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[wind blowing softly]
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[soft, indistinct chatter]
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[man 1] Ms. Kaiser,
you seem to have traveled a long way
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from an idealistic intern
in Barack Obama's campaign
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to working for an organization
that keeps pretty unsavory company.
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Didn't that make you uncomfortable at all?
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[man 2] You referred to having two sets
of business cards.
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Who did you work for?
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[explosions booming]
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[man 1] Don't take this the wrong way.
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In your life, have you ever worked for
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or provided information
to any country's intelligence agency?
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[man] Hi. A small coffee, please?
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- Uh, $2.25.
- Great.
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All right.
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- [phone chimes]
- [man] Who has seen an advertisement
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that has convinced you
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that your microphone is listening
to your conversations?
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[class laughing]
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[man] It's hard for us to imagine
how else it could work,
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but what's happening
is that your behavior
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is being accurately predicted.
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So, the ads that seem uncannily accurate,
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that have to be eavesdropping on us,
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are more likely to be evidence
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that the targeting works,
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and that it predicts our behavior.
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Maybe it's because I grew up
with the Internet as a reality.
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The ads don't bother me all that much.
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When does it turn sour?
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[electronic chiming]
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[phone chimes, vibrates]
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[female voice over PA]
This is a Brooklyn-bound Q express train.
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- The next stop is Canal Street.
- [phone vibrates]
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[phone vibrates]
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[Carroll] It began with the dream
of a connected world.
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A space where everyone could share
each other's experiences
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and feel less alone.
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It wasn't long before this world
became our matchmaker,
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instant fact-checker,
personal entertainer,
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guardian of our memories,
even our therapist.
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[speaks indistinctly to students]
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[Carroll] I was teaching digital media
and developing apps.
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So, I knew that the data
from our online activity
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wasn't just evaporating.
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And as I dug deeper, I realized...
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these digital traces of ourselves
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are being mined
into a trillion-dollar-a-year industry.
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We are now the commodity.
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But we were so in love
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with the gift of this free connectivity...
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that no one bothered to read
the terms and conditions.
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- [overlapping voices]
- [digital noise]
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[Carroll] All of my interactions,
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my credit card swipes, web searches,
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locations, my likes,
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they're all collected in real time
and attached to my identity,
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giving any buyer direct access
to my emotional pulse.
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Armed with this knowledge,
they compete for my attention,
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feeding me a steady stream of content
built for and seen only by me.
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And this is true
for each and every one of us.
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What I like,
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what I fear,
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what gets my attention,
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what my boundaries are,
and what it takes to cross them.
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[overlapping voices]
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[woman 1] Go back to Washington.
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[woman 2]
Crooked Hillary tells lots of lies.
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The stock market's gonna crash.
I mean, this'll cause a civil war.
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[Carroll] We saw the fallout
of our filtered realities
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in the 2016 election.
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[woman 3] ...you were not offended
when Donald Trump said it!
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[overlapping shouts and jeers]
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- [man 1] Get the fuck out!
- [angry shouts overlapping]
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[Carroll] The real world became
a deeply divided wreckage site.
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- [protesters chanting indistinctly]
- [overlapping shouts]
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[man 2]
Fuck those dirty beaners! Build the wall!
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[man 3] Whoo!
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[men shouting] Fight!
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[Carroll] How did the dream
of the connected world tear us apart?
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[static crackles]
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[Carroll]
My daughter is eight, and my son is four.
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Uh, every app is carefully scrutinized
before ins... being installed, and...
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And, like, now, I'm the dad
who reads the privacy policy and says,
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"No, you see here?
They read your messages.
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Are you okay with that?" [chuckles]
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That's, like, the new way
I'm gonna be an annoying parent.
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- Hey.
- [kids chattering]
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[Carroll]
I've been concerned for a long time
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about how the misuse
of our data and information
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could affect my children's future.
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But it wasn't until
after the 2016 election that I realized
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it had already happened on our watch.
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It was really, like, a feeling of, like...
