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To the Point

The Downside of Data Mining

To the Point

KCRW

News

4.4 β€’ 583 Ratings

πŸ—“οΈ 21 October 2014

⏱️ 52 minutes

🧾️ Download transcript

Summary

Whatever you do on line β€” from filling out forms to making innocent requests for information β€” is subject to data mining. That can lead to unflattering profiles or put you on lists that can be damaging β€” even though the data is often wrong. We hear calls for transparency and regulation.

Transcript

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0:00.0

From KCRW in Santa Monica and PRI, Public Radio International, this is To the Point.

0:07.9

The downside of data mining.

0:14.0

Hello again, I'm Arminolny, and this is To the Point from Public Radio International,

0:17.8

a daily look at the issues Americans care about most.

0:20.4

Your personal data is all over the Internet, and it's up for sale, not just to marketers,

0:24.8

but to financial institutions and possible employers.

0:28.0

If you've just applied for a warranty or Googled somebody else's chronic disease,

0:33.1

you could be on a list of bad credit risks or unsuitable employees.

0:37.1

If the information is wrong, there's not much you can do to correct it because it's secret,

0:41.8

and there's almost no regulation.

0:43.9

And don't forget about the NSA.

0:45.5

It might be secretly mining even the data of its own corporate partners.

0:49.9

Today's talking point, do campaign contributions threaten the independence of judges?

0:55.0

First, here's the news.

1:01.4

Listen to KCRW's 24-hour all-news channel.

1:05.2

Stream BBC World Service, NPRW programs, continuous coverage and accessible via our smartphone app or online at kCRW.com.

1:19.7

Support for To The Point comes from the members of KCRW and from the Public Radio International Program Fund.

1:26.6

Hello again, we're not only back with

1:27.9

To the Point. Whatever you do online, from filling out forms to making innocent requests for

1:32.5

information, it's subject to data mining. That can lead to unflattering profiles or put you on

1:38.5

lists that can be damaging even though the data turns out to be wrong. We hear calls for transparency

1:43.5

and for regulation.

...

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