Four billion people lack an address. Machine learning could change that | Intelligent Machines - MIT Technology Review

Karen Hao, artificial intelligence reporter for MIT Technology Review notes, Researchers at MIT and Facebook are proposing a new way to generate street addresses by extracting roads from satellite images. 

Photo: Thor Alvis/Unsplash

An estimated 4 billion people in the world lack a physical address. Without one, residents lose access to important services like package deliveries, medical care, and disaster relief, as well as the ability to register to vote or obtain a driver’s license. Cities also have trouble planning new infrastructure, such as schools, water pipes, and electricity lines. (And this isn’t just in the developing world.) 

“As you move into a more global economy and more people order and get goods delivered at a distance, you need a more specific address than ‘the house with the red door across from the cathedral,’” says Merry Law, the president of a company that provides international addressing information.
Researchers at the MIT Media Lab and Facebook are now proposing a new way to address the unaddressed: with machine learning.

The team first trained a deep-learning algorithm to extract the road pixels from satellite images. Another algorithm connected the pixels together into a road network. The system analyzed the density and shape of the roads to segment the network into different communities, and the densest cluster was labeled as the city center...

But Ilke Demir, a researcher at Facebook and one of the creators of the new system, says its main advantage is that it follows existing road topology and helps residents understand how two addresses relate to one another.

“If you have the address—let’s say—‘parrot.failed.casino’ and someone else has the address ‘tables.chairs.television,’ you have no idea if you are neighbors with that person,” she says. “That’s the whole point. We want addresses that people can relate intuitively.”

“I think it’s bloody brilliant,” says Charles Prescott, an international lawyer and founder of the nonprofit Global Address Data Association. “If you can code the system to generate addresses based on local conventions, that would be incredibly efficient and cost effective.”

Both Law and Prescott note, however, that there are limitations to this approach. “Generating the addresses isn’t the main issue,” says Prescott. “It’s getting people to adopt them.”
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Source: MIT Technology Review