe this issue can be made easier, by reverting to the negative/not positive Issue an automatic letter via the new Client Application Portal upon request (i.e. ASAP) where a student shows they are either a full-time student or are exempt for final semester.

Interim Solution 2: Clarify that R. 186(v) and (w) work different and don’t need this permissive language

It is clearly an error in law to suggest that all work needs to be permitted by R. 186(f) IRPR. The instructions should reflect this and exempt either the R.186(v) and (w) IRPR work. If all these need to be permitted by permissive language, I think you are turning a border officer into a detail-oriented immigration officer, and more problems will arise where some receive and some do not receive this condition

 

Ultimate Solution: Standardize Permissions to Be Only Permissive or Only Restrictive and Not a Mix

Between the system changes, I believe IRCC will need to make a choice: either make it permissive and make it standard practice (not subject to error) to have the permissive conditions printed OR (and as I prefer) specifically exclude those who are not eligible on a case-by-case basis and not throw all the responsibility onto study permit holders to do the work correcting errors while being harmed by the waiting period. As great as the Ask or Update Your Application portal is, I am sure the volume of requests will eventually impact it also.

There’s no reasons, in my mind, we need to have permissive and restrictive conditions mixing and blurring the lines of the Regulations. So few students are even being admitted these days for language courses and part-time studies, and those that are – from my perspective – are a much easier group to manage restrictions for then to impact 98% of folks by requiring permissive conditions.

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A Closer Look at How IRCC’s Officer and Model Rules Advanced Analytics Triage Works

As IRCC ramps up to bring in advanced analytics to all their Lines of Business (LOBs), it is important to take a closer look at what the foundational model, the China TRV Application Process, looks like. Indeed, we know that this TRV model will be the TRV model for the rest of the world sometime this year (if not already).

While this chart is from a few years back, reflecting as I have discussed in many recent presentations and podcasts, how behind we are in this area, my understanding that this three Tier system is still the model in place

Over the next few posts, I’ll try and break down the model in more detail.

This first post will serve as an overview to the process.

I have included a helpful chart, explaining how an application goes from intake to decision made and passport request.

While I will have blog posts, that go into more detail about what ‘Officer Rules’ and ‘Model Rules’ are, here is the basic gist of it. A reminder it only represents the process to approval NOT refusal, and such a similar chart was not provided.

Step 1) Officer’s Rules Extract Applications Out Based on Visa Office-Specific Rules

Each Visa Office has it’s own Officer’s Rules. If an application triggers one of those rules, it no longer gets processed via the Advanced Algorithm/AI model. Think about it as a first filter, likely for those complex files that need a closer look at by IRCC.

You will recall in our discussion of Chinook, the presence of “local word flags” and “risk indicators.” There is no evidence I have yet which links these two pieces together, but presumably the Officer Rules must also be triggered by certain words and flags.

Other than this, we are uncertain about what Officer’s Rules are and we should not expect to know. However, we do know that the SOPs (Standard Operating Procedures) at each Visa Office then apply, rather than the AA/AI model. What it suggests is that the SOPs (and access to these documents) may have the trigger for the word flags.

Step 2) Application of Model Rules

This is where the AA/AI kick in. Model Rules (which I will discuss in a future blog post) are created by IRCC data experts to replicate a high confidence ability to separate applications into Tiers. Tier 1 are the applications that to a high level of confidence, should lead the Applicant to obtain positive eligibility findings. Indeed, Tier 1 Applications are decided with no human in the loop but the computer system will approve them. If the Application is likely to fail the eligibility process, and lead to negative outcomes, it goes to Tier 3. Tier 3 requires Officer review, and – unsurprisingly – has the highest refusal rate as we have discussed in this previous piece.

It is those files that are between positive and negative (the ‘maybe files’) and also the ones that do not fit in the Model Rules nor Officer Rules that become Tier 2. Officers also have to review these cases, but the approval rates are better than Tier 3.

3) Quality Assurance

The Quality Assurance portion of this model, has 10% of all files, filtered to Tier 2 to verify the accuracy of the model.

The models themselves become ‘production models’ when a high level of confidence is met, and they are finalize – such as the ones we have seen for China TRV, India TRV, we believe also China and India Study Permits, but also likely cases such as VESPA (yet this part has not been confirmed). Before it becomes a Production Model, it is in the Exploratory model zone.

How do we know there is a high QA? Well this is where we look at the scoring of the file.

I will break down (and frankly need more research) into this particular model later and it will be the subject of a later piece, but applications are scored to ensure the model is working effectively.

It is interesting that Chinook also has a QA function (and a whole QA Chinook module 6), so it appears there’s even more overlap between the two systems, probably akin to a front-end/back-end type relationship.

4) Pre-Assessment

Tier 1 applications go straight to admissibility review, but those in 2 and 3 go to pre-assessment review by a Clerk.

Important to note here and in the module that these clerks and officers appear to be citing in CPC-O, not the local visa offices abroad. This may also explain why so many more decisions are being made by Canadian decision-makers, even though it may be ultimately delivered or associated with a primary visa office abroad.

But here-in lies a bit of our confusion.

Based on a 2018 ATIP we did, we know that they are triaging different of cases based on case types into “Bins” so certain officers or at least certain lettered numbers – would handle like cases. Yet, this appears to have been the India model then, but the China TRV model seems to centralize it more in Ottawa. Where does the local knowledge and expertise come in? Are there alternative models now that send the decisions to the local visa office or is it only Officer’s rules? Is this perhaps why decisions rendered on the TRVs from India and China are lacking the actual local knowledge that we used to see in decisions because they have been taken outside of the hands of those individuals.

Much of the work locally used to be done on verifying employers, confirming certain elements, but is that now just for those files that are taken out of the triage and flagged as being possible admissibility concerns? Much to think about here.

Again, note that Chinook as a pre-assessment module also that seems to be responsible for many of the same things, so perhaps Chinook is also responsible for presenting the results of that analysis in a more Officer friendly way but why is it also directing the pre-assessment, if it is being done by officers?

5) Eligibility Assessment

What is important to note that this stage is Eligibility where there is no automated approval is still being done by Officers. What we do not know is if there is any guidance directed at Officers to approve/refuse a certain number of Tier 2 or Tier 3 applicants. This information would be crucial. We also know IRCC is trying to automate refusals, so we need to track carefully what that might look like down the road as it intersects with negative eligibility assessments.

6) Admissibility Review + Admissibility Hits

While this likely will be the last portion to be automated, given the need to cross-verify many different sources we also know that IRCC has programs in place such as Watchtower, again the Risk Flags, which may or may not trigger admissibility review. Interestingly enough, even cases where it seems admissibility (misrep) may be at play, it seems to also lead to eligibility refusals or concerns. I would be interested in knowing whether the flagging system also occurs as the eligibility level or whether there is a feedback/pushback system so a decision can be re-routed to eligibility (on an A16 IRPA issue for example).

KEY: Refusals Not Reflected in Chart

What does the refusal system look like? This becomes another key question as decisions are often skipping even the biometrics or verifications and going straight to refusal. This chart obviously would look much more complicated, with probably many more steps at which a refusal can be rendered without having to complete the full eligibility assessment.

Is there a similar map? Can we get access to it?

