JetBlue has been hit with a proposed class action lawsuit alleging that the airline uses customers' personal data to dynamically set ticket prices, a practice known as surveillance pricing. The legal action follows a social media exchange where JetBlue's response to a passenger's complaint about a price increase sparked concerns over privacy violations.
Lawsuit Details
Filed late Wednesday in Brooklyn federal court, the complaint claims JetBlue conceals its use of tracking technologies to adjust fares in real time and shares data with third-party vendors to determine when to raise prices. Plaintiff Andrew Phillips argues that consumers should not have to sacrifice their privacy to participate in what he calls a digital rat race for airline tickets, which should cost the same for passengers in similar seats.
JetBlue declined to comment on the lawsuit on Thursday but reiterated that it does not use personal data or artificial intelligence to set ticket prices. The airline had previously stated that fares can change at any moment based on seat purchases or inventory adjustments.
Social Media Exchange
The controversy began on April 18 when a passenger on X praised JetBlue but noted a $230 increase on a ticket after one day, saying they were trying to make it to a funeral. JetBlue's response suggested clearing the cache and cookies or booking with an incognito window, adding an apology for the loss. The airline later acknowledged the response was incorrect.
Congressional Scrutiny
Following the incident, two Democratic lawmakers in Congress requested detailed answers from JetBlue about its pricing practices, including whether personal data informs fares. In November, a group of two dozen lawmakers had similarly questioned Delta Air Lines about its use of generative AI in pricing, which Delta denied.
Legal Claims
The lawsuit seeks unspecified damages for alleged violations of federal anti-wiretapping law and New York state consumer protection statutes. Surveillance pricing, as described in the complaint, enables companies to set individual prices based on browsing histories, locations, and other personal data.
