U.S. consumers generally believe that gig workers who labor for companies such as Uber Technologies Inc. and Lyft Inc. are free to set their own hours and thus able to determine broadly how much they will earn while ferrying passengers to and from their different destinations. Consumers of these services make a series of assumptions based on shared knowledge of how employment arrangements in the United States work or should work.
Riders probably assume, for example, that the longer gig workers labor at the wheel, the more they will make per hour, and that skills acquired over time mean that these workers can improve their hourly pay because, say, they can learn what areas and times are lucrative or how to game the algorithms.
But, as it turns out, these assumptions do not pan out. Gig work is far from flexible. Gig workers are highly “incentivized” through pay structures to work at specific times. Not working at those times or in the ways that Uber and Lyft want their contract drivers to work can result in them losing money, instead of earning it.
Using data extracted from drivers’ labor and then fed into machine-learning technologies, these companies can personalize base pay and the opportunities to raise base pay. This may sound like a rewards system for individual hard-working gig workers, but in fact because every gig driver is ostensibly an “independent contractor,” the two companies can drive down individual pay while maximizing their own corporate profits.
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