 

Conclusion – we know nothing yet, but this also changes everything

This model, and this idea of an application being taken out of the assembly line at various places, going through different systems of assessment, really in my mind suggest that we as applicant’s counsel know very little about how our applications will be processed in the future. These systems do not support cookie cutter lawyering, suggest flags may be out of our control and knowledge, and ultimately lead us to question what and who makes up a perfect Tier 1 application.

Models like this also give credence to IRCC’s determination to keep things private and to keep the algorithms and code away from prying investigators and researchers, and ultimately those who may want to take advantage of systems.

Yet, the lack of transparency and concerns that we have about how these systems filter and sort appear very founded. Chinook mirrors much of what is in the AA model. We have our homework cut out for us.

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Three Belated Crystal Ball Predictions for Canadian Immigration in 2022

While March may seem for some a little late to be predicting a year’s events (given Q1 is nearing it’s end), I will take a contrarian position that is not. Right now is perhaps the perfect time to try and make a prediction. All the big picture pieces are out of the way. We know what the levels plan looks like, especially in terms of the reduction of CECs landed in 2022.

Prediction 1: 2022 will be about AI vs. IA

I believe IRCC is full throttle trying to implement AI (Advanced Analytics) across all their Lines of Business (LOBs), from temporary to permanent residence to citizenship. The speed by which artificial intelligence can be implemented with public support to process high volume of applications to Canada will be pitted against the impact of international affairs/crises/refugee producing situation.  If Ukraine is the new precedent set by IRCC to tackle refugee/humanitarian wars and crises, which politically appears it will have to be – so that the Government can appear anti-racist (see prediction 3), this will inevitably delay/shift resources. If AI can be quickly implemented to deal with the quick decisions (both approvals/refusals) this might be the best solution for the Government. Meanwhile those who are more critical of AI systems (myself included) might ask for more caution in the process;

Email headings between senior A2SC (Advanced Analytics) folks, received via ATIP

 

Prediction 2: TEERing Up the Economic Immigration System Will Leave Some Behind 

The new TEER system replaces NOC in a year where economic permanent resident applications, largely filled by NOC B positions, are backlogged and paused. How will IRCC adapt and change the rules of the game, with the implementation of TEER. What does this mean for the future of FSW/CEC?

If the math is as it is above, we could see a shrinking of NOC 0AB so that that the 70% of unit groups once eligible (NOC 0, A,B) turns into 59% (Tier 0, 1, 2). While it seems like a lot of what will occur will be ‘mergers’, I am eager to see what happens to tweener jobs such as administrative assistant and retail sales supervisor. I suspect, the first place we will see a major impact will be in the Federal Skilled Worker where we may move to exclusion lists or targeted draws for specific TEER categories.

 

Prediction 3: IRCC will be forced/asked to clean up the house on anti-racismIRCC’s Anti-Racism Polaris Report and recent concerns (including the next Parliamentary Study) about discrepant processing rates will lead the Department to try and address this in policy options and offerings.

The emails between IRCC staff looking into preventing bias and anti-racism in systems is good work in the right direction, but growing calls will be for an independent oversight commission or ombudsperson.

Immigration is so deeply entrenched with racist roots from our history of exclusion, now manifested in explicit and implicit biases, two tiered systems, secret programs, and different criteria, that I really do not see how we can build an anti-racist system without first tearing down the first one. Economically (in terms of investment into things such as technology) and politically (given we are still considered globally to have a decent/attractive system), I don’t see us doing that.

What you will likely see is a greater platforming and emphasis of the Gender Based Analysis (GBA+) work as well as projects taken up that give at least a cover or presentation of progress. Yet, myself and other critiques are still hopeful that the Government does not shy away from a hard, introspective, look at the systems that have already been developed and paid for to see where key fixes are needed.

I do see that those on the other side, advocates, lawyers, etc. are shifting away from their own Whiteness and once those litigation skills and experiences are transferred to the new generation of racialized lawyers who have a keen sense of justice and have lived/feel the discrepancy, they will start attacking the foundations. I think right now is the perfect time for IRCC to do some public relations/communication work around anti-racism, to pad the intention piece, and build in justifications/explanations/evidence for when these matters eventually get litigated.

As I have presented and said – immigration is itself state-sponsored discrimination. I don’t think we will ever eliminate it to a point where Applicants are happy and Immigration loses its role as a filtering mechanism based on race + citizenship, as a defining feature. Yet, I definitely see a bigger role for those who advocate for safeguards and 2022 as the year some of those safeguards start being introduced.

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Why If There’s No “N/A” Risk Flag on Your GCMS Notes, You May Have Been Risk Flagged

One of the more fascinating modules in Chinook is Module 5 – Indicator Management.

Many of you who have received ATIPs for Officer’s GCMS notes or received Rule 9 Reasons from the Federal Court probably see this in your GCMS notes:

But what if this is missing? Folks have yet to see any actual risk indicators processing priority word flags actually show up in ATIP, well here is probably why.

Indicators and Word Flags are Deleted If There is any Indicator/Word Flag

This email exchange from October 2020 between IRCC program officers and ATIP Officers (I won’t get into why I find this problematic in this piece) tells you why.

In this email, guidance is being provided to only use the wording “Indicator: N/A Processing Priority Word Flag: N/A” where there is Indicator or Priority Flag. In other words, the entire section is omitted where there is an Indicator or Priority Word Flag.

Hence the title of this piece.

Question then becomes, how does one actually challenge the lack of disclosure of a risk flag or priority word flag in a decision? For example, in Federal Court. In litigation, reverse engineered explanations will be put forward for why the decision was reasonable – but without the actual indicator/word flag – a large chunk of the decision or perhaps the impetus behind a fettered decision will be missing.

Furthermore, is it one way access. A big defense of the transparency of fairness of Chinook is that the same information is available in GCMS as is in Chinook minus the deletions of working notes (that apparently are not substantive). However, as we have discovered otherwise these notes can be substantive and if Officers are recommended to use standard form wording in refusing cases – we might only be able to rely on things such as risk flags/work indicators – but these are being deleted from GCMS notes and Rule 9 reasons. What if the Department of Justice has access to them (from their client) but we do not. Does that create a procedural fairness issue?

 

Let’s take a step back and look at what we know so far about Module 5.

Below I will write a running commentary of paras 48-53 of the Daponte Affidavit.

Module 5: Indicator Management (Risk Indicators and Local Word Flags)

38. As described above, Module 5 allows a Chinook user to submit requests to a Chinook administrator to add, renew, or modify “risk indicators” and “local word flags”. “Risk indicators” and “local word flags” are intended to assist Decision-Makers in their review of Applications.

It is to be noted, we still do not know how the system flags/indicates these words to the case. Where it shows up (in what module) to trigger action.

Risk Indicators

39. “Risk indicators” are used to notify Decision-Makers of trends that IRCC has detected, such as a trend that a falsified document was submitted by a certain company in a high number of Applications from different clients or otherwise to highlight a particular factor of concern.

40. “Risk indicators” are also utilized to notify Decision-Makers of potentially low risk Applications; for example, if an international medical conference is being held in Canada, a “risk indicator” may be created to identify entry for such purpose to be of low risk to program integrity.

