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(bright music)
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- A man checks his smartwatch.
- Our modern,
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00:00:07,540 --> 00:00:10,743
digital lives offer limitless
convenience, community,
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00:00:10,776 --> 00:00:14,080
and easy to access everything.
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00:00:14,113 --> 00:00:16,783
- [Speaker] The internet opens
unbelievable opportunities.
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00:00:18,517 --> 00:00:21,621
- [Host] But there's a
trade-off. Your personal data.
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00:00:21,654 --> 00:00:23,256
- [Speaker] Pretty much
everything you do on the web
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00:00:23,289 --> 00:00:25,058
is being tracked and logged.
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00:00:25,091 --> 00:00:26,826
- Who you are, what you're
doing, and where you're going.
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00:00:26,859 --> 00:00:28,394
- This is the mothership.
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00:00:28,427 --> 00:00:31,597
Can you show me what I've
inadvertently given up?
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00:00:31,630 --> 00:00:34,834
And that personal data
is worth a fortune.
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00:00:34,867 --> 00:00:37,203
- People expect it to
grow to $400 billion.
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00:00:38,337 --> 00:00:40,440
- To completely
avoid data collection
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00:00:41,507 --> 00:00:45,078
requires you to
go live in a cave.
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00:00:45,111 --> 00:00:46,679
- [Host] Thankfully,
there are tools
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00:00:46,712 --> 00:00:50,450
to help maintain your
privacy and security online.
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00:00:50,483 --> 00:00:54,487
- Let's create some strong
and unique passwords.
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00:00:54,520 --> 00:00:56,522
- Everything has
privacy settings.
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00:00:56,555 --> 00:00:59,625
We can dial to whatever
level we feel comfortable.
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- [Host] And some coders are
rewriting the rules of the web.
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00:01:03,195 --> 00:01:05,331
- The decentralized
web is our antidote
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00:01:05,364 --> 00:01:07,433
to the web as we
now think of it.
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00:01:07,466 --> 00:01:09,502
- New technologies
can proliferate
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without centralized control.
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- This is about technological
self-determination.
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- [Host] Secrets in your
data right now on "NOVA."
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(triumphant upbeat music)
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ANNOUNCER:
As an American-based supplier
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to the construction industry,
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Carlisle is committed to
developing a diverse workplace
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that supports
our employees' advancement
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00:01:41,467 --> 00:01:43,436
into the next generation
of leaders,
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00:01:43,469 --> 00:01:45,671
from the manufacturing floor
to the front office.
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00:01:45,704 --> 00:01:47,574
Learn more at Carlisle.com.
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00:01:55,214 --> 00:01:57,650
(phone camera clicking)
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PATEL:
Our world runs on data.
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When you're shopping online,
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00:02:02,154 --> 00:02:04,090
streaming
your favorite shows...
40
00:02:04,123 --> 00:02:05,158
(mouse clicking)
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00:02:05,191 --> 00:02:06,592
posting family pics--
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00:02:06,625 --> 00:02:08,127
that's all your personal data
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00:02:08,160 --> 00:02:10,062
leaving your device.
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00:02:10,095 --> 00:02:12,532
(on phone):
What's up, everyone?
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I'm about to head to
the hospital
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00:02:13,766 --> 00:02:14,734
for a night shift...
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00:02:14,767 --> 00:02:17,103
(voiceover):
I'm Alok Patel, a pediatrician,
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00:02:17,136 --> 00:02:17,970
medical journalist,
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00:02:18,004 --> 00:02:21,207
and all-around
social media enthusiast.
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00:02:21,240 --> 00:02:22,508
(on phone):
Just got here at the
children's hospital...
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(voiceover):
I kinda love our
connected lives,
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00:02:24,210 --> 00:02:26,078
and I haven't been shy at all
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00:02:26,111 --> 00:02:29,282
about sharing mine
pretty publicly.
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(on phone):
30 million children...
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(voiceover):
And I know that sharing
personal data
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00:02:33,185 --> 00:02:34,187
can have major upsides.
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00:02:34,220 --> 00:02:35,521
The media's reported
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00:02:35,554 --> 00:02:37,190
on some of
the most dramatic examples.
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NARRATOR (archival):
...is conducting several studies
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to see how far wearables can go
in detecting disease.
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A California man,
rescued yesterday
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after going missing
credits a social media post
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for helping save his life.
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00:02:48,400 --> 00:02:50,336
Six out of ten people
with Alzheimer's or dementia
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will wander away from home,
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00:02:51,637 --> 00:02:54,207
and that's where
this little box comes in.
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PATEL:
There's no doubt,
our data is out there,
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00:02:57,710 --> 00:03:00,179
but did you ever
wonder where it goes
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00:03:00,212 --> 00:03:02,148
and how it's used?
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00:03:02,181 --> 00:03:03,216
I do.
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00:03:03,249 --> 00:03:06,018
I want to know: what are the
benefits of sharing
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00:03:06,051 --> 00:03:07,587
and the risks?
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00:03:07,620 --> 00:03:11,123
And what can we do to
make our connected world safer
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00:03:11,156 --> 00:03:14,060
and just generally better
for everyone?
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00:03:18,430 --> 00:03:20,633
First, the basics.
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I want to know:
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how much personal data
have I been sharing?
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Meet Hayley Tsukayama,
tech journalist
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and data privacy advocate.
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(chuckles)
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PATEL:
You must be Hayley.
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Hi, nice to meet you.
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What is going on?
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(voiceover):
Okay, hold on,
wasn't expecting this.
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She's already got
my whole life up on the screen.
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00:03:41,520 --> 00:03:44,490
So this is a data report
gathered about you
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00:03:44,523 --> 00:03:46,726
from social media posts,
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from the images of you
that may be on the internet,
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00:03:48,661 --> 00:03:51,130
from publicly available
information.
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00:03:51,163 --> 00:03:53,132
This is like
a family business.
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00:03:53,165 --> 00:03:54,634
That's my dad's
cell phone number.
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00:03:54,667 --> 00:03:56,469
Why is this available?
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00:03:56,502 --> 00:03:58,671
(groaning):
Oh, this is my address!
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00:03:58,704 --> 00:03:59,839
This is just available?
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00:03:59,872 --> 00:04:00,773
Just available online.
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00:04:00,806 --> 00:04:02,642
Okay,
you guys are going to
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00:04:02,675 --> 00:04:04,577
blur all this, right?
Please?
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00:04:04,610 --> 00:04:07,079
There's-- oh, okay, cool,
there's my cell phone number.
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00:04:07,112 --> 00:04:09,749
Oh, this is concerning.
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00:04:09,782 --> 00:04:12,551
As a medical doctor,
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00:04:12,584 --> 00:04:15,021
we all have
license numbers
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00:04:15,054 --> 00:04:17,256
and issue dates
and expiration dates.
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(chuckling):
And it's literally right here.
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00:04:19,124 --> 00:04:20,793
This is so weird,
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00:04:20,826 --> 00:04:22,428
these are the names
of my neighbors
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from my childhood home.
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(whispering):
Why do you have
this information?
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00:04:27,166 --> 00:04:29,535
Like, I haven't
seen these names in...
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00:04:29,568 --> 00:04:31,037
years.
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00:04:31,070 --> 00:04:31,971
(voiceover):
Not gonna lie,
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00:04:32,005 --> 00:04:34,640
I expected some of
my data to be out there,
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00:04:34,673 --> 00:04:35,641
but this is...
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this is just creepy.
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00:04:38,210 --> 00:04:39,111
How is there a report
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00:04:39,145 --> 00:04:42,415
about who my neighbors were
in the '80s?
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00:04:42,448 --> 00:04:44,283
LEVY:
You can be assured that
pretty much
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00:04:44,316 --> 00:04:45,551
everything you do on the web
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00:04:45,584 --> 00:04:46,552
and with a browser
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00:04:46,585 --> 00:04:48,220
is being tracked and logged.
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00:04:48,253 --> 00:04:50,523
Where you go, what you look at,
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00:04:50,556 --> 00:04:51,824
what apps you use.
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00:04:51,857 --> 00:04:54,660
SAFIYA NOBLE:
Modern life has been arranged
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00:04:54,693 --> 00:04:57,096
so that every aspect of
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00:04:57,129 --> 00:04:58,597
what we do and how we live
can be captured.
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00:04:58,631 --> 00:05:02,001
MEREDITH WHITTAKER:
They pick up our faces
as we walk down the street.
126
00:05:02,034 --> 00:05:06,238
They track our keystrokes
while we're at work
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00:05:06,271 --> 00:05:08,040
on behalf of our employer.
128
00:05:08,073 --> 00:05:08,941
(keys clacking)
129
00:05:08,974 --> 00:05:10,676
GALPERIN:
And ad networks use a bunch of
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00:05:10,709 --> 00:05:13,112
creepy and nefarious ways
of figuring out
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00:05:13,145 --> 00:05:14,747
who you are, what you're doing,
and where you're going.
132
00:05:15,647 --> 00:05:18,150
PATEL:
What happened to the web
I grew up with?
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00:05:18,183 --> 00:05:21,087
♪ ♪
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00:05:21,120 --> 00:05:24,123
I came of age when the internet
was a fun and weird party,
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00:05:24,156 --> 00:05:25,157
and everyone was invited.
136
00:05:25,190 --> 00:05:27,226
Remember GeoCities,
137
00:05:27,259 --> 00:05:29,128
AOL Instant Messenger,
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00:05:29,161 --> 00:05:32,031
or the dancing "ooga chacka,
ooga chacka" baby?
139
00:05:32,064 --> 00:05:33,532
♪ ♪
140
00:05:33,565 --> 00:05:35,435
Today, it's clear
that innocence is gone.
141
00:05:36,668 --> 00:05:37,704
Is the party over?
142
00:05:40,205 --> 00:05:44,643
To understand the present,
I want a refresher on the past.
143
00:05:44,676 --> 00:05:46,112
(machinery whirring)
144
00:05:46,145 --> 00:05:48,581
So I'm visiting
the Computer History Museum
145
00:05:48,614 --> 00:05:50,149
in Silicon Valley.
146
00:05:50,182 --> 00:05:51,684
(video game music,
Patel chuckling)
147
00:05:51,717 --> 00:05:54,387
MARC WEBER:
Okay, I'm headed
straight for the sun...
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00:05:54,420 --> 00:05:56,789
PATEL:
I'm meeting
computer historian Marc Weber.
149
00:05:56,822 --> 00:05:58,758
What a maneuver!
There's a straight line
150
00:05:58,791 --> 00:06:00,292
of bullets coming
right at you--
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00:06:00,325 --> 00:06:01,460
(exploding sound effect,
Patel groans)
152
00:06:01,493 --> 00:06:02,695
(voiceover):
...Who just wasted me
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00:06:02,728 --> 00:06:04,764
in the cosmic battlefield of
"Space War,"
154
00:06:04,797 --> 00:06:06,532
one of the first video games.
155
00:06:06,565 --> 00:06:09,001
(laughing)
156
00:06:06,565 --> 00:06:09,001
This is actually really fun.
157
00:06:09,034 --> 00:06:10,569
♪ ♪
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00:06:10,602 --> 00:06:12,638
This is cool.
159
00:06:12,671 --> 00:06:16,108
ICBM computer from
a nuclear missile.
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00:06:16,141 --> 00:06:17,243
Woah.
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00:06:17,276 --> 00:06:19,044
Human-computer interaction.
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00:06:19,077 --> 00:06:21,447
PATEL:
Now, this looks fascinating.
163
00:06:21,480 --> 00:06:22,615
I can't tell if this is like,
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00:06:22,648 --> 00:06:25,518
this universal clock
apparatus,
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00:06:25,551 --> 00:06:27,052
or what's happening here?
166
00:06:27,085 --> 00:06:30,456
This is the first
punch card machine.
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00:06:30,489 --> 00:06:33,058
And this was an invention
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00:06:33,091 --> 00:06:35,694
to make the U.S. census
faster.
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00:06:35,727 --> 00:06:36,728
PATEL (voiceover):
It's kind of wild,
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00:06:36,762 --> 00:06:40,132
but the dawn of automated
personal data collection
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00:06:40,165 --> 00:06:41,801
looks like this--
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00:06:41,834 --> 00:06:45,304
census info poked into
humble little punch cards.
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00:06:45,337 --> 00:06:48,107
Marc, can you explain
punch cards to me?
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00:06:48,140 --> 00:06:49,141
Because when
I think punch cards,
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00:06:49,174 --> 00:06:51,544
I'm thinking
lottery tickets,
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00:06:51,577 --> 00:06:55,147
or "buy nine cups of coffee,
and your tenth is free."
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00:06:55,180 --> 00:07:00,019
Well, it was the first way to
record machine-readable data.
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00:07:00,052 --> 00:07:04,056
PATEL:
Okay, let's make sense
of the census.
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00:07:04,089 --> 00:07:06,358
This kind of data collection
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00:07:06,391 --> 00:07:08,060
has been going on
for centuries.
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00:07:08,093 --> 00:07:10,463
But starting in 1890,
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00:07:10,496 --> 00:07:12,565
data was recorded
in a pattern of holes
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00:07:12,598 --> 00:07:14,733
"punched" into a census card.
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00:07:14,766 --> 00:07:17,403
So the cards were used to
collect census data.
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00:07:17,436 --> 00:07:20,105
What exact questions
were on there?
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00:07:20,138 --> 00:07:23,976
So things like age, gender,
number of children.
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00:07:24,843 --> 00:07:27,146
PATEL:
When a card passes through
the machine,
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00:07:27,179 --> 00:07:30,082
the holes allow pins to
make electrical connections
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00:07:30,115 --> 00:07:31,083
through the card.
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00:07:31,116 --> 00:07:33,452
A counter keeps a running tally
191
00:07:33,485 --> 00:07:34,453
in each census category
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00:07:34,486 --> 00:07:37,056
as more cards pass through.
