Friday, 14 August 2026
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CulturePublished: 14 August 2026 at 13:08

Art Project Makes Citi Bikes Harder to Pedal in Rent-Burdened NYC Neighborhoods

An artist has created a device that applies resistance to Citi Bikes when riding through neighborhoods with heavy rent burdens, making the city's housing affordability crisis physically felt.

Foto: Wired

After losing his job shortly before the Covid-19 pandemic hit in 2020, Brooklyn artist Justin Blinder began delivering food by bicycle across New York City. The work exposed major economic divides between nearby blocks, influencing his latest project, Ground Truth.

Ground Truth was developed with a $10,000 grant from Idle Hands, a Brooklyn arts organization. Blinder, who also works as a contractor at Meta, designed the device to attach to a bike's fork and front brake line. A GPS module tracks the bike's location, cross-referencing it with household economic data from the US Census Bureau's American Community Survey. When the bike enters a block where residents spend more than 30 percent of their income on rent, a microcontroller activates a small motor that engages the brake, creating pedal resistance and slowing the bike to a crawl. In wealthier areas, the bike rides normally.

Two versions exist: one for regular bicycles and one specifically for Citi Bikes, the Lyft-owned rental bikes found throughout the city. Blinder says the device is not a commercial product and probably cannot be used by others for legal reasons. He has ridden roughly 35 miles with it, filming how it behaves in different communities.

This is not Blinder's first project combining data and physical sensation. Earlier, he created Pandemic Pulse, an app that used live Covid-19 statistics to change a phone screen's brightness: it dimmed when infections rose and blacked out when a death was recorded.

Blinder hopes Ground Truth draws attention not only to the housing crisis but also to the rising cost of renting Citi Bikes, whose prices have increased for five consecutive years. He wants to make large data sets feel more tangible and embodied, forcing people to reconsider how they think about urban inequality.

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