41. “Risk indicators” may apply to all Applications or to a specific migration office. The inclusion of “risk indicators” within Chinook allows Decision-Makers to view applicable indicators in a centralized manner when determining an Application.

While it is presumed that some of the larger “Risk indicators” are big picture anti-fraud pieces, what about the local office ones? What if something – single, older woman going to attend wedding is an indicator at one visa office, but not at the other? Is local knowledge and Officer’s expertise enough of a justification? Does there need to be oversight?

42. An approved “risk indicator” within Chinook is linked to set criteria. For example, a “risk indicator” may be linked to a client’s declared occupation, such as “petroleum geologist”, or intended employer, such as “Acme Oil”, or a specified combination of criteria, such as “petroleum geologist” for “Acme Oil”.

Again, the specific I understand – the broader flag of “petroleum geologist” seems like it has the possibility of discriminating and I would want it subject to independent oversight.

43. Approved “risk indicators” are presented in the Module 3 Report, along with a recommendation that Decision-Makers perform an activity in assessing an Application, such as a review of proof of credentials or an employment offer letter. The recommendation, however, does not direct Decision-Makers to arrive at any specific conclusion in conducting their assessment, but rather suggests steps to be taken to ascertain information.

I would be interested to seeing what the approval and refusal rates are for cases that are flagged. It would seem to be like a lower Tier flag that could create major challenges. Even though it does not direct a decision, it is hard to see how this does not fetter a discretion with a word such as ‘flag.’

Local Word Flags

44. A “local word flag” is used to assist in triaging an Application in order to ensure priority processing of time-sensitive Applications, such as an Application to attend a wedding or a funeral.

45. A “local word flag” is specific to a particular migration office. For example, the Beijing migration office may obtain approval from the Chinook administrator to include words associated to a wedding, such as “wedding”, “marriage”, or “ceremony”. The matched word found in any Application at the Beijing migration office is then presented in the Module 3 Report.

What separates a risk flag versus a word flag? A local word flag seems to support ‘priority processing’ but how many of these decisions are positive per word versus ultimately, negative?

Indicator Management

46. There is a process to create a “risk indicator” or “local word flag” within Chinook. An IRCC Risk Assessment Officer (“RAO”) or other approved user may submit requests to create such an indicator. A Chinook administrator then reviews requests for approval within Module 5. Each submission must be justified through rationale statements and are subject to modification or denial by the administrator.

This is not surprising. We are aware of this process, although I would mention that from an ATIP on the RAO email account I only saw one Mod5 request (perhaps others redacted) but you can see it below. I also share a copy of what type of flags can be raised.

47. Following the above example, a RAO may find that a number of WP applications have included falsified letters of offer under the name of a specific company, such as “Acme Oil”. The RAO may then submit a request that the company name be included as a “risk indicator” due to concerns of falsified documentation.

This is by all accounts a very positive use of risk indicators. Why not let those who have applied know they have been flagged and perhaps these flags can be accumulated (and some even publicly shared) so we do not have repeat applicants falling for the same trap?

48. Chinook searches for “risk indicators” and “local word flags” in all Applications that are contained in a Module 3 Report. However, such indicators appear in the Module 3 Report only when they may be relevant to a particular Application.

Hence the N/A on several applications. That makes sense.

49. “Risk indicators” and “local word flags” are valid for four months from the date of approval, after which a Chinook administrator may renew or modify the indicator.

What oversight is there of this individual? Their role? Their anti-racism training? Is there a committee or only ONE administrator?

50. As noted above, Decision-Makers or other assigned Chinook users are to “copy and paste” any “risk indicators” or “local word flags” presented in the Module 3 Report into GCMS, where they will be retained. If there are no such indicators, Decision-Makers are to note that these are not applicable to an Application by recording “N/A” in GCMS. I expand on this process immediately below.

Again – why the language of N/A shows up in GCMS.

COMPLETION OF APPLICATION PROCESSING WITHIN CHINOOK

51. Once Decision-Makers finalize decisions for all Applications in a given Module 3 Report, they are to ensure that the decision, reasons, and any “risk indicators” or “local word flags” in the Module 3 Report are recorded in GCMS using the steps described in the paragraphs that follow.

Again, the problem is it is recorded in GCMS but it is disappeared for the Applicant trying to access their own GCMS. Is this fair?

52. Decision-Makers are to click a button labelled “Action List” located within Column A of the Module 3 Report, which organizes data for ease of transfer into GCMS. The created “Action List” presents the decision, reasons for refusal if applicable, and any “risk indicators” or “local word flags” for each Application. If there were no “risk indicators” or “local word flags” associated with a given Application, then Decision-Makers must populate the corresponding GCMS “Notes” field with “N/A” to reflect that no such terms were present in the Module 3 Report.

Which is what we saw with the Rule 9 excerpt I took out. Again, we’ve seen this.

53. Decision-Makers are then required to “copy and paste” the final decision from Chinook into the “Final” field contained in GCMS. Decision-Makers, or assigned Chinook users on their behalf, are also required to “copy and paste” any reasons for decision and the field contents for “risk indicators” and “local word flags” from Chinook into the “Notes” field of GCMS.

So, as counsel, we need to really figure out how to get our hands on these risk indicators because often times – we may be trapped against a flag on our clients, without us even knowing and with the bulk nature by which these flags are being triggered – that will limit the transparency of the final decision. Clients may […]

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Chinook is AI – IRCC’s Own Policy Playbook Tells Us Why

One of the big debates around Chinook is whether or not it is Artificial Intelligence (“AI”). IRCC’s position has been that Chinook is not AI because there is a human ultimately making decisions.

In this piece, I will show how the engagement of a human in the loop is a red herring, but also how the debate skews the real issue that automation, whether for business function only or to help administer administrative decision, can have adverse impacts – if unchecked by independent review.

The main source of my argument that Chinook is AI is from IRCC itself – the Policy Playbook on Automated Support on Decision-Making 2021. This an internal document, which has been updated yearly, but likely captures the most accurate ‘behind the scenes’ snapshot of where IRCC is heading. More on that in future pieces.

AI’s Definition per IRCC

The first, and most important thing is to start with the definition of Artificial intelligence within the Playbook.

The first thing you will notice is that the Artificial Intelligence is defined so broadly by IRCC, which seems to go against the narrow definition it seems to paint with respect to defining Chinook.

Per IRCC, AI is:

If you think of Chinook dealing with the cognitive problem of attempting to issue bulk refusals – and utilizing computer science (technology) – to apply to learning, problem solving and pattern recognition – it is hard to imagine that a system would even be needed if it weren’t AI.

Emails among IRCC, actively discuss the use of Chinook to monitor approval and refusal rates utilizing “Module 6”

Looking at the Chinook Module’s themselves, Quality Assurance (“QA”) is built in as a module. It is hard to imagine a QA system that looks at refusal and approval rates, and automates processes and is not AI.

As this article points out:

Software QA is typically seen as an expensive necessity for any development team; testing is costly in terms of time, manpower, and money, while still being an imperfect process subject to human error. By introducing artificial intelligence and machine learning into the testing process, we not only expand the scope of what is testable, but also automate much of the testing process itself.

