
StreetScore scores a street view based on how safe it looks to a human - lbotos
http://streetscore.media.mit.edu/about.html
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jamesbritt
What I would like is something that took street photos and safety info and
somehow deduced what visible characteristics correlated with safety.

A while back I was reading a mailing list thread where someone claimed that
adding more street lighting didn't improve safety. This struck me as bullshit.

I did some Googling to dig up some fact to show just how right I was.
Apparently, not so right at all. There were assorted studies that showed (or
suggested, not sure) that adding more lights might actually make a street more
dangerous. They can make it easier for a hidden thief to case a place or a
target, and some lights create enough glare that it becomes harder to see past
a certain distance.

It got me thinking that popular notions of how to judge safety may be very
wrong, and that reality may be quite counter-intuitive.

Another example: I grew up in a city, lived in apartment buildings. Anyone who
had any money moved out of an apartment and moved into a house. Hence,
anyplace that was all houses was a good neighborhood.

Years later I discovered how totally wrong this was and marveled at how such
impressions get formed.

Having better evidence about what factors make a location safer, and to what
extent one can accurately determine safety by visual inspection, would be very
beneficial.

~~~
test431
I'm using a throwaway account so that I don't inadvertently reveal my
location.

The area where I live is on the map. I found it very interesting that the
safety ratings seemed to be closely correlated with lighting. Street View took
pictures of one popular outdoor area near me on a rainy day. Of course, it was
deserted due to the weather, so the entire area received safety ratings of
around 0. However, on a sunny day, the area is filled with families, and I'm
sure that it would have consistently received a 10.

Likewise, my building received low ratings when compared to the surrounding
area due to the presence of an alley (which is actually a gated entrance).
However, no crimes have taken place there for a very long time. An area just
up the street received a rating close to a 10, yet armed carjackings have
taken place there before.

At least from my own (rather anecdotal) experience, it's fascinating that the
factors which cause people to perceive something as safe or unsafe can
actually be far from reality. Anyway, StreetScore is an Awesome piece of
research from the ML. I'm interested in seeing the direction that it's headed.

~~~
zheshishei
I'm confident that incorporating pictures of the same place at different
times/days (like Google Map's wayback machine) would boost the accuracy, but
I'm not too sure how you would need to change the model.

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suprgeek
How safe does this street "look" to a Human?

NOT

How safe is this street?

Very important distinction - I would suggest changing the name of the project
to "PerceivedStreetScore".

What is now needed is actually part 2 of this project - one that pull records
from City/County/Federal crime stats, overlays them with a Map and then
actually produces a "ActualCrimeScore" for each of these highlighted streets.

Then compare the two scores and write an (excellent) definitive paper titled
"Factors that influence Human perceptions of safety - Lessons for City
Planners"

~~~
icommenttoo
If you look at the 2013 paper from this same group you will find that this is
exactly what they did
([http://pulse.media.mit.edu/papers/](http://pulse.media.mit.edu/papers/)).

Even further, they used geospatial statistics techniques to control for the
effects of the income, area, and population in an area, and hence, developed a
model that incorporated not only perception, but also demographics, when
predicting the location of homicides.

~~~
Houshalter
From the site's FAQ:

>StreetScore is a machine learning algorithm that predicts how safe the image
of a street looks to a human observer. We trained StreetScore to predict
perceived safety using a 'training dataset' consisting of 3,000 street views
from New York and Boston and their rankings for perceived safety obtained from
Place Pulse — a crowdsourced survey.

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jleader
Corrected headline: "How safe would humans say this street looks?"

Not the same question at all.

