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Congestion Pricing and the Surveillance State July 23, 2019

Posted by Peter Varhol in Machine Learning, Technology and Culture.
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Not many people are aware that New York City is instituting congestion pricing, both to ease traffic (mostly in Manhattan) and to provide additional funding for public transportation.  Both are laudable goals.  This is to be implemented by using one or more cameras to take a photo of each car’s license plate, and generate a bill that can be sent to the owner of that car.  One of the proposals for the technology to implement it was delivered by a company called Perceptics.

Perceptics proposed a solution that included the ability to identify cars not only by license plate number, but also by the characteristics of the car itself.  The car is like a fingerprint, the company says.  It has characteristics that provide a unique identification.

Still okay, but it’s starting to get a little bit out there in credulity.

Then we find out that Perceptics proposes using a large number of cameras across the congestion zone, back-ended by AI-type algorithms and Big Data analytics whose purpose is to determine the number of people in the car, who they are (through facial recognition), where they came from, where they are going, and how often they do so.

Go back and read that sentence again.  To send out congestion pricing bills, they want to know who is in the car, where it is going, and how often it does so, among other things.  Even I know that is some serious overkill for the stated purpose.  But that data can be used for a lot of other things that have nothing to do with congestion pricing.  In fact, it provides a window into almost everything thing that someone who drives into the congestion area does.

London has been wired extensively with CCTV cameras since at least the 1990s.  Today, the best estimate for the number of CCTVs in London is 500,000.  The average person in London is caught on camera 300 times a day.  Today, thanks to facial recognition and analytics, you don’t have dozens of analysts sorting through tapes to desperately find a particular person, but rather an unstructured cloud database that with the right algorithms for searching and finding a particular person in a particular location within seconds.

Those numbers alone should blow your mind.

I don’t know why proposals like this don’t bother people.  I’m guessing that the cameras are unobtrusive, people don’t see them, and can push the abstract thought of surveillance out of their minds.  Further, they reason that they are not criminals, and these types of technology serve to protect rather than harm them.  Kind of the same reasons why they post anything they like on Facebook, without thought of the consequences.

Today, the cacophony of opinion says that if you’re not doing anything wrong, you are silly or unpatriotic to be afraid of the surveillance state.  Wrong.  The algorithms are by no means perfect, and could mistake you for someone else, sometimes with disastrous consequences.  Further, the data could be stolen and used against you.  As a guiding principal, we as free individuals in a free country should not be subject to constant video scrutiny.

Yet here we are.

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Comments»

1. Your Face Looks Familiar | Cutting Edge Computing - August 17, 2019

[…] gets worse with face recognition. I wrote recently that a vendor has proposed using facial recognition software to identify and track individual […]


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