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[takes a deep breath]
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...the worst-case scenario has happened
with technology.
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Hmm.
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I became obsessed with finding answers.
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And the question I kept asking myself was:
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Who was feeding us fear?
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And how?
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This was our Project Alamo,
where the digital arm
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of the Trump campaign operation was held.
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When Project Alamo was at its peak,
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they were spending
one million dollars a day
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on Facebook ads.
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We had the Facebook,
and YouTube, and Google people.
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They would kind of congregate here.
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I mean, they were basically
our hands-on partners
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as far as, you know,
being able to utilize the platform
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as effectively as possible.
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But what we also learned
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is that a company
called Cambridge Analytica...
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was also working on Project Alamo.
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Cambridge Analytica was here.
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And this is kind of the brain of... of,
you know, the data.
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- [over video] This was the data center.
- [man] Right.
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"We gotta target this state.
We gotta target that state."
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- So, within that...
- [man] How would they know that?
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- How would they know that...
- That's... That's their secret sauce.
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- [computer chimes]
- [mouse clicks]
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- [Carroll] Paul-Olivier?
- [Paul-Olivier] I'm there.
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Okay. Let me just, uh, set up my screen.
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[Carroll] I connected with a mathematician
based out of Switzerland
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named Paul-Olivier Dehaye.
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[Dehaye] I've been looking
at Cambridge Analytica for over a year
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and I think there's more to be found.
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[Carroll] Both Paul and I understood that
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in order to send people
personalized messages,
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you need people's data.
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And Cambridge Analytica
claimed to have 5,000 data points
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on every American voter.
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But it was invisible.
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And so the question is,
how do you make the invisible visible?
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[sighs] That's the hardest part. Um...
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- [marker squeaks]
- [Carroll] Paul-Olivier Dehaye had
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a hypothesis,
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and the hypothesis was that US voter data
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was processed
by Cambridge Analytica's parent company
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in Great Britain.
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And if it was true,
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I could use a British lawyer
to force Cambridge Analytica
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to give me my data.
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[man] I think the beauty of David's case
is it encapsulates
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why data rights should be considered
just fundamental rights, simple rights.
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Because all he wants to know
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is what did you do?
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And if David finds out
the data beneath his profile,
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you'll start to be able
to connect the dots in various ways
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with Facebook and Cambridge Analytica
and Trump and Brexit
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and all these loosely-connected entities.
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Because you get to see inside the beast,
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you get to see inside the system.
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[man] I used to be the COO and CFO
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of the Cambridge Analytica, or SCL, Group.
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If you spoke to most people
that worked at Cambridge Analytica,
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they would say the same thing.
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It was, uh...
an environment of great innovation.
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Hello, my name is Alexander Nix.
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I'm CEO of Cambridge Analytica,
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the world's leading
data-driven communications company.
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From Mad Men of old to Math Men of today,
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expert data scientists whose insight
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can tell you far more about audiences
that you want to reach
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and how to reach them.
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[Wheatland] Alexander Nix was very focused
on building a strong elections business.
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And then the Obama campaign
very successfully used data
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and digital communications,
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which created a market opportunity
to provide a service
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to Republican politics in the US.
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[crowd cheering]
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[Cruz] God bless the great state of Iowa.
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[crowd cheering]
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[Wheatland] Ted Cruz went
from the lowest rated candidate
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in the primaries
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to being the last man standing
before Trump got the nomination.
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[crowd members cheer]
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Let me first of all say...
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- to God be the glory.
- [crowd cheering]
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[reporter] Everyone said Ted Cruz had
this amazing ground game,
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and now we know
who came up with all of it.
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Joining me now, Alexander Nix,
CEO of Cambridge Analytica,
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the company behind it all.
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It's fascinating, Alexander,
to look at all of the work
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that goes into the ground game.
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Have any of the other candidates
called you?
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Well, um...
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[audience applauding]
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It's my privilege to speak to you today
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about the power of big data
and psychographics.
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When Cambridge Analytica
joined the Trump campaign,
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we were an attractive proposition.