193
00:07:37,089 --> 00:07:39,158
Census data
is how the government
194
00:07:39,191 --> 00:07:41,560
allocates resources
for schools and hospitals;
195
00:07:41,593 --> 00:07:44,096
draws the lines for districts;
196
00:07:44,129 --> 00:07:46,031
and decides
how many representatives
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00:07:46,064 --> 00:07:48,033
each state will send to
congress.
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00:07:48,066 --> 00:07:52,304
It's a reminder of the value of
collecting data,
199
00:07:52,337 --> 00:07:53,706
but it's a far cry from
200
00:07:53,739 --> 00:07:55,441
having my every move
tracked on the internet.
201
00:07:57,376 --> 00:07:59,044
To help connect the dots,
202
00:07:59,077 --> 00:08:00,980
Marc shows me
the next surprising step
203
00:08:01,013 --> 00:08:03,482
in the evolution
of data collection.
204
00:08:03,515 --> 00:08:05,751
♪ ♪
205
00:08:05,784 --> 00:08:07,419
I look at this
and I'm almost like,
206
00:08:07,452 --> 00:08:09,588
"Oh, this looks like a
modern office building to me."
207
00:08:09,621 --> 00:08:11,757
WEBER:
Exactly. Each one of those
208
00:08:11,790 --> 00:08:14,627
is one of these
giant terminals here.
209
00:08:14,660 --> 00:08:15,761
(static hissing)
210
00:08:15,794 --> 00:08:18,030
PATEL:
During the Cold War,
211
00:08:18,063 --> 00:08:19,732
IBM figured out
how to hook up computers
212
00:08:19,765 --> 00:08:21,767
from all across the country
to monitor
213
00:08:21,800 --> 00:08:24,270
U.S. airspace in real-time.
214
00:08:24,303 --> 00:08:26,038
(rocket blasting off)
215
00:08:26,071 --> 00:08:30,342
So, this is a terminal
from SAGE.
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00:08:30,375 --> 00:08:34,146
(beeping, static)
217
00:08:35,347 --> 00:08:39,084
PATEL:
It was the first real-time
networked data system.
218
00:08:39,117 --> 00:08:41,287
Real-time is just that:
219
00:08:41,320 --> 00:08:42,521
instantaneous.
220
00:08:42,554 --> 00:08:45,791
And "networked" means connected.
221
00:08:45,824 --> 00:08:47,560
Computers from all across
the country
222
00:08:47,593 --> 00:08:49,161
were hooked up to each other,
223
00:08:49,194 --> 00:08:51,063
so they could share data
in real time,
224
00:08:51,096 --> 00:08:54,166
Sort of like the internet.
225
00:08:54,866 --> 00:08:59,204
WEBER:
The whole point was to track
incoming Soviet bombers,
226
00:08:59,237 --> 00:09:01,574
and they built, arguably,
227
00:09:01,607 --> 00:09:04,510
the first computer network
in the world.
228
00:09:04,543 --> 00:09:06,011
PATEL:
IBM soon realized
229
00:09:06,044 --> 00:09:08,547
that their
aircraft-tracking computers
230
00:09:08,580 --> 00:09:10,382
could be used commercially.
231
00:09:10,415 --> 00:09:14,086
♪ ♪
232
00:09:14,119 --> 00:09:17,089
So In 1960,
along came SABRE.
233
00:09:17,122 --> 00:09:19,625
(beeping, static)
234
00:09:19,658 --> 00:09:21,694
A real-time networked
data system
235
00:09:21,727 --> 00:09:25,097
that shared personal data.
236
00:09:25,130 --> 00:09:27,266
WEBER:
The story goes that
237
00:09:27,299 --> 00:09:30,736
the head of American Airlines
met with IBM,
238
00:09:30,769 --> 00:09:33,105
and they decided to do
a partnership,
239
00:09:33,138 --> 00:09:35,608
the key idea being real time.
240
00:09:35,641 --> 00:09:38,744
They could look at
your age, your name,
241
00:09:38,777 --> 00:09:40,446
financial information,
242
00:09:40,479 --> 00:09:41,747
what flights
you'd been on before,
243
00:09:41,780 --> 00:09:45,050
your dietary preferences
for your meal,
244
00:09:45,083 --> 00:09:47,586
all of this right then
in real time.
245
00:09:47,619 --> 00:09:50,589
PATEL:
We went from tracking bombs to
246
00:09:50,622 --> 00:09:51,590
tracking butts on planes.
247
00:09:51,623 --> 00:09:52,692
WEBER:
Exactly.
248
00:09:54,626 --> 00:09:56,662
PATEL (voiceover):
Between "Pong," punch cards,
249
00:09:56,695 --> 00:09:58,130
and planes...
250
00:09:56,695 --> 00:09:58,130
Whoa, whoa, whoa!
251
00:09:58,163 --> 00:10:01,200
PATEL (voiceover):
I could see how data started
connecting the world--
252
00:10:01,233 --> 00:10:03,335
the military to our airspace
253
00:10:03,368 --> 00:10:05,438
and companies
to their customers.
254
00:10:06,305 --> 00:10:08,707
But what if those customers
all over the world
255
00:10:08,740 --> 00:10:11,110
were linked up to each other?
256
00:10:11,143 --> 00:10:12,778
What would we even call that?
257
00:10:12,811 --> 00:10:16,248
Oh yeah,
the World Wide Web.
258
00:10:16,281 --> 00:10:18,450
PRESENTER:
The World Wide Web
is a part of our lives
259
00:10:18,483 --> 00:10:20,719
and getting bigger every day.
260
00:10:20,752 --> 00:10:23,255
But what about the man
who dreamt it all up?
261
00:10:23,288 --> 00:10:25,691
PATEL:
News reports opened our eyes
262
00:10:25,724 --> 00:10:27,593
to this innovation
and its creator,
263
00:10:27,626 --> 00:10:29,495
Tim Berners-Lee.
264
00:10:29,528 --> 00:10:30,763
PRESENTER:
He simply wanted
265
00:10:30,796 --> 00:10:33,366
to give it away
for the benefit of others.
266
00:10:34,133 --> 00:10:35,567
TIM BERNERS-LEE:
When the web started,
267
00:10:35,600 --> 00:10:38,137
anybody could make a website.
268
00:10:38,170 --> 00:10:40,172
You could make your own style,
269
00:10:40,205 --> 00:10:42,174
your own poems, your own blogs,
270
00:10:42,207 --> 00:10:43,609
and you could link to
other people.
271
00:10:43,642 --> 00:10:47,613
The feeling and the sense
was of tremendous empowerment.
272
00:10:47,646 --> 00:10:49,181
(modem dialing up)
273
00:10:49,214 --> 00:10:51,350
NOBLE:
Some of us remember
the internet
274
00:10:51,383 --> 00:10:54,353
when it was managed
and curated by people.
275
00:10:54,386 --> 00:10:55,788
Where it was, you know,
276
00:10:55,821 --> 00:10:57,656
bulletin board systems
and chat rooms.
277
00:10:57,689 --> 00:11:00,092
♪ ♪
278
00:11:00,125 --> 00:11:01,627
PATEL:
In the late '90s,
small start-ups
279
00:11:01,660 --> 00:11:04,196
were maturing into
big tech companies--
280
00:11:04,229 --> 00:11:07,733
with lots of users
and user data.
281
00:11:09,201 --> 00:11:10,803
KAHLE:
As the web grew,
282
00:11:10,836 --> 00:11:12,471
we ended up with
a very few companies
283
00:11:12,504 --> 00:11:14,139
going and doing
all of the hosting.
284
00:11:14,172 --> 00:11:17,076
It wasn't your actual
personal computer doing it.
285
00:11:17,109 --> 00:11:21,747
NOBLE:
The large platforms
that have emerged are dependent
286
00:11:21,780 --> 00:11:24,183
upon user-generated content
287
00:11:24,216 --> 00:11:25,751
and user engagement.
288
00:11:25,784 --> 00:11:30,355
The modern internet is a wholly
commercial kind of internet.
289
00:11:30,388 --> 00:11:33,659
PATEL:
And as web traffic started
to flow more and more
290
00:11:33,692 --> 00:11:35,494
through just a few companies,
291
00:11:35,527 --> 00:11:38,530
they began to realize the value
of all this personal data
292
00:11:38,563 --> 00:11:40,833
piling up on their servers.
293
00:11:40,866 --> 00:11:43,402
ALEKSANDRA KOROLOVA:
Google started to understand
294
00:11:43,435 --> 00:11:46,172
the power
of individual's data.
295
00:11:47,105 --> 00:11:49,174
They have information about
296
00:11:49,207 --> 00:11:50,309
not just how the websites
297
00:11:50,342 --> 00:11:51,577
are interconnected,
298
00:11:51,610 --> 00:11:55,147
but also information
about the individuals.
299
00:11:55,180 --> 00:11:57,082
HILL:
The big technology companies.
300
00:11:57,115 --> 00:11:59,218
They're looking at
where you are,
301
00:11:59,251 --> 00:12:00,586
They're wanting to know
what your gender is,
302
00:12:00,619 --> 00:12:01,720
what your age is,
303
00:12:01,753 --> 00:12:03,388
you know,
how much you have to spend,
304
00:12:03,421 --> 00:12:05,791
what your political beliefs are.
305
00:12:05,824 --> 00:12:08,227
They have a lot of power
to determine
306
00:12:08,260 --> 00:12:09,561
what our privacy is.
307
00:12:09,594 --> 00:12:12,030
RASKAR:
That's trillions of dollars
308
00:12:12,063 --> 00:12:14,099
of economic value
that's out there,
309
00:12:14,132 --> 00:12:15,467
and there's a constant struggle
310
00:12:15,500 --> 00:12:17,035
between who owns the data.
311
00:12:17,068 --> 00:12:18,036
We create the data,
312
00:12:18,069 --> 00:12:20,139
but somebody else monetizes it.
313
00:12:21,773 --> 00:12:23,575
PATEL:
As big tech was maturing,
314
00:12:23,608 --> 00:12:26,378
early data collection on
websites was pretty limited.
315
00:12:27,412 --> 00:12:29,348
So what happened
to supercharge it?
316
00:12:29,381 --> 00:12:31,817
To create the vast
tracking infrastructure
317
00:12:31,850 --> 00:12:35,053
that allowed Hayley
to find out so much about me?
318
00:12:35,086 --> 00:12:37,556
It turns out things
really got going
319
00:12:37,589 --> 00:12:39,725
when someone invented...
320
00:12:39,758 --> 00:12:41,093
Cookies?
321
00:12:41,993 --> 00:12:44,596
A cookie is not
actually a tasty snack.
322
00:12:44,629 --> 00:12:46,732
When you go to a website,
323
00:12:46,765 --> 00:12:50,202
the website sends
324
00:12:50,235 --> 00:12:51,670
a small file to your browser.
325
00:12:51,703 --> 00:12:52,704
(keys clacking)
326
00:12:52,738 --> 00:12:54,840
PATEL:
That small file
allows the websites
327
00:12:54,873 --> 00:12:56,742
to collect information
about your visit,
328
00:12:56,775 --> 00:12:59,711
and update it every time
you come back.
329
00:12:59,744 --> 00:13:02,014
You might have
heard of cookies
330
00:13:02,047 --> 00:13:03,248
because a lot of websites
331
00:13:03,281 --> 00:13:04,716
pop up with messages
prompting you
332
00:13:04,749 --> 00:13:06,218
to accept theirs.
333
00:13:06,251 --> 00:13:10,222
But what happens
after you hit "accept"?
334
00:13:10,255 --> 00:13:12,057
GALPERIN:
It then uses cookies
335
00:13:12,090 --> 00:13:14,626
to track who you are
and what you're doing,
336
00:13:14,659 --> 00:13:16,161
including in many cases,
337
00:13:16,194 --> 00:13:18,297
all of the other websites
that you go to.
338
00:13:18,330 --> 00:13:21,200
RUMMAN CHOWDHURY:
Cookies have the cutest name,
339
00:13:21,233 --> 00:13:23,735
but they're actually
a really important
340
00:13:23,768 --> 00:13:26,471
piece of information
about you.
341
00:13:26,504 --> 00:13:28,073
Every time you click on a menu,
342
00:13:28,106 --> 00:13:29,274
every time you look at an item
343
00:13:29,307 --> 00:13:30,609
or put it in your cart,
344
00:13:30,642 --> 00:13:33,111
every time you
want to buy something
345
00:13:33,144 --> 00:13:35,614
and click out of the website
and come back in.
346
00:13:35,647 --> 00:13:37,249
A cookie is what's
enabling you to do that.
347
00:13:37,282 --> 00:13:39,117
It's a piece of
tracking information.
348
00:13:39,150 --> 00:13:42,354
You can impute data
and information about you
349
00:13:42,387 --> 00:13:45,324
from the seemingly
innocent behavior online
350
00:13:45,357 --> 00:13:47,092
that's tracked via cookies.
351
00:13:47,125 --> 00:13:49,528
Do you have certain
lifestyle conditions?
352
00:13:49,561 --> 00:13:51,163
What age are you?
353
00:13:51,196 --> 00:13:52,331
What gender or race are you?
354
00:13:52,364 --> 00:13:54,300
Do you have children?
355
00:13:56,201 --> 00:13:57,836
PATEL:
Okay, so I'm starting to get
356
00:13:57,869 --> 00:13:59,638
that these tech companies
357
00:13:59,671 --> 00:14:01,373
use things like cookies
to keep track of
358
00:14:01,406 --> 00:14:03,008
what sites I'm on,
what I'm shopping for,
359
00:14:03,041 --> 00:14:04,176
and what I'm watching.
360
00:14:04,209 --> 00:14:06,778
♪ ♪
361
00:14:06,811 --> 00:14:08,480
(doorbell chimes)
362
00:14:08,513 --> 00:14:09,648
But do they have other ways
363
00:14:09,681 --> 00:14:11,517
of learning the secrets
in my data?
