Having just raised rider rates and reporting a $690 million loss from fare jumpers, New York’s MTA has turned to Artificial Intelligence to create turnstile stats. But the high tech advantage won’t be used to catch evaders, only provide information on the losses.
In use at seven Metropolitan Transportation Authority-managed subway stations, the system is tracking when fare evasion spikes and the methods fare evaders use. AI capabilities are planned to be expanded to 19 stations later this year. The authority won’t say which stations will be monitored.
The AI crunches video data in real time to provide stats on when and how people are getting onto the subway without paying.
The system is similar to one used in Barcelona that is giving inspectors instant evasion alerts through a smart phone app allowing for rapid interventions before the offenders reach the platform. They can then log the outcome of the encounter as to whether an offender was apprehended, fined, not fined, etc.
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So far, AI analysis has shown that around 50% of subway evasion comes from people walking in through the emergency exit gates, 20% jump or climb over the turnstile, and 12% duck underneath. The tactics add up to $690 million in losses that will have to be covered by the honest riders, toll increases on motorists using MTA bridges and tunnels, and state taxpayer subsidies.
"It helps us just measure the amount of fare evasion happening," the MTA spokesperson said. "It's not alerting any NYPD officers in real time if fare evasion takes place, it's not used to ping an officer and have them go after a person who fare evades. That's not how the system works. It's just our effort to see what is happening out there."