I think it's important to recognize that de-identification and anonymization techniques live on a spectrum. Anonymization is at the far extreme end. De-identification is something far more simple.
The committee in its earlier deliberations today referenced some cases that go back to the mid-2000s where information was stripped out of a dataset and it was easy to reidentify it. That's exactly the kind of issue we're trying to combat by establishing a higher bar for anonymization.
Anonymization techniques are generally algorithmic in nature. They involve things like differential privacy, or K-anonymization. These are very sophisticated mathematical algorithmic techniques that, of course, because they are algorithmic in nature can over time have their efficacy degraded. As other algorithms are developed, as new mathematical techniques are developed, as computing becomes more powerful vis-à-vis quantum computing, for example, there are opportunities downstream for what was at one point considered anonymous in nature to later, in a matter of years, become much more easy to break.
The reason for including a standard that says “generally accepted best practices” is that it requires an organization to continually review and update.
The whole point of anonymization in the context of the act here is to ensure that truly anonymized data can be used for beneficial things like improving health informatics, health systems and delivery. When it is at risk of reidentification, it means it's then back into the auspices of the act and all the requirements apply.
In practice, the way we would see the Office of the Privacy Commissioner using a generally accepted best practices requirement is if there were a case in which there was a security breach, or the personal information was leaked, they would then be able to point at the act and say the act requires that you anonymize in accordance with generally accepted best practices and we can or cannot find evidence that you have done so, or that you have maintained a modernity or contemporaneously with generally accepted best practices. Maybe you did it eight years or 10 years ago, but then you left the dataset alone and it became breachable.
What this does is it requires a constant evolution of standards that says if you're going to try to maintain this as being an anonymized dataset and the protections that includes, you have to keep updating the standards by which you have applied that anonymization.