364
00:14:12,517 --> 00:14:14,119
To learn more,
365
00:14:14,152 --> 00:14:16,021
I'm tracking down
a data security expert
366
00:14:16,054 --> 00:14:17,422
in his hacking
high-tech superhero lair...
367
00:14:17,455 --> 00:14:19,725
naturally.
368
00:14:19,758 --> 00:14:23,028
(door rolling open)
369
00:14:23,061 --> 00:14:25,030
Are you Patrick Jackson?
My name's Alok.
370
00:14:25,063 --> 00:14:26,031
Yes, I am.
371
00:14:26,064 --> 00:14:27,266
Awesome,
I'm in the right place.
372
00:14:27,299 --> 00:14:29,668
(door rolls shut)
373
00:14:29,701 --> 00:14:31,270
Your phone is sending
this extra data
374
00:14:31,303 --> 00:14:32,271
to these people that
375
00:14:32,304 --> 00:14:33,505
you don't know exist.
376
00:14:33,538 --> 00:14:35,107
PATEL:
Patrick Jackson has been
377
00:14:35,140 --> 00:14:37,109
all over the news for
his work as
378
00:14:37,142 --> 00:14:38,810
a former NSA research scientist,
379
00:14:38,843 --> 00:14:40,579
and is now chief tech officer
380
00:14:40,612 --> 00:14:43,148
for the internet security firm
Disconnect.
381
00:14:43,181 --> 00:14:45,117
And if anyone can help me
382
00:14:45,150 --> 00:14:48,186
understand how
my personal data is leaking,
383
00:14:48,219 --> 00:14:49,488
it's him.
384
00:14:49,521 --> 00:14:51,790
Patrick,
when I think about
385
00:14:51,823 --> 00:14:56,395
the main control of my
work, life, play,
386
00:14:56,428 --> 00:14:58,363
what I'm doing at home,
when I'm on the road,
387
00:14:58,396 --> 00:14:59,631
this is the mothership.
388
00:14:59,664 --> 00:15:02,100
If I were to
relinquish control
389
00:15:02,133 --> 00:15:04,069
of this precious device
for a few moments,
390
00:15:04,102 --> 00:15:06,071
can you show me, like,
391
00:15:06,104 --> 00:15:07,306
what I've
inadvertently given up?
392
00:15:07,339 --> 00:15:08,473
Yes, yeah.
393
00:15:08,506 --> 00:15:10,108
I can show you what
these data companies
394
00:15:10,141 --> 00:15:12,044
know about you and
what they're collecting.
395
00:15:12,844 --> 00:15:14,579
PATEL (voiceover):
Using a hacking technique
396
00:15:14,612 --> 00:15:15,781
called a
"man-in-the-middle attack,"
397
00:15:15,814 --> 00:15:18,550
Patrick can intercept
the personal data
398
00:15:18,583 --> 00:15:20,152
that's leaving my device,
399
00:15:20,185 --> 00:15:23,021
essentially eavesdropping
on a conversation
400
00:15:23,054 --> 00:15:24,523
between me and the websites
401
00:15:24,556 --> 00:15:27,125
and applications I use.
402
00:15:27,158 --> 00:15:28,493
JACKSON:
Contact information,
403
00:15:28,526 --> 00:15:30,395
name, phone number,
email address.
404
00:15:30,428 --> 00:15:32,531
When you agree to allow them
to have your location,
405
00:15:32,564 --> 00:15:36,034
I can see not only where
you're at on a map,
406
00:15:36,067 --> 00:15:38,070
but also where you're at
in your house,
407
00:15:38,103 --> 00:15:39,604
whether you're
at the back of the house
408
00:15:39,637 --> 00:15:41,306
or the front of the house.
409
00:15:41,339 --> 00:15:43,442
When you look at the data
410
00:15:43,475 --> 00:15:45,644
leaving the phone,
every time you open an app,
411
00:15:45,677 --> 00:15:48,113
you send about, maybe,
412
00:15:48,146 --> 00:15:50,315
500 kilobytes of data
to their servers.
413
00:15:50,348 --> 00:15:54,386
That is equivalent to
about 125 pages of text
414
00:15:54,419 --> 00:15:56,388
that you would print
in a printer.
415
00:15:59,858 --> 00:16:03,428
PATEL (voiceover):
It's one thing if the apps
on my phone are collecting data,
416
00:16:03,461 --> 00:16:05,130
I chose to download them.
417
00:16:05,163 --> 00:16:07,766
But Patrick says
that other companies
418
00:16:07,799 --> 00:16:10,168
have even sneakier ways
to get my data.
419
00:16:10,201 --> 00:16:11,670
Like something as harmless
420
00:16:11,703 --> 00:16:13,305
as a marketing email.
421
00:16:13,338 --> 00:16:15,507
To demonstrate,
Patrick sends me
422
00:16:15,540 --> 00:16:17,542
a mock promotional email.
423
00:16:17,575 --> 00:16:19,511
I have an email that says
424
00:16:19,544 --> 00:16:21,079
"Shoe Sale."
425
00:16:21,112 --> 00:16:23,181
It says "open
to view the shoe sale,"
426
00:16:23,214 --> 00:16:26,151
and I want to open it,
so I'm going to.
427
00:16:26,184 --> 00:16:29,321
"Hi, Alok, get ready for
upcoming shoe sale."
428
00:16:29,354 --> 00:16:31,390
I like this graphic,
and there's like,
429
00:16:31,423 --> 00:16:33,558
social media icons.
This looks legit.
430
00:16:33,591 --> 00:16:35,160
(voiceover):
It turns out,
431
00:16:35,193 --> 00:16:37,529
emails can include
a tracking pixel--
432
00:16:37,562 --> 00:16:41,333
also known as
a spy or invisible pixel.
433
00:16:41,366 --> 00:16:44,036
JACKSON:
An invisible pixel is
a type of image
434
00:16:44,069 --> 00:16:46,038
you're never intended to see,
435
00:16:46,071 --> 00:16:49,341
but it still initiates
a handshake of data
436
00:16:49,374 --> 00:16:52,177
from your device
to these data companies.
437
00:16:52,210 --> 00:16:53,545
(keys clacking)
438
00:16:53,578 --> 00:16:55,380
Most of the emails
that you receive
439
00:16:55,413 --> 00:16:57,282
likely have these
tracking pixels in them.
440
00:16:57,315 --> 00:17:00,052
Most?
441
00:16:57,315 --> 00:17:00,052
Most.
442
00:17:01,252 --> 00:17:02,988
This invisible pixel
is actually
443
00:17:03,021 --> 00:17:04,523
disguised as the banner
444
00:17:04,556 --> 00:17:06,124
in that email.
445
00:17:06,157 --> 00:17:10,095
In other cases, the tracking
pixel will be a one-pixel,
446
00:17:10,128 --> 00:17:11,530
very, very tiny image
447
00:17:11,563 --> 00:17:13,165
that you would never see
with your eyes,
448
00:17:13,198 --> 00:17:15,067
and it's not meant to be seen.
449
00:17:15,100 --> 00:17:16,368
(zooming in)
450
00:17:16,401 --> 00:17:17,769
PATEL:
That little pixel,
that little spy.
451
00:17:17,802 --> 00:17:20,038
See it?
Right there.
452
00:17:20,071 --> 00:17:22,507
It can hide in images
embedded in an email,
453
00:17:22,540 --> 00:17:25,444
like a banner, or even an
"unsubscribe" button.
454
00:17:25,477 --> 00:17:27,245
And when you open the email,
455
00:17:27,278 --> 00:17:31,016
it contacts a tracking website
to collect data about you.
456
00:17:31,049 --> 00:17:33,051
It can suck up
your device model,
457
00:17:33,084 --> 00:17:35,087
location, and even
some browsing history.
458
00:17:35,987 --> 00:17:39,057
JACKSON:
This is essentially
a digital fingerprint
459
00:17:39,090 --> 00:17:41,193
of your device.
460
00:17:39,090 --> 00:17:41,193
PATEL:
No!
461
00:17:41,226 --> 00:17:44,196
JACKSON:
That fingerprint would
identify you as who you are,
462
00:17:44,229 --> 00:17:45,664
and somebody else in
the future
463
00:17:45,697 --> 00:17:46,798
could look at
that fingerprint,
464
00:17:46,831 --> 00:17:49,134
make you do
a new fingerprint,
465
00:17:49,167 --> 00:17:52,137
and they would know that
this is the same person.
466
00:17:52,170 --> 00:17:54,806
PATEL:
Companies are snatching copies
of my digital fingerprints
467
00:17:54,839 --> 00:17:57,042
wherever I go online.
468
00:17:57,075 --> 00:17:59,111
And by following that trail...
469
00:17:59,144 --> 00:18:01,113
JACKSON:
Companies are, over time,
470
00:18:01,146 --> 00:18:03,515
collecting
everything about you.
471
00:18:03,548 --> 00:18:06,051
That's how they
build up this,
472
00:18:06,084 --> 00:18:07,986
this digital profile about you.
473
00:18:10,021 --> 00:18:13,225
HILL:
The internet is this
data collection machine,
474
00:18:13,258 --> 00:18:15,260
and as we're moving
through the internet,
475
00:18:15,293 --> 00:18:16,428
there are these companies
476
00:18:16,461 --> 00:18:17,596
whose whole job is
477
00:18:17,629 --> 00:18:19,198
to reassemble that trail.
478
00:18:20,232 --> 00:18:23,535
PATEL:
So now I know how my digital
profile is out there,
479
00:18:23,568 --> 00:18:25,103
but why?
480
00:18:25,136 --> 00:18:26,638
Who really cares that
481
00:18:26,671 --> 00:18:28,273
I take pictures doing
handstands
482
00:18:28,306 --> 00:18:30,075
and own way too many
sneakers?
483
00:18:32,076 --> 00:18:34,112
Turns out,
there's a whole industry
484
00:18:34,145 --> 00:18:36,148
devoted to selling my data.
485
00:18:36,181 --> 00:18:38,283
It's the data brokers.
486
00:18:38,316 --> 00:18:40,418
♪ ♪
487
00:18:40,451 --> 00:18:42,554
Data brokers are companies
that are set up to
488
00:18:42,587 --> 00:18:44,689
collect information,
repackage it,
489
00:18:44,722 --> 00:18:46,258
and resell it or re-share it
490
00:18:46,291 --> 00:18:48,193
to other companies
that may want to know
491
00:18:48,226 --> 00:18:50,128
information about you.
492
00:18:50,161 --> 00:18:53,498
So what do data brokers want
with all our personal data?
493
00:18:53,531 --> 00:18:56,301
Why do they care that
I love chicken mole
494
00:18:56,334 --> 00:18:57,569
and that "Cool Runnings"
495
00:18:57,602 --> 00:18:59,971
is in my top five movies
of all-time?
496
00:19:00,004 --> 00:19:01,740
TSUKAYAMA:
They collect all this
information,
497
00:19:01,773 --> 00:19:03,675
and then they're really
trying to slice and dice it
498
00:19:03,708 --> 00:19:05,410
in ways that are
appealing to customers.
499
00:19:05,443 --> 00:19:07,112
You know,
it could be an employer
500
00:19:07,145 --> 00:19:08,713
who's doing research on you,
501
00:19:08,746 --> 00:19:11,049
it could be a retailer
who wants to know
502
00:19:11,082 --> 00:19:13,452
what kind of customers
they can target with ads.
503
00:19:14,719 --> 00:19:16,087
That kind of information
504
00:19:16,120 --> 00:19:18,089
is really valuable
for advertisers,
505
00:19:18,122 --> 00:19:19,191
because they want
to target advertising
506
00:19:19,224 --> 00:19:20,559
to a certain type of person.
507
00:19:21,526 --> 00:19:24,262
PATEL:
Our data ends up eventually
getting compiled
508
00:19:24,295 --> 00:19:25,764
into reports like these,
509
00:19:25,797 --> 00:19:28,033
that are then sold to...
510
00:19:28,066 --> 00:19:29,434
whoever's interested?
511
00:19:29,467 --> 00:19:31,136
TSUKAYAMA:
Data brokers are able to say,
512
00:19:31,169 --> 00:19:33,071
"Look,
we have a group of people
513
00:19:33,104 --> 00:19:35,574
"that will fit the audience
of your product.
514
00:19:35,607 --> 00:19:39,110
"We really are happy to serve
this list of people to you,"
515
00:19:39,143 --> 00:19:41,313
or to make a score about
how likely they might be
516
00:19:41,346 --> 00:19:43,315
to purchase your product.
517
00:19:45,116 --> 00:19:47,219
Okay,
I know people say
518
00:19:47,252 --> 00:19:48,787
"Oh, your phones
aren't listening to you,"
519
00:19:48,820 --> 00:19:51,756
but we were just talking
about retro video games,
520
00:19:51,789 --> 00:19:53,792
and here is an ad for
521
00:19:53,825 --> 00:19:56,027
home mini-arcade machines--
522
00:19:56,060 --> 00:19:57,362
which looks kind of cool--
but how did it know
523
00:19:57,395 --> 00:19:59,130
we were just
talking about that?
524
00:19:59,163 --> 00:20:00,265
Is my phone listening?
525
00:20:00,298 --> 00:20:01,466
Is it a psychic?
526
00:20:01,499 --> 00:20:03,335
What's happening?
527
00:20:03,368 --> 00:20:04,502
People always say,
528
00:20:04,535 --> 00:20:05,570
"I was talking about
this product,
529
00:20:05,603 --> 00:20:07,072
and then I saw an ad for it.
530
00:20:07,105 --> 00:20:09,774
"Matt, are they listening
through my phone?"
531
00:20:09,807 --> 00:20:11,109
And I'm like,
"Well, they didn't hear you,
532
00:20:11,142 --> 00:20:12,611
they didn't listen
to anything."
533
00:20:12,644 --> 00:20:14,179
The truth is actually
more frightening.
