Teresa Scassa - Blog

The Federal Court has released a decision in a case that raises important issues about transparency and accountability under Canada’s private sector privacy legislation.

The Personal Information Protection and Electronic Documents Act (PIPEDA) governs privacy with respect to the collection, use and disclosure of personal information by private sector organizations. Under PIPEDA, individuals have the right to access their personal information in the hands of private sector organizations. The right of access allows individuals to see what information organizations have collected about them. It is accompanied by a right to have incorrect information rectified. In our datified society, organizations make more and more decisions about individuals based upon often complex profiles built with personal information from a broad range of sources. The right of access allows individuals to see whether organizations have exceeded the limits of the law in collecting and retaining personal information; it also allows them the opportunity to correct errors that might adversely impact decision-making about them. Unfortunately, our datified society also makes organizations much more likely to insist that the data and algorithms used to make decisions or generate profiles, along with the profiles themselves, are all confidential business information and thus exempt from the right of access. This is precisely what is at issue in Bertucci v. Royal Bank of Canada.

The dispute in this case arose after the Bertuccis – a father and son who had banked with RBC for 35 and 20 years respectively, and who also held business accounts with the bank – were told by RBC that the bank would be closing their accounts. The reason given for the account closure was that the bank was no longer comfortable doing business with them. Shortly after this, the Bertuccis made a request, consistent with their right of access under PIPEDA, to be provided with all of their personal information in the hands of RBC, including information as to why their bank accounts were closed. RBC promptly denied the request, stating that it had already provided its reason for closing the accounts and asserting that it had a right under its customer contracts to unilaterally close accounts without notice. It also indicated that it had received no personal information from third parties about the Bertuccis and that all of the information that they sought was confidential commercial information.

RBC relied upon paragraph 9(3)(b) of PIPEDA, which essentially allows an organization to refuse to provide access to personal information where “to do so would reveal confidential commercial information”. On receiving RBC’s refusal to provide access, the Bertuccis complained to the Office of the Privacy Commissioner. The OPC investigated the complaint and ultimately sided with RBC, finding that it was justified in withholding the information. In reaching this conclusion, the OPCC relied in part on an earlier Finding of the Privacy Commissioner which I have previously critiqued, precisely because of its potential implications for transparency and accountability in the evolving big data context.

In reaching it conclusion on the application of paragraph 9(3)(b) of PIPEDA, the OPC apparently accepted that the information at issue was confidential business information, noting that it was “treated as confidential by RBC, including information about the bank’s internal methods for assessing business-related risks.” (At para 10)

After having their complaint declared unfounded by the OPC, the applicants took the issue to the Federal Court. Justice Martineau framed the key question before the court in these terms: “Can RBC refuse to provide access to undisclosed personal information it has collected about the applicants on the grounds that its disclosure in this case would reveal confidential commercial information” (at para 16)

RBC’s position was that it was not required to justify why it might close an account. It argued that if it is forced to disclose personal information about a decision to close an account, then it is effectively stripped of its prerogative to not provide reasons. It also argued that any information that it relied upon in its risk assessment process would constitute confidential business information. This would be so even if the information were publicly available (as in the case of a newspaper article about the account holder). The fact that the newspaper article was relied upon in decision-making would be what constituted confidential information – providing access to that article would de facto disclose that information.

The argument put forward by RBC is similar to the one accepted by the OPC in its earlier (2002) decision which was relied upon by the bank and which I have previously criticized here. It is an argument that, if accepted, would bode very ill for the right of access to personal information in our big data environment. Information may be compiled from all manner of sources and used to create profiles that are relied upon in decision-making. To simply accept that information used in this way is confidential business information because it might reveal how the company reaches decisions slams shut the door on the right of access and renders corporate decision-making about individuals, based upon the vast stores of collected personal information, essentially non-transparent.

The Bertuccis argued that PIPEDA – which the courts have previously found to have a quasi-constitutional status in protecting individual privacy – makes the right of access to one’s personal information the rule. An exception to this rule would have to be construed narrowly. The applicants wanted to know what information led to the closure of their accounts and sought as well to exercise their right to have this information corrected if it was inaccurate. They were concerned that the maintenance on file of inaccurate information by RBC might continue to haunt them in the future. They also argued that RBC’s approach created a two-tiered system for access to personal information. Information that could be accessed by customers whose accounts were not terminated would suddenly become confidential information once those accounts were closed, simply because it was used in making that decision. They argued that the bank should not be allowed to use exceptions to the access requirement to shelter itself from embarrassment at having been found to have relied upon faulty or inadequate information.

