When Your Boss Is an Algorithm
When Your Boss Is an Algorithm
For Uber drivers, the workplace can feel like a world of
constant surveillance, automated manipulation and threats of “deactivation.”
By Alex Rosenblat Oct. 12, 2018 Ms. Rosenblat is the author of the
forthcoming book “Uberland: How Algorithms Are Rewriting the Rules of Work.”
There are nearly a million active Uber drivers in the
United States and Canada, and none of them have human supervisors. It’s better
than having a real boss, one driver in the Boston area told me. “Except when
something goes wrong.”
When something does go wrong, Uber drivers can’t tell the
boss or a co-worker. They can call or write to “community support,” but the
results can be enraging. Cecily McCall, an African-American driver from Pompano
Beach, Fla., told me that a passenger once called her “dumb” and “stupid,”
using a racial epithet, so she ended the trip early. She wrote to a support rep
to explain why and got what seemed like a robotic response: “We’re sorry to
hear about this. We appreciate you taking the time to contact us and share
details.”
The rep offered not to match her with that same passenger
again. Disgusted, Ms. McCall wrote back, “So that means the next person that picks
him up he will do the same while the driver gets deactivated” — fired by the
algorithm — because of a low rating or complaint from an angry passenger.
“Welcome to America.”
Over the past four years, I have traveled more than 5,000
miles in more than 25 cities, interviewing 125 drivers for Uber and other
ride-hailing apps, as well as taxi drivers, and observing hundreds more. And I
have spent countless hours in Facebook groups and other online forums for
drivers, which collectively have 300,000 members, to better understand their
experiences. I have learned that drivers at ride-hailing companies may have the
freedom and flexibility of gig economy work, but they are still at the mercy of
a boss — an algorithmic boss.
Data and algorithms are presented as objective, neutral,
even benevolent: Algorithms gave us super-convenient food delivery services and
personalized movie recommendations. But Uber and other ride-hailing apps have
taken the way Silicon Valley uses algorithms and applied it to work, and that’s
not always a good thing.
The algorithmic manager seems to watch everything you do.
Ride-hailing platforms track a variety of personalized statistics, including
ride acceptance rates, cancellation rates, hours spent logged in to the app and
trips completed. And they display selected statistics to individual drivers as
motivating tools, like “You’re in the top 10 percent of partners!”
Uber uses the accelerometer in drivers’ phones along with
GPS and gyroscope to give them safe driving reports, tracking their performance
in granular detail. One driver posted to a forum that a grade of 210 out of 247
“smooth accelerations” earned a “Great work!” from the boss.
Surge pricing, which multiplies prices for passengers and
earnings for drivers during periods of high demand, is another form of
algorithmic management that encourages drivers to relocate to certain areas at
certain times. The drivers get in-app notifications, heat maps and emails with
real-time and predictive information about spikes in demand. A driver who wants
to go home and is trying to log out might be prompted with an automatic
message: “Your next rider is going to be awesome! Stay online to meet him.”
It’s easy enough to dismiss those gentle nudges, but
in-app notifications like “Fares are at 3.0X right now!” or “There are lots of
events in New Orleans this weekend where we expect Uber demand to be high!”
raise expectations and are hard for drivers to ignore. But by wording its
expectations as helpful hints, rather than orders, ride-hailing companies can
avoid the appearance of a direct supervisory relationship with their drivers.
Some Uber drivers say they feel misled when they travel to a surge area in high
demand only to find that it has disappeared. The consensus in driver forums is,
“Don’t chase the surge.”
Uber takes fees and commissions on every ride, and complaints
about low pay and rate cuts are common. In 2016, Uber started charging
passengers on some rides more than drivers were paid, without notifying them,
in a policy called “upfront pricing.”
By the logic of Silicon Valley, the company was simply
trying out a new pricing policy, but many drivers were angry that their
livelihoods were part of this experiment. One group of drivers filed a
class-action lawsuit in San Francisco, arguing that Uber violated the terms of
its contract by changing the policy without notifying drivers. Uber has said
that it is not a violation of their contract because drivers continue to be
paid per mile and per minute. A settlement is pending, and drivers can now view
the prices charged to passengers.
While critics use the language of the workplace to
describe the treatment of drivers, the language of technology can deflect such
concerns. When payments for trips are missing, labor advocates might call it
wage theft, but Uber says it’s a glitch. When Uber charges passengers what it predicts
they are willing to pay based on their route rather than standard rates,
economists may call it price discrimination, but Uber explains it as an
innovation in artificial intelligence.
Other tools, like the rating system, serve as automatic
enforcers of the nudges made by algorithmic managers. In certain services on
Uber’s platform, if drivers fall below 4.6 stars on a 5-star rating system,
they may be “deactivated” — never “fired.” So some drivers tolerate bad
passenger behavior rather than risk losing their livelihoods because of retaliatory
reviews.
To be sure, drivers are not simply passive victims of
algorithms. Uber drivers figured out the upfront pricing scheme by sharing
pictures of passengers’ receipts alongside their own pay stubs in online driver
forums.
Their experiences serve as a useful warning about the
algorithms that are so closely integrated into our daily lives. Algorithms
determine the news we see on Facebook and the search results we review on
Google. And whenever we use a ride-hailing app, algorithms manage what we do as
passengers, by controlling and manipulating the information we have about the
price and location of available cars. (The car icons circling your location
onscreen, for example, may not exist in real life. Uber has said its goal is to
make the icons “as accurate as possible in real time.”)
A driver in New York City told me about the first time he
realized how upfront pricing worked. “A passenger and I started talking about
it during the trip, and he offered to show me his invoice at the end of the trip,”
he said. “Seeing it for real just outraged me so much! It was like somebody had
cheated on me.” The passenger shrugged it off, until he saw that he had been
charged $40 for a ride that should have cost only $28. “Then suddenly he got
it, too!”
Whether we realize it or not, algorithms are managing all
of us.
Alex Rosenblat is a researcher at Data & Society and
the author of the forthcoming book “Uberland: How Algorithms Are Rewriting the
Rules of Work,” from which this essay is adapted.
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