| There was a (now deleted comment) about how there is no proof of wage discrimination for Uber/Lyft drivers, which was posted with no evidence. This video (https://www.youtube.com/watch?v=OEXJmNj6SPk) was recently published which shows drivers being offered the same gigs, but different payment amounts. Note that I could not find a published version of the data they collected in this video. That is not explicitly proof of wrongdoing, but clearly algorithmic price setting can be demonstrated as not always offering the same payment to the same drivers for the same work. There may be a valid reason to why this is the case, but as the calculation method is closed source, the individuals being offered the wage are unaware of why they would be paid less than their peers. This is work that is often considered "low skill" - which should actually make it extremely cut and dry as to why an individual would be paid more or less. Are they making their pickups faster? Are their customers more satisfied? If that's the case, why would they sometimes be offered more money than their peers and sometimes less money? Almost all workers here are price takers, and suffer greatly from the information asymmetry present. Companies hiding behind "oh but the algorithm says..." is a poor excuse for inequality. Edit: Because discrimination is in the title of the OP, I feel the need to clarify: in no way is the above saying that the video posted is proof of discrimination. Inequality need not be discrimination. When there is inequality without any measurable source, we need to be skeptical of the reason. Maybe one driver has better customer feedback, therefore they get offered a higher wage. There are many logical explanations for the result, but Uber/Lyft do not seem to engage with the discussion. This should raise red flags. That does not conclude that they are discriminating against anyone, and that would be a poor conclusion to draw without a true investigation. |
This isn't really abnormal. Every job does this by setting a wage they are willing to pay and seeing who signs up, knowing that person will now need to only be paid that wage. What is different is the scale and the frequency this is being done. Instead of doing this in a way that impacts a person once every job change, it now impacts them multiple times a day, and the data recorded is more detailed and can be acted on more directly.
None of this is discrimination against a protected class, but if there are any reasons one demographic might, on average, accept lower pay than another, it will lead to large scale discrimination.
The problem is that our common discussion on these topics is lacking the rigor, nuance, or depth to handle questions about this, and thus ends up with two large camps. One that looks at the methods, sees no obvious discrimination in the methods, and say it doesn't count as inequality. The other that looks at the outcomes, notices the clear difference in outcome this leads to, and calls it inequality. Both are, by their own metrics, correct.