Given how readily the OPC – the guardian of Canadians’ personal information in the hands of private sector organizations – accepted RBC’s characterization of this information as confidential, Justice Martineau’s decision is encouraging. He largely agreed with the position of the applicants, finding that the exceptions to the right to access to one’s personal information must be construed narrowly. Significantly, Justice Martineau found that courts cannot simply defer to a bank’s assertion that certain information is confidential commercial information. He placed an onus on RBC to justify why each withheld document was considered confidential. He noted that in some circumstances it will be possible to redact portions of reports, documents or data that are confidential while still providing access to the remainder of the information. In this case, Justice Martineau was not satisfied that the withheld information met the standard for confidential commercial information, nor was he convinced that some of it could not have been provided in redacted form.

Reviewing the documents at issue, Justice Martineau began by finding that a list of the documents relied upon by the bank in reaching its decision was not confidential information, subject to certain redactions. He noted as well that much of what was being withheld by the bank was “raw data”. He distinguished the raw data from the credit scoring model that was found to be confidential information in the 2002 OPC Finding mentioned above. He noted as well that the raw data was not confidential information and had not, when it was created, been treated as confidential information by the bank. He also noted that the standard for withholding information on an access request was very high.

Justice Martineau gave RBC 45 days to provide the applicants with all but a few of the documents which the court agreed could be withheld as confidential commercial information. Although the applicants had sought compensatory and punitive damages, he found that it was not an appropriate case in which to award damages.

Given the importance of this decision in the much broader big data and business information context, RBC is likely to appeal it to the Federal Court of Appeal. If so, it will certainly be an important case to watch. The issues it raises are crucial to the future of transparency and accountability of corporations with respect to their use of personal information. In light of the unwillingness of the OPC to stand up to the bank both in this case and in earlier cases regarding assertions of confidential commercial information, Justice Martineau’s approach is encouraging. There is a great deal at stake here, and this case will be well worth watching if it is appealed.

I was at the United Nations last week for an Expert Group Meeting on Moving from commitments to results in building effective, accountable and inclusive institutions at all levels. On February 18, 2016, I gave a presentation on balancing privacy with transparency in open government. This is a challenging issue, and one that is made even more so by digitization, information communication technologies and the big data environment.

Openness access to government information and data serve the goals of greater transparency and greater public trust in government. They are essential in fighting corruption, but they are also important in holding governments to account for their decision-making and for their spending of public funds. However, transparency must also be balanced against other considerations, including privacy. Privacy is a human right, and it protects the dignity, autonomy and integrity of individuals. Beyond this, however, the protection of privacy of personal information in the hands of governments also enhances public trust in governments and can contribute to citizen engagement.

How, then, does one balance privacy with transparency when it comes to information in the hands of government? There are no easy answers. My slides from my presentation can be found here, and these slides contain some links to some other publicly available work on this topic.

The rise of big data analytics, combined with a movement at all levels of government in Canada towards open data and the proactive disclosure of government information have created a context in which privacy interests are increasingly likely to conflict with the goals of transparency and accountability. In some cases these conflicts may be small and easily reconciled, but in other cases they may be more substantial. In addition, some means of reconciling the conflict must be found; where privacy and transparency conflict, for example, which value should prevail and under what conditions?

Conflicts between transparency and privacy have been seen recently in, for example, concerns expressed over the amount of personal information that might be found in court and tribunal decisions that are published online. Sunshine lists – lists of salaries of public employees that are over a certain amount – also raise issues. Provinces that publish such lists have tended to do so using file formats that do not lend themselves to easy digital manipulation. But of course these modest technological barriers are routinely overcome, and individual name and salary information is absorbed into the big data universe for purposes quite distinct from meeting a government’s transparency objectives. Open municipal data files may include information about specific individuals: for example, a database of all home renovation permit applications would have privacy implications for those individuals who applied for such permits. Even with names were redacted, it is easy enough to identify the owners of any homes for which renovation permits were obtained. In some cases, the level of connection may be less direct. For example, a public restaurant inspection record that cited kitchen staff at a small local restaurant for failure to wash their hands on a specific inspection date might indirectly reveal the identity of the persons who did not wash their hands, particularly if the staff of the restaurant is quite small. And, of course, in the big data context, even anonymized data, or data that is not personal information on its face, can be matched with other available data to identify specific individuals.

