Algorithmic Pricing and Digital Sovereignty

The adoption of AI and advanced algorithms has turned pricing into an exact science for firms—one by which consumers are constantly subject to pricing experiments they do not even realize that they are participating in.

Prices for everyday goods can fluctuate between different store locations, according to different weather conditions or even between in-person and online shopping.

Most concerningly, they can also fluctuate according to what a firm knows about you and what they infer you are willing to pay. We prefer to call this type of calibration “surveillance pricing.” No other term better captures the reality of what is happening.

This Committee will hear from stakeholders who will insist that this does not occur, or that it is a form of “low-stakes personalization” that benefits consumers. But surveillance pricing does occur, and ultimately it only benefits firms. The research and the patents prove it, as do the software companies advertising pricing optimization as a service.

According to research by Dr. Lindsay Owens, who recently published a best-selling book on surveillance pricing, Walmart has patented technology that would allow it to scan what a consumer places in their shopping basket, at a physical store, in order to charge different consumers different prices for the same item. Walmart itself provides an example of how this could be applied. If a consumer puts a can of tinned tuna in their shopping basket, that information could then be used to alter the price they see for the mayonnaise a few aisles over. 

What is this if not surveillance?

In fact, it is the perfect example of how surveillance we thought was once confined to the online world, where you can be followed across every move you make, is increasingly entering physical spaces. 

The ability to price discriminate is not new. What is new, is the sheer amount of personal data that is now available for firms to use to set prices, while advancements in AI and ML have supercharged their ability to analyze it at an unprecedented scale

In most cases, surveillance pricing is a black box for consumers. A consumer does not know when they are seeing a different price from others, nor why. And when prices are so volatile, the ability to comparison shop and to budget becomes limited.

Manitoba has taken an important step in addressing surveillance pricing through Bill-49. For even longer, Quebec has had a provision on profiling in its privacy law that would ostensibly apply to the practice.

It is encouraging to see movement on the issue at the federal level, but should it pass, the protections promised by Bill C-36 are unlikely to be in place before 2028. And from what we have heard so far, we are concerned that enough exceptions and loopholes will be made to allow surveillance pricing to continue—simply with a few more boxes for retailers to tick.

While the U.S. is ahead of us in regulating surveillance pricing, many of the bills that have passed or been proposed make broad exceptions for loyalty programs, leaving the door open to massive amounts of surveillance. We must not follow this example.

Agentic commerce will add another layer of obscurity in pricing as shopping is outsourced to AI agents. We have already seen that Google’s AI overview recommends products that have on average 22% higher prices than they do when using regular search.

While we tend to focus on the use of algorithms for pricing consumer goods, we urge the committee to also consider the use of data and algorithms to set rental prices and wages. Otherwise, we risk leaving these equally exploitative practices out of our attempts to regulate.

That is why we need to address surveillance pricing and all related practices at the root of the issue—the invasive collection of personal information or of behavioural data to rig markets against us. Rental and labour ones included. Simply requiring firms to tell us in the fine print when they are engaging in such practices is not enough. We need to say point-blank that this is not an appropriate use of our personal information.

At the Canadian Shield Institute, we are fond of saying that governance is the foundation of digital sovereignty. If we are unwilling to simply accept data-driven business practices—such as algorithmic pricing—that have been pioneered by global technology giants, then we must be prepared to assert governance over how Canadians experience the digital realm.