New research from a team of data scientists can predict which areas of a city will gentrify next, says CityLab's Richard Florida. He writes:
The research, conducted by Jonathan Reades, Jordan De Souza, and Phil Hubbard of Kings College London and published in the Urban Studies journal, uses an artificial intelligence technique called machine learning that essentially trains computer models to learn from past data to predict future patterns. In this case, the research team used data on past gentrification in London to predict where it will next occur.
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.
Continue to CityLab to see the model used on neighborhoods in London.Read More