[cameldrv]

The state of the art has advanced so far in doing this. I remember way back in 2017, 9 years ago now, at the Scaled ML conference, Claudia Perlich gave a presentation about using RTB data to target ads. When she got to slide 23 [1] my jaw hit the floor. This was a small ad targeting company, and again, 9 years ago. Here's what they publicly said they had:

Consumer Events:

• 100B DailyEvents

• 20+ data integrations

• Clickstream

• App usage

• Ecommerce sales

• Cash register sales

• Precise Location

Context Data:

• User

• Device

• Location

• URL

• IP

• 200 Million Devices Daily

Universal DataStore

• 50 Trillion Record Consumer History

That's about 150,000 datapoints on everyone in the U.S. For a small company. In 2017.

[1] https://cdn2.hubspot.net/hubfs/6212008/ScaledML%20Media%20Ar...

[taurath]

The personalization stuff is why I avoided ML like the plague - all these folks making huge money but all of it to build a surveillance state for advertisers. Already having value my privacy enough to never work for an ad revenue company, they all seemed beyond the pale.

[rdevilla]

See also Dark Data from DEFCON 25: https://youtube.com/watch?v=yWqdTVQsnPg

But it doesn't need to be marketed in such a sinister fashion. In 2012 when Google Maps informed me of delays along my usual commute, complete with a GPS trace of my route home, completely unprompted, I started turning off location history (lol, yeah right). I didn't even know they were collecting that data, much less analysing it that hard.

These days, that would be considered a feature - not a dystopian hellhole, and you would be a Luddite for turning off this new smartphone augmented brain. The product will make you happy. [0]

Welcome, to City 17. You have chosen, or been chosen, to relocate to one of our finest remaining urban centers. It's safer here.

[0] https://youtube.com/watch?v=5PZ73nLZaqc