Google Street Views AI Can Now Predict Race and Political Party
In a paper published earlier this year, Stanford computer scientist Timnit Gebru wrote about how neighborhoods can be evaluated by the makes and models of the cars parked in their driveways. The paper appeared in the Proceedings of the National Academy of Sciences and it's an interesting read.
By analyzing the images already available as part of Google Street Views, the research team was able to identify which neighborhoods were Republican and which were Democrat as well as many other characteristics.
It determined that in those areas where the number of sedans is higher than pickup trucks, there’s an 88 percent chance of the district voting Democratic. Where there are more pickup trucks, there’s an 82 percent chance it’s a Republican-voting district.
The project devised an automated methodology that estimated the social characteristics of regions covering 200 U.S. cities based on analyzing 50 million images from Street Views. The images were originally created by Google sending cars through every neighborhood in the country, capturing images that are then displayed and accessed on Google Maps. Their automated process took two weeks, compared to 15 years if the images had been analyzed by hand.
The automated process to analyze the images was accomplished using computers and artificial intelligence software called “convolutional neural networks” that learned to recognize the vehicles by identifying unique features on each. That allows the computer to identify the make and model, year, value, and fuel efficiency of the vehicle.