Where did it come from?

The personal data economy took root around 2012, when Google changed its privacy policy to allow all its various services to combine your data across everything you did on their platform. It ushered in "the platform" era.

It was largely a Hail Mary to not lose ground to Facebook, which was already monetizing based on people's data, posts, and images.

Hey, thought the companies, who in the wake of the financial crisis were worried about causing another Dot Com Crash. We are sitting on a gold mine of user data! Stuff people are just inputting into the web! Into our websites! We should monetize it!

Never mind that you think you're just talking to a friend, or buying a new notebook, or looking for decorating ideas, or seeking health care information. If they snoop on you while you're doing it, they can learn more about who you are and what you care about. This helps them send you targeted ads, but it also helps them to figure out what makes people like you tick.

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The Personal Data economy relies on everything you do on the internet leaving some kind of trail. Perhaps it's the photos you uploaded and tagged of your dad's birthday party. Perhaps it's a user log that records everything you looked at on a web store, browsing for a gift for your neice or buying supplies for a camping trip. Anything that you do on the web, data sniffers are looking to build a profile about you so that they can sell access to your eyeballs to advertisers.

Advertisers largely use a "real time bidding" service, also innovated by Big Tech, so that companies bid for your eyeballs while the website loads.

Even if your ad blocker is on, you may still be feeding the companies data behind the scenes, which they will use to target (if not you, then) other people who they presume have similar habits to you.

Maybe because they live in the same region, maybe because they are the same age or have the same religion or skin color or political beliefs. They're looking for target markets. This has given them the ability to target individuals and lump us into different categories, so we all see different internets and information every time we log in.

It has also turned the Internet into a grand targeting machine -- for their profit.

Targeting through Personal Data

The personal data economy (and its offspring, "generative AI") were born of specific advances in data processing that we call machine learning. Machines can 'learn' by frequencies of association -- what word is likely to come next, what products people are likely to buy together, etc.  To do this, they have developed ways of associating data to know what data typically comes together and which things are categorically separate.

The initial approach to this was based on relational databases, which is just a special way of saying a way of keeping data in such a way that preserves relationships between items in the database, or across datasets.

Say you have three datasets about different things -- music, shopping, and email, for instance. But they all have an email address or a phone number in common. With that one element in common, it becomes possible to tie those three datasets together and associate them with an individual.

That's not all. With advances in data mining, it was soon clear that you could pinpoint somone with just three pieces of information that didn't have a single element in common -- a phone number, an E-Z pass ID, a zip code, for instance. It turns out that bringing these three disparate things together, you end up with unique combinations. Just three pieces of information, even if they are about disparate things, are enough to pinpoint an individual. The needle in the haystack is found.

Another issue has to do with single datasets, because if they're capacious enough and contain enough different kinds of information, they can also be de-anonymized and individuals can be identified. My Princeton colleague Arvind did this with the Netflix dataset about a decade ago: it turns out, your combination of preferences for slasher films, rom coms, and sci fi is unique to you. So we want to be careful about how much of the many aspects of our lives we give to one company as well.

There is more, of course, and systems have moved on since them too. But a key element here is that companies profit by bringing your datasets about disparate things together. They can do that through having single ID's or sign-on's (phone numbers, etc). Or they can do that through owning many digital systems and elements and bringing them together.  Or they can do that by having a big enough catalog that you will show many sides of your personality while using them.

How to De-Platform the Platforms

You can see how platforms got so good at this game, and how our every interaction on them fed their empire. If we want to break that party up, we need to do what we can to keep our datastreams separate.

Some systems will help you do this. They will protect your data to the death. They will erect a Fort Knox just for you. They will keep working at privacy and protection, because that is the core of their product. In the coming weeks, you will come to know these companies and explore their services.  You will migrate some of your services over to them. If they betray you, you will move again. You will learn how to figure this out and it will feel more like a fun game than a chore. 

Many lawyers and public policy advocates are also helping you do this, by introducing legislation that makes this kind of monetization illegal. I recommend you support them (like the Electronic Frontier Foundation).

For everything else, you have a few other options. I'll be posting tactics to learn how to spread your data traces far and wide and evade detection, while undoing the data economy and its platform giants at the same time.