Second study finds Uber used opaque algorithm to dramatically boost profits

Shifting Economics and Driver Pay

• Several comments report Uber’s take rising from ~16–17% to 25%+ while hourly driver earnings fall, even as rider prices increase.
• Riders note specific routes that went from ~$17–20 to $25+ while the driver’s cut stayed flat, implying the spread now goes to the platform.

Comparison with Traditional Taxis

• Some argue predatory pricing existed with cabs (fake “flat rates,” broken meters, refusal to take cards).
• Others counter that regulated taxis in many regions must post fixed, public fares and driver IDs, making abuse easier to contest.
• Uber’s upfront pricing and route tracking are widely seen as a major usability and trust improvement over legacy taxi experiences.

Consumer Surplus and Price Discrimination

• Earlier research that praised Uber’s consumer surplus is contrasted with today’s individualized, opaque pricing that appears to skim surplus from both riders and drivers.
• Many describe this as algorithmic “haggling” where the platform infers willingness to pay and charges different riders different prices for similar trips.
• Some defend this as standard business practice (akin to coupons, loyalty programs, airlines), while others stress the asymmetry of information and lack of transparency as fundamentally unfair.

Market Power, Competition, and Regulation

• Commenters describe a playbook: underpriced rides to kill taxis, then post-dominance price hikes, aided by regulatory arbitrage around labor laws.
• Debate over whether Uber is a monopoly: in many cities, Lyft and some cabs still compete; elsewhere users feel stuck in a de facto duopoly.

Impact on Drivers and Algorithmic Wage Setting

• Discussion of “price discrimination on the supply side”: the system tests how low each driver will work by gradually raising offers, then subtly ratcheting pay down over time.
• Frequent, “loyal” drivers may earn less than those who only drive when bonuses or surges are high, leading some to call this exploitative even if not illegal.

Trust, Safety, and Alternatives

• Uber’s moats are seen as brand, scale, payments, and perceived accountability, especially for vulnerable riders, despite recurring harassment stories.
• Driver-owned or FOSS co-op platforms exist in some cities, but face challenges: safety oversight, background checks, payments, airport integrations, and enough liquidity to match Uber’s reliability.

Manipulation, Tracking, and User Tactics

• Users describe installing multiple ride apps to trigger discounts and avoid being “captured” by one platform.
• There is concern over apps detecting each other, using location or travel data (e.g., airport arrival notifications) and personalized promos, reinforcing perceptions of pervasive, manipulative data use.