Stolen Data is a Risk, Here’s an Example of Altered Data That is Worse
We can argue about how damaging constant surveillance is for the public. You might not care that someone, somewhere, knows everything about where you’ve been or who you’ve been with. You may think you have nothing to hide.
For you, the danger of someone knowing all of your activities might not seem like a huge risk. You “have nothing to hide”.
You should be worried about the other risks of all that data, though, and this story from the UK is a pretty good example.
The UK uses Automated License Plate Readers extensively. They issue speeding tickets, charge impact fees for areas like the center of London, and accumulate a ton of data about where citizens go, how they drive, etc.
However, that data can be manipulated in very low-tech ways.
The problem is that people are making copies of other drivers’ license plates, and using them on similar-looking vehicles — generally the same model and same color — to break the law with impunity.
The entire system is based on the license plate database being connected to all of the automated plate readers. All it took for this to become a problem was for part of that not to stay safe. Since the license plate database isn’t, anyone can create a fake license plate, pop it on a similar-looking vehicle, and the collected data is tainted. All those people who had nothing to hide now have a system that assumes they were driving illegally, causing accidents, etc. They are facing actual fines, increased insurance costs, and possible arrests because of surveillance data that’s been hacked. Data that should show them as innocent but false information has been injected into it.
This is only small potatoes. It takes very little skill to make a fake license plate. Imagine what highly skilled hackers with AI tools could do with access to surveillance systems if they decide to target you individually. How will you prove your innocence when photos or videos show you aren’t? Since that risk isn’t going away, we should be looking at why we are collecting all of this data in the first place.
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