FTC takes action against Uber for deceptive billing and cancellation practices

Original Article ↗ Hacker News Discussion ↗

The FTC’s case against Uber over deceptive billing and obstructive cancellation flows is prompting broader scrutiny of how ride‑hailing and food‑delivery apps use “dark patterns” to lock in subscriptions, inflate prices, and avoid refunds. Commenters describe confusing Uber One sign‑ups, multi‑step or time‑restricted cancellation, opaque fees and dynamic pricing that penalize business accounts or users with credits, and refunds routed into app‑only balances. Many call for stronger consumer‑protection rules—such as requiring cancellations to be as easy as sign‑ups—while others respond by using virtual cards, chargebacks, or abandoning the platforms altogether.

Subscription & Cancellation Dark Patterns

  • Many report being tricked into Uber One during checkout (e.g., a trial screen visually identical to the “place order” screen, inserted mid-flow).
  • Cancellation is often described as convoluted: multiple screens, hidden options, and sometimes being blocked within 24–48 hours of renewal.
  • Some users say their own cancellation was “only” ~9–10 screens and not as bad as the FTC’s “23 screens,” suggesting variation by A/B test, location, or time.
  • Comparisons are made to other industries (gyms, Equifax, OnStar, newspapers) that force phone calls or in‑person visits to cancel, reinforcing a general pattern of hostile design.
  • Several propose a rule: cancelling must be at least as easy and via the same channel as signing up.

Pricing, Fees & Dynamic Behavior

  • Users report:
    • Business profiles and Uber Cash/gift cards often yielding higher quoted fares than personal profiles or no credit balance.
    • Food delivery markups of 20–100% over restaurant prices plus multiple “service” fees.
    • Teaser ride/delivery ETAs and times that jump significantly after payment, viewed as intentional underestimation.
    • “Priority” fees to get a driver or delivery sooner, with skepticism that it truly improves timing when many people pay it.

Refunds, Credits & Support Mazes

  • Common pattern: when Uber fails to deliver (wrong order, missing items, delays), refunds default to in‑app credits, not the original payment method.
  • Some regions report easy, automated refunds; others describe chatbot loops, inability to reach a human, or only partial credits.
  • Chargebacks often succeed but can lead to effective account lockout or “ransom” balances.

Food Delivery Economics & Ethics

  • Many see delivery apps as “markup on markup,” yet some urban users find the time savings worth a small premium.
  • Disabled and car‑less users describe feeling trapped: they depend on these services yet are repeatedly hit by deceptive pricing and opaque “minimums.”
  • Skepticism that the underlying unit economics work even with aggressive dark patterns; Uber is seen as barely profitable despite scale.

Impact on Drivers & Taxis

  • Drivers report:
    • Highly opaque compensation; some claim to receive only ~25–30% of the fare while riders believe the opposite split.
    • Suspicion that drivers who accept low offers are targeted with worse pay.
    • GPS routing that lengthens trips, increasing time and costs.
  • Users lament the destruction or weakening of traditional taxi systems, while noting taxis had their own problems (poor service, rent‑seeking medallion systems, scams in some cities).

Regulation, Enforcement & Broader Concerns

  • Many welcome the FTC action and cite similar state laws (e.g., “if you can sign up online, you must be able to cancel online”).
  • Others are cynical, viewing enforcement as sporadic or politically influenced.
  • Dynamic pricing and personalization are broadly criticized as enabling price discrimination with no clear consumer upside.
  • Several argue that real solutions require stronger consumer protection, antitrust enforcement, or treating ride-hailing more like a regulated utility.