534
00:20:14,212 --> 00:20:16,181
You talked about that thing
535
00:20:16,214 --> 00:20:17,682
because they influenced you
536
00:20:17,715 --> 00:20:20,085
into having this conversation.
537
00:20:20,118 --> 00:20:23,188
It's because the algorithm
took you to this place.
538
00:20:23,221 --> 00:20:24,723
And that's the situation
with our data.
539
00:20:25,490 --> 00:20:28,126
PATEL:
There have been some outlier
examples
540
00:20:28,159 --> 00:20:30,328
of ad tech companies
listening without consent,
541
00:20:30,361 --> 00:20:31,730
but that's against the law.
542
00:20:31,763 --> 00:20:34,666
For the most part,
advertising algorithms
543
00:20:34,699 --> 00:20:36,801
know you so well
that they can predict
544
00:20:36,834 --> 00:20:38,470
what you would find interesting.
545
00:20:38,503 --> 00:20:40,705
They are so good
because they've studied
546
00:20:40,738 --> 00:20:42,607
all the data
gathered about you--
547
00:20:42,640 --> 00:20:44,343
from the data brokers.
548
00:20:46,144 --> 00:20:47,112
There's this kind of dossier
549
00:20:47,145 --> 00:20:48,580
that's being created
about you
550
00:20:48,613 --> 00:20:50,215
as you're wandering around
the internet,
551
00:20:50,248 --> 00:20:52,217
and it's being used to,
552
00:20:52,250 --> 00:20:54,353
you know,
decide what ad you see.
553
00:20:56,220 --> 00:20:59,224
PATEL:
Advertising fuels
the economics of the internet.
554
00:20:59,257 --> 00:21:01,226
And advertising is fueled by
555
00:21:01,259 --> 00:21:03,261
you, me, us--
556
00:21:03,294 --> 00:21:05,530
our personal data.
557
00:21:05,563 --> 00:21:09,567
So how do the algorithms
actually work?
558
00:21:09,600 --> 00:21:11,469
You land on a webpage,
559
00:21:11,502 --> 00:21:13,505
and that webpage
560
00:21:13,538 --> 00:21:15,173
gets your I.P. address.
561
00:21:15,206 --> 00:21:17,575
A unique identifier is
returned to a data broker.
562
00:21:17,608 --> 00:21:18,810
That data broker
563
00:21:18,843 --> 00:21:20,278
looks up all the facts
564
00:21:20,311 --> 00:21:21,646
that were ever
gleaned about you.
565
00:21:21,679 --> 00:21:25,183
A dossier that describes you.
566
00:21:25,216 --> 00:21:27,686
PATEL:
And then advertisers
literally bid,
567
00:21:27,719 --> 00:21:30,121
they bid on you,
in a real-time auction
568
00:21:30,154 --> 00:21:32,257
based on the only lesson
I remember
569
00:21:32,290 --> 00:21:36,061
from Econ 101:
supply and demand.
570
00:21:36,094 --> 00:21:37,029
DOCTOROW:
The demand-side platform
571
00:21:37,062 --> 00:21:40,298
that the advertiser is on
says, "I have here
572
00:21:40,331 --> 00:21:42,167
"an 18- to 34-year-old
man-child
573
00:21:42,200 --> 00:21:43,735
"with an Xbox
in Southern California.
574
00:21:43,768 --> 00:21:46,504
"Who wants to pay to
cram something
575
00:21:46,537 --> 00:21:48,239
nonconsensually
into his eyeballs?"
576
00:21:48,272 --> 00:21:51,142
And that takes place in
a marketplace,
577
00:21:51,175 --> 00:21:52,844
and you have advertisers
on the other side
578
00:21:52,877 --> 00:21:54,379
who have standing orders.
579
00:21:54,412 --> 00:21:56,214
They're like,
"I want to advertise to
580
00:21:56,247 --> 00:21:58,283
"18- to 34-year-old man-children
in Southern California
581
00:21:58,316 --> 00:21:59,584
who own Xboxes,"
582
00:21:59,617 --> 00:22:02,320
and the marketplace conducts
583
00:22:02,353 --> 00:22:04,756
an automated high-speed auction
where it's just like,
584
00:22:04,789 --> 00:22:07,258
"I'll pay so many
fractions of a cent,"
585
00:22:07,291 --> 00:22:08,760
"I'll pay that
plus ten percent."
586
00:22:08,793 --> 00:22:10,195
(auction bell rings)
587
00:22:10,228 --> 00:22:12,097
The high bidder
gets to show you an ad.
588
00:22:13,498 --> 00:22:15,533
PATEL:
All of this happens
nearly instantly.
589
00:22:15,566 --> 00:22:18,470
And it's possible
because data brokers
590
00:22:18,503 --> 00:22:20,372
sort and cull personal data
591
00:22:20,405 --> 00:22:22,474
into super detailed
consumer groups.
592
00:22:22,507 --> 00:22:25,243
This is the process
that delivers
593
00:22:25,276 --> 00:22:27,178
relevant personalized ads
594
00:22:27,211 --> 00:22:28,780
for cute shoes
595
00:22:28,813 --> 00:22:30,115
or that new tea club--
596
00:22:30,148 --> 00:22:31,750
if you're into
that sort of thing--
597
00:22:31,783 --> 00:22:33,618
which all the ads
seem to know about you.
598
00:22:35,086 --> 00:22:36,688
TSUKAYAMA:
Here we have,
for example, Soccer Mom.
599
00:22:36,721 --> 00:22:38,089
PATEL:
Okay.
600
00:22:38,122 --> 00:22:39,291
I might be able
to identify with that.
601
00:22:40,325 --> 00:22:43,828
A sporting goods retailer could
then go and check out a file
602
00:22:43,861 --> 00:22:46,731
on what a Soccer Mom's
online activity is like.
603
00:22:46,764 --> 00:22:49,401
TSUKAYAMA:
What are the things that
they tend to spend money on,
604
00:22:49,434 --> 00:22:50,535
and do they like to save?
605
00:22:50,568 --> 00:22:51,669
Are there
certain times of year
606
00:22:51,702 --> 00:22:53,471
where they might
spend more or less?
607
00:22:53,504 --> 00:22:58,209
PATEL:
With all this data about
Soccer Mom's consumer habits,
608
00:22:58,242 --> 00:23:01,446
retailers can send personalized
ads with uncanny timing.
609
00:23:02,313 --> 00:23:06,017
Some people like the results--
soccer moms get deals.
610
00:23:06,050 --> 00:23:09,020
Advertisers keep websites
we love in business.
611
00:23:09,053 --> 00:23:10,321
But...
612
00:23:10,354 --> 00:23:12,791
some consumer categories
can be more concerning.
613
00:23:12,824 --> 00:23:15,026
HILL:
Sometimes they'll
have categories
614
00:23:15,059 --> 00:23:16,127
that are like,
615
00:23:16,160 --> 00:23:19,063
"This person has erectile
dysfunction,
616
00:23:19,096 --> 00:23:21,099
"this person
has a gambling problem.
617
00:23:21,132 --> 00:23:23,368
"This is a list of, kind of,
618
00:23:23,401 --> 00:23:26,271
people that are likely
to fall for frauds."
619
00:23:26,304 --> 00:23:29,141
So these can be really powerful
and damaging lists.
620
00:23:30,675 --> 00:23:31,810
TSUKAYAMA:
So this one, for example,
621
00:23:31,843 --> 00:23:34,112
diabetes.
622
00:23:31,843 --> 00:23:34,112
PATEL:
Wow.
623
00:23:34,145 --> 00:23:36,147
Okay,
healthcare demographic...
624
00:23:36,180 --> 00:23:38,616
The thing about that,
right, is like,
625
00:23:38,649 --> 00:23:41,052
when you're thinking
particularly about health data,
626
00:23:41,085 --> 00:23:42,187
that indicates
that you're probably
627
00:23:42,220 --> 00:23:43,822
in a pretty sensitive
situation.
628
00:23:43,855 --> 00:23:48,159
PATEL:
I'm now thinking about
all the patients I take care of.
629
00:23:48,192 --> 00:23:49,627
And I shudder to think
630
00:23:49,660 --> 00:23:51,329
at the targeted ads
that are
631
00:23:51,362 --> 00:23:53,097
deliberately targeting
these individuals.
632
00:23:53,130 --> 00:23:54,498
(keys clacking)
633
00:23:54,532 --> 00:23:57,068
TSUKAYAMA:
Data brokers have lists
about sexual assault victims,
634
00:23:57,101 --> 00:23:59,370
they have lists
about dementia sufferers.
635
00:23:59,403 --> 00:24:01,272
Those are some really
concerning types of categories,
636
00:24:01,305 --> 00:24:03,308
and you could
definitely see how
637
00:24:03,341 --> 00:24:05,677
an advertising company
could take advantage
638
00:24:05,710 --> 00:24:07,245
of people on those lists.
639
00:24:09,046 --> 00:24:11,015
So I think a lot of
people's first reaction
640
00:24:11,048 --> 00:24:12,383
on seeing these
data broker reports
641
00:24:12,416 --> 00:24:14,118
is like, where has
all of this come from?
642
00:24:14,151 --> 00:24:17,689
There are a lot of places where
data brokers get information.
643
00:24:17,722 --> 00:24:19,290
Most commonly apps that
644
00:24:19,323 --> 00:24:21,159
you download that have deals
645
00:24:21,192 --> 00:24:23,194
with data brokers
to share information.
646
00:24:23,227 --> 00:24:26,164
PATEL:
All right, I knew that apps
were getting my data,
647
00:24:26,197 --> 00:24:29,300
but I had no idea some were
sharing it with data brokers.
648
00:24:29,333 --> 00:24:32,170
How is that even legal?
649
00:24:32,203 --> 00:24:34,305
TSUKAYAMA:
How often have you seen
a terms and conditions screen
650
00:24:34,338 --> 00:24:36,174
just like this?
651
00:24:36,207 --> 00:24:37,675
All the time.
Anytime I download
652
00:24:37,708 --> 00:24:40,378
anything, basically.
653
00:24:37,708 --> 00:24:40,378
(both chuckle)
654
00:24:40,411 --> 00:24:43,748
I download apps
all the time
655
00:24:43,781 --> 00:24:46,050
for work, play, life,
convenience.
656
00:24:46,083 --> 00:24:48,119
I just scroll all the way down
and hit accept.
657
00:24:48,152 --> 00:24:49,187
because I'm over it.
658
00:24:48,152 --> 00:24:49,187
Right.
659
00:24:49,220 --> 00:24:50,321
And I think that's how
660
00:24:50,354 --> 00:24:52,123
most people feel about it.
661
00:24:52,156 --> 00:24:54,125
PATEL:
"By accepting these terms,
662
00:24:54,158 --> 00:24:56,127
you allow the platform
to freely..."
663
00:24:56,160 --> 00:24:57,195
"...content for demonstration,
promotion, and..."
664
00:24:57,228 --> 00:24:58,730
TSUKAYAMA:
Terms and conditions
are really long.
665
00:24:58,763 --> 00:25:00,665
Cool, I'm in a commercial
666
00:25:00,698 --> 00:25:03,101
and don't even know about it.
667
00:25:03,134 --> 00:25:04,602
TSUKAYAMA:
Carnegie Mellon once did a study
that said it would take
668
00:25:04,635 --> 00:25:07,205
days for somebody to get through
all of the terms and conditions.
669
00:25:07,238 --> 00:25:09,007
They actually
use the word exploiting.
670
00:25:09,040 --> 00:25:11,142
"You represent and warrant..."
671
00:25:11,175 --> 00:25:13,578
TSUKAYAMA:
That puts people in
a really difficult position
672
00:25:13,611 --> 00:25:16,548
when we're supposed
to manage our own privacy,
673
00:25:16,581 --> 00:25:18,650
but we're also supposed
to use all these things
674
00:25:18,683 --> 00:25:21,152
that are products that
will make our lives better.
675
00:25:21,185 --> 00:25:23,054
(papers rustling,
teacup clatters)
676
00:25:25,590 --> 00:25:28,359
Data brokers
are a big industry.
677
00:25:28,392 --> 00:25:31,029
It's about a $200 billion
industry right now.
678
00:25:31,062 --> 00:25:33,131
I think a lot of people
expect it to grow to,
679
00:25:33,164 --> 00:25:35,500
you know, $400 billion
in the next few years.
680
00:25:37,201 --> 00:25:40,505
NOBLE:
That level of data
from our past,
681
00:25:40,538 --> 00:25:42,807
all the things
we've done being used
682
00:25:42,840 --> 00:25:44,142
and put into systems
683
00:25:44,175 --> 00:25:45,176
to help predict our futures,
684
00:25:45,209 --> 00:25:47,045
that's unprecedented,
685
00:25:47,078 --> 00:25:51,416
and that's rife with the
potential for discrimination,
686
00:25:51,449 --> 00:25:53,184
for harm,
for exclusion.
687
00:25:55,119 --> 00:25:56,220
PATEL:
Okay, I know I said
688
00:25:56,253 --> 00:25:58,456
that I'm not the type
to log in to...
689
00:25:58,489 --> 00:26:00,124
(voiceover):
Look, I love being online.
690
00:26:00,157 --> 00:26:02,093
I like sharing what I'm up to
on social media,
691
00:26:02,126 --> 00:26:04,495
and I'm not afraid to
share my thoughts.
692
00:26:04,528 --> 00:26:07,031
Okay, bugs, I don't bite you,
693
00:26:07,064 --> 00:26:08,032
you don't bite me.
694
00:26:08,065 --> 00:26:09,133
It's that easy.
695
00:26:09,166 --> 00:26:11,436
But some of
this personal data
696
00:26:11,469 --> 00:26:13,237
is, well, personal.
697
00:26:13,270 --> 00:26:14,739
So, now I need to know:
698
00:26:14,772 --> 00:26:17,008
What can I do
to make my digital life
699
00:26:17,041 --> 00:26:19,010
more private and secure?
