Is Google's personalized pricing actually surveillance pricing?

Cory Doctorow argues that Google's actual AI monetization plan — not chatbots, but "personalized pricing" sold to partners including "Walmart, Visa, Mastercard, Shopify, Gap, Kroger, Macy's, Stripe, Home Depot, Lowe's, American Express, etc" — is surveillance pricing under a polite name: "a company spies on you in order to figure out how much they can get away with charging you (or how little they can get away with paying you)." He calls it "a weird form of cod-Marxism, whose tenet is 'From each according to their desperation; to each according to their vulnerability.'"

Doctorow walks through the industry's own justification and then its own rebuttal. Surveillance-pricing advocates claim the practice is efficient because it lets sellers offer targeted discounts — his example is an airline reading signals that a traveler won't pay $200 for a last-minute seat but will pay $100, and pricing accordingly. He dismisses this as "nonsense": airlines "jack up the price of a last-minute journey to farcical heights" rather than discount it. Google states its surveillance-pricing facility will only generate discounts, never premiums, but Doctorow cites Stoller's point that there is "a well-developed playbook for making premiums look like discounts," illustrated by the MRI billing example: an $8,000 list price, a $6,000 insurer "discount," and a $1,970 actual payment, leaving the patient a $30 co-pay. In Stoller's framing, "the $8000 is a fake number, and so is the $6000 — the only real price is the $30 you're paying." Doctorow extends this to "department stores who routinely mark everything as 80% off" and pharmacy benefit managers, naming it a general ruse that personalized pricing inherits rather than invents.

This bears directly on Can a seller infer what a buyer really wants to pay?, which measures the mechanism Doctorow describes rhetorically: an experiment found a seller-side inference agent recovering a buyer's willingness to pay from dialogue alone, with no price ever stated by the buyer. Doctorow's essay supplies the business-model and regulatory framing that experiment's authors leave implicit — personalized pricing isn't a side effect of agentic shopping, it is, on his account, the thing Google is actually trying to sell. It also sits near Can EU consumer law protect AI agents as algorithmic buyers?: that note argues existing consumer-protection law assumes a human buyer and needs redesign for algorithmic consumers, while Doctorow's argument is that the seller side needs no redesign at all to exploit buyer data at scale — Google is building the infrastructure for it now, ahead of any regulatory response.

As a Medium opinion essay quoting Stoller's commentary, this piece establishes an argument and an analogy (the MRI billing ruse), not a measurement of how much personalized pricing actually shifts what any buyer pays under Google's new facility, which has not yet launched broadly. Doctorow does not quantify the "partners'" pricing behavior or Google's take; the claim is a prediction grounded in how surveillance pricing and discount-disguised-as-premium schemes have worked elsewhere. The implication, at the strength this evidence allows, is that scrutiny of Google's "personalized pricing" rollout should treat its discount framing as a claim to be verified against actual price changes, not a fact to be assumed from Google's own description of the facility.