Algorithms Drive Management-Free Workplaces

Algorithms and the Future of Work

The Rise of Algorithmic Management

How do things work out when people are managed by algorithms, versus actual human beings? Likely, jobs get shredded into microtasks. At this time, algorithmically managed jobs tend to be contract or gig roles. But the day may come when full-time jobs will be guided, to some degree, by algorithms – for better or worse. Can people accomplish work without direct supervision by live human bosses?

The Pros and Cons of Algorithmic Management

Lindsey Cameron, a professor at the Wharton School of the University of Pennsylvania, has studied this phenomenon. A lack of direct human oversight can be freeing, and at the same time, frustrating to workers, she explained in a recent interview published by Knowledge@Wharton.

"There’s this joy in schedule flexibility, and then there’s this issue of when things don’t go right – whether it’s pay, something with a customer, or not getting rides. Then you’re talking to a robot and it’s hard to get resolution," she said.

The Best Use Case: Ridesharing Apps

The best working use case for algorithmic management is working for ridesharing apps such as Uber or Lyft, which employ software to manage their contract drivers. Workers enjoy the flexibility the app work provides, but at the same time, they could be "punished" – being kicked off the app for several days, due to a bad rating from a customer. There is no human to appeal such machine-made decisions.

Microtasking and the Risk of Deskilling

Algorithmic management may extend its reach beyond gig work, Cameron said. The common denominator is that algorithmic management slices work into the smallest possible units or microtasks – a process known as deskilling, which has been the core practice seen in assembly lines for more than a century. Except microtasks get much more granular than assembly lines.

The Risks of Algorithmic Management

Rideshare is built upon a lot of microtasks, Cameron pointed out. Workers make decision microtask by microtask, such as, "Will I accept this ride or not? Am I going to follow the GPS, Uber’s or Waze’s, to go where I’m going? Am I going to talk to the customer? Which way will I drive? And then do I rate them or not?"

These moves are all very small components of a task, and since they are so small, "they can be algorithmically managed," Cameron said. "And at the same time, the workers feel like they have choice. Because there are all these little individual elements, I have a very small but very real amount of choice. And I think that’s one of the reasons why people like this work so much, is this feeling of choice."

The Risk of Deskilling and Low Wages

A risk with deskilling and de-splicing the work is that it may drive down wages, since "people can’t really build skill," she cautioned. "And algorithms make mistakes. Without a human in the loop, the human is lost."

The Problem with Algorithmic Management

The problem is "people hold these algorithms to god-like status, that they can’t make a mistake," she continued. "There’s always going to be a gap between how the technology is designed, and how it’s used and implemented by the workers. And in that space, you see agency, but you also see mistakes the technical system is making. And I think the more we start getting blinded by techno-utopianism, that increases the risk."

Conclusion

The result of having workers who are being algorithmically managed, microtask by microtask, calls for a rethinking of the way organizations are structured. "Because this is not Walmart. But nor is it really a bunch of free-floating consultants that are meeting through a job board. It’s a new organizational form, and it does have some responsibilities and liabilities in play."

FAQs

• What is algorithmic management?
  Algorithms are used to manage and guide workers, often in gig or contract roles, by breaking down tasks into small, manageable pieces.
• What are the benefits of algorithmic management?
  Workers may enjoy schedule flexibility and a sense of choice, as they are able to make small decisions along the way.
• What are the risks of algorithmic management?
  There is a risk of deskilling, or reducing the need for skilled workers, and potential mistakes made by algorithms.