Given the volume of files that IRCC is dealing with, it is unlikely that the QA process relies only on humans and not technology (else why would Chinook be implemented). And if it involves technology and automation (a word that shows up multiple times in the Chinook Manual) to aid the monitoring of a subjective administrative decision – guess what – it is AI.

We also know also that Chinook is underpinned with ways to process data, look at historical approval and refusal rates, and flag risks. It also integrates with Watchtower to review the risk of applicants.

It is important to note that even in the Daponte Affidavit in Ocran that alongside ATIPs is the only information we have about Chinook, the focus has always been on the first five modules. Without knowledge of the true nature of something like Module 7 titled ‘ToolBox’ it is certainly premature to be able to label the whole system as not AI.

 

Difficult to Argue Chinook is Purely Process Automation Given Degree of Judgment Exercised by System in Setting Up Findecs (Final Decisions)

Where IRCC might be trying to carve a distinction is between process automation/digital transformation and automated decision support systems.

One could argue, for example, that most of Chinook is process automation.

For example, the very underpinning of Chinook is it allows for the entire application to be made available to the Officer in one centralized location, without opening the many windows that GCMS required. Data-points and fields auto populate from an application and GCMS into a Chinook Software, allowing the Officer to render decisions easier. We get this. It is not debatable.

But does it cross into automated decision support system? Is there some degree of judgment that needs to be applied when applying Chinook that is passed on to technology that would traditionally be done by humans.

As IRCC defines:

The Chinook directly assists an Officer in approving or refusing a case. Indeed, Officers have to apply discretion in refusing, but Chinook presents and automates the process. Furthermore, it has fundamentally reversed the decision-making processing, making it a decide first, justify later approach with the refusal notes generator. Chinook without AI generating the framework, setting up the bulk categories, automating an Officer’s logical reasoning process, simply does not exist.

These systems replace the process of Officer’s  needing to manually review documents and render a final decision, taking notes to file, to justify their decision. It is to be noted that this is still the process at low volume/Global North visa offices where decisions do this and are reflected in the extensive GCMS notes.

In Chinook, any notes taken are hidden and deleted by the system, and a template of bulk refusal reasons auto-populate, replace, and shield the actual factual context of the matter from scrutiny.

Hard to see how this is not AI. Indeed, if you look at the comparables provided – the eTA, Visitor Record and Study Permit Extension automation in GCMS, similar automations with GCMS underpin Chinook. There may be a little more human interaction, but as discussed below – a human monitoring or implementing an AI/advanced analytics/triage system doesn’t remove the AI elements.

 

Human in the Loop is Not the Defining Feature of AI

The defense we have been hearing from IRCC is that there is a human ultimately making a decision, therefore it cannot be AI.

This is obscuring a different concept called human-in-the-loop, which the Policy Playbook suggests actually needs to be part of all automated decision-making processes. If you are following, what this means is the defense of a human is involved (therefore not AI), is actually a key defining requirement IRCC has placed on AI-systems.

It is important to note that there is certainly is a spectrum of application of AI at IRCC that appears to be leaning away from human-in-the-loop. For example, IRCC has disclosed in their Algorithmic Impact Assessment (“AIA”) for the Advanced Analytics Triage of Overseas Temporary Resident Visa (“TRV”) Applications that there is no human in the loop with the automation of Tier 1 approvals. The same system without a human-in-the-loop is done for automating eligibility approvals in the Spouse-in-Canada program, which I will write about shortly.

 

Why the Blurred Line Between Process Automation and Automated Decision-Making Process Should Not Matter – Both Need Oversight and Review

Internally, this is an important distinguishing characteristic for IRCC because it appears that at least internal/behind-the-scenes strategizing and oversight (if that is what the Playbook represents) applies only to automated decision-support systems and not business automations. Presumably such a classification may allow for less need for review and more autonomy by the end user (Visa Officer).

From my perspective, we should focus on the last part of what IRCC states in their playbook – namely that ‘staff should consider whether automation that seems removed from final decisions may inadvertently contribute to an approval or a refusal.’

To recap and conclude, the whole purpose of Chinook is to be able to render the approval and refusal in a quicker and bulk fashion to save Officer’s time. Automation of all functions within Chinook, therefore, contribute to a final decision – and not inadvertently but directly. The very manner in which decisions are made in immigration shifts as a result of the use of Chinook.

Business automation cannot and should not be used as a cover for the ways that what appear routine automations actually affect processing that would have had to be done by humans, providing them the type of data, displaying it on the screen, in a manner that can fetter their discretion and alter the business of old.

That use of computer technology – the creation of Chinook – is 100% definable as the implementation of AI.

 

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The Play is Under Review: A Closer Look at IRCC’s Policy Playbook on Automated Decision Making (Pending Feature)

Over the next several weeks, I’ll be doing a series of shorter blog posts on IRCC’s Policy Playbook on Automated Support for Decision-making (2021 edition).

The first one (hopefully released this week or by the weekend) will be about IRCC’s concerns that applicants are “gaming by claiming” and their preference for “objective evidence” for the inputs of IRCC’s Chinook system.

We will focus our attention of the manual we find could drastically change the landscape for applicants, practitioners, and the courts reviewing decision. We will get critical on ways we expect transparency in the use of AI as we move forward.

I am also doing two parallel judicial review of AI decisions as part of my practice right now, and will keep everyone informed as to how those cases are going and things we are learning.

Should be exciting. Welcome to this space, and looking forward to the conversation.

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New Year, New Me – Gratitude + the Canadian Immigration Issue I’m Tackling in 2022

I have a tradition every year of listening to the same Death Cab for Cutie song, The New Year.

“So this is the new year
And I have no resolutions
For self assigned penance
For problems with easy solutions”

The pursuit of ‘easy’ seems to be the antithesis of my current path. In 2021 (after a late 2020 move), I started a new Firm and had a new baby, each of which has taken it’s relative toll. I’m ready for a reset, a change of focus, and a quieter year. I look forward to announcing those details in early February.

 

Gratitude for another Clawbies Win

I was definitely pleasantly surprised that I received another Clawbies (my third!) for Best Law and Commentary Blog in Canada. This year’s award is dedicated to my readers. Without the engagement, I’ve received on topics such as Chinook and our broader policy discussions, I would not have had the motivation to write. This year, my writing was split largely between this blog and my Firm’s blog.

I suspect 2022 to bring similar things, but I definitely realize how much I miss regular writing after my brief hiatus. I am going to try my best to spend my mornings writing – as regularly as I can amid my year focused on system-building, conference organizing, and too much creative day-dreaming (more on that to come too).

 

Question of 2022: Question of Inequity, Technology, and If (or How) the Courts Will Respond

If I were to crystal ball the central and most pressing issue in 2022, I would suggest it is that of the inequity, particularly technology facilitated inequity, that the current Canadian immigration systems have created. The follow-up question will be how (if at all) the Courts will choose to respond to these arguments, which should be brought forward more.

The Supreme Court of Canada in Vavilov has emphasized the importance of individual’s affected by a decision to be able to present their case fully and fairly. What does that mean within a system that appears to be molding what that means.