While the research into computer vision and machine learning is interesting,
as a human I'd like to know when my intuition about safety is wrong, not just
have a machine that can mimic my intuition.

~~~
HillRat
Unfortunately, once you place the imprimatur of machine learning upon it,
people will tend to conflate "perceived safety" with "actual safety." At the
extreme, it becomes a way to create an apparent but false confirmation of the
prejudices of the crowd.

This is one of those rare cases in computer science research where there is an
actual ethical component to the work being done; while machine scoring
landscapes according to their relative attractiveness is fairly harmless,
scoring them according to "perceived safety" _without mentioning the obvious
limitations thereof_ is heading towards trouble. As I recall, there was a
crowdsourced app last year that supposedly would inform its users if they were
in "bad" neighborhoods (using the opinions of other users to tag areas), and
it received a wave of criticism for essentially similar reasons.

~~~
duderific
If it was crowdsourced, why would you need an app to know if you were in a bad
neighborhood? Your perception should be roughly similar to those who had
contributed their opinions as crowd source data. Kind of like needing an app
to tell you it's raining when you're standing in a downpour.

~~~
notahacker
The act of using the app can increase that perception though; if you get
mugged whilst checking your smartphone in the middle of the street it's a
pretty good indicator the area isn't safe :-)

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JumpCrisscross
Would be fascinating to see how these data correlate with crime statistics, in
particular for violent crimes. Perhaps more fascinating would be if changes in
these scores could actually _predict_ changes in crime levels. I'm sure the
authors–or their colleagues-are already working on this.

~~~
awhitty
This isn't the best visualization, but I just spent a couple minutes
overlaying the New York map with Trulia's crime risk heat map[1,2]. I think
the important takeaway is that the green dots visible in the red areas can be
interpreted as false negatives for danger. Of course, this is a really, really
rough sketch so take it with a grain of salt.

[1]: [http://www.trulia.com/local/new-york-
ny/tiles:1|points:1_cri...](http://www.trulia.com/local/new-york-
ny/tiles:1|points:1_crime)

[2]: [http://imgur.com/HOuJFKZ](http://imgur.com/HOuJFKZ)

~~~
jrockway
The crime map seems awfully suspicious to me. It appears to be more of a
population density map than anything. All the red areas south of 34th St. just
look like common places for people to hang out (and drink alcohol).

I think what people really want is a crime map that plots crimes committed at
random, rather than drinking buddies beating each other up.

I also took a look at vermont, and the red areas were because of things like
"traffic stop" or "e911 hangup".

~~~
icommenttoo
Check this map instead
[http://i.imgur.com/QwvATt1.jpg](http://i.imgur.com/QwvATt1.jpg) The authors
already did that analysis, but they incorporated population, area, age, income
and perception of safety into a statistical model used to predict violent
crimes.

It is important to go beyond the bivariate case here. Comparing streetscore to
crime is too simple to be meaningful if other co-variates are not taken into
account. For the full description
([http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjourna...](http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0068400))

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hawkharris
It's actually well understood which landscape features contribute to or
prevent crime. Things like sidewalks and bright street lamps have a positive
effect (no surprise there). Bushes, certain fences and other objects that
obstruct the view from the road can have a negative effect. As a reporter I
once did a ride-along with a police sergeant who took it upon himself to cut a
set of hedges (with the property owner's permission, of course) that helped
facilitate drug deals and prostitution.

The point is, I wonder if the machine learning approach used here is overly
complex. After all, the set of environmental factors affecting crime is so
well understood and thoroughly researched that you could focus on detecting
tried-and-true things such as sidewalks. This would entail applying a clear
set of rules instead of using the relatively unsupervised approach with
training data. To be fair, ML is a complicated subject and I'm not an expert;
maybe their approach draws heavily on these things.