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We'd just spent 14 months
working on the Ted Cruz campaign,
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and had collected a huge amount
of voter data and research,
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which we were able to hand over
to the Trump team.
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By having hundreds and hundreds
of thousands of Americans
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undertake this survey,
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we were able to form a model,
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where we have somewhere close
to four or five thousand data points
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we can use to predict the personality
of every adult in the United States.
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Because it's personality
that drives behavior,
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and behavior that obviously influences
how you vote.
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We could then start to target people
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with highly-targeted
digital video content.
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[man 1] Secretary Clinton said there was
nothing marked classified on her emails
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either sent or received. Was that true?
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[Trump] Our movement is about replacing
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00:14:39,920 --> 00:14:44,049
a failed
and corrupt political establishment.
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Why aren't I 50 points ahead,
you might ask?
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[man 2] Do you really need to ask?
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[Clinton coughing]
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- [crowd cheering]
- [rousing orchestral theme plays]
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00:15:02,735 --> 00:15:04,445
A night that will go down in history,
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00:15:04,528 --> 00:15:07,698
a stunning upset as Donald Trump
triumphs over Hillary Clinton,
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00:15:07,781 --> 00:15:11,368
defying the polls, the pundits,
and the political class once again,
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00:15:11,452 --> 00:15:14,163
this time elected president
of the United States.
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00:15:16,624 --> 00:15:18,626
[orchestral theme continues]
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[crowd cheering]
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00:15:31,889 --> 00:15:34,308
[crowd chanting] USA! USA!
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00:15:34,391 --> 00:15:36,435
- Thank you.
- [chanting continues]
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[Trump]
Thank you very much, everybody.
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[Nix] If there's one singular takeaway
from this event,
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that is that these sorts
of technologies
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can make a huge difference
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and will continue to do so
for many years to come.
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Thank you.
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[audience applauding]
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[Wheatland] After the election,
it was really exciting.
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[cheering]
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[Wheatland] We could see the path
to being a billion-dollar company.
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We were on top of the world.
Or at least we thought we were.
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[Cadwalladr] This is the exciting box.
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I've been investigating
Cambridge Analytica
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and how that ties to the Brexit campaign
to leave the European Union.
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And this has been my full-time,
12-hours-a-day,
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seven-days-a-week kind of obsession,
I would say, since then.
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It's been all-consuming.
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[sighs]
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When I first started looking
into this whole web of links
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between Cambridge Analytica and Brexit...
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I emailed Andy Wigmore,
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00:17:22,708 --> 00:17:26,754
who is an associate of Nigel Farage.
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And Nigel Farage is a very central figure
in the Brexit campaign.
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I sort of said,
"Oh, can we go for a coffee?
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I'm really interested in technology
and campaigning."
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And then he just sort of like,
he just like laid it all out.
247
00:17:45,355 --> 00:17:47,357
[upbeat jazz playing]
248
00:17:51,236 --> 00:17:53,280
[Cadwalladr]
It was just after the Inauguration.
249
00:17:53,697 --> 00:17:57,034
So, Andy, he was just like sort of, like,
showing me all the photos on his phone.
250
00:17:57,117 --> 00:17:58,869
"This is the inauguration."
251
00:18:00,913 --> 00:18:02,414
Then, "Oh, it's such a laugh!
252
00:18:02,664 --> 00:18:04,583
We had such a good time. Oh, Donald..."
253
00:18:06,543 --> 00:18:09,588
And I was like, "How did the introduction
to Cambridge Analytica come out?"
254
00:18:10,923 --> 00:18:14,301
He was like, "You know, it's 'cause Nigel.
Nigel's friends with Steve Bannon."
255
00:18:14,593 --> 00:18:17,805
- Ladies and gentlemen, Steve Bannon!
- [audience cheers]
256
00:18:18,263 --> 00:18:22,101
[Cadwalladr] Steve Bannon headed
the campaign for Trump.
257
00:18:23,102 --> 00:18:26,772
He's also the Vice President
of Cambridge Analytica.
