More and more riders want to know how much the driver is getting paid. They know it’s not much in comparison to what they pay. They are not happy with getting price gouged. This is especially true for rides to the airport. Here, they have no choice but to accept whatever Uber offers them for a price. Uber has them right where they want them.
The ride below is a good example and the numbers are very bad. There are 4 screenshots. Following is the details.
| Distance | 10.37 miles |
| Fare | $10.31 |
| Tip | $9.00 |
| Driver earnings | $19.31 |
| Refund (tolls) | $2.65 |
| Customer paid | $23.08 |
| IRS Mileage Expense $.70/mile | 10.37 miles x $.70 = $7.26 |
| Taxable income without tip | $10.31 – $7.26 = $3.05 |
The customer paid over twice what the driver was paid. Customer paid $23.08. This customer tipped at some point after the ride was completed. Perhaps while waiting for his flight? The tip was nearly 90%. I am sure this was given knowing my taxable income from this trip was just $3.05.
This Boston Globe article written by Katie Johnston and published on August 3, 2024 details how big data is used.
Who’s really at the wheel for Uber and Lyft? In many ways, AI.
Yes, it’s paywalled. Visible only to paying subscribers. Here’s some excerpts.
David Weil, a Brandeis University professor and labor market expert, knew that Uber and Lyft had long used algorithms to match the supply of drivers to demand from riders, and set prices accordingly.
But as he sifted through depositions, documents, and data made available in a recent Massachusetts lawsuit against the ride-hailing companies, he discovered the artificial intelligence behind the algorithms was far more sophisticated than he imagined. The algorithms, learning from massive amounts of data gleaned from millions of trips, could predict how much riders in certain situations might be willing to pay, and how much compensation drivers might accept.
After a Celtics game, for example, someone heading to Weston might be charged a higher rate than another person going to Framingham, based on the insight that Weston passengers might be wealthier and willing to pay more to get home quickly
The insights into how Uber and Lyft operate grew from materials turned over to state during the discovery phase of a lawsuit against the companies for misclassifying drivers as independent contractors rather than employees.
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