How the price of things became the highest price that you are willing to pay
Algorithmic pricing gives corporations an unfair advantage over consumers and gig sector workers. New legislation is urgently needed.
On June 10, the Competition Bureau released a discussion paper on algorithmic pricing. The paper was the first official acknowledgment by the federal government that Canadian consumers and gig workers have a problem - a problem that is growing bigger by the day and demands a forceful government response.
Algorithmic pricing refers to the use of automated software—often powered by artificial intelligence—to set prices for goods or services based on real-time data, consumer behavior, and market conditions
Algorithmic pricing was pioneered in the hotel and airline industries, where firms constantly strive to match available capacity to consumer demand, at the highest possible price. It is now commonplace in many other industries, from rental apartments to supermarkets.
This technology can even set individualized prices, based on personal data (generally from past purchases) that reveals what each consumer is willing to pay. Take this description of a technology that Kroger, a giant U.S. food chain, is testing:
Kroger’s ESL device, called Enhanced Display for Grocery Environment (EDGE) Shelf, also threatens consumer privacy. In partnership with Microsoft, Kroger plans to place cameras on its EDGE Shelf displays and use facial recognition to determine information about its shoppers, including gender and age, to push personalized offers and advertisements.
It gets worse. Platform businesses like Uber apply this strategy in two directions at once. Uber’s passenger pricing and driver compensation are governed by sophisticated algorithmic pricing systems that dynamically adjust based on real-time data and behavioral patterns. Here's how it works on both ends.
Uber drivers can’t predict what they’ll earn for any given trip because Uber doesn’t use a fixed formula based on the time it takes to get from one location to the next as with taxis. Instead, it customizes pay based on driver behavior history. For example, if a driver has accepted low-paying jobs in the past, the algorithm may interpret this as a sign of desperation and offer similarly low compensation going forward. Similarly, if a driver has a history of declining short rides, the driver may receive fewer or less lucrative offers to teach him a lesson.
Uber passenger fares are also algorithmically determined and vary widely for the same distance due to:
Surge pricing: Prices rise when demand outpaces supply—like during rush hour, bad weather, transit shutdowns or major events;
Personal data: Uber may use past passenger behavior, demographics, and even social media signals, to estimate a rider’s “willingness to pay”; and
Trip urgency: If the algorithm detects urgency (e.g., repeated app refreshes or proximity to transit hubs), it may raise the price for the passenger.
Whether it’s supermarkets or Uber, with the rise of pricing algorithms, consumers can no longer have confidence about the “going price” for any product or service: it all depends on what the algorithms dictate at any particular minute of any particular day. And as is the case with Uber drivers, it is not just consumers that end up being exploited under the tyranny of the algorithm.
In looking for solutions to this problem, Canada’s Competition Act would seem to be the logical place to look. After all, it was the Competition Bureau who produced the June discussion paper and it is the Competition Act that has long been Canada’s foremost legal vehicle for preventing price collusion between dominant firms.
Unfortunately, smoke filled rooms are no longer the place where price collusion between firms takes place with flesh and blood humans making the decisions. Now, algorithms gathering information from a variety of sources are setting a price based on the maximum an individual consumer is willing to pay. While the Competition Act was substantially strengthened in 2023 and 2024, it still may not contain the tools necessary to clamp down on algorithmic pricing.
In its submission to the the Competition Bureau’s consultation, the Canadian Anti- Monopoly Project (CAMP) suggests that additional reforms to the Competition Act should build on provisions contained in the U.S. Preventing Algorithmic Collusion Act (PACA).
The PACA is a proposed piece of federal legislation introduced by Democratic Senator Amy Klobuchar and others in 2024, that aims to prohibit the use of pricing algorithms that rely on competitor data to facilitate anticompetitive practices, such as price fixing and price gouging. The bill seeks to update U.S. antitrust laws to address the complexities of modern algorithmic pricing by creating new enforcement tools, increasing transparency, and empowering anti-trust enforcement agencies like the Federal Trade Commission and the Department of Justice to hold companies accountable for their algorithmic pricing strategies.
The core of the U.S. bill is a provision barring the use of pricing algorithms that are trained on nonpublic data, which can enable companies to coordinate on prices, leading to higher costs for consumers.
The law also seeks to adapt existing American antitrust frameworks to the new technological landscape, ensuring that companies cannot use algorithms to engage in practices that would be illegal if performed by humans.
Finally, PACA aims to make the operation of pricing algorithms more transparent, allowing for better oversight and enforcement.
Going beyond reforms to the Competition Act, the CAMP brief also suggests that the provinces can play a parallel role to federal competition law enforcement in limiting or banning the use of these pricing algorithms in markets where Canadians face limited choice and that are under provincial jurisdiction. For example, algorithmic pricing is playing an increasing role in the rental housing markets, an area where the provinces have primary responsibility.
Algorithmic pricing is only one digital area where there is a need for a a clearer legal framework to prevent online harm in its many forms. Whether the issue is algorithmic pricing, data privacy, AI, online harms to children and youth or cyber security, there is an urgent need for federal legislative action. Most of these issues were dealt with in legislation that died on the order paper in January when Parliament was prorogued, so it is not as if the Liberal government and the bureaucrats who actually draft legislation, haven’t already given these issues some thought.
Canada now has its first ever Minister solely in charge of digital affairs, Evan Solomon. The Fall session of Parliament is scheduled to begin on September 15 and it is time for Minister Solomon to get to work and table some badly needed legislation.