Teresa Scassa - Blog

Monday, 17 October 2022 04:11

Procedural fairness and AI - Some lessons from a recent decision

Written by  Teresa Scassa
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Artificial intelligence (AI) is already being used to assist government decision-making, although we have little case law that explores issues of procedural fairness when it comes to automated decision systems. This is why a recent decision of the Federal Court is interesting. In Barre v. Canada (Citizenship and Immigration) two women sought judicial review of a decision of the Refugee Protection Division (RPD) which had stripped them of their refugee status. They raised procedural fairness issues regarding the possible reliance upon an AI tool – in this case facial recognition technology (FRT). The case allows us to consider some procedural fairness guideposts that may be useful where evidence derived from AI-enabled tools is advanced.

The Decision of the Refugee Protection Division

The applicants, Ms Barre and Ms Hosh, had been granted refugee status after advancing claims related to their fear of sectarian and gender-based violence in their native Somalia. The Minister of Public Safety and Emergency Preparedness (the Minister) later applied under s. 109 of the Immigration and Refugee Protection Act to have that decision vacated on the basis that it was “obtained as a result of directly or indirectly misrepresenting or withholding material facts relating to a relevant matter”.

The Minister had provided the RPD with photos that compared Ms Barre and Ms Hosh the applicants) with two Kenyan women who had been admitted to Canada on student visas shortly before Ms Barre and Ms Hosh filed their refugee claims (the claims were accepted in 2017). The applicants argued that the photo comparisons relied upon by the Minister had been made using Clearview AI’s facial recognition service built upon scraped images from social media and other public websites. The Minister objected to arguments and evidence about Clearview AI, maintaining that there was no proof that this service had been used. Clearview AI had ceased providing services in Canada on 6 July 2020, and the RPD accepted the Minister’s argument that it had not been used, finding that “[a]n App that is banned to operate in Canada would certainly not be used by a law enforcement agency such as the CBSA” (at para 7). The Minister had also argued that it did not have to disclose how it arrived at the photo comparisons because of s. 22 of the Privacy Act, and the RPD accepted this assertion.

The photo comparisons were given significant weight in the RPD’s decision to overturn the applicants’ refugee status. The RPD found that there were “great similarities” between the photos of the Kenyan students and the applicants, and concluded that they were the same persons. The RPD also considered notes in the Global Case Management System to the effect that the Kenyan students did not attend classes at the school where they were enrolled. In addition, the CBSA submitted affidavits indicating that there was no evidence that the applicants had entered Canada under their own names. The RPD concluded that the applicants were Kenyan citizens who had misrepresented their identity in the refugee proceedings. It found that these factual misrepresentations called into question the credibility of their allegations of persecution. It also found that, since they were Kenyan, they had not advanced claims against their country of nationality in the refugee proceedings, as required by law. The applicants sought judicial review of the decision to revoke their refugee status, arguing that it was unreasonable and breached their rights to procedural fairness.

Judicial Review

Justice Go of the Federal Court ruled that the decision was unreasonable for a number of reasons. A first error was allowing the introduction of the photo comparisons into evidence “without requiring the Minister to disclose the methodology used in procuring the evidence” (at para 31). The Minister had invoked s. 22 of the Privacy Act, but Justice Go noted that there were many flaws with the Minister’s reliance on s. 22. Section 22 is an exception to an individual’s right of access to their personal information. Justice Go noted that the applicants were not seeking access to their personal information; rather, they were making a procedural fairness argument about the photo comparisons relied upon by the Minister and sought information about how the comparisons had been made. Section 22(2), which was specifically relied upon by the Minister, allows a request for disclosure of personal information to be refused on the basis that it was “obtained or prepared by the Royal Canadian Mounted Police while performing policing services for a province or municipality…”, and this circumstance simply was not relevant.