[127]                      The principles of justification and transparency require that an administrative decision maker’s reasons meaningfully account for the central issues and concerns raised by the parties. The principle that the individual or individuals affected by a decision should have the opportunity to present their case fully and fairly underlies the duty of procedural fairness and is rooted in the right to be heard: Baker, at para. 28. The concept of responsive reasons is inherently bound up with this principle, because reasons are the primary mechanism by which decision makers demonstrate that they have actually listened to the parties.

Let me give just a few examples of where I think there is clear system-built inequity. Study plans – for many of my clients in the Global South are not required documents for all applicants.  Indeed, my colleague Patrick Bissonnette and I are preparing for a webinar in March where we will explore how there appears to quite a discrepancy between the instructions directed at applicants depending on visa office. Even more troubling, some applicants from high refusal visa offices are not given clear and complete instructions on what such letter should even include, or ultimately recommended to keep their plans to 1 or 2 pages. On the back end, cases (both where IRCC was successful and unsuccessful) are increasingly going after the ‘vague’ nature of the study plans submitted. This vagueness is entirely created by the system, but with ultimate consequences being borne by the Applicant.

I would suggest the same concern is raised about IRCC’s temporary resident portals, limiting uploads to 2MB for applicants. The reality is that 2MB isn’t fair where each visa office has vastly different requirements. In addition to study plans, many applicants from high refusal countries also need to add additional documents about their parents, sources of income, and ties. As we uncovered in our discussion of VESPA for TRV-exempt countries, cases are prima facie approved at a rate of 95+%. For those clients from high refusal countries, they struggle to be able to legibly combine documents and even properly categorize them under the new portal. I have spent much of the later part of 2021 having to re-apply and pursue legal remedies for folks who used the temporary resident portals, where their submissions were reduced and attachments had to be randomly submitted in a way a visa officer would likely have missed.

The other big question comes in the rollout of the use of AI (the China and India TRV model) to other visa officers and lines of work. For IRCC these systems have been working great, but on the other side we’re seeing only the back end of either quick approvals or refusals with very limited justification (as a result of Chinook’s use on the back-end). My hope is that in addition to a bit more transparency (and independent oversight) on the AI system expansion process, that IRCC can do proper outreach on the ongoing use of Chinook or Chinook’s pending replacement.

We have to remember that the Courts too are (and I have to say I am very pleasantly surprised, some what crushing) the recent move to technology. Still, AI and the administrative choices surrounding use of technology will be a whole new conversation to be had. My hope is that this conversation is not simply about deference to the experts. The experts themselves need to ensure their systems do not reproduce yesterday’s inequities.

I will be doing a lot of writing on this in 2022 and cannot wait to share what I uncover!

Ttfn. 2022 let’s go.

 

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Why VESPA’s Internal Only Instructions are Exhibit “A” to Our Two-Tiered Temporary Resident System

Mamelfi, CC BY-SA 4.0 <https://creativecommons.org/licenses/by-sa/4.0>, via Wikimedia Commons

Much like we knew very little about #Chinook until recently, we are now learning more about a March 2020 Program Delivery Instruction [PDI] (with a June 2021 update) on a decade-old IRCC initiative called #VESPA.

VESPA has existed for a decade, but much of it’s existence has been behind relative closed doors. It was introduced to streamline processing for those from visa-exempt countries, but with the expansion of that list (via the Electronic Travel Authorization) regime and the movement towards e-APPS system large, it morphed into another ‘secret’ internal tool utilized at certain IRCC visa offices.

Now that an ‘internal only’ PDI has come to the forefront, it is an appropriate time to revisit VESPA and why I think it exemplifies the type of two-tiering of temporary residents that will become the trend moving forward. It also serves as an antithesis to Chinook, and not unlike Chinook, raises questions about why it is being kept under wraps and what the implications are if it entered greater public consciousness.

What We Knew Before – VESPA as a Pilot for Online Applications

IRCC first launched VESPA in 2011 to operate in 14-visa exempt countries. It was announced by Operational Bulletin 304 – May 2, 2011.

The eligibility criteria were established as follows:

It appears that at the the time, the big ‘advantage’ of VESPA was that the applications were streamlined online. This is re-iterated in a September 2012 presentation by then CIC.

A 2015-2016 Evaluation of IRCC’s Internatoinal Student Program similarly lauded VESPA as part of a modernization initiative for workload redistribution:

There are a variety of modernization initiatives that
CIC has implemented over the past several years,
and more initiatives are planned. Many of these
initiatives are designed to have a positive impact on
the processing of study permits and study TRVs,
including e-Application, e-Medical, GCMS, workload
distribution (e.g. VESPA), VACs and other facilitation
measures for international students such as the
Student Partner Program (SPP). It is difficult to
isolate the impact of particular modernization
initiatives and report on these distinctly in relation to
processing times

Seemingly and as stated by CIC in Operational Bulletin – 486 in December 2012,  the introduction of e-Apps effectively ended the VESPA pilot.

Or so we thought.

 

What We Know Now – VESPA Transformed into a Powerful Tool to Approve Applications

From internal only March 2020 program delivery instructions I received from an Access to Information request, we learn that VESPA not only still exists but has transformed into an even more powerful tool.

I am sharing the instructions from the final draft versions, as the final version I received contained redactions that were answered by the draft versions. This shows the contours of what VESPA now does – streamline straight-forward applications to in-Canada processing, and ultimately supporting an approval for these applicants.

Recall, other than Barbados in the Caribbean, these countries are noticeably Global North and noticeably White.

An internal email between IRCC policy folks on the removal of the age requirement, reveals both that the program is an expedited SP processing stream for citizens and residents of visa-exempt country to apply for an SP from outside Canada AND that the PDI is not accessible to the general public.

We learn that VESPA has been in the works since late 2019 and that originally it was a mission (read: visa office) specific process for low-risk SP applications. 

In June 2021, the instructions were further updated to remove the age requirement as a primary change while maintaining the requirement to be both a citizen and resident of a visa-exempt country and applying electronically for a study permit while overseas.

One interesting question is whether the country list has expanded and arguably it has. I am certainly interested in learning whether VESPA is now for all eTA countries and as we move forward whether this creates a proverbial splitting of approval rates. IRCC policy team’s comment that citizenships were added suggests that this list likely is much longer than 14 countries.

Our statistics from 2020, and taking into account an IRCC policy team member’s comment that VESPA is not the same as SDS, of which all the countries are visa-requiring. If we compare only the 14 countries on the original VESPA list and compare it to the SDS list (noting that not all applications from citizens of each of these countries are VESPA or SDS), this type of divide becomes abundantly clear. It also shows how VESPA files likely do not contribute the same type of volume that SDS contributes.

Citizens from VESPA countries had a 96% study permit approval rate in 2020 (Jan – Nov), with only Iceland’s approval rate deviating from the 90%+ norm. Meanwhile SDS countries produced a below 50% approval rate. I do not have the SDS approval stats, but again I would be grateful if anyone could provide those to me.

Implications of VESPA

What VESPA suggests to me, alongside what we are learning more about from Chinook, is that your vital statistics – what citizenship you hold, where you live, and what you are applying for may ultimately become the determinants for whether or not you are approved in Canada.

VESPA raises many questions: namely, why is preferential treatment being given to folks who may not even hold eTAs and never been to Canada, but those who hold TRVs are often being refused study permits? We know programs such as CAN+ exist but these have not factored into study permit refusals, which refuse often on the change in purpose from visiting to studying.