258
00:18:27,940 --> 00:18:31,068
So he's like, "Yeah, there's this bunch
of billionaires in the States.
259
00:18:31,360 --> 00:18:33,445
We've all got the same aims,
260
00:18:33,946 --> 00:18:38,283
and Brexit was the petri dish for Trump."
261
00:18:38,367 --> 00:18:41,411
For most of my life,
America is the leader.
262
00:18:41,703 --> 00:18:44,998
Now, I would like to think,
in my own little way,
263
00:18:45,499 --> 00:18:47,292
that what we did with Brexit
264
00:18:47,751 --> 00:18:51,380
was the beginning
of what is gonna turn out to be
265
00:18:51,463 --> 00:18:53,674
a global revolution
266
00:18:53,757 --> 00:18:56,176
and that Trump's victory
is a part of that.
267
00:18:56,260 --> 00:18:58,137
[people cheering, applauding]
268
00:19:01,557 --> 00:19:05,644
[scoffs] Anyway, and then he told me
all sorts of other stuff
269
00:19:05,727 --> 00:19:08,605
about, you know, how they used
artificial intelligence,
270
00:19:08,689 --> 00:19:12,651
you know,
how they were mining details from Facebook
271
00:19:12,734 --> 00:19:14,278
and, um...
272
00:19:14,361 --> 00:19:18,115
And he was like... And he was like,
"It's creepy, Carole!" He said,
273
00:19:18,198 --> 00:19:20,450
"The amount of information
you can get on people...
274
00:19:20,534 --> 00:19:22,369
People just give it to you!"
275
00:19:22,452 --> 00:19:24,132
And he sort of said,
"It's just so creepy!"
276
00:19:26,039 --> 00:19:28,041
So, I just kind of kept going.
277
00:19:29,751 --> 00:19:31,044
The Brexit work.
278
00:19:32,462 --> 00:19:37,134
I'd started tracking down all these
Cambridge Analytica ex-employees.
279
00:19:40,470 --> 00:19:44,892
And, eventually, I got one guy
who was prepared to talk to me.
280
00:19:46,476 --> 00:19:47,519
Chris Wylie.
281
00:19:51,190 --> 00:19:54,735
We had this first telephone call,
which was insane.
282
00:19:54,818 --> 00:19:57,654
It was about eight hours long. And...
283
00:19:58,655 --> 00:20:00,324
[mimics explosion sound]
284
00:20:05,704 --> 00:20:08,373
My name is Christopher Wylie,
I'm a data scientist
285
00:20:08,457 --> 00:20:10,500
and I helped set up Cambridge Analytica.
286
00:20:12,044 --> 00:20:15,297
It's incorrect to call Cambridge Analytica
287
00:20:15,380 --> 00:20:19,551
a purely sort of data science company
or an algorithm, you know, company.
288
00:20:19,676 --> 00:20:22,930
You know, it is a full-service
propaganda machine.
289
00:20:26,516 --> 00:20:29,561
[interviewer] You were an investor
in Cambridge Analytica.
290
00:20:29,645 --> 00:20:32,624
- I helped put the company together.
- [interviewer] And... Yes, you did. And...
291
00:20:32,648 --> 00:20:34,733
And gave it...
And gave it that amazing name.
292
00:20:35,192 --> 00:20:38,111
[Wylie]
Steve Bannon was the editor of Breitbart.
293
00:20:39,613 --> 00:20:42,366
He follows this idea
of the Breitbart doctrine,
294
00:20:42,449 --> 00:20:46,370
which is that, if you want
to fundamentally change society,
295
00:20:46,495 --> 00:20:48,121
you first have to break it.
296
00:20:48,455 --> 00:20:49,915
And it's only when you break it
297
00:20:49,998 --> 00:20:54,711
is when you can remold the pieces
into your vision of a new society.
298
00:20:58,257 --> 00:20:59,925
This was the weapon
299
00:21:00,008 --> 00:21:03,178
that Steve Bannon wanted to build
to fight his culture war.