EDIT: I understand that perception, rather than the actual crime rate, is the
focus of this research. Still, there seems to be a tight correlation between
the features that are known to be dangerous and those that appear sketchy. The
major ones - an absence of lights, few walkways, etc. - are obvious to most
pedestrians.

~~~
jamesbritt
_Things like sidewalks and bright street lamps have a positive effect (no
surprise there)._

There may be some surprise there.

The correlation between street lighting and safety is not obvious.

"In 2008, PG&E Corp., the San Francisco-based energy company, reviewed the
research and found 'either that there is no link between lighting and crime,
or that any link is too subtle or complex to have been evident in the data.'"

[http://www.bloombergview.com/articles/2013-02-24/turn-
down-t...](http://www.bloombergview.com/articles/2013-02-24/turn-down-the-
city-lights-and-make-streets-safer)

[http://www.popcenter.org/responses/street_lighting/2](http://www.popcenter.org/responses/street_lighting/2)

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mcdan
One thing they should consider doing is using the average of the surrounding
points to rise or lower the score of a particular spot. For instance, near
where I live there a number of examples where there is a green dot on one side
of the street and a red on the other, just down the block they reverse, this
doesn't make any objective sense at all.

~~~
pimlottc
I'd be cautious about that. You can easily have a dark foreboding alleyway
just off a bright, well-lit street. Safety gradients (perceived and actual)
can be quite steep.

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nacho_weekend
Interesting program. This info needs to be taken with a grain of salt, or
somehow correlate to existing statistical information on certain neighborhoods
- I doubt ~400 W 63rd Street in Chicago is a 9.1. The theory of it is great
for visualization, and I'd love to see more incorporated data in the future.

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sirdogealot
I remember clicking through those same pictures a few days back and I was
under the impression that I was telling the observers what pictures I thought
were more beautiful, not safer.

Did they just re-label the same data here or is this another separate program?

~~~
sp332
Yup. The data is from here
[http://streetscore.media.mit.edu/data.html](http://streetscore.media.mit.edu/data.html)
and it's used in all PlacePulse surveys.
[http://pulse.media.mit.edu/](http://pulse.media.mit.edu/) You can choose
which question you want from the big menu at the top.

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ChikkaChiChi
I guess this would be a good data point in building a "safety" score, but by
no means would I consider this telling me if an area was "safe."

Crime statistics, thoroughfare, property value trends, population density and
other environmental factors are just a few of the things I would consider
looking at as well if I was compiling data.

Interesting start to an interesting question. I'm just not comfortable with
this "judging a book by its cover" mentality to this...

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nateguchi2
The police in the UK actually have a map of all crimes that have taken place
recently in a neighbourhood [1], I think this is a better way of going about
the issue, crime rates seem to correlate more closely to safety than how a
place looks, I think.

[1] [http://www.police.uk/](http://www.police.uk/)

~~~
icommenttoo
I think you fail to understand the point. The point is not too replace a map
of crime, but to help develop variables that can help explain the location of
crime. Look at what they did in their 2013 paper
([http://pulse.media.mit.edu/papers/](http://pulse.media.mit.edu/papers/))
that is exactly that.

The problem they are trying to solve is that there are no good measures of
perception to evaluate whether the environment affects crime or not. This is
an old question for which there has been much research, as it is explained in
the point 7 of their FAQ.
[http://streetscore.media.mit.edu/faq.html](http://streetscore.media.mit.edu/faq.html)

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infinitebattery
Being from Detroit, I found the map particularly interesting to look at.

Personally not a fan of the UI currently. However there could be a lot done
with the itself- such as providing safer routes by utilizing the data.

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nkozyra
How badly does gentrification break this system? After all, any cred you have
as a trust fund hipster is lost if your home looks like it's in a "safe" part
of town ;)

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Spooky23
It's a good start. With individual pictures it's sketchy, but on the aggregate
the map I looked at trends with my own perception of the area, generally
speaking.

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nisse72
Somewhat related:
[https://news.ycombinator.com/item?id=8005529](https://news.ycombinator.com/item?id=8005529)

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jermaink
You should also checkout project Pantheon:
[http://pantheon.media.mit.edu](http://pantheon.media.mit.edu)

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bluthru
They should add an urban planner to the team.

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mistaken
It seems to classify open areas as unsafe and photos with lots of variation as
safe.

