As
reported by Motherboard:When you walk around a city, there are things you can just sense, like if
you've wandered into a dodgy neighborhood, or where the new happening spot is.
Intuitively, we know that a city's more intangible characteristics, like class
or uniqueness, play a big role in what it’s like to live there, but until now
there was no way to actually quantify that idea.
Researchers from MIT Media Lab may have found a way to measure this
"aesthetic capital" of cities, with their website
Place Pulse, a tool
to crowdsource people’s perception of cities by judging digital snapshots—a sort
of “hot or not” for urban neighborhoods.
Some 4,000 geotagged Google Streetview images and 8,000 participants later,
the team found that by using digital images and crowdsourced feedback, they can
accurately quantify the diverse vibes within a city, which in turn can help us
better understand issues like inequality and safety. The results were
published in the journal PloS One.
The results could be used to someday map the intangible uniqueness of
neighborhoods around the world, which could help improve neighborhoods and
design future cities.
The data could also add some weight to the controversial “
Broken Windows Theory,” which suggests that physical signs of disorder in a neighborhood—like
broken windows—can lead to crime, causing a vicious cycle. The theory has been
hotly debated since it came out of Harvard in the 80s, partly because it’s hard
to actually measure and quantify “disorder.”
The Place Pulse experiment could change that. From the study:
Cities are not just collections of demographics, but places that people
experience. Urban environments are known to elicit strong evaluative responses,
and there is evidence and theories suggesting that these responses may affect
criminal and health behaviors. Yet, we lack good quantitative data on the
responses elicited by urban environments. Place Pulse is an effort to help
collect quantitative data of urban perception to help advance these research
efforts and open new avenues of research.
In other words, there's more to measure in a city than just demographics and
income. Things like energy level, architecture, beauty, and so on can impact
people’s social behavior. While Place Pulse 1.0 was a small experiment—it looked
at images from just four cities, Boston and New York in the US and Salzburg and
Linz in Austria—the method proved effective enough to be worth exploring
further, according to the report.
Now MIT has expanded the study out to 56 cities around the world, with more
than 100,000 geotagged images. Place Pulse 2.0 also measures more
characteristics, looking at how boring, depressing, lively, safe, and wealthy
the cities seem.
The team wants to use this second, larger dataset to train machine learning
algorithms to understand what kind of features in the photos lead humans to
answer the way they do—in a sense, to teach computers intuition, so the research
could scale.
The Place Pulse experiment is simple. Like Mark Zuckerberg’s infamous
pre-Facebook FaceMash site, it shows two images side by side and asks people to
answer questions like "which place looks safer?" or "which place looks more
upper-class?"
The first experiment found that the US cities, Boston and New York, were more
unequal than the Austrian cities. There was a wider gap between "good" and "bad"
neighborhoods. The researchers compared the results with actual statistics on
homicides in New York and found a strong correlation between their data on how
safe neighborhoods seem, and the existing data on how safe neighborhoods
are.
With a larger dataset, being analyzed by learning machines, the findings
could be used to design the city of tomorrow. "Ultimately, the goal of this
study,” researchers wrote, “is to contribute to our understanding of the urban
environments that we have built, with the goal of improving them, and their
ability to include their citizens, while also informing the construction of
future cities.”