A recent investigation from Consumer Reports details how Uber and Lyft use AI to get more money out of you and charge different prices for the same ride. It’s an interesting read.
Lyft’s patents go much further, outlining “sensitivity” scores and models, which can be used to predict the “importance” or “priority” of a given trip, arrival, or drop-off location…and a willingness-to-pay score, defined as the “willingness by the mobile requestor device to pay a higher transportation service amount.”
We discussed in the past the rumors that Uber & Lyft charge more for those with credits, gift cards, and promos on their account. In my opinion, the idea of using a “willingness to pay” score has serious legal questions.
It’s clear that someone with a gift card balance sitting in their account will be more willing to pay for a ride and use up their balance. And so, if they use the patented method, that would systematically charge more to users with a gift/credit balance.
I’m no legal expert, but don’t see how it can be legal to offer a prepayment option (load/giftcard) and then charge more for the ride. They’re basically charging you $100 for a load and not giving you $100 of services.
Similarly, imagine someone pays monthly Uber One or Lyft Pink fees for the promised ride discounts (5% from Lyft and 6% from Uber) and then gets upcharged on rides which gets zeroed out by the discount. I don’t see how it can be legal to charge for a subscription and not provide the stated benefits.
Also unethical (but possibly not illegal) would be partnering to give a benefit to Chase or AmEx cardholders (Chase for Lyft, Amex for Uber), and then charging more due to their “willingness to pay” score and zeroing out the benefit. In this case, cardholders are paying an annual fee, though not to Uber or Lyft themselves.
We don’t have the data to know whether Uber and Lyft actually ARE using the patented ‘willingness to pay’ score – all we have is the anecdotal rumors/reports of people being charged more when they have a gift card balance. If they are using the ‘willing to pay’ as a factor, there are serious legal issues to consider.
Even if they specifically train the algorithms to ignore credit balances, the balance will still influence rider behavior (e.g. ordering the ride quickly versus checking competition) which then results in a higher “willingness to pay” and higher prices.
These are just my two cents, happy to hear other analyses in the comments below.