The point is not that the disclosure of such information must be avoided at all costs – rather, the issue is how to determine where to draw the line between privacy and transparency, and what steps might be taken to protect privacy while still ensuring transparency. No new legislative framework has been created to specifically guide the move towards open government in Canada, notwithstanding the fact that government data is fuel for the engines of big data.

In a paper that has just been published by the Alberta Law Review, my co-author Amy Conroy and I explore these issues, using a recent Supreme Court of Canada decision as a departure point for our analysis. Although the Court’s decision in Ministry of Community Safety and Correctional Services v Information and Privacy Commissioner (Ontario) (Ministry of Community Safety) does not specifically address either open data or proactive disclosure, the case nevertheless offers important insights into the gaps in both legislation and case law in this area.

In our paper we consider the challenges inherent in the release of government data and information either through pro-active disclosure or as open data. A key factor in striking the balance between transparency and privacy is the definition of personal information – information that is not personal information has no privacy implications. Another factor is, of course, the meaning given to the concept of transparency. Our paper considers how courts and adjudicators understand transparency in the face of competing claims to privacy. We challenge the simple equation of the release of information with transparency and argue that the coincidence of open government with big data requires new approaches that are informed by the developing relationship between privacy and transparency.

“Promoting Transparency While Protecting Privacy in Open Government in Canada” by Amy Conroy and Teresa Scassa is published in (2015) 53:1 Alberta Law Review 175-206. A pre-print version is available here.

A long past and largely forgotten ‘finding’* from the Office of the Privacy Commissioner of Canada offers important insights into the challenges that big data and big data analytics will pose for the protection of Canadians’ privacy and consumer rights.

13 years ago, former Privacy Commissioner George Radwanski issued his findings on a complaint that had been brought against a bank. The complainant had alleged that the bank had wrongfully denied her access to her personal information. The requirement to provide access is found in the Personal Information Protection and Electronic Documents Act (PIPEDA). The right of access also comes with a right to demand the correction of any errors in the personal information in the hands of the organization. This right is fundamentally important, not just to privacy. Without access to the personal information being used to inform decision-making, consumers have very little recourse of any kind against adverse or flawed decision-making.

The complainant in this case had applied for and been issued a credit card by the bank. What she sought was access to the credit score that had been used to determine her entitlement to the card. The bank had relied upon two credit scores in reaching its decision. The first was the type produced by a credit reporting agency – in this case, Equifax. The second was an internal score generated by the bank using its own data and algorithm. The bank was prepared to release the former to the complainant, but refused to give her access to the latter. The essence of the complaint, therefore, was whether the bank had breached its obligations under PIPEDA to give her access to the personal information it held about her.

The Privacy Commissioner’s views on the interpretation and application of the statute in this case are worth revisiting 13 years later as big data analytics now fuel so much decision-making regarding consumers and their entitlement to or eligibility for a broad range of products and services. Credit reporting agencies are heavily regulated to ensure that decisions about credit-worthiness are made fairly and equitably, and to ensure that individuals have clear rights to access and to correct information in their files. For example, credit reporting legislation may limit the types of information and the data sources that may be used by credit reporting agencies in arriving at their credit scores. But big data analytics are now increasingly relied upon by all manner of organizations that are not regulated in the same way as credit-reporting agencies. These analytics are used to make decisions of similar importance to consumers – including decisions about credit-worthiness. There are few limits on the data that is used to fuel these analytics, nor is there much transparency in the process.

In this case, the bank justified its refusal to disclose its internal credit score on two main grounds. First, it argued that this information was not “personal information” within the meaning of PIPEDA because it was ‘created’ internally and not collected from the consumer or any other sources. The bank argued that this meant that it did not have to provide access, and that in any event, the right of access was linked to the right to request correction. The nature of the information – which was generated based upon a proprietary algorithm – was such that was not “facts” that could be open to correction.

