I always like a good hack. And this story delivers. Basically, the New York City bikeshare program has a system to reward people who move bicycles from full stations to empty ones. By deliberately moving bikes to create artificial problems, and exploiting exactly how the system calculates rewards, some people are making a lot of money.

    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.

Nicely done, people.

Now it’s Lyft’s turn to modify its system to prevent this hack. Thinking aloud, it could try to detect this sort of behavior in the Bike Angels data—and then ban people who are deliberately trying to game the system. The detection doesn’t have to be perfect, just good enough to catch bad actors most of the time. The detection needs to be tuned to minimize false positives, but that feels straightforward.