- Report: Mark Zuckerberg advised Pete Buttigieg on campaign hires 2 Years Ago
- ‘New Girl’ star Lamorne Morris handcuffed by white cop for recording his friend’s arrest 2 Years Ago
- Mitt Romney, aka ‘Pierre Delecto,’ uses a fake account to lurk on Twitter 2 Years Ago
- ‘The Laundromat’ sacrifices narrative for artistic experimentation Today 9:24 AM
- James Charles mocks the Dobre Brothers’ fan controversy Today 9:22 AM
- Vin Diesel stars in the first trailer for comic book movie ‘Bloodshot’ Today 7:48 AM
- MAGA rappers are dropping beats for Trump Today 6:30 AM
- How to stream Patriots vs. Jets on Monday Night Football Today 6:00 AM
- How to stream Arsenal vs. Sheffield United Today 1:00 AM
- If you have doubts about HBO’s ‘Watchmen,’ give it more time Sunday 9:00 PM
- Video shows moment coach disarmed student of shotgun, then hugged him Sunday 7:38 PM
- Jared Leto reportedly tried to stop ‘Joker’ from happening Sunday 4:12 PM
- People are grossed out by cow insemination-themed pregnancy announcement Sunday 3:13 PM
- Major protests in Lebanon triggered by plan to tax WhatsApp calls Sunday 1:38 PM
- Frank Ocean’s $60 HIV prevention drug-themed shirts called tone-deaf Sunday 12:49 PM
Nervous about all the underreported white collar crime going on in your neighborhood? Well, a new app launched Tuesday that uses machine learning to predict neighborhoods with the highest risk of financial crimes. So stay out of FiDi, New Yorkers!
For White Collar Crime Early Warning System, programmers developed an interactive heat map that makes search results public and searchable. Created by Sam Lavigne, Francis Tseng, Brian Clifton, and Rachel Rosenfelt, co-founder of the New Inquiry, and in collaboration with its latest issue, the app is meant to mock American prison and policing systems.
“In some ways, it’s a troll, because financial crime is not location-based, but it’s also about the absurdity of predictive policing as a technology,” Lavigne told BuzzFeed News. “It’s both a troll and totally sincere—what if cops went to financial neighborhoods and stopped and frisked white guys in business suits?”
Users of the mobile app can sign up for alerts upon entering really “red” areas. Manhattan, especially Wall Street and Midtown, is littered with tiny red dots on the map.
The app also features headshots of CEOs to compile images of what potential offenders would look like.
“Unlike typical predictive policing apps which criminalize poverty,” the creators say in an article announcing their project, “White Collar Crime Risk Zones criminalizes wealth.”
The system relies on years of enforcement data from FINRA, a private financial industry regulator.
“We used FINRA data because it represented the largest available dataset about financial malfeasance that was tied to physical location,” Lavigne said. “From a predictive policing standpoint, they represent a pool of potential suspects.”
These suspects, however, have not been convicted of a crime. The developers are trying to point out another problem with the way the industry is regulated—not by police, but by private regulators who may not have the authority or motive to convict for the breaking of federal laws.
Tseng compared his co-creation to another app called Metadata, which notifies users every time a United States drone strike is reported in the news.
“Both these projects are about making violence that is difficult to see visible,” he said.
Check out the app here.
H/T BuzzFeed News
Anastassia Gliadkovskaya is a lifestyle and politics reporter. Her work has been published by Empire State Tribune and Urban Watch magazine.