Section 22(1)(b), which was not specifically argued by the Minister, allows for a refusal to disclose personal information where to do so “could reasonably be expected to be injurious to the enforcement of any law of Canada or a province or the conduct of lawful investigations…” Justice Go noted that case law establishes that a court will not support such a refusal on the basis that because there is an investigation, harm from disclosure can be presumed. Instead, the head of an institution must demonstrate a “nexus between the requested disclosure and a reasonable expectation of probable harm” (at para 35, citing Canadian Association of Elizabeth Fry Societies v. Canada). Exceptions to access rights must be given a narrow interpretation, and the burden of demonstrating that a refusal to disclose is justifiable lies with the head of the government institution. Justice Go also noted that “the Privacy Act does not operate “so as to limit access to information to which an individual might be entitled as a result of other legal rules or principles”” (at para 42) such as, in this case, the principles of procedural fairness.

Justice Go found that the RPD erred by not clarifying what ‘personal information’ the Minister sought to protect; and by not assessing the basis for the Minister’s 22 arguments. She also noted that the RPD had accepted the Minister’s bald assertions that the CBSA did not rely on Clearview AI. Even if the company had ceased offering its services in Canada by July 6, 2020, there was no evidence regarding the date on which the photo comparisons had been made. Justice Go noted that the RPD failed to consider submissions by the applicants regarding findings by the privacy commissioners of Canada, BC, Alberta and Quebec regarding Clearview AI and its activities, as well as on the “danger of relying on facial recognition software” (at para 46).

The Minister argued that even if its s. 22 arguments were misguided, it could still rely upon evidentiary privileges to protect the details of its investigation. Justice Go noted that this was irrelevant in assessing the reasonableness of the RPD’s decision, since such arguments had not been made before or considered by the RPD. She also observed that when parties seek to exempt information from disclosure in a hearing, they are often required at least to provide it to the decision-maker to assess. In this case the RPD did not ask for or assess information on how the investigation had been conducted before deciding that information about it should not be disclosed. She noted that: “The RPD’s swift acceptance of the Minister’s exemption request, in the absence of a cogent explanation for why the information is protected from disclosure, appears to be a departure from its general practice” (at para 55).

Justice Go also observed that information about how the photo comparisons were made could well have been relevant to the issues to be determined by the RPD. If the comparisons were generated through use of FRT – whether it was using Clearview AI or the services of another company – “it may call into question the reliability of the Kenyan students’ photos as representing the Applicants, two women of colour who are more likely to be misidentified by facial recognition software than their white cohorts as noted by the studies submitted by the Applicants” (at para 56). No matter how the comparisons were made – whether by a person or by FRT technology – some evidence should have been provided to explain the technique. Justice Go found it unreasonable for the RPD to conclude that the evidence was reliable simply based upon the Minister’s assertions.

Justice Go also found that the RPD’s conclusion that the applicants were, in fact, the two Kenyan women, was unreasonable. Among other things, she found that the decision “failed to provide adequate reasons for the RPD’s conclusion that the two Applicants and the two Kenyan students were the same persons based on the photo comparisons” (at para 69). She noted that although the RPD referenced ‘great similarities’ between the women in the two sets of photographs, there were also some marked dissimilarities which were not addressed. There simply was no adequate explanation as to how the conclusion was reached that the applicants were the Kenyan students.

The decision of the RPD was quashed and remitted to be reconsidered by a differently constituted panel of the RPD.

Ultimately, Justice Go sends a clear message that the Minister cannot simply advance photo comparison evidence without providing an explanation for how that evidence was derived. At the very least, then, there is an obligation to indicate whether an AI technology was used in the decision-making process. Even if there is some legal basis for shielding the details of the Minister’s methods of investigation, there may still need to be some disclosure to the decision-maker regarding the methods used. Justice Go’s decision is also a rebuke of the RPD which accepted the Minister’s evidence on faith and asked no questions about its methodology or probity. In her decision, Justice Go take serious note of concerns about accuracy and bias in the use of FRT, particularly with racialized individuals, and it is clear that these concerns heighten the need for transparency. The decision is important for setting some basic standards to meet when it comes to reviewing evidence that may have been derived using AI. It is also a sobering reminder that those checks and balances failed at first instance – and in a high stakes context.

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