The rewards and risks of lying to tech companies

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DIY data poisoning can feel subversive, but is it?

, and it’s a technique that aims to obscure your true identity by generating a large quantity of inaccurate information. The concept refers to synchronized attacks that deliberately seek to erase or alter the datasets fueling a platform’s algorithms to make them underperform and fail. This requires specific skills and know-how, as well as aYou may not have any of those things, but you can use the same principle to protect yourself from constant surveillance online.

The easiest way to engage in data poisoning is to use a name, gender, location, and date of birth that is not yours when you sign up for a service. To advance beyond that baseline, you can like posts you don’t actually like, randomly click on ads that don’t interest you, or play content that’s not to your taste. For the last of those options, just press play on whatever platform you’re using, turn off your screen, turn down the volume, and let it run overnight.

Playing content that doesn’t interest you while you sleep may throw off the recommendation algorithms on whatever platform you’re using, but doing so will also require resources you may not have at your disposal. You’ll need a device consuming electricity for hours on end, and an uncapped internet connection fast enough to stream whatever comes through the tubes. Messing with the algorithms also messes up your user experience.

Also, just as eating one salad doesn’t make you healthy, your data poisoning schemes must be constant to make a long-lasting impression. It’s not enough to click on a couple of uninteresting ads here and there and hope that’s enough to throw off the algorithm—you need to do it repeatedly to reinforce that aspect of your fake profile.

But the biggest caveat of all is uncertainty—we just don’t know how much damage we’re doing to the data tech companies and advertisers are collecting from us. Studies suggest thatcan significantly affect the performance of an algorithm that’s trying to figure out what you like. This means that even clicking on a small percentage of uninteresting ads might prompt an algorithm to put you in the wrong category and assume, for example, that you’re a parent when you’re not.

 

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