> Who knows why? I’m usually more willing to spend than she is, and I bet that's represented on my user profile. I was paying with a gift card, which surely contributes. Maybe it was a price scraping update, comparison shopping detection, or a system that explores “face-in-the-door” high prices before backing down. From the outside, no one really knows.

The most obvious possibility omitted is that your wife got the first, easy, cheap car and then Uber had to quote you a higher price to get a second car. Cars don't fall from the sky; if two people successively ask for bids, how else could it work? What if the app quoted you both the cheap price for the only car within X blocks, and you bought it before she did? Is it suddenly going to go 'oops sorry, changed my mind, it now costs twice as much'? Sounds like a very bad experience to me! More sensible to give the first person a low quote and then when - unexpected and unpredictably - someone requests something similar, quote them the higher price reflecting the sudden local micro-shortage.

(author here) I believe I had checked first in this case, which is why it was surprising. Sorry not to mention that in the post. This was in San Francisco, and there were multiple cars shown on the map.

In my experience, I usually don't see this kind of price change before the request has actually been confirmed - and I have seen Lyft change the price between showing me the estimate and confirming the request (with an apologetic confirmation dialog, possibly only after some holding period has timed out).

Maybe in my case where the high quote came first, the opposite scenario happened - a glut of drivers appeared between my request and hers, raising supply.

Opaque pricing is powerful partly because we don't know. This enables people to construct a plausible story to explain any price.

it would be great if this were the case. unfortunately, Uber has been documented to practice individual price discrimination at a massive scale, using factors like if you’re in a low-income vs high-income neighborhood, individual rider “price sensitivity”, etc, in addition to market conditions (surge pricing), and as a result they have netted billions in profit [1]. i would guess this is why Uber AI researchers are paid so much.

[1] https://len-sherman.medium.com/how-uber-became-a-cash-genera...

That raises an interesting question: if 10 people in a room request ubers without confirming the ride-hail, does the price go up for successive requests?