700
00:26:19,043 --> 00:26:23,281
GALPERIN:
Privacy and security
are not the same thing.
701
00:26:23,314 --> 00:26:24,682
For example, uh,
702
00:26:24,715 --> 00:26:26,751
Facebook is extremely interested
703
00:26:26,784 --> 00:26:28,319
in protecting your security.
704
00:26:28,352 --> 00:26:31,155
They want to make sure
that it is always you
705
00:26:31,188 --> 00:26:32,590
logging in to your account.
706
00:26:32,623 --> 00:26:34,659
They will go through
a great deal of trouble
707
00:26:34,692 --> 00:26:37,395
to keep your account secure.
708
00:26:38,195 --> 00:26:41,299
But you enter all kinds
of data into that account.
709
00:26:41,332 --> 00:26:43,034
You tell it
where you are located.
710
00:26:43,067 --> 00:26:44,435
You send it all
of your pictures.
711
00:26:44,468 --> 00:26:46,137
You send messages
712
00:26:46,170 --> 00:26:49,107
and Facebook collects
all of that data.
713
00:26:49,140 --> 00:26:51,042
They don't want you
to keep it private.
714
00:26:51,075 --> 00:26:54,479
They want you to hand it to them
so that they can use it in order
715
00:26:54,512 --> 00:26:57,515
to serve you targeted ads
and make them money.
716
00:26:57,548 --> 00:26:59,550
PATEL (voiceover):
My accounts are mostly secure
717
00:26:59,583 --> 00:27:01,653
when I control access to them.
718
00:27:01,686 --> 00:27:04,522
But that doesn't mean
the data I put in them
719
00:27:04,555 --> 00:27:07,392
stays private, far from it.
720
00:27:07,425 --> 00:27:10,762
Privacy and security
are not the same.
721
00:27:10,795 --> 00:27:13,598
But they are two sides
of the same coin,
722
00:27:13,631 --> 00:27:15,166
and I have to understand both
723
00:27:15,199 --> 00:27:16,467
if I'm gonna protect
724
00:27:16,500 --> 00:27:18,002
my personal data.
725
00:27:18,035 --> 00:27:20,471
MITCHELL:
When your privacy
is taken from you,
726
00:27:20,504 --> 00:27:22,373
your agency is taken from you.
727
00:27:22,406 --> 00:27:25,009
Privacy is that whisper.
728
00:27:25,042 --> 00:27:27,679
When you think you're whispering
to your friend,
729
00:27:27,712 --> 00:27:30,114
but you're shouting
in a crowded elevator,
730
00:27:30,147 --> 00:27:32,016
you're robbed of something.
731
00:27:32,049 --> 00:27:34,753
And that's why privacy
is so important.
732
00:27:35,720 --> 00:27:39,023
PATEL:
What can I do right now
to protect my privacy
733
00:27:39,056 --> 00:27:40,158
and my security?
734
00:27:41,325 --> 00:27:44,696
To learn tips and tools to
preserve my data on both fronts,
735
00:27:44,729 --> 00:27:48,132
I'm chatting with hacker
and educator Matt Mitchell
736
00:27:48,165 --> 00:27:52,170
and cybersecurity
expert Eva Galperin.
737
00:27:52,203 --> 00:27:55,039
First up: privacy.
738
00:27:55,072 --> 00:27:56,240
Sorry.
739
00:27:56,273 --> 00:27:58,142
(whispering):
Privacy.
740
00:27:58,175 --> 00:28:00,311
Matt is a privacy advocate
741
00:28:00,344 --> 00:28:02,547
at CryptoHarlem,
as in cryptography,
742
00:28:02,580 --> 00:28:06,551
the process of hiding
or coding information.
743
00:28:06,584 --> 00:28:09,287
Hey. I'm Matt. Thanks for coming
to CryptoHarlem.
744
00:28:09,320 --> 00:28:13,524
MITCHELL (voiceover):
CryptoHarlem is
anti-surveillance workshops
745
00:28:13,557 --> 00:28:15,259
for the Black community
746
00:28:15,292 --> 00:28:17,328
and all marginalized communities
around the world.
747
00:28:18,128 --> 00:28:21,399
And our mission is to develop
people's digital skills
748
00:28:21,432 --> 00:28:23,034
so they can actually
help us in the fight
749
00:28:23,067 --> 00:28:25,403
to push back on digital harms.
750
00:28:25,436 --> 00:28:28,039
MITCHELL:
Privacy is not secrecy.
751
00:28:28,072 --> 00:28:28,773
Privacy is just a door.
752
00:28:28,806 --> 00:28:31,008
A door in your home.
753
00:28:31,041 --> 00:28:32,143
There's a sense of, like,
754
00:28:32,176 --> 00:28:34,245
I want to control
what can be seen,
755
00:28:34,278 --> 00:28:35,747
what can't be seen just for me.
756
00:28:36,547 --> 00:28:38,683
PATEL (voiceover):
And I want to close that door.
757
00:28:38,716 --> 00:28:40,151
So how do I do this?
758
00:28:40,184 --> 00:28:41,552
Even just a little?
759
00:28:41,585 --> 00:28:43,020
PATEL:
Okay, what do I do
760
00:28:43,053 --> 00:28:45,490
to make all this safer for me?
761
00:28:45,523 --> 00:28:48,059
What do I do, who do I talk to,
how do I start?
762
00:28:48,092 --> 00:28:49,260
You have to ask yourself,
763
00:28:49,293 --> 00:28:51,229
"Is this a problem
that needs to be fixed?"
764
00:28:51,262 --> 00:28:53,030
Privacy isn't a switch.
765
00:28:53,063 --> 00:28:54,332
It's a dial.
766
00:28:54,365 --> 00:28:56,567
You get to control
how much you share
767
00:28:56,600 --> 00:28:58,102
with who and with what.
768
00:28:58,135 --> 00:29:00,438
PATEL (voiceover):
Let's start with a big one,
769
00:29:00,471 --> 00:29:03,007
something I use all the time,
every day,
770
00:29:03,040 --> 00:29:05,076
and I bet you do, too.
771
00:29:05,109 --> 00:29:08,146
Have you ever used
this website called Google?
772
00:29:08,179 --> 00:29:09,413
I've heard of it.
773
00:29:08,179 --> 00:29:09,413
Yeah.
774
00:29:09,446 --> 00:29:10,648
Well, let's check this out.
775
00:29:10,681 --> 00:29:11,983
Well, if we go here
776
00:29:12,016 --> 00:29:17,322
to myactivity.google.com...
777
00:29:19,123 --> 00:29:22,260
...it'll show us all the things
that you've been doing.
778
00:29:22,293 --> 00:29:23,461
So for example,
779
00:29:23,494 --> 00:29:25,029
when we go here,
780
00:29:25,062 --> 00:29:28,633
we see all the different
Google services that you use.
781
00:29:28,666 --> 00:29:30,702
I don't think they make
a service you don't use.
782
00:29:31,502 --> 00:29:34,539
PATEL (voiceover):
These platforms are so deeply
embedded in many of our lives
783
00:29:34,572 --> 00:29:36,040
and for good reason.
784
00:29:36,073 --> 00:29:39,043
They make products
that can be really useful.
785
00:29:39,076 --> 00:29:40,478
It's hard for me to imagine
786
00:29:40,511 --> 00:29:42,213
going a single day
without searching the web
787
00:29:42,246 --> 00:29:44,382
or using a navigation app.
788
00:29:44,415 --> 00:29:47,118
But they also suck up
a lot of our data.
789
00:29:47,151 --> 00:29:49,387
It's a trade-off
that I'm comfortable making,
790
00:29:49,420 --> 00:29:51,022
within reason.
791
00:29:51,055 --> 00:29:55,259
I've used literally everything
Google has ever offered.
792
00:29:55,292 --> 00:29:57,562
And it knows what you've used.
793
00:29:57,595 --> 00:29:59,630
And it records everything
you've ever used
794
00:29:59,663 --> 00:30:01,098
and how you've used it.
795
00:30:01,131 --> 00:30:02,533
Every search term you've used,
796
00:30:02,566 --> 00:30:06,037
every, uh, you know,
shopping item you've used.
797
00:30:06,070 --> 00:30:10,808
But this is the dashboard
to delete it.
798
00:30:10,841 --> 00:30:13,044
PATEL (voiceover):
I didn't know this,
but I can literally just delete
799
00:30:13,077 --> 00:30:16,047
huge amounts of data
that Google is storing about me.
800
00:30:16,080 --> 00:30:19,350
And the same is true
for a lot of other services.
801
00:30:19,383 --> 00:30:22,053
We can dial to whatever
level we feel comfortable.
802
00:30:22,086 --> 00:30:23,588
For example, on LinkedIn,
803
00:30:23,621 --> 00:30:25,056
you would just click on me,
804
00:30:25,089 --> 00:30:29,293
and then you would go to
your settings and privacy.
805
00:30:29,326 --> 00:30:30,828
Here, when we go to
manage your activity,
806
00:30:30,861 --> 00:30:33,231
it tells you that, you know,
807
00:30:33,264 --> 00:30:34,498
you started sharing
your LinkedIn data
808
00:30:34,531 --> 00:30:36,534
with a permitted application.
809
00:30:36,567 --> 00:30:40,838
PATEL (voiceover):
Treating privacy like a dial
means it's not all or nothing.
810
00:30:40,871 --> 00:30:45,176
You can have your data cake
and eat it, too.
811
00:30:45,209 --> 00:30:47,445
Like now I'm thinking I want
to log into everything--
812
00:30:47,478 --> 00:30:50,481
all my social media, my email,
my LinkedIn, everything--
813
00:30:50,514 --> 00:30:54,118
regularly and look to
see who is using these.
814
00:30:54,151 --> 00:30:56,554
Exactly, it is about awareness.
815
00:30:56,587 --> 00:30:58,723
Furthermore, the companies,
816
00:30:58,756 --> 00:31:01,425
they know how many people
actually use
817
00:31:01,458 --> 00:31:02,426
the privacy controls.
818
00:31:02,459 --> 00:31:04,061
And by you even
peeking in it,
819
00:31:04,094 --> 00:31:08,099
you're saying
I believe privacy matters.
820
00:31:08,132 --> 00:31:11,335
At the Electronic
Frontier Foundation,
821
00:31:11,368 --> 00:31:14,138
Eva shows me how I can take
my privacy game
822
00:31:14,171 --> 00:31:15,373
to the next level...
823
00:31:15,406 --> 00:31:19,143
learning some
Surveillance Self-Defense.
824
00:31:20,010 --> 00:31:25,283
Although, apparently not
that kind of self-defense.
825
00:31:25,316 --> 00:31:27,218
GALPERIN:
So, the next step in
your privacy journey
826
00:31:27,251 --> 00:31:29,320
is fighting back against
827
00:31:29,353 --> 00:31:31,122
types of corporate surveillance.
828
00:31:31,155 --> 00:31:33,057
I-- and one of the things
829
00:31:33,090 --> 00:31:35,660
that websites really like
to do when, uh,
830
00:31:35,693 --> 00:31:38,296
is not just to track what
you are doing on their website,
831
00:31:38,329 --> 00:31:40,698
but to track all the other
websites that you go to.
832
00:31:40,731 --> 00:31:42,433
And they do this using cookies.
833
00:31:42,466 --> 00:31:43,734
There's some companies I trust,
834
00:31:43,767 --> 00:31:45,636
and I'm like, fine,
you have these cookies.
835
00:31:45,669 --> 00:31:47,538
They're chocolate chip.
I know where they were made.
836
00:31:47,571 --> 00:31:48,773
I know what
you're doing with them.
837
00:31:48,806 --> 00:31:49,840
But then there's
these third party companies,
838
00:31:49,873 --> 00:31:52,143
I don't want them
around me.
839
00:31:52,176 --> 00:31:54,145
You can use a
browser extension
840
00:31:54,178 --> 00:31:56,547
to eat these cookies, uh,
841
00:31:56,580 --> 00:31:57,815
and fight back against
this kind of tracking
842
00:31:57,848 --> 00:32:00,451
and keep those websites from
seeing where else you're going.
843
00:32:00,484 --> 00:32:04,088
PATEL (voiceover):
Browser extensions are
add-ons for your web browser
844
00:32:04,121 --> 00:32:07,191
that give it extra features
and functionality,
845
00:32:07,224 --> 00:32:09,260
like eating cookies.
846
00:32:09,293 --> 00:32:10,494
I'm imagining this,
847
00:32:10,527 --> 00:32:14,165
like, digital Cookie Monster
that's eating up
848
00:32:14,198 --> 00:32:17,168
all these pieces
of my online activity
849
00:32:17,201 --> 00:32:20,071
so that companies don't know
what I'm doing online.
850
00:32:20,104 --> 00:32:22,139
And it reduces the amount
of privacy tracking.
851
00:32:22,172 --> 00:32:23,507
Am I understanding that?
852
00:32:23,540 --> 00:32:25,309
What these
browser extensions
853
00:32:25,342 --> 00:32:30,281
do is they get rid of,
uh, the tracking cookies
854
00:32:30,314 --> 00:32:32,116
that these websites use to see
855
00:32:32,149 --> 00:32:33,818
all the other sites
that you're going to,
856
00:32:33,851 --> 00:32:35,052
which is none of their business.
857
00:32:35,085 --> 00:32:37,121
(knuckles crack)
858
00:32:37,154 --> 00:32:39,056
PATEL (voiceover):
My personal digital world
is starting to feel
859
00:32:39,089 --> 00:32:42,026
comfy, controlled
and a lot more private.
860
00:32:42,993 --> 00:32:45,596
I've learned how to close
the doors and blinds.
861
00:32:45,629 --> 00:32:49,133
But still, someone could
open them right back up.
862
00:32:49,166 --> 00:32:50,701
I could get hacked.