On that point, other than the eTA being more accessible than a TRV and easier to obtain, in what ways does VESPA actually speak to the merits of a study permit applicant?

Study permit applicants must demonstrate per R.216(1) IRPR that they will leave Canada the end of their authorized stay. They are refused, however, largely on their intention to study, their employment and career prospects, their family ties, the availability of their financial support, their travel history, and their immigration status.

There’s very little in VESPA nor in a logical sense, to suggest that a student from a Global North/largely White country is a more genuine/bona fide student able to facilitate their ability to leave Canada at the end of their stay. In essence, VESPA has removed the study permit considerations out of the study permit for those who are on the current, undisclosed, list.

A final question I would raise is – why is this program being held under wraps and internal only? Much like #Chinook which I still view and see as IRCC’s refusal mechanism for Global South applicants in high volume countries, the antithesis #VESPA seems to be the privilege pass.

Why not disclose that certain countries hold privileged status (I mean, we already have an eTA/TRV required list)?

Is there something about these instructions that fundamentally does not accord with what the public might perceive – i.e. – that VESPA undermines the very foundation of the study permit regime by granting approvals for folks who do not need to even demonstrate their ability to meet the requirement of the Act and Regs?

Lots of food for thought. Perhaps I have opened up a lid of something that was brewing deep in IRCC’s fridge. It’s time to check out what’s actually in the pot.

 

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Predictive/Advanced Analytics + Chinook – Oversight = ?

In September 2021’s issue of Lexbase, my mentor Richard Kurland, provides further insight into what happens behind the scenes of Immigration, Refugees, and Citizenship Canada (“IRCC”) processing, specifically providing a section titled: “Overview of the Analytics-Based Triage of Temporary Resident Visa Applications.

At the outset, a big thank you to the “Insider” Richard Kurland for the hard digging that allows for us to provide this further analysis.

 

What the Data Suggests

I encourage all of you to check out the first two pages from the Lexbase issue, as it contains direct disclosure from IRCC’s Assistant Director, Admissibility opening up the process by way Artificial Intelligence is implemented for Temporary Resident Visas (‘TRVs’), specifically in China and India, the two countries that have implemented it so far. By way of this June 2020 disclosure, we confirm that IRCC has been utilizing these systems for online applications since April 2018 for China, August 2018 for India, and for Visa Application Centre (“VAC”) based applications since January 2020.

To summarize (again – go read Lexbase and contact Richard Kurland for all the specific details and helpful tables), we learn that there is a three Tier processing system in play. This filters the simplest applications (Tier 1), medium complexity applications (Tier 2), and higher complexity applications (Tier 3). While human officers are involved in all three Tiers, Tier 1 allows a model to recommend approval based on analytics, where as Tier 2 and Tier 3 are flagged for manual processing. IRCC claims that the process is only partially automated.

The interesting factor, and given we have been as a law firm focusing a lot on India, is how the designated of a Tier 2 file drives the approval rates from the high nineties (%) to 63% for online India apps to 37%  for India VAC applications. Moving to Tier 3, it is only 13% for online India and 5% for India VAC. The deeming of a file Tier 3 appears to make refusal a near surety.

What is fascinating is how this information blends usage of “Officer Rules,” the first stage filter which  actually precedes the computerized Three Tier triages and is targeted at cases with higher likelihood of ineligibility or inadmissibility.

The Officer Rules system would be the system utilized at other global visa offices that do not use the computerized AI decision-making of India and China. Looking specifically at the case of India, the Officer Rules system actually approves cases at a much higher rate (53% for online India, and 38% for India VAC).

These rates are in-fact comparable to Tier 2 moderately complex cases – ones that presumably do not contain the serious ineligibility and inadmissibility concerns of Officer Rules or Tier 3 . It suggests that the addition of technology can sway even a moderately complex case into the same outcomes as a hand-pulled out complex case.

Ultimately, this suggests that complete human discretion or time spent assessing factors can be much more favourable than when machines contribute to overall decision-making.

It Comes Down to Oversight and How These Systems Converge

Recently, we’ve been discussing in Youtube videos (here and here), podcasts, and articles about IRCC’s Chinook system for processing applications. Using an excel-based model (although moving now to an Amazon-based model in their latest version), applicants data are extracted into rows, that contain batch information for several applicants, presumably allowing for all the analytics to be assessed.

Given we know IRCC takes historic approval rates and data as a main driving factor, it is reasonable to think Immigration Officers are given these numbers as internal targets. I am sure, as well, that with major events like COVID and the general dissuasion of travel to Canada, that these goalposts can be moved and expanded at direction.

An excel-based system tracking approvals and refusals likely put these stats front and centre to an officer’s discretion (or a machine’s) on an application. Again to utilize a teaching analogy (clearly I miss teaching), I utilized a similar ‘Speedgrader’ type app which forced me, mid-marking, to often to revisit exams that I had already graded because I had awarded the class average marks that were too high. I have no doubt a parallel system exists with IRCC.

What this all means, as my colleague, Zeynab Ziaie has pointed out in our discussions, there are major concerns that Chinook and the AI systems have not been developed and rolled out with adequate lawyer/legal input and oversight, which leads to questions about accountability. Utilizing the Chinook example, what if the working notes that are deleted contain the very information needed to justify or shed light on how an application was processed.

My question, in follow-up, is how are the predictive/advanced analytics systems utilized by India and China for TRVs influencing Chinook? Where is the notation to know whether one’s file was pre-assessed by “Officer’s Rule” or through the Tiers. I quickly reviewed a few GCMS notes prior to this call, and though we know whether a file was pre-accessed, we have no clue which Tier it landed on.

Furthermore, how do we ensure that the visa-office subjective “Officer Rules” or the analytical factors that make up the AI system are not being applied in a discriminatory manner to filter cases into a more complex/complex stream. For example, back in 2016 I pointed how the Visa-Office training guides in China regionally and geographically discriminate against those applying from certain Provinces assigning character traits and misrepresentation risks. We know in India, thanks to the work of my mentor Raj Sharma, that the Indian visa offices have a training guide on genuine relationships and marriage fraud that may not accord with realities.

Assuming that this AI processing system is still being used only for TRVs and not for any other permits, it must be catching (with the assistance of Chinook’s key word indicators no less) words such as marriage, the names of rural communities, marital status, perhaps the addresses of unauthorized agents, and businesses that often have been used as a cover for support letters. Within that list there’s a mix of good local knowledge, but also the very stereotypes that have historically kept families apart and individuals from being able to visit without holding a study permit or work permit.

If we find out, for example, that filtering for complex cases only happens at visa offices with high refusal rates or in the Global South, does that make the system unduly discriminatory?

We acknowledge of course that the very process of having to apply to enter the borders, the division of TRV and electronic Travel Authorization (eTA) requiring countries is discriminatory by nature, but what happens when outcomes on similar facts are so discrepant?

In other areas of national bureaucracy, Governments have moved to blind processing to try and limit discrimination around ethnic names, or base decisions on certain privileges (ability to travel and engage in previous work), and remove identifying features that might lead to bias. For immigration it is the opposite, you see their picture, their age, and where they are from, and why they want to come (purpose of visit). As we have learned from Chinook, that is the baseline information that is being extracted for Officers to base their decisions on.

