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StreetScore scores a street view based on how safe it looks to a human

streetscore.media.mit.edu

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Re: StreetScore scores a street view based on how safe it looks to a human

#11

Post by HillRat »

jleader wrote: post #8

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.

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.

Re: StreetScore scores a street view based on how safe it looks to a human

#12

Post by notahacker »

jleader wrote: post #8

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.

"Would humans say" is also subtly different from "do humans actually think". The Williamsburg bridge in NY has a particularly odd pattern where pictures showing steelwork have particularly "safe" ratings and pictures showing river panoramas have extremely low ratings. Maybe HNers other than me have an idea of why that might be, but I find it hard to believe the steelwork is incredibly reassuring and the view of Manhattan behind utterly terrifying as the polarized figures would have you believe

Re: StreetScore scores a street view based on how safe it looks to a human

#13

Post by zheshishei »

test431 wrote: post #5
jamesbritt wrote: post #4

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 assorte…

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…

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.

Re: StreetScore scores a street view based on how safe it looks to a human

#14

Post by awhitty »

JumpCrisscross wrote: post #6

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.

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...

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

Re: StreetScore scores a street view based on how safe it looks to a human

#16

Post by 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.

Re: StreetScore scores a street view based on how safe it looks to a human

#17

Post by 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...

Re: StreetScore scores a street view based on how safe it looks to a human

#18

Post by beejiu »

jamesbritt wrote: post #4

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 assorte…

We have odd perceptions of safety. If you look at the website, you'll see the first photo labelled 0.51 for safety. But, honestly, what's the worst that could happen there? There'll be no theft, because there are no houses. There will be less street crime, because there are no people. In fact, the one rated highest is probably the least safe, as it would likely be targeted by thieves looking for high valued property in houses from a nice neighbourhood. As far as murders and violence is concerned, these crimes are mostly targeted and it doesn't really depend on where you live.

Re: StreetScore scores a street view based on how safe it looks to a human

#19

Post by 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"

Re: StreetScore scores a street view based on how safe it looks to a human

#20

Post by duderific »

HillRat wrote: post #11
jleader wrote: post #8

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.

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 accor…

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.
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