Can A.I. Predict Gentrification?
A research team in London is using artificial intelligence and machine learning to predict patterns of gentrification.
The study, conducted by researchers at Kings College London, used machine learning to analyze 2001 data and predict where gentrification occurred in 2011, City Lab reports. Using that model, the program then predicted where gentrification will likely occur in 2021.
When the 2001 model predicted what would happen in 2011, it lined up quite accurately with what had occurred in real life. It generated a very close statistical fit, compared to other traditional models like standard regression analysis.
Surprisingly, the study found that key demographic factors, like the presence of “DINKs” (Dual Income, No Kids couples), vehicle ownership, or ethnicity, did not rank strongly on the list of top predictors for gentrification. Immigration did predict gentrification, but only from other members of the EU (as of 2001), the Americas, and Australia and New Zealand. The type of building also had some predictive value, especially for terraced or older buildings. Ultimately, the study found that most of the top predictors reflected occupation: working long hours, skills and qualifications, and job flexibility, such as self-employment or working from home.