863
00:32:50,734 --> 00:32:53,104
How do I lock my doors?
864
00:32:53,137 --> 00:32:55,439
Time to talk about security.
865
00:32:55,472 --> 00:32:56,807
MITCHELL:
The tragedy of
866
00:32:56,840 --> 00:32:58,242
this recent pandemic teaches us
867
00:32:58,275 --> 00:33:01,112
that we're all
pretty vulnerable.
868
00:33:01,145 --> 00:33:03,014
And without that herd immunity,
869
00:33:03,047 --> 00:33:05,182
without that community response,
870
00:33:05,215 --> 00:33:07,485
you can't just say,
"I'm okay,
871
00:33:07,518 --> 00:33:10,788
and therefore I don't
have to worry about this."
872
00:33:10,821 --> 00:33:13,224
This is the first time
that I've ever heard
873
00:33:13,257 --> 00:33:16,027
someone compare data privacy
874
00:33:16,060 --> 00:33:19,797
to epidemiology
and herd immunity.
875
00:33:19,830 --> 00:33:23,601
All you need is one person
to make a mistake
876
00:33:23,634 --> 00:33:25,302
and it's game over.
877
00:33:25,335 --> 00:33:29,640
That's what happens to so many
other corporations, businesses,
878
00:33:29,673 --> 00:33:31,709
even hospitals during
a ransomware attack
879
00:33:31,742 --> 00:33:34,245
that'll freeze all machines
and stop them from working
880
00:33:34,278 --> 00:33:36,547
until someone pays
a bunch of hackers.
881
00:33:36,580 --> 00:33:39,050
My one error could
compromise the security
882
00:33:39,083 --> 00:33:41,218
of my entire institution.
883
00:33:41,251 --> 00:33:42,486
MITCHELL:
Human beings will make mistakes.
884
00:33:42,519 --> 00:33:45,156
Folks won't wash
their hands sometimes, right?
885
00:33:45,189 --> 00:33:49,260
But we try to teach best
practices to prevent the worst.
886
00:33:49,293 --> 00:33:50,728
Okay, Matt, you have
my wheels spinning.
887
00:33:50,761 --> 00:33:53,431
I do not want
to be patient zero
888
00:33:53,464 --> 00:33:56,267
in this, like, massive
infectious data leak.
889
00:33:56,300 --> 00:33:58,636
What can I do to start
pulling it back
890
00:33:58,669 --> 00:34:00,438
and better protecting
my information?
891
00:34:00,471 --> 00:34:02,573
Well, I got something
for that, okay?
892
00:34:02,606 --> 00:34:04,642
Oh, you have, like,
a bag of tricks.
893
00:34:02,606 --> 00:34:04,642
I've got a bag.
894
00:34:04,675 --> 00:34:06,510
I thought you were just gonna
say, like, change your password.
895
00:34:06,543 --> 00:34:08,446
We got to go all the way.
896
00:34:08,479 --> 00:34:10,114
This is a privacy screen.
897
00:34:10,147 --> 00:34:12,650
And this will keep
people from being able
898
00:34:12,683 --> 00:34:14,085
to look over your shoulder.
899
00:34:14,118 --> 00:34:15,319
Shoulder surfers beware.
900
00:34:15,352 --> 00:34:16,487
Can't look through that.
901
00:34:16,520 --> 00:34:17,655
This is for like,
using my computer
902
00:34:17,688 --> 00:34:19,223
in a public space,
the airplane.
903
00:34:19,256 --> 00:34:21,392
Everywhere.
904
00:34:21,425 --> 00:34:23,160
This is a Faraday bag.
905
00:34:23,193 --> 00:34:24,728
You got to keep
your phone in here.
906
00:34:24,761 --> 00:34:26,430
This blocks RF signals.
907
00:34:26,463 --> 00:34:27,765
It's basically aluminum foil...
908
00:34:26,463 --> 00:34:27,765
PATEL (voiceover):
Yo, Matt?
909
00:34:27,798 --> 00:34:29,767
Can we slow this down
a little bit?
910
00:34:29,800 --> 00:34:31,635
You can't get hacked when
you're not attached to anything.
911
00:34:31,668 --> 00:34:34,138
Is this really necessary,
a Faraday bag?
912
00:34:34,171 --> 00:34:37,141
PATEL (voiceover):
Okay, this looks a little more
complicated than I expected.
913
00:34:37,174 --> 00:34:39,343
I guess I just have to become
Dr. 007.
914
00:34:39,376 --> 00:34:41,612
We also have a Wi-Fi pineapple.
915
00:34:41,645 --> 00:34:44,148
This is a portable access point.
916
00:34:44,181 --> 00:34:45,783
And we also could
use it to detect
917
00:34:45,816 --> 00:34:48,152
and stop access points
from going bad.
918
00:34:48,185 --> 00:34:50,354
PATEL (voiceover):
Okay, Matt,
now you've just gone rogue.
919
00:34:50,387 --> 00:34:52,356
MITCHELL:
Let's say you
have a hard drive
920
00:34:52,389 --> 00:34:54,258
with some important
files from work in it.
921
00:34:54,291 --> 00:34:55,459
What happens if you lose it?
922
00:34:55,492 --> 00:34:56,794
Someone can plug that
in and have access
923
00:34:56,827 --> 00:34:58,195
to all your stuff.
924
00:34:58,228 --> 00:35:00,064
Not if it's an
encrypted hard drive.
925
00:35:00,097 --> 00:35:02,366
I understand--
926
00:35:00,097 --> 00:35:02,366
There's more.
927
00:35:02,399 --> 00:35:04,135
How do you know that
you're not being bugged?
928
00:35:04,168 --> 00:35:05,503
This is nuts.
929
00:35:05,536 --> 00:35:07,304
This is something
I could use to find out
930
00:35:07,337 --> 00:35:10,341
if there is a
audio bug in the room.
931
00:35:07,337 --> 00:35:10,341
(beeping)
932
00:35:10,374 --> 00:35:12,009
I can find Wi-Fi signals...
933
00:35:10,374 --> 00:35:12,009
(device beeps)
934
00:35:12,042 --> 00:35:13,678
Oops, something's here,
right?
935
00:35:14,512 --> 00:35:17,648
PATEL (voiceover):
Honestly, I thought being
a spy would be more fun.
936
00:35:17,681 --> 00:35:20,351
But I'm starting
to feel shaken, not stirred.
937
00:35:20,384 --> 00:35:23,220
How am I supposed to keep track
of all this stuff?
938
00:35:23,253 --> 00:35:26,324
I'm no hacker genius like Matt.
939
00:35:27,158 --> 00:35:31,162
What if I just left all
of this behind and just quit.
940
00:35:31,195 --> 00:35:33,397
Goodbye, digital world.
941
00:35:38,101 --> 00:35:43,141
(clock ticking)
942
00:35:46,376 --> 00:35:48,112
(yawning)
943
00:35:51,515 --> 00:35:52,616
Do you know if there's
breaking news?
944
00:35:51,515 --> 00:35:52,616
(cat meows)
945
00:35:52,649 --> 00:35:53,684
Look in my eyes and tell me.
946
00:35:53,717 --> 00:35:55,119
What are we doing here?
947
00:35:55,152 --> 00:35:56,353
What are we doing?
948
00:35:56,386 --> 00:35:57,354
Like, I don't even know
949
00:35:57,387 --> 00:35:58,622
how many steps I've taken today.
950
00:35:58,655 --> 00:36:00,491
Because my step counter
is not on my hand.
951
00:36:00,524 --> 00:36:03,360
I'm technically disconnected,
this isn't cheating,
952
00:36:03,393 --> 00:36:05,462
but can someone tell me
what the Suns score is?
953
00:36:05,495 --> 00:36:07,164
CREW MEMBER:
Uh, down by 11 at the half.
954
00:36:07,197 --> 00:36:08,165
(groans)
955
00:36:08,198 --> 00:36:10,067
(cat purring)
956
00:36:10,100 --> 00:36:12,303
Oh, I am supposed to
pick up my daughter.
957
00:36:12,336 --> 00:36:15,306
How long do
I have to do this for?
958
00:36:16,106 --> 00:36:18,275
(voiceover):
All right,
maybe it's not that easy.
959
00:36:18,308 --> 00:36:19,777
But there's got to be
some middle ground
960
00:36:19,810 --> 00:36:22,446
between Inspector Gadget
and Fred Flintstone
961
00:36:22,479 --> 00:36:24,615
that's right for me.
962
00:36:24,648 --> 00:36:27,451
Instead of going completely
off the grid,
963
00:36:27,484 --> 00:36:29,687
I'm checking back in with Eva
964
00:36:29,720 --> 00:36:32,089
for some more surveillance
self-defense.
965
00:36:32,122 --> 00:36:37,428
And the best place to start is
with the basics: passwords.
966
00:36:37,461 --> 00:36:39,463
I'll be honest,
967
00:36:39,496 --> 00:36:40,731
my current password
968
00:36:40,764 --> 00:36:41,799
is basically a combination
969
00:36:41,832 --> 00:36:44,501
of my first pet's name
plus my birthday
970
00:36:44,534 --> 00:36:47,171
or a favorite
video game or song.
971
00:36:47,204 --> 00:36:48,806
I don't think any hacker's
really gonna guess that.
972
00:36:48,839 --> 00:36:52,142
But you're telling me that there
is still a vulnerability there.
973
00:36:52,175 --> 00:36:54,078
Yes.
974
00:36:54,111 --> 00:36:55,679
Hackers can go
find out information
975
00:36:55,712 --> 00:36:56,880
about you from data brokers,
976
00:36:56,913 --> 00:37:00,184
including, you know, the name
of the street you grew up on
977
00:37:00,217 --> 00:37:03,220
or the city where
you went to college.
978
00:37:03,253 --> 00:37:07,124
So you wouldn't want a password
like the name of your pet.
979
00:37:07,157 --> 00:37:08,659
Or password123.
980
00:37:08,692 --> 00:37:13,197
Well, I did have a pet fish,
and his name was Password123.
981
00:37:13,230 --> 00:37:14,765
So, I guess that
kind of, like,
982
00:37:14,798 --> 00:37:17,334
hits both boxes and
makes me more vulnerable.
983
00:37:17,367 --> 00:37:22,606
Let's start by, uh, creating
some strong and unique passwords
984
00:37:22,639 --> 00:37:24,708
for all of your, uh,
your different accounts.
985
00:37:24,741 --> 00:37:26,744
And that will make them
much more hacker-proof.
986
00:37:26,777 --> 00:37:28,545
I'm all ears.
987
00:37:26,777 --> 00:37:28,545
Fantastic.
988
00:37:28,578 --> 00:37:34,051
Well, we're going to start
by rolling these five dice.
989
00:37:35,352 --> 00:37:38,055
GALPERIN (voiceover):
There are easy ways
to create passwords
990
00:37:38,088 --> 00:37:40,491
that are long and strong
991
00:37:40,524 --> 00:37:43,027
and easy to remember that
are not based on information
992
00:37:43,060 --> 00:37:46,196
that attackers
can easily find about you.
993
00:37:46,229 --> 00:37:49,333
And the way that we do that
is we use word lists and dice.
994
00:37:50,233 --> 00:37:54,038
The word list is essentially
just a long list
995
00:37:54,071 --> 00:37:58,042
of dictionary words
with numbers attached.
996
00:37:58,075 --> 00:38:00,010
So what we're going
to do is we're going
997
00:38:00,043 --> 00:38:01,979
to write down the
numbers on this dice.
998
00:38:02,012 --> 00:38:04,715
45263, my new lucky numbers.
999
00:38:02,012 --> 00:38:04,715
Okay.
1000
00:38:04,748 --> 00:38:07,618
And now we are
going to look up
1001
00:38:07,651 --> 00:38:11,488
45263 in this book.
1002
00:38:11,521 --> 00:38:13,991
So there are words that
correlate to the numbers
1003
00:38:14,024 --> 00:38:15,592
that I just randomly rolled.
1004
00:38:14,024 --> 00:38:15,592
Yes.
1005
00:38:15,625 --> 00:38:17,761
Okay. I want a cool
word like "tiger."
1006
00:38:17,794 --> 00:38:20,431
The word is
"presoak."
1007
00:38:20,464 --> 00:38:21,966
"Presoak?"
1008
00:38:20,464 --> 00:38:21,966
"Presoak."
1009
00:38:23,100 --> 00:38:27,304
34115.
1010
00:38:27,337 --> 00:38:28,572
"Henna."
1011
00:38:28,605 --> 00:38:30,240
Okay, I like this.
1012
00:38:30,273 --> 00:38:32,109
PATEL (voiceover):
The idea behind this dice game
1013
00:38:32,142 --> 00:38:35,045
is that
it's both random and long.
1014
00:38:35,078 --> 00:38:38,048
Hackers using fast,
powerful computers
1015
00:38:38,081 --> 00:38:40,284
and sophisticated
password-cracking software
1016
00:38:40,317 --> 00:38:43,620
are able to try many,
many passwords a second.
1017
00:38:43,653 --> 00:38:45,789
A recent study
by a security firm
1018
00:38:45,822 --> 00:38:48,525
showed that a seven-character
password can be cracked
1019
00:38:48,558 --> 00:38:50,627
in just a few seconds.
1020
00:38:50,660 --> 00:38:52,196
But a 12-character password
1021
00:38:52,229 --> 00:38:54,031
with uppercase letters
and symbols
1022
00:38:54,064 --> 00:38:56,433
is much more difficult to break.
1023
00:38:56,466 --> 00:38:58,035
Studies show
it could take hackers
1024
00:38:58,068 --> 00:39:00,304
well over 100 years to crack.
1025
00:39:00,337 --> 00:39:02,072
That's safe.
1026
00:39:02,105 --> 00:39:05,075
But also more difficult
to type or remember.