When – as a society – do we decide to move away (as we have) on what were once harmful norms to new realities? Who is it that makes the call or calls for reviews for things such as consistency or whether a particular discriminatory input in the AI system is no-longer consistent with Charter values?

Right now, it is all in the Officer’s discretion and by extension, the Visa Offices, but I would recommend some unified committee of legal experts and race/equity scholars need to be advising on the strings of the future, inevitable, AI systems. This would also unify things across visa offices so that there is less discrepancy in the way systems render decisions. While it makes sense that heavier volume visa offices have more tools as their disposal, it should not depend on where you live to receive less access to human decision-makers or to an equal standard of decision-making. We do not want to get to a place where immigration applicants are afraid to present their stories or speak their truths for fear of being filtered by artificial intelligence. From my perspective, we are better of being transparent and setting legitimate expectations.

What are your thoughts on the introduction of AI, the interaction with Chinook, and the need for oversight? Feel free to engage in the comments below or on social media!

Thanks again for reading.

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Three Common Mistakes Canadian Immigration Applicants Make When Documenting Employment/Personal History and My New Strategy

Recently, I have had a major increase in misrepresentation consultations and other related issues with one common starting point: incorrect work/personal history that either Canadian immigration has found or will eventually find out about.

There are several forms that canvass work/personal history. This ranges from initial application forms (IMM 1294, IMM 1295, etc.) to the IMM 5257E Application for a Temporary Resident Visa Forms, to the dreaded IMM 5669 – Schedule A.

Excerpt from IMM 1294 form

Each form (and accompanying instructions) often ask for the materials a different way. Some forms ask for only employment history, whereas others as for a full ten-year history. Complexities also arise when certain visa offices want a full personal history starting from the age of 18, but do not make these instructions apparent at the outset, requiring them later in request letters.

What often happens is a hot mess of unclear work dates, forgotten travels, mistaken residences, and IRCC analyzing all of these for possibly material misrepresentations that may impact officer assessment.

To make things even more complicated, misrepresentations can extend to past applications, even if it is attempted to be corrected. Memories are imperfect, what is required to be disclosed is confusing, and unfortunately perfectly innocent applicants can make devastating mistakes.

While there are some positive trends in judicial interpretation, the law around misrepresentation in Canada is harsh: a five-year bar from Canada (and from applying for permanent residence) regardless of the intent of the error or omission, and a thin-exception for innocent misrepresentation.

In this post, I look at three common mistakes I see applicants (and their representatives make) and how to avoid them. I will close with a new approach I am taking to documenting work history for my clients on temporary resident applications.

 

Mistake 1: Omitting Material Personal History/Blurring Dates Together

There are several sub-mistakes under this category:

[1] Applicants often include only their last position held, rather than to breakdown the various positions within a company

This one may seem innocuous now, but on a PR application or when facing an employer’s reference letter that paints a different picture this could be an issue. Often times these dates are also contradicted by public information you may have about yourself online, such as your LinkedIn profile or a biography you hastily submitted to a third-party who has posted it online.

Visa Offices also have many internal tools at their fingertips. For example, for China, they have access to a quite comprehensive ‘legal persons’ registry for businesses. Particularly for entrepreneurs or businesspersons who own multiple businesses, failures to disclose one (even if it is unclear whether it constitutes employment or ownership) could constitute misrepresentation. This was the fact pattern in the Federal Court’s decision in Sun v. Canada (Citizenship and Immigration), 2019 FC 824 (CanLII).

My rule of thumb is to over-disclose rather than under-disclose if there are no inadmissibility risks to the additional details being disclosed and it may set forward a good groundwork to get ahead of a potential issue or pave the way for a future application. If your disclosure of the item could affect your eligibility, consider whether applying on misrepresented information could come back to haunt you in the future.

Yet, many times the information being omitted is not itself going to change the decision of the Officer, but the very omission of the information could impact the Officer’s processing or review of the requirements, which could make it a material misrepresentation.

 

[2] Applicants often don’t include periods of unemployment, self-employment, and educational pursuits

Often times Applicants only provide just the formal work/employment history and forget to include the personal history. Again, the forms make it a bit confusing. In the description of the form, it asks for employment history, but in the fine print it may say to include periods of unemployment or leave no gaps. Another challenging aspect is that certain applications (co-op work permits and post-graduate work permits) do not actually require full disclosure of work history, whereas other applications (temporary resident visas inside Canada) do. We play it safe by including a running 10-year history for all applicants, regardless of it is a requirement.

This often rears its head as an issue when a visa is refused for lack of continuous study or lack of relevant employment history demonstrating there are opportunities in the country of residence. When it is only indicated that one is ‘unemployed’, the literal interpretation  the Officer will take is that you are at home doing nothing. Trying to start up your own business or taking pre-requisite courses for a formal program of study, is not sitting home doing nothing and may be very material. Failure to include this initially could create discrepancies later (see mistake 3 below).

 

[3] Applicants do not disclose sufficient details in the personal histories

In my work often reviewing materials for refused clients, often who applied the first time themselves or less competent counsel, there are common themes.

Rather than put detailed descriptions of position or title – words such as “employee” or “management” or “police officer” are used. Alternatively, when discussing employment rather than put the company or school name, answers such as “restaurant business” or “self-employed” or put down. Immigration Officers may want to conduct an inadmissibility inquiry into your former work place, or verify that you indeed worked for said employer or that such a company/organization exists.

If there is an admissibility concern or clarification to be made, make sure to make it on a letter of explanation or clarify (see attached). Too often I see clarifying explanation missing until after a Procedural Fairness Letter (PFL) is received. This is often times far too late in the game.

 

 

Mistake 2: Not Correcting the Mistake When IRCC Gives You a Chance (Requests vs. PFLs)

When IRCC notices an inconsistency (and depending on what visa office and what type of application), there may be the opportunity provided to fix an inconsistency. Commonly, especially if a misrepresentation is not apparent on the surface, a request letter will be issued offering an opportunity to clarify or seeking further information. `

The tendency with request letters, I find, is to blindly try and answer them as soon as possible. Applicants immediately take a defensive position, without thinking at that stage that the request letter could be the set up for an A16(1) IRPA (failure to truthfully provided requested documents) or worse yet, an A40 IRPA (misrepresentation) refusal. Given the withdrawal of an application is unlikely to be granted after a PFL is issued and the leg work is all but done at that stage, it is as the request letter stage that clarifications need to be sought and legal arguments made.

Repeated errors in providing accurate information or misunderstanding request letters could later lead to further challenges arguing innocent misrepresentation or seeking discretion later on in the process.

 

Mistake 3: Not Keeping Adequate Records and Inconsistencies Between Applications

Visa Offices such as those in India (especially Delhi and Chandigarh) and China (Beijing) now utilize artificial intelligence tools that will be able to spot an inconsistency instantaneously.

Before submitting an application, if possible, compare your forms with previous forms submitted. Better yet, request or obtain (by access to information) a copy of all final forms before a representative submits any application for you.

