How I Tricked Big Tech’s AI Pricing Algorithms to Save $8,793
Chris the Producer
Surveillance pricing: AI-driven, individualized price differences are already changing what consumers pay
The video documents 'surveillance pricing' — companies using personal data and AI to set individualized maximum prices — and shows concrete tests where identical products or services cost different amounts for different profiles. The presenter cites a public opinion figure ('76% of people think it should be illegal') and explains the mechanism: data brokers collect browser information, location, app activity, past transactions and financial signals; firms then feed those inputs into pricing algorithms (David Dan is named as the person who coined 'surveillance pricing').
A chain of experiments illustrates the effect. Controlled buys found: Target 'Spam' listed $4.99 vs $4.59; an UberX quoted $36.94 vs $52.95 (about a 30% difference); La Quinta Hotel Denver $122 vs $84; Pampers on Instacartan/phone $34.99 vs $28.99. The creator tried to erase identity via a Wyoming LLC (Frank Reynolds, LLC), obtained an EIN and credit card, and used a dedicated 'track phone' and an actor ('comrade') instructed to display the lowest possible purchase intent. That low-intent profile produced mixed results: in one run Uber prices averaged 11% lower for Frank, but creating the corporate identity initially led to paying about 20% more on diapers.
Additional evidence: investigative SF Gate tests reportedly saw hotel prices drop by $500 or $200 when IP/location changed; Kroger profiles are said to be '63 pages long on average'. A focused geographic test used a drone to place Frank's phone inside North Oaks (the wealthiest Minnesota enclave) and found an Uber from inside priced $54.95 versus $75.96 from outside ($21 difference, 28% decrease); DoorDash White Castle order showed $39.47 vs $47.25 (19% decrease). The presenter notes over half of their random tests showed similar prices, but highlights the large divergences as proof the practice exists and is opaque. The conclusion: surveillance pricing creates unfair, hard-to-challenge discrimination and the speaker argues government regulation and state-level bills are needed to protect consumers (bills introduced in roughly 20 states, per the video).