1027
00:39:05,108 --> 00:39:06,610
Eva's six-word random passphrase
1028
00:39:06,643 --> 00:39:09,747
is easier to remember than a
random string of 12 characters
1029
00:39:09,780 --> 00:39:12,349
and practically
impossible to break.
1030
00:39:12,382 --> 00:39:13,384
"Stinging."
1031
00:39:13,417 --> 00:39:14,618
"Ignition."
1032
00:39:17,087 --> 00:39:19,223
Six is "Clutch."
1033
00:39:17,087 --> 00:39:19,223
"Clutch," okay.
1034
00:39:19,256 --> 00:39:24,128
"Presoak Henna Stinging
Ignition Clutch Handbrake."
1035
00:39:24,161 --> 00:39:25,195
(bell dings)
1036
00:39:24,161 --> 00:39:25,195
Fantastic.
1037
00:39:25,228 --> 00:39:26,397
Now you have a passphrase.
1038
00:39:26,430 --> 00:39:27,398
These six words.
1039
00:39:27,431 --> 00:39:29,433
It is long. It's unique.
1040
00:39:29,466 --> 00:39:31,168
It's difficult to guess.
1041
00:39:31,201 --> 00:39:32,736
And it's relatively
easy to remember,
1042
00:39:32,769 --> 00:39:35,072
considering how long it is.
1043
00:39:35,105 --> 00:39:37,174
It is a very good way of
creating random passwords,
1044
00:39:37,207 --> 00:39:40,644
but a lot of password managers
will automatically
1045
00:39:40,677 --> 00:39:42,479
do this for you.
1046
00:39:42,512 --> 00:39:45,516
PATEL (voiceover):
Once you have a passphrase,
you can use this
1047
00:39:45,549 --> 00:39:48,719
to unlock a password manager
that generates
1048
00:39:48,752 --> 00:39:53,023
strong random passwords
and stores them securely.
1049
00:39:53,056 --> 00:39:57,161
Now I have this beautiful
random password or passphrase,
1050
00:39:57,194 --> 00:39:59,430
but what happens
if someone steals this?
1051
00:39:59,463 --> 00:40:01,632
Is it just game over,
efforts are gone?
1052
00:40:01,665 --> 00:40:02,766
No, it is not.
1053
00:40:02,800 --> 00:40:06,036
Uh, that leads us to the
next step on your surveillance
1054
00:40:06,069 --> 00:40:09,373
self-defense journey, and that
is two-factor authentication.
1055
00:40:10,374 --> 00:40:13,744
PATEL (voiceover):
This may sound
like a hacker ninja term,
1056
00:40:13,777 --> 00:40:16,046
but it's just
an added layer of security,
1057
00:40:16,079 --> 00:40:20,184
requiring an additional method
of confirming your identity.
1058
00:40:20,217 --> 00:40:22,386
Most of the time,
it's just a simple text message.
1059
00:40:22,419 --> 00:40:23,587
GALPERIN:
Because it requires
1060
00:40:23,620 --> 00:40:25,189
that you have two things
1061
00:40:25,222 --> 00:40:26,557
in order to log
into your account.
1062
00:40:26,590 --> 00:40:30,160
You will need both your password
and also this code,
1063
00:40:30,193 --> 00:40:33,764
so the site
will send you a text message.
1064
00:40:33,797 --> 00:40:36,567
There is also
an authenticator app.
1065
00:40:36,600 --> 00:40:41,138
The site will ask you to take
a photo of and then go to
1066
00:40:41,171 --> 00:40:43,540
the site in a QR code.
1067
00:40:43,573 --> 00:40:46,143
The best way to be
a security superhero
1068
00:40:46,176 --> 00:40:49,079
is to find the stuff
that works for you
1069
00:40:49,112 --> 00:40:51,215
and implement it
as sort of smoothly
1070
00:40:51,248 --> 00:40:53,451
and seamlessly as you can.
1071
00:40:54,518 --> 00:40:56,787
PATEL (voiceover):
These data self-defense
tweaks are great
1072
00:40:56,820 --> 00:40:58,822
for me and my own data.
1073
00:40:58,855 --> 00:41:01,058
But what about everyone else?
1074
00:41:01,091 --> 00:41:05,028
I'm wondering, is there a way
for all of us to share data
1075
00:41:05,061 --> 00:41:07,164
and get all the sweet benefits,
1076
00:41:07,197 --> 00:41:08,699
without sacrificing
privacy and security?
1077
00:41:11,067 --> 00:41:12,536
At M.I.T.'s Media Lab,
1078
00:41:12,569 --> 00:41:15,239
I'm meeting up
with Ramesh Raskar,
1079
00:41:15,272 --> 00:41:17,808
who is working on a way
to access the benefits
1080
00:41:17,841 --> 00:41:19,476
of personal health data--
1081
00:41:19,509 --> 00:41:21,478
finally, a topic I understand--
1082
00:41:21,511 --> 00:41:24,248
without compromising
our private information.
1083
00:41:25,382 --> 00:41:27,384
At Ramesh's Camera Culture Lab,
1084
00:41:27,417 --> 00:41:29,453
they're building
some data collecting tools
1085
00:41:29,486 --> 00:41:32,189
that seem straight out of
a science fiction movie.
1086
00:41:32,222 --> 00:41:35,292
PATEL:
Love when a sign says
"Danger: Laser."
1087
00:41:35,325 --> 00:41:37,227
You know important things
are happening in here.
1088
00:41:37,260 --> 00:41:41,732
(voiceover):
They've got cameras that can
literally see around corners.
1089
00:41:41,765 --> 00:41:43,534
PATEL:
Get out!
1090
00:41:41,765 --> 00:41:43,534
(both laughing)
1091
00:41:43,567 --> 00:41:46,036
RASKAR:
We are not violating
the laws of physics.
1092
00:41:46,903 --> 00:41:50,207
PATEL (voiceover):
And cameras that can see
inside our own bodies.
1093
00:41:50,240 --> 00:41:53,110
That's about as personal
as it gets.
1094
00:41:53,143 --> 00:41:57,548
For Ramesh, protecting
patient privacy is paramount.
1095
00:41:57,581 --> 00:41:59,850
But he's found a drawback
in how we do that.
1096
00:41:59,883 --> 00:42:02,185
Since data is locked up
for privacy,
1097
00:42:02,218 --> 00:42:06,056
advancement in medical science
is not as fast as it could be.
1098
00:42:06,089 --> 00:42:09,393
Because, think about it, access
to tons of personal health data
1099
00:42:09,426 --> 00:42:12,162
could help researchers make
major medical breakthroughs.
1100
00:42:12,195 --> 00:42:16,099
But today, researchers have
to ask for your consent
1101
00:42:16,132 --> 00:42:19,069
to peek at your data
in order to learn from it.
1102
00:42:19,102 --> 00:42:20,504
RASKAR:
When we talk about consent,
1103
00:42:20,537 --> 00:42:22,806
someone's still peeking
into your data.
1104
00:42:22,839 --> 00:42:25,375
A no-peek privacy,
on the other hand,
1105
00:42:25,408 --> 00:42:27,111
is where nobody
can peek at your data.
1106
00:42:27,911 --> 00:42:29,580
PATEL (voiceover):
No-peek privacy?
1107
00:42:29,613 --> 00:42:31,415
But how could
researchers learn anything?
1108
00:42:31,448 --> 00:42:33,183
RASKAR:
There are many ways
1109
00:42:33,216 --> 00:42:35,452
to create no-peek privacy.
1110
00:42:35,485 --> 00:42:39,290
First one is the notion
of smashing information.
1111
00:42:42,726 --> 00:42:45,162
PATEL (voiceover):
No, not literally
smashing your phone.
1112
00:42:45,195 --> 00:42:47,131
But I'm not gonna lie...
1113
00:42:48,698 --> 00:42:50,801
...that was really fun.
1114
00:42:50,834 --> 00:42:53,337
Smashing is basically
the idea of taking raw data
1115
00:42:53,370 --> 00:42:55,673
and smashing it
into just the wisdom.
1116
00:42:56,740 --> 00:42:58,842
PATEL (voiceover):
According to Ramesh,
smashing data
1117
00:42:58,875 --> 00:43:00,243
is simply the process
1118
00:43:00,276 --> 00:43:02,446
of extracting
the useful information,
1119
00:43:02,479 --> 00:43:04,147
which he calls the "wisdom,"
1120
00:43:04,180 --> 00:43:06,383
while obscuring
the private data.
1121
00:43:06,416 --> 00:43:10,153
In other words, a collection
of private health records
1122
00:43:10,186 --> 00:43:12,055
contains two kinds of data.
1123
00:43:12,088 --> 00:43:14,625
One kind is the personal data--
1124
00:43:14,658 --> 00:43:17,160
the names,
conditions, and histories,
1125
00:43:17,193 --> 00:43:19,730
the stuff we absolutely
want to protect.
1126
00:43:19,763 --> 00:43:25,068
But collectively, the records
may contain valuable information
1127
00:43:25,101 --> 00:43:26,103
about patterns in health care.
1128
00:43:26,136 --> 00:43:28,472
The wisdom.
1129
00:43:28,505 --> 00:43:30,674
I'm thinking about
examples in health care,
1130
00:43:30,707 --> 00:43:34,244
and the individual data,
the patient data
1131
00:43:34,277 --> 00:43:37,080
is protected, and
you can't reverse engineer it.
1132
00:43:37,113 --> 00:43:39,650
Let's take a concrete example
of COVID.
1133
00:43:41,184 --> 00:43:43,620
Imagine during the early days
of the pandemic,
1134
00:43:43,653 --> 00:43:45,222
we could have sent
medical experts
1135
00:43:45,255 --> 00:43:48,425
from here in Boston
to China, to Korea, to Italy,
1136
00:43:48,458 --> 00:43:51,294
and embedded them in
those hospitals to understand
1137
00:43:51,327 --> 00:43:54,665
what COVID pneumonia looks like
on a chest X-ray.
1138
00:43:54,698 --> 00:43:56,400
And they could have
come back to Boston,
1139
00:43:56,433 --> 00:43:57,834
all those medical experts,
1140
00:43:57,867 --> 00:44:01,705
and said, "Hey, together,
we can figure out what this is."
1141
00:44:02,605 --> 00:44:06,209
PATEL (voiceover):
So, the experts would return
back with just the wisdom,
1142
00:44:06,242 --> 00:44:07,778
an understanding of COVID
1143
00:44:07,811 --> 00:44:10,614
derived from being exposed
to large data sets.
1144
00:44:10,647 --> 00:44:14,017
But they wouldn't come back
with specific patient info.
1145
00:44:14,050 --> 00:44:18,088
None of the raw, sensitive,
and private data.
1146
00:44:18,121 --> 00:44:20,057
But of course,
that would require
1147
00:44:20,090 --> 00:44:22,626
initially sharing patient data;
1148
00:44:22,659 --> 00:44:25,095
a non-starter.
1149
00:44:25,128 --> 00:44:27,097
Because of privacy,
because of regulations,
1150
00:44:27,130 --> 00:44:29,233
because of national security
issues, they couldn't.
1151
00:44:30,400 --> 00:44:33,370
PATEL (voiceover):
This is where A.I.,
Artificial Intelligence,
1152
00:44:33,403 --> 00:44:34,604
comes in.
1153
00:44:34,637 --> 00:44:37,040
Instead of sending
experts to each hospital,
1154
00:44:37,073 --> 00:44:40,377
Ramesh is working on a way
to send A.I. to learn instead.
1155
00:44:41,177 --> 00:44:44,114
An A.I. model could be trained
on patients' lung X-rays
1156
00:44:44,147 --> 00:44:46,216
to learn what signs of COVID
look like.
1157
00:44:46,249 --> 00:44:50,120
The private health data
would never be copied
1158
00:44:50,153 --> 00:44:52,622
and would never leave the
hospital or the patient's file.
1159
00:44:52,655 --> 00:44:55,325
The A.I. would only
transmit its conclusions,
1160
00:44:55,358 --> 00:44:57,828
the wisdom, the smashed data.
1161
00:44:57,861 --> 00:44:59,262
RASKAR:
It's not enough to just
1162
00:44:59,295 --> 00:45:02,099
remove the name
from the chest X-ray,
1163
00:45:02,132 --> 00:45:04,034
but make sure
that you don't send
1164
00:45:04,067 --> 00:45:06,003
any of the pixels
of the chest X-ray at all.
1165
00:45:06,937 --> 00:45:09,773
PATEL (voiceover):
The A.I. can learn patterns
and gain knowledge
1166
00:45:09,806 --> 00:45:12,109
without having to keep hold
of everyone's data.
1167
00:45:12,142 --> 00:45:15,112
So the "wisdom"
from one hospital
1168
00:45:15,145 --> 00:45:17,614
can be combined
with the "wisdom" of others.
1169
00:45:17,647 --> 00:45:22,219
RASKAR:
Achieving privacy and benefits
of the data simultaneously,
1170
00:45:22,252 --> 00:45:25,422
it's like having a cake and
eating it, too; it's available.
1171
00:45:25,455 --> 00:45:28,158
And it's just a matter of
convincing large companies
1172
00:45:28,191 --> 00:45:30,494
to play along those rules.
1173
00:45:30,527 --> 00:45:34,297
PATEL:
Smashed data is one way
we can learn to stop worrying
1174
00:45:34,330 --> 00:45:37,033
and love sharing
our personal data.
1175
00:45:37,066 --> 00:45:39,803
But every corporate network
would have to agree
1176
00:45:39,836 --> 00:45:42,639
to smash our raw data.
1177
00:45:43,840 --> 00:45:46,042
I'm not convinced
we should wait around
1178
00:45:46,075 --> 00:45:48,378
for big tech companies
to do this.
1179
00:45:49,178 --> 00:45:50,781
HILL:
The big technology companies,
1180
00:45:50,814 --> 00:45:53,750
they have built
the infrastructure
1181
00:45:53,783 --> 00:45:54,784
of the whole internet.