The argument that generated information is not personal information is a dangerous one, as it could lead to a total failure of accountability under data protection laws. The Commissioner rejected this argument. In his view, it did not matter whether the information was generated or collected; nor did it matter whether it was subject to correction or not. The information was personal information because it related to the individual. He noted that “opinions” about an individual were still considered to be personal information, even though they are not subject to correction. This view of ‘opinions’ is consistent with subsequent findings and decisions under PIPEDA and comparable Canadian data protection laws. Thus, in the view of the Commissioner, the bank’s internally generated credit score was the complainant’s personal information and was subject to PIPEDA.

The bank’s second argument was more successful, and is problematic for consumers. The bank argued that releasing the credit score to the complainant would reveal confidential commercial information. Under s. 9(3)(b) of PIPEDA, an organization is not required to release personal information in such circumstances. The bank was not arguing so much that the complainant’s score itself was confidential commercial information; rather, what was confidential were the algorithms used to arrive at the score. The bank argued that these algorithms could be reverse-engineered from a relatively small sample of credit scores. Thus, a finding that such credit scores must be released to individuals would leave the bank open to the hypothetical situation where a rival might organize or pay 20 or so individuals to seek access to their internally generated credit scores in the hands of the bank, and that set of scores could then be used to arrive at the confidential algorithms. The Commissioner referred this issue to an expert on algorithms and concluded that “although an exact determination of a credit-scoring model was difficult and highly unlikely, access to customized credit scores would definitely make it easier to approximate a bank’s model.”

The Commissioner noted that under s. 9(3)(b) there has to be some level of certainty that the disclosure of personal information will reveal confidential commercial information before disclosure can be refused. In this case, the Commissioner indicated that he had “some difficulty believing that either competitors or rings of algorithmically expert fraud artists would go to the lengths involved.” He went on to say that “[t]he spectre of the banks falling under systematic assault from teams of loan-hungry mathematicians is simply not one I find particularly persuasive.” Notwithstanding this, he ruled in favour of the bank. He noted that other banks shared the same view as the respondent bank, and that competition in the banking industry was high. Since he had found it was technically possible to reverse-engineer the algorithm, he was of the view that he had to find that the release of the credit score would reveal confidential commercial information. He was satisfied with the evidence the bank supplied to demonstrate how closely guarded the credit-scoring algorithm was. He noted that in the UK and Australia, relatively new guidelines required organizations to provide only general information regarding why credit was denied.

The lack of transparency of algorithms used in the big data environment becomes increasingly problematic the more such algorithms are used. Big data analytics can be used to determine credit-worthiness – and such these determinations are made not just by banks but by all manner of companies that extend consumer credit through loans, don’t-pay-for-a-year deals, purchase-by-installment, store credit cards, and so on. They can also be used to determine who is entitled to special offers or promotions, for price discrimination (where some customers are offered better prices for the same products or services), and in a wide range of other contexts. Analytics may also be used by prospective employers, landlords or others whose decisions may have important impacts on people’s lives. Without algorithmic transparency, it might be impossible to know whether the assumptions, weightings or scoring factors are biased, influenced by sexism or racism (or other discriminatory considerations), or simply flawed.

There may be some comfort to be had that in this case the Commissioner was allowed to have access to the scoring model used. He stated that he found it innocuous – although it is not clear what kind of scrutiny he gave it. After all, his mandate extended only to decisions relating to the management of personal information, and did not extend to issues of discrimination. It is also worth noting that the Commissioner seems to suggest that each case must be decided on its own facts, and that what the complainant stood to gain and the respondent stood to lose were relevant considerations. In this case, the complainant had not been denied credit, so in the Commissioner’s view there was little benefit to her in the release of the information to be weighed against the potential harm to the bank. Nevertheless, the decision raises a red flag around transparency in the big data context.

In the next week or so I will be posting a ‘Back to the Future II’ account of another, not quite so old, PIPEDA finding that is also significant in the big data era. Disturbingly, this decision eats away at Commissioner Radwanski’s conclusion on the issue of “personal information” as it relates to generated or inferred information about individuals. Stay tuned!