Another discrepancy I see is with address history, travel history, and work history on forms. Where these do not align, and particularly when it comes to permanent residence applications that look into where work was performed and where the Applicant was located, and whether or not the claimed work matches with past records – this becomes ever so important. Virtual work or work through multiple client sites is becoming more popular, and failure to properly document this in respective applications may complicate things when permanent residence rolls around.

 

My New Approach: Focusing on Forms First, and then Attachments

In the past, a move I did (and one I know many counsel mirror) is to put “please see attached” on the work history sections or personal history sections of some validated temporary resident forms and then add a work document. This option will not be available with the new online temporary resident portal, which like Express Entry do not allow you to move on to the next page until there are no gaps. In the interim, what I am suggesting with the validated forms is still to list as much as possible on the form and then add ‘see attached’ on the final line before continuing.

The reason for this is that IRCC has been focusing on auto-populating systems like Chinook that appear to extract information directly from forms into their internal processing system. I am worried that my attached table found at the back of my rep’s submission letter is missed by a processing agent or in review. We know increasingly that the Officers are only accessing the information extracted for their review and are under a major time crunch. This little tip might help practitioners and self-reps.

 

Some Positive News: Court Critical on IRCC’s Need for a Materiality Analysis of Misrepresentation

While misrepresentation is often a death trap for an immigration application, the Federal Court has recently been pushing back on the tendency of IRCC to equate a mistake as misrepresentation, without an analysis of materiality.

In Alves v. Canada (Citizenship and Immigration), 2021 FC 716 (CanLII), Justice Manson allowed a judicial review after finding that an Officer’s finding of misrepresentation was unreasonable. The Applicant disclosed one of his previous refusals to the United States, but had omitted an earlier one.

Justice Manson writes:

[19] However, an officer must consider the totality of the evidence before the decision maker (Koo v Canada (Minister of Citizenship and Immigration)2008 FC 931 at para 23). The Officer, in this case, failed to recognize the potential significance of the mitigating evidence, as it relates to the finding of misrepresentation without meaningfully coming to grips with the facts before the Officer. Instead, the Officer broadly found that the Applicant had […]

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Canadian Immigration Self-Employment Woes and Why We Need to Prioritize the Triple A (Athletes, Actors, and Artists)

Like many others, I have spent the last several weeks glued to my TV to the athletic wonders of the Olympic Games.  From perfect dives to strained bike rides, we have witnessed incredible feats from Canadian athletes, but also around the world.

One of the major elements that was showcased, and by Canada too, is the power of (im)migration to new assumed identities and countries of citizenship. Some of my favourite athletes of the games were Somalian Canadians, Brazilian-Poles, and Spanish-Russians. Many of the best athletes representing countries, were not born there, often did not grow up there nor have family there, but found themselves pursuing opportunities for the country and obtaining citizenship through naturalization in the process or as a result of their talent and self-employment as world-class ahtletes.

 

A Difficult Pathway to Permanent Residence and Citizenship for Athletes, Actors, and Artists

In order to become a Canadian citizen on the basis of athletic talent is not simple, especially if you are a rising star rather than an established one. Discretionary grants are rare, and unfortunately, the past few years have seen the self-employment program for permanent residency face major delays and is on the brink of dissolution. I have clients who are close to two-years in to processing, inside Canada, and without access to bridging open work permits that are a lifeline for permanent residence applicants.

Unsurprisingly, self-employed applicants who are in Canada (many of whom have worked for years as actors and artists in Canada or started their own businesses here rather than become employees) are hooped.

Canada cut off invitations to the Federal Skilled Workers invitations under Express Entry, even where applicants were actually in Canada and working – a policy flaw I believe will directly impact our immigrant talent pool. While programs like the start-up visa or provincial programs supporting nominees or work permit processes do exist, they do not begin to capture the type of sole practitioner/small business self-employed individual seeking stability for their immigration status. COVID has inspired more of these businesses. It is a shame and inexplicable that this work is not considered Canadian work experience for the purposes of supporting permanent residence under Express Entry.

On the other hand, one can somewhat understand this. Self employment is difficult to assess – difficult but not impossible. Many self-employed individuals do not incorporate or earn income in the traditional sense. When one is declaring one’s own experiences, it might not allow for the usual objective “validation” or “work experience letter” that IRCC puts heavy weight on. Yet, IRCC provides guidelines for applicants and like the self-employment permanent residence process requires, there can be letters of support and other public proof of one’s accomplishments and work. Self-employed work experience is often heavily scrutinized, especially in the context of foreign work experience.

The reality is, in this day and age contractors and multiple self-employed jobs are becoming the future norm. It is difficult for small businesses and start-ups to engage employees when their own operating budget is not there yet.

In addition to athletes, actors and artists are also struggling. Many film schools that attract applicants to Hollywood North are private institutions, unable to provide post-graduate work permits. IRCC has cut off largely matriculation agreements or those arrangements that allowed applicants to benefit from their time at the private institution when calculating post-graduate work permit duration. At the same time, work permits for film and television workers (that are labour market impact assessment (LMIA) exempt) are difficult to secure when union membership and opportunities require the work permit first as entry for opportunities and the type of indie-films and underground artists that become global talents, are often shutout from the process.

In addition to expanding the post-graduate work permit to these educational sectors and perhaps creating new programs to recruit international talent at a younger age, I would also suggest that openly and transparently supporting an easy process for work permits and a feasible pathway to permanent residence for world class talent who are training, interning, or endorsed by Canadian actor and artists unions, and athletics committees, would be a welcome step.

The current self-employed program falls short for not having specific streams or criteria specific to those areas. They require proof of ability to be self-employed in Canada and bring demonstrated economic benefits, but there is little follow-up or accountability and no role for Canadian supporters to be primary endorsers.

Rather than limit immigration targets to a mere 1000 a year, with a greater emphasis on the start-up visa, such a program could target sports Canadian seek to grow in, art forms that Canada needs practitioners in, and provide permanent residence to aspiring actors, actresses, and entertainment folks working for up and coming Canadian-based production companies.

 

Returning to the Olympics: The Global Recruitment for Talent

There are also a number of athletes I recognized from watching the Olympics who have decided to represent other countries, even while they were either born in Canadian, naturalized  While there are many factors for this that are outside immigration, no doubt other countries are recruiting and many have ways to fast-track immigration and naturalizations in order to allow athletes to compete for them.

The steps being taken by Sheridan College, through the private sponsorship process, to support refugee Olympic athletes to represent Canada is laudable. Yet, think about a greater possibility where athletes who have demonstrated exceptional talent, years of commitment, and meeting certain world standards could come to Canada first as permanent residents, train for several years, and obtain citizenship in time to compete within one Olympic cycle.  Think about global artists bringing their art form and inspiring interaction and the preservation of Indigenous art across cultures. I think about about as well being able to have more productions like Kim Convenience, or even the recent Manifest, forming movies that attract global audiences.

I truly hope Canada works out better self-employment processes and streams for our future athletes, actors, artists reflecting the growing entrepreneurial nature of these times.

 

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About Us
Will Tao is an Award-Winning Canadian Immigration and Refugee Lawyer, Writer, and Policy Advisor based in Vancouver. Vancouver Immigration Blog is a public legal resource and social commentary.

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