1182
00:45:54,818 --> 00:45:57,287
You're not just interacting
with these companies
1183
00:45:57,320 --> 00:45:59,022
when you know you're interacting
with them.
1184
00:46:00,256 --> 00:46:02,092
PATEL:
Even if it seems like you're on
1185
00:46:02,125 --> 00:46:05,762
a totally independent website,
big tech still sees you.
1186
00:46:05,795 --> 00:46:08,999
For example, tons of websites,
1187
00:46:09,032 --> 00:46:12,135
like some of the ones owned
by NASA, Pfizer, BMW,
1188
00:46:12,168 --> 00:46:15,372
even PBS,
use Amazon Web Services,
1189
00:46:15,405 --> 00:46:19,543
which means Amazon gets
some data when you visit them.
1190
00:46:19,576 --> 00:46:22,145
Or when you visit
any app on your iPhone,
1191
00:46:22,178 --> 00:46:24,014
Apple knows.
1192
00:46:24,047 --> 00:46:26,149
Also, every time
you've been to a webpage
1193
00:46:26,182 --> 00:46:28,385
that has
a Facebook "like" button,
1194
00:46:28,418 --> 00:46:31,521
Facebook gets to gobble up
your personal data.
1195
00:46:31,554 --> 00:46:33,089
KAHLE:
So it may seem
1196
00:46:33,122 --> 00:46:34,324
like the web is decentralized
1197
00:46:34,357 --> 00:46:35,759
because it comes from
many different places.
1198
00:46:35,792 --> 00:46:37,160
But in fact,
1199
00:46:37,193 --> 00:46:39,429
there's centralized points
of control.
1200
00:46:40,229 --> 00:46:43,600
CHOWDHURY:
Right now, for example, when
you are in a social media app,
1201
00:46:43,633 --> 00:46:44,768
you're sort of locked in, right?
1202
00:46:44,801 --> 00:46:46,436
All your information
is on there.
1203
00:46:46,469 --> 00:46:48,138
It's hard to leave a social
media app
1204
00:46:48,171 --> 00:46:49,239
because you're like,
"All my friends are there,
1205
00:46:49,272 --> 00:46:50,640
all my photos are there.
1206
00:46:50,673 --> 00:46:52,342
"If I move to another app,
1207
00:46:52,375 --> 00:46:53,710
I have to rebuild
that community."
1208
00:46:54,644 --> 00:46:57,814
GALPERIN:
Those social media websites
are controlled
1209
00:46:57,847 --> 00:46:59,516
by a very small
number of companies.
1210
00:46:59,549 --> 00:47:02,052
And the rules about
using those websites,
1211
00:47:02,085 --> 00:47:06,456
who has access to them and what
kind of behavior is acceptable
1212
00:47:06,489 --> 00:47:10,027
on them, are set by
the websites themselves.
1213
00:47:11,161 --> 00:47:16,166
PATEL:
This centralized data monopoly,
how do we start to dismantle it?
1214
00:47:16,199 --> 00:47:18,468
That's exactly what
proponents of an idea
1215
00:47:18,501 --> 00:47:22,272
called the decentralized web
want to do.
1216
00:47:23,139 --> 00:47:26,142
GALPERIN:
The decentralized web
is sort of our antidote,
1217
00:47:26,175 --> 00:47:30,080
the antithesis of the web
as we now think of it.
1218
00:47:30,113 --> 00:47:32,449
CHRISTINE LEMMER-WEBBER:
The decentralized web
can be seen in contrast
1219
00:47:32,482 --> 00:47:34,618
to the centralized web,
of course.
1220
00:47:34,651 --> 00:47:37,354
Instead of what has become,
1221
00:47:37,387 --> 00:47:41,157
on the internet, of a few big
players kind of controlling
1222
00:47:41,190 --> 00:47:42,659
a lot of the web
and the internet space,
1223
00:47:42,692 --> 00:47:44,661
we're really kind of
rolling things back
1224
00:47:44,694 --> 00:47:46,463
to kind of what
the vision of the internet was.
1225
00:47:47,464 --> 00:47:50,066
PATEL:
I'm wondering
what a decentralized web
1226
00:47:50,099 --> 00:47:52,235
would look and feel like?
1227
00:47:52,268 --> 00:47:55,672
So I'm meeting up with coder
Christine Lemmer-Webber,
1228
00:47:55,705 --> 00:47:57,440
who is working on writing
the standards and rules
1229
00:47:57,473 --> 00:48:01,578
for how social media could work
on a decentralized web.
1230
00:48:01,611 --> 00:48:03,246
LEMMER-WEBBER:
Most people are familiar
1231
00:48:03,279 --> 00:48:05,248
with social networks:
you know, they've used,
1232
00:48:05,281 --> 00:48:07,150
you know, X-slash-Twitter;
1233
00:48:07,183 --> 00:48:09,219
they've used Facebook;
they've used Instagram.
1234
00:48:09,252 --> 00:48:11,988
The decentralized social web is
1235
00:48:12,021 --> 00:48:14,758
like that, but no one company,
1236
00:48:14,791 --> 00:48:17,127
no one gatekeeper
controls the thing.
1237
00:48:17,160 --> 00:48:18,995
We want to be able to have
1238
00:48:19,028 --> 00:48:20,764
all of our different
social media sites,
1239
00:48:20,797 --> 00:48:23,199
all of our different
online communication tools
1240
00:48:23,232 --> 00:48:25,302
be able to talk to each other.
1241
00:48:25,335 --> 00:48:26,536
DOCTOROW:
A decentralized web
1242
00:48:26,569 --> 00:48:29,105
is one that is focused on
1243
00:48:29,138 --> 00:48:31,074
the self-determination of users.
1244
00:48:31,107 --> 00:48:32,242
You're not locked in.
1245
00:48:33,476 --> 00:48:36,179
So you find a service,
and you like it.
1246
00:48:36,212 --> 00:48:37,480
(duck quacks)
1247
00:48:37,513 --> 00:48:39,283
And then you and they
start to part ways.
1248
00:48:40,083 --> 00:48:43,753
The art you made,
the stories you told are there.
1249
00:48:43,786 --> 00:48:47,057
In a decentralized web,
you go somewhere else.
1250
00:48:47,090 --> 00:48:49,726
You go somewhere else,
and you don't lose any of that.
1251
00:48:53,629 --> 00:48:57,100
PATEL (voiceover):
But imagine, instead of having
one Facebook-type company,
1252
00:48:57,133 --> 00:49:00,036
we each had our own data
live on our own devices,
1253
00:49:00,069 --> 00:49:02,639
and it was easy to join
or merge with others,
1254
00:49:02,672 --> 00:49:04,374
or disconnect from them.
1255
00:49:04,407 --> 00:49:06,576
Leaving one group
and joining another
1256
00:49:06,609 --> 00:49:09,112
wouldn't mean rebuilding
everything from scratch
1257
00:49:09,145 --> 00:49:12,015
because
your data moves with you.
1258
00:49:13,116 --> 00:49:14,751
It sounds like a tech fantasy.
1259
00:49:14,784 --> 00:49:17,020
But it's actually something
we've already proven
1260
00:49:17,053 --> 00:49:18,321
works online.
1261
00:49:18,354 --> 00:49:21,758
Consider something you may use
every day,
1262
00:49:21,791 --> 00:49:24,995
or if you're like me,
every minute: email.
1263
00:49:25,028 --> 00:49:26,763
LEMMER-WEBBER:
So what a lot of people
don't realize
1264
00:49:26,796 --> 00:49:29,132
is that they use decentralized
networks every day.
1265
00:49:29,165 --> 00:49:30,734
It doesn't matter
if somebody's on Gmail,
1266
00:49:30,767 --> 00:49:32,268
or if they're on Hotmail,
1267
00:49:32,301 --> 00:49:34,004
they're on
their university email.
1268
00:49:34,037 --> 00:49:35,238
They don't even
have to think about it.
1269
00:49:35,271 --> 00:49:37,040
They type an email
to their friend,
1270
00:49:37,073 --> 00:49:39,175
and they send it off,
and it gets there, right?
1271
00:49:39,208 --> 00:49:41,111
At the heart of it,
that's kind of the basics
1272
00:49:41,144 --> 00:49:42,179
of what we're doing.
1273
00:49:43,480 --> 00:49:47,083
PATEL:
In other words, you can get
an email sent from Hotmail
1274
00:49:47,116 --> 00:49:48,685
even if you have
a Gmail account.
1275
00:49:48,718 --> 00:49:52,389
Or you can create your own
email server, for that matter.
1276
00:49:52,422 --> 00:49:55,492
It doesn't matter what
email service you use
1277
00:49:55,525 --> 00:49:58,161
because the protocol,
the rules, are written
1278
00:49:58,194 --> 00:50:01,631
to allow the email servers
to talk to one another.
1279
00:50:02,465 --> 00:50:04,667
LEMMER-WEBBER:
That's because there's
a shared protocol that says,
1280
00:50:04,700 --> 00:50:07,270
here's how we get the messages
from place to place.
1281
00:50:07,303 --> 00:50:09,740
Social networks
could just work like email.
1282
00:50:10,540 --> 00:50:12,809
PATEL:
And in fact, there are plenty
of decentralized projects
1283
00:50:12,842 --> 00:50:14,644
out there like Mastodon
1284
00:50:14,677 --> 00:50:15,745
and Blue Sky
1285
00:50:15,778 --> 00:50:17,647
putting the user's
profile and data
1286
00:50:17,680 --> 00:50:19,049
back into the users' hands.
1287
00:50:19,949 --> 00:50:21,618
LEMMER-WEBBER:
In the systems we're
moving towards
1288
00:50:21,651 --> 00:50:23,319
that will be much more the case
1289
00:50:23,352 --> 00:50:25,588
where private communication
is much more private.
1290
00:50:25,621 --> 00:50:28,625
They're, by default,
secure in that type of way.
1291
00:50:28,658 --> 00:50:31,661
We're building new foundations
1292
00:50:31,694 --> 00:50:34,130
for the internet
that allow for healthier,
1293
00:50:34,163 --> 00:50:38,368
safer, more decentralized
systems, gatekeeper-free.
1294
00:50:38,401 --> 00:50:41,405
That's the vision and the future
we're trying to build.
1295
00:50:42,839 --> 00:50:46,342
PATEL:
No doubt,
there are secrets in your data.
1296
00:50:46,375 --> 00:50:49,679
NOBLE:
Everything we touch
is increasingly datafied,
1297
00:50:49,712 --> 00:50:51,848
every dimension of our lives.
1298
00:50:51,881 --> 00:50:55,185
CHOWDHURY:
All of this data
goes into feed algorithms.
1299
00:50:55,218 --> 00:50:57,654
And algorithms make predictions
1300
00:50:57,687 --> 00:50:59,122
about how long you will live,
1301
00:50:59,155 --> 00:51:01,224
or your health,
or your lifestyle.
1302
00:51:02,058 --> 00:51:04,160
PATEL (voiceover):
And while I learned
how to protect
1303
00:51:04,193 --> 00:51:06,229
my personal privacy
and security,
1304
00:51:06,262 --> 00:51:09,065
there's only so much
I can do myself.
1305
00:51:09,098 --> 00:51:10,467
HILL:
There are things
that individuals
1306
00:51:10,500 --> 00:51:12,402
can do to protect their privacy.
1307
00:51:12,435 --> 00:51:14,204
Ultimately, in order to
1308
00:51:14,237 --> 00:51:18,175
avoid a huge crisis,
it requires systemic change.
1309
00:51:18,875 --> 00:51:23,046
GALPERIN:
There are limits to
what we can do as individuals.
1310
00:51:23,079 --> 00:51:25,281
There are also things
that need to be addressed
1311
00:51:25,314 --> 00:51:27,650
through regulation,
through litigation,
1312
00:51:27,683 --> 00:51:32,288
and through legislation in
order to make all of us safer.
1313
00:51:32,321 --> 00:51:35,525
PATEL:
It's comforting to know
there are techies out there
1314
00:51:35,558 --> 00:51:38,428
trying to protect us
and our data,
1315
00:51:38,461 --> 00:51:41,064
designing new ways to enjoy
the fun and convenience
1316
00:51:41,097 --> 00:51:44,300
of the digital world
without being exploited.
1317
00:51:44,333 --> 00:51:48,104
KAHLE:
New technologies,
new games can proliferate
1318
00:51:48,137 --> 00:51:50,206
without centralized
points of control.
1319
00:51:50,239 --> 00:51:53,176
That's the excitement
of the decentralized web.
1320
00:51:53,209 --> 00:51:56,546
LEMMER-WEBBER:
I can't wait for people
to see this vision
1321
00:51:56,579 --> 00:52:00,016
we're building for
collaborative, more consensual,
1322
00:52:00,049 --> 00:52:01,684
decentralized social networks.
1323
00:52:01,717 --> 00:52:04,621
That's going to be
really exciting.
1324
00:52:05,421 --> 00:52:07,657
PATEL:
The future we're building
might not look too different
1325
00:52:07,690 --> 00:52:10,493
from the internet of today.
1326
00:52:10,526 --> 00:52:13,062
But it could be much more
private and secure,
1327
00:52:13,095 --> 00:52:16,199
if we get it right.
1328
00:52:16,232 --> 00:52:19,169
DOCTOROW:
This is about how technological
self-determination
1329
00:52:19,202 --> 00:52:21,437
and regulation work together
1330
00:52:21,470 --> 00:52:25,041
to make a world that is
more safe for human habitation.
1331
00:52:37,853 --> 00:52:41,124
♪ ♪
1332
00:52:41,857 --> 00:52:49,399
♪ ♪
1333
00:52:53,236 --> 00:53:00,977
♪ ♪
1334
00:53:04,614 --> 00:53:12,155
♪ ♪
1335
00:53:13,789 --> 00:53:21,331
♪ ♪
1336
00:53:23,165 --> 00:53:30,507
♪ ♪
95747
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