I noticed this week that Google has started to overlay augmented reality-type place markers onto Street View. The markers are designed to help surface the kind of local business information that you might otherwise find in search -- phone number, hours of operation, and so on. Apparently not everyone is seeing them, but the feature is starting to roll out in certain cities. Above is a photo of Dundas Street West in the Junction.

This transforms Street View into even more of a wayfinding tool, but it also offers up a glimpse of how the world might look with augmented reality. But to make this ultimately happen, you really do need to figure out how to get people to start wearing smart glasses. Lots of companies, including Google and Snap, have been trying. None of their products have really stuck -- though Snap's Spectacles are easily the best looking ones.

However, last month Google did announce that it had acquired Canadian smart glasses company, North. I was invited to try out a pair of North Focals 1.0 glasses, which I wrote about over here. They were exceedingly cool, but definitely not ready for mainstream and daily usage. The sides were thick and you had to wear a ring joystick in order to navigate through its menus. Too much work. Too nerdy.

But that's okay because Google didn't buy North for the Focals product. They bought them for talent, patents, and for probably a bunch of other things. They bought them to help Google invest in its "hardware efforts and ambient computing future." The little markers you might now be seeing on Google Street View are likely part of that.

Starting in the late 1930s, New York City began hiring photographers to document each and every building in the city. It did this to improve the accuracy of its tax assessments, and so every photo was taken with a sign board indicating the building’s block and lot number. The photos looked like this (taken from here):

The initiative produced over 700,000 black and white photos, all of which have been recently digitized according to the New York Times. The Times also recently published this interactive piece where they go back to these archival photos to see how the city has and hasn’t changed. 

In the late 1930s and early 1940s, documenting a city and its buildings was clearly a manual endeavor. Today we have Google Street View (launched in 2007), which has now photographed much of the world. Many countries, including all of North America, are reported as having “mostly full coverage.”

But already autonomous vehicles (and their supporting services) are starting to scan and map our cities in new ways. So it will be interesting to see what ends up getting built on top of this data. I am certain it will empower much more than just better tax assessments.

Happy New Year, friends. Thanks for reading over the last year.

This is an interesting study from a team of AI researchers at Stanford. What they did was use car images taken directly from Google Street View (so images of cars parked on-street) to predict income levels, racial makeup, educational attainment, and voting patterns at the zip code and precinct level.

Admittedly, it’s not a perfect survey, but when they compared their findings to actual or previously collected data (such as from the American Community Survey), it turns out that their study was actually remarkably accurate. Google Street View allowed them to survey 22 million cars, or about 8% of all cars in the US.

Here are some of the things they found:

-  Toyota and Honda vehicles are strongly associated with Asian neighborhoods.

- Buick, Oldsmobile, and Chrysler vehicles are strongly associated with black neighborhoods.

- Pickup trucks, Volkswagens and Aston Martins are strongly associated with white neighborhoods.

Interestingly enough, the ratio of pickup trucks to sedans, alone, is a pretty reliable indicator of voting patterns. If a neighborhood has more pickup trucks than sedans, there’s an 82% chance it voted Republican in the last election.

Perhaps this isn’t all that surprising given that car purchases are highly symbolic. But given that the American Community Survey costs $250 million a year to administer, this study is a good preview of what cheaper and more realtime data collection might look like.