Gonzales v. Uber Techs., Inc.

305 F. Supp. 3d 1078
CourtDistrict Court, N.D. California
DecidedApril 18, 2018
DocketCase No.17–cv–02264–JSC
StatusPublished
Cited by7 cases

This text of 305 F. Supp. 3d 1078 (Gonzales v. Uber Techs., Inc.) is published on Counsel Stack Legal Research, covering District Court, N.D. California primary law. Counsel Stack provides free access to over 12 million legal documents including statutes, case law, regulations, and constitutions.

Bluebook
Gonzales v. Uber Techs., Inc., 305 F. Supp. 3d 1078 (N.D. Cal. 2018).

Opinion

JACQUELINE SCOTT CORLEY, United States Magistrate Judge

Plaintiff Michael Gonzales brings this action on his own behalf and as a putative class action for Lyft drivers whose electronic communications and whereabouts were allegedly intercepted, accessed, monitored, and/or transmitted by Defendants Uber Technologies, Inc., Uber USA LLC, and Raiser-CA (together, "Uber"). Now pending before the Court is Defendants' motion to dismiss Plaintiff's First Amended Complaint ("FAC"). (Dkt. No. 38.) Having carefully reviewed the parties' briefing and having had the benefit of oral argument on January 11, 2018, the Court GRANTS Defendants' motion with leave to amend.

FIRST AMENDED COMPLAINT ALLEGATIONS

A. The Lyft App

"Lyft provides technology that operates similar to a taxi company's dispatch system." (Dkt. No. 34 ¶ 3.) "A rider requests a ride using a software application on his or her phone (the 'Lyft App')." (Id. ) After a rider logs on to the Lyft App, the App sends a Hypertext Transfer Protocol ("HTTP") request to Lyft's servers. (Id. ¶ 65.) The HTTP request contains the passenger's Lyft ID and GPS coordinates. (Id. ¶ 66.) Lyft's servers respond to the Lyft App's request with a list of nearby drivers who are logged in and who have affirmatively indicated they are available for work; the list includes the drivers' Lyft IDs and GPS coordinates. (Id. ¶ 67.) The list is transmitted to riders through Lyft's servers. (Id. ) "The locations of nearby Lyft drivers are displayed to the rider as dots on a map, along with the estimated price and wait time for arrival once the ride request is submitted." (Id. at ¶ 3.)

"Drivers also use the Lyft App." (Id. ¶ 4.) "When a driver is ready to accept work, the driver swipes a switch on the Lyft App, directing the Lyft App to continuously transmit the driver's geolocation data and his or her willingness to accept work to servers maintained by Lyft." (Id. ) Lyft drivers used the Lyft App to communicate with Lyft servers by transmitting and receiving "packets" of information. (Id. ¶ 55.) "A packet is analogous to a physical letter mailed from one address to the other, and the protocol used to transmit the packet is analogous to the physical envelope that holds the letter." (Id. ) "While traditional envelopes use physical postal addresses, packets use computer Internet Protocol (IP) addresses." (Id. ¶ 70.) The digital letter transmitted from the driver to Lyft's servers in response to a rider's HTTP request includes (1) the driver's *1083unique identifier, (2) the driver's precise geolocation data, (3) the driver's affirmation that the driver is available to provide rides for Lyft users, and (4) an estimated price for the rider's requested ride. (Id. ¶ 72.) Lyft, acting as the driver's agent, forwards a driver's geolocation and willingness to drive to those requesting a ride. (Id. ¶ 4.)

B. Uber's Hell Spyware

Uber offers technology that competes with the Lyft App and operates in the same geographic regions as Lyft. (Id. ¶¶ 5, 6.) Some drivers perform transport services through the two platforms simultaneously. (Id. at ¶ 6.) Lyft's and Uber's systems store the location of every driver, whether on duty or off duty, every few seconds. (Id. ¶¶ 87, 88.) "[N]either Uber nor Lyft ever delete the geolocation data they collect from drivers, at least in part because they consider it valuable to their respective businesses." (Id. ¶ 90.)

Starting in 2014 or earlier and continuing into 2016, Uber secretly used 'Hell spyware' to access servers and smartphones owned and operated by Plaintiff, Class Members, and Lyft. (Id. ¶ 52.) The "spyware extracted information from Lyft by posing as Lyft customers in search of rides." (Id. ¶ 7.) These fake Lyft riders sent forged requests to Lyft's servers. (Id. ) When Lyft's servers received "a request from a forged rider account, they believed that the ride requests were coming from actual Lyft riders, not the Hell spyware." (Id. ¶ 77.) As a result, Lyft's servers transmitted a response to Uber's fake Lyft requesters containing the IDs, on duty status, pricing, and exact locations of nearby Lyft drivers. (Id. ) "The data transmitted was provided by Lyft drivers and was only intended to be delivered to actual nearby Lyft riders." (Id. )

Uber used the fraudulently received geolocation data and driver identifiers "to create grid-like detection nets over cities including San Francisco, Los Angeles, and New York." (Id. ¶ 80.) For instance, a forged rider account would transmit a request indicating that the rider was at the Philip Burton Federal Building with specific GPS coordinates. (Id. ) In response, Lyft's servers "would transmit back information for all nearby Lyft drivers." (Id. ) The Hell spyware would simultaneously also send another set of requests indicating that a different fake Lyft rider was a few blocks north on O'Farrell Street with specific geolocation data. (Id. ) This process was repeated with a large number of fake Lyft accounts, "allowing Uber to obtain complete geographic coverage of entire metropolitan areas, and the exact locations of all Lyft drivers and other information." (Id. ) "Uber repeated this process millions of times using the Hell spyware from 2014 through 2016." (Id. ¶ 8.)

Uber used the data collected in conjunction with other databases "to learn personal details about Lyft drivers including, but not limited to, the drivers' full names, their home addresses, when and where they typically work each day and for how many hours, and where they take breaks." (Id. ¶ 83.) "Uber was able to use this data to determine the identities of the drivers' rider customers." (Id. )

"Uber combined the data harvested by Hell [spyware] with Uber's internal records, including historical location data, to identify Lyft drivers who also worked for Uber." (Id. ¶ 9.) "Uber used the information gleaned from Hell to direct more frequent and more profitable trips to Uber drivers who also used the Lyft App." (Id. ¶ 101.) "By inundating these drivers [with] Uber rides, Uber was able to discourage drivers from accepting work on the Lyft platform, reducing the effective supply of available Lyft drivers." (Id. ¶ 101.) "With the supply of Lyft drivers reduced, Lyft *1084customers faced longer wait times." (Id. ¶ 102.) As a result, Lyft riders would cancel the ride requested with Lyft and request a new ride from Uber, and Lyft drivers experienced decreased earnings. (Id. ¶¶ 9, 102.) "Over time, this would reduce the effectiveness of the Lyft App, thus harming drivers such as Plaintiff and absent Class Members." (Id. ¶ 102.)

PROCEDURAL HISTORY

Plaintiff filed an initial complaint seeking injunctive relief and damages based on four claims: (1) Federal Wiretap Act as amended by the Electronic Communications Privacy Act (the "ECPA"), (2) the California Invasion of Privacy Act ("CIPA"), (3) the California Unfair Competition Law (the "UCL"), and (4) common law invasion of privacy. (Dkt. No. 1.) Defendants moved to dismiss all four claims. (Dkt. No. 17.) The Court granted Defendants' motion with leave to amend. (Dkt. Nos. 27.)

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305 F. Supp. 3d 1078, Counsel Stack Legal Research, https://law.counselstack.com/opinion/gonzales-v-uber-techs-inc-cand-2018.