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What Next TBD: The Man Who Turned You Into Data

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Slate Podcasts

News, Business, Society & Culture

41.1K Ratings

🗓️ 7 October 2023

⏱️ 24 minutes

🧾️ Download transcript

Summary

Hank Asher was a lot of things: a Florida condo maven, a drug runner, a DEA informant—and a tech visionary who created the mixed blessing of turning everyone’s online activity into an unshakable shadow profile. Guest: McKenzie Funk, reporter for Pro Publica and the author of The Hank Show If you enjoy this show, please consider signing up for Slate Plus. Slate Plus members get benefits like zero ads on any Slate podcast, bonus episodes of shows like Slow Burn and Dear Prudence—and you’ll be supporting the work we do here on What Next TBD. Sign up now at slate.com/whatnextplus to help support our work. Learn more about your ad choices. Visit megaphone.fm/adchoices

Transcript

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0:00.0

For decades there has been something that's keeping tabs on you. It's called a persistent

0:12.0

identifier or PID. One way to think about them is it's like a social security number,

0:18.7

but one that is not assigned to you by the government but by a private company.

0:23.9

That's Mackenzie Funk, a reporter for ProPublica and the author of The Hankship. A book about

0:29.0

the man largely responsible for these shadow social security numbers, Hank Asher. Mackenzie

0:36.4

looked up one of his persistent identifiers, a Lex ID compiled by Lexus Nexus, one of

0:42.4

many companies stockpiling data on us. His Lex ID knew a lot about him, beyond the details

0:49.0

you'd find and say a credit report. The data even threw some shade his way.

0:54.7

After it performed my Ernie potential.

0:57.3

Ouch. Mackenzie's Lex ID took every bit of data it could find on him to paint a picture

1:03.5

of the man it thought he was. But it's not just Mackenzie, it's everyone.

1:09.2

You can see where they lived. You can see what kind of neighborhood that was. You can

1:14.1

see what college they went to and what jobs they had. They have all of your relatives.

1:19.9

Anyone could map your social network and see, okay, this person came from money. This

1:24.6

person had a lot of privilege in life. This person went to a pretty good college and in

1:30.3

case of my underperformance. Yeah, I grew up comfortably middle class. I went to a small

1:36.6

college and then I became a journalist. So there you have it. They could see where I've

1:43.1

lived. If I owned the house, what kind of cars I have, every job I've had, every opportunity

1:47.5

I've had.

1:49.5

And with all this data, these companies are able to map not just your past life, but what

1:56.6

your future might look like too. You can derive maybe a model of their health is based on

2:02.2

the neighborhoods the person has lived in. The air quality, the access to transportation,

...

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