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As we all know, data targeting and profiling online can be used for both good and bad things.
For instance, I love how my online grocery store is profiling and targeting me (with my consent). Whenever I shop, it remembers what items I usually buy, it offers me a way to mark selected items as favorites, and then it tailors my shopping experience around those.
For instance, if I visit it right now, it will give me a list of all my favorite items that are currently on sale. It also gives me a way to maintain lists of items I always need, so I don't forget to buy something essential.
It's not perfect, but it's a great way to think about data, profiling and targeting.
However, most of the web isn't like this, and within the ad tech world, it's almost always used in the wrong way. And so in this article, I'm going to talk about this, but in particular look at the problem with how Twitter derives 'interests'.
There are generally four problems today.
The first problem is privacy violation. Most ad tech companies operate in the dark, using shady tactics, non-transparent methods, essentially acting like a stalker for profit.
I don't have a problem with my grocery store tracking what I buy, in a transparent and valuable way. I also don't have a problem with YouTube tracking what videos I watch so as to improve my experience there, just as I have no problem with a magazine knowing what articles I read so that they can improve their journalism.
But the idea of allowing hundreds of mostly unknown ad tech companies to track my every move and build up giant databases about me is not acceptable.
There is no functional society where you would consider that to be okay.
The second problem with ad tech is the complexity. I talked about this problem in one of my newsletters, where I illustrated how the complexity of the ad tech ecosystem drains the revenue publishers make (the ones actually showing the ads to people).
This is also not acceptable.
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