Cutting edge data-driven analysis directs Los Angeles patrol officers to likely future crime scenes – but critics worry that decision-making by machine will bring a ‘tyranny of the algorithm.’ The Los Angeles Police Department, like many urban police forces today, is both heavily armed and thoroughly computerized.

The Real-Time Analysis and Critical Response Division in downtown LA is its central processor.

Rows of crime analysts and technologists sit before a wall covered in video screens stretching more than 10-metres wide.

Multiple news broadcasts are playing simultaneously and a real-time earthquake map is tracking the region’s seismic activity. Half-a-dozen security cameras are focused on the Hollywood sign, the city’s icon.

In the center of this video menagerie is an over-sized satellite map showing some of the most recent arrests made across the city – a couple of burglaries, a few assaults, and a shooting.

On a slightly smaller screen the division’s top official, Captain John Romero, mans the keyboard and zooms in on a comparably micro-scale section of LA.

It represents just 500 feet by 500 feet. Over the past six months, this sub-block section of the city has seen three vehicle burglaries and two property burglaries – an atypical concentration.

And, according to a new algorithm crunching crime numbers in LA and dozens of other cities worldwide, it’s a sign that yet more crime is likely to occur right here in this tiny pocket of the city.

Predictive Policing
The algorithm at play is performing what’s commonly referred to as predictive policing. Using years —and sometimes decades— worth of crime reports, the algorithm analyses the data to identify areas with high probabilities for certain types of crime, placing little red boxes on maps of the city that are streamed into patrol cars.

“Burglars tend to be territorial, so once they find a neighbourhood where they get good stuff, they come back again and again,” Romero says. “And that assists the algorithm in placing the boxes.”