In an era where artificial intelligence is often sold as a tool for efficiency, Cory Doctorow reveals its most sinister application yet: the automation of price gouging. This piece cuts through the marketing noise to expose how "surveillance pricing" transforms personal data into a weapon, allowing corporations to extract every possible cent from the most vulnerable consumers. It is a stark reminder that without intervention, the next frontier of AI isn't innovation—it's exploitation.
The Algorithm of Exploitation
Doctorow argues that the real breakthrough for artificial intelligence isn't in generating art or text, but in its ability to conduct multivariate statistical analysis on a massive scale. He writes, "With 'surveillance pricing,' businesses have finally found something AI can do way, way, way better than people: price gouging." This framing is crucial because it shifts the blame from human malice to systemic design. The technology doesn't need to be explicitly programmed to be racist or predatory; it simply optimizes for profit by identifying who is desperate and charging them the most.
The author illustrates this with a chilling example of how these systems operate without human oversight. "If you're hiring in an industry that practices a lot of tacit racial discrimination, a system like this can figure out on its own that people of color typically accept lower wages... and recommend lowball salary offers, all without you ever typing 'please be racist' into an AI prompt." This observation holds significant weight because it explains how discrimination becomes automated and harder to trace, a dynamic that echoes historical redlining practices where algorithms now replace the biased human loan officer. The system finds the weak spots and weaponizes them.
"You don't have to know why one group of purchasers consistently accept higher prices between 6AM and 8AM — you can just automatically jack up prices on them without knowing or caring that you're gouging parents of young children."
Doctorow points out that this is not theoretical. Ecommerce sites are already charging parents of newborns extra for thermometers ordered at 2 AM. The goal, he explains, is to shift all "consumer surplus"—the difference between what a customer is willing to pay and what they actually pay—to the corporation. He describes this as a form of "cod-Marxism where you are gouged according to your ability (to pay) and charged according to the desperation of your need." Critics might argue that dynamic pricing has always existed in markets like airlines, but the scale and personalization enabled by AI data dossiers represent a qualitative leap that traditional market forces cannot address.
The Political Conundrum
The piece then pivots to the political landscape, highlighting the tension between voter anger and corporate influence. While consumers are increasingly aware of this exploitation, as seen when Delta Airlines faced massive backlash for a failed surveillance pricing rollout, politicians are often paralyzed by donor pressure. Doctorow notes that the standard political response is to "enact legislation that seems to address the problem, but stuff it with so many loopholes that it does nothing." This creates a cycle where officials declare themselves champions of the people while leaving the underlying mechanisms of price gouging intact.
However, there is a glimmer of hope in California with bill AB-2564. Doctorow praises it as a "smart, well-written bill that bans surveillance pricing" because it includes a clear definition and logical carve-outs for legitimate cost differences. The bill defines the practice as "a customized price for a good for a specific consumer or group of consumers based, in whole or in part, on personally identifiable information collected through electronic surveillance." This clarity is essential, as it prevents the vague language that often allows corporations to claim they are offering "discounts" while actually engaging in discrimination.
"The idea that you should have to give up your privacy to get a fair price is just a fancy way of saying that privacy should be the exclusive preserve of people who can afford to pay more."
The Electronic Frontier Foundation (EFF) has stepped in to debunk the objections raised by the San Francisco Chamber of Commerce, which has stalled a local resolution supporting the bill. The Chamber's arguments, which claim the bill would ban common discounts for seniors or loyalty programs, are described by Doctorow as "flaming garbage." The EFF's rebuttal clarifies that the bill explicitly allows for discounts based on broadly defined groups or participation in loyalty programs, exposing the Chamber's claims as disinformation designed to protect corporate profits.
The Human Cost of Data
At its core, Doctorow's argument is about dignity and fairness. He posits that when a company charges one person double what they charge another for the same item, they are essentially devaluing the first person's money. "Companies shouldn't be able to reach into your wallet or your bank account and chop your money in half," he writes. This is a powerful metaphor that translates complex economic concepts into a visceral sense of injustice. The argument is strengthened by the historical context of the Chamber of Commerce, which Doctorow notes has been "pissing in San Franciscans' faces and telling them it was raining since 1850."
The piece also references the broader context of "enshittification," where platforms degrade in quality to extract more value from users. Surveillance pricing is the logical endpoint of this trend. While the technology promises to make markets more "efficient," Doctorow shows that this efficiency is entirely one-sided, benefiting only the seller. The lack of federal privacy law updates since 1988 leaves a gaping hole that these AI systems are rushing to fill.
"With surveillance pricing, politicians face a familiar conundrum: if they do the thing that's popular with voters, they'll enrage donors."
Bottom Line
Cory Doctorow's analysis is a vital intervention in the debate over AI regulation, successfully reframing surveillance pricing not as a market innovation but as a systemic threat to economic justice. The strongest part of the argument is its exposure of how AI automates discrimination without requiring explicit human intent, making it a uniquely difficult problem to solve without strict legislative boundaries. The biggest vulnerability remains the political will to enforce these rules against well-funded corporate interests, but the clarity of the proposed legislation in California offers a concrete roadmap for what effective regulation could look like.