In more and more workplaces, important decisions aren’t made by managers but by algorithms that have increasing levels of access to and control over workers. While algorithmic management can boost efficiency and flexibility (as well as enabling a new class of quasi-self-employed workers on platforms like Uber and Instacart), critics warn of heightened surveillance and reduced autonomy for workers.
In a new published paper, Wharton management professor Lindsey Cameron examines how ride-hail drivers interact with the algorithmic management tools that make app-based work possible.
Cameron’s research explores how ride-hail workers interact with their algorithmic managers—specifically, how they exert autonomy and make decisions. Her research highlights how drivers devise ways to exert more control.
“I look at each of a worker’s interactions with the algorithmic management system as an instance in which consent is produced,” says Cameron. “By consent, I mean, ‘How do you get people to enthusiastically comply with rules?’ Through these small interactions, people feel like they have a sense of choice. It’s a small choice, but it is very real.”
Cameron explains that while algorithmic management is associated with low-wage, precarious jobs like ride-hail driving or warehouse work, it is already embedded in white collar jobs as well.
“We’re seeing a broad sweep of new tools, technology, and digitization under the future of work. Surveillance of at-home workers exploded during the pandemic, with the introduction of tools that could track your keystrokes or whether you were active at your computer or Bloomberg terminal. If you do any kind of customer-facing job, an algorithm keeps track of your ratings and reviews,” says Cameron.
Algorithms are endemic to this new world of work, regardless of the type of job you’re doing. I just chose to study a type of work—ride-hail driving and app-based work—in which they are very prevalent,” she says. “If you look at the most disenfranchised, vulnerable, marginalized workers, that is where new tools and technology get tested first.”
Read more at Knowledge at Wharton.
