Take Advantage of the Algorithm! (Citi Bike Edition)
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It was the perfect New York hustle, a scam of subtle perfection. And for three years, it helped Mark Epperson pay his rent.
The hustle, in its simplest form: Borrow a Citi Bike. Ride it one block. Wait 15 minutes, then ride it back.
Earn $6,000 a month (under ideal conditions, and with lots of work).
“This is one of my side hustles,” said Mr. Epperson, an actor who lives on the Upper West Side and works as an understudy in “Perfect Crime,” an Off Broadway play. “I’m probably a vulture in some people’s eyes. And I guess that’s fair.”
If Mr. Epperson’s insight into the scheme is simple, the circumstances surrounding it are anything but. Citi Bike, a bike-sharing program operated by Lyft that offers 27,000 bikes throughout New York City, Hoboken and Jersey City, promises seamless pickup and drop-off. Occasionally, though, a ride to work ends with the rider’s discovery that the docking station nearest the office is full. A dash to brunch is foiled by an empty dock, with no bikes available.
Both situations are annoying, especially for Citi Bike subscribers, who now pay $220 a year. To fix the imbalance, Citi Bike uses various tactics to move bikes to in-demand stations. One involves hiring workers to drive panel trucks around the city, delivering bikes where they’re needed.
Another, created in 2016, is a program called Bike Angels, in which Citi Bike users move bikes in exchange for points that could be cashed in for swag like water bottles and backpacks, membership discounts and gift cards. This being New York, where even charitable activities quickly develop overtones of competition, a handful of users started racing to see who could win the most points. Citi Bike called them Power Angels.
They won bragging rights, killer aerobic stamina (in the beginning, there were no electric Citi Bikes) and their initials atop an online leaderboard.
“We imagined people would do it as a recreational fitness kind of thing,” said David B. Shmoys, a data scientist at Cornell University whose research team created Citi Bike’s first rebalancing algorithm in 2014. “We never imagined anyone getting really obsessed.”
Over the years, a few users found ways to maximize the program’s financial benefits. By monitoring a map of stations on Lyft’s app, they noticed that the algorithm awards points on a sliding scale based on need. Removing a bike from a completely full station: up to four points. Docking at an empty station? That’s worth up to another four. People who move at least four bikes in a 24-hour period get all their points multiplied by a factor of three.
Lyft pays 20 cents per point. Each ride generates a maximum of 24 points. In perfect conditions, a person on a 3X streak who relocates a bike from a full dock to a completely empty one can earn as much as $4.80 for a single ride.
That doesn’t sound like a quick way to get rich. But a few riders realized that by working as a team, and quickly, they could exploit the algorithm. For Mr. Epperson and his fellow hustlers, it “created an opportunity to make a lot of money,” he said.
At 10 a.m. on a Tuesday last month, seven Bike Angels descended on the docking station at Broadway and 53rd Street, across from the Ed Sullivan Theater. Each rider used his own special blue key — a reward from Citi Bike — to unlock a bike. He rode it one block east, to Seventh Avenue. He docked, ran back to Broadway, unlocked another bike and made the trip again.
By 10:14, the crew had created an algorithmically perfect situation: One station 100 percent full, a short block from another station 100 percent empty. The timing was crucial, because every 15 minutes, Lyft’s algorithm resets, assigning new point values to every bike move.
The clock struck 10:15. The algorithm, mistaking this manufactured setup for a true emergency, offered the maximum incentive: $4.80 for every bike returned to the Ed Sullivan Theater. The men switched direction, running east and pedaling west.
When asked about this venture, some of them became defensive.
“How are we cheating?” said one Angel in a baggy gray T-shirt, black athletic shorts and sneakers, who declined to give his name. “If Lyft wants something else, they can change the algorithm.”
https://www.nytimes.com/2024/09/19/nyregion/citi-bike-scam-nyc.html?smid=em-share
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Brilliant!