300
00:21:04,179 --> 00:21:05,847
And we could build them for him.
301
00:21:06,431 --> 00:21:09,393
But I needed to figure out a way
of getting data,
302
00:21:09,476 --> 00:21:12,938
and so I went
to these Cambridge University profs
303
00:21:13,021 --> 00:21:14,606
and asked, "What do you think?"
304
00:21:28,328 --> 00:21:33,750
Kogan offered us apps on Facebook
that were given special permission
305
00:21:33,959 --> 00:21:39,756
to harvest data not from just the person
who used the app or joined the app,
306
00:21:41,049 --> 00:21:45,053
but also it would then go
into their entire friend network
307
00:21:45,637 --> 00:21:48,724
and pull out
all of the friends' data as well.
308
00:21:50,475 --> 00:21:53,061
If you were a friend of somebody
who used the app,
309
00:21:53,145 --> 00:21:56,148
you would have no idea
that I just pulled all of your data.
310
00:22:00,777 --> 00:22:03,780
We took things like status updates, likes,
311
00:22:03,864 --> 00:22:06,116
in some cases, private messages.
312
00:22:08,660 --> 00:22:10,954
We wouldn't just be targeting you
as a voter,
313
00:22:11,038 --> 00:22:14,333
we'd be targeting you as a personality.
314
00:22:16,460 --> 00:22:20,672
We would only need to touch
a couple hundred thousand people
315
00:22:20,756 --> 00:22:23,342
to build a psychological profile
316
00:22:23,425 --> 00:22:28,013
of each voter in all of the United States.
317
00:22:31,975 --> 00:22:33,244
[Cadwalladr] And people had no idea
318
00:22:33,268 --> 00:22:35,354
that their data was being taken
in this way?
319
00:22:36,313 --> 00:22:37,314
[Wylie] No.
320
00:22:42,486 --> 00:22:44,363
[Cadwalladr]
You didn't ever stop and think,
321
00:22:44,446 --> 00:22:47,866
"Actually, this is people's
personal information,
322
00:22:47,949 --> 00:22:52,579
and we're taking it, and we're using it
in ways that they don't understand"?
323
00:22:53,288 --> 00:22:54,288
[Wylie] No.
324
00:22:56,375 --> 00:23:00,670
Throughout history, you have examples
of grossly unethical experiments.
325
00:23:01,129 --> 00:23:02,631
[Cadwalladr] Is that what this was?
326
00:23:03,382 --> 00:23:07,636
[Wylie] I think that, yes,
it was a grossly unethical experiment.
327
00:23:08,970 --> 00:23:12,182
You are playing with the psychology
of an entire country
328
00:23:12,265 --> 00:23:14,434
without their consent or awareness.
329
00:23:15,769 --> 00:23:17,729
And not only are you, like,
330
00:23:17,813 --> 00:23:20,190
playing with the psychology
of an entire nation,
331
00:23:20,273 --> 00:23:22,377
you're playing with the psychology
of an entire nation
332
00:23:22,401 --> 00:23:24,111
in the context of the democratic process.
333
00:23:24,194 --> 00:23:27,280
[news anchor speaks indistinctly nearby]
334
00:23:31,034 --> 00:23:33,578
[Carroll]
The revelations have started to spill out.
335
00:23:34,663 --> 00:23:40,460
We're now not just threatening
to do things, but we're actually doing it.
336
00:23:42,671 --> 00:23:45,590
- [anchor] Okay, we're ready, guys.
- [man] One, two, three...
337
00:23:45,966 --> 00:23:48,093
We turn now to the burgeoning scandal
338
00:23:48,176 --> 00:23:51,054
around voter-profiling company
Cambridge Analytica.
339
00:23:51,388 --> 00:23:54,724
David Carroll filed a legal challenge
in Britain
340
00:23:54,808 --> 00:23:57,352
asking the court
to force Cambridge Analytica
341
00:23:57,436 --> 00:24:00,564
to turn over all the data it harvested
on him.
342
00:24:00,814 --> 00:24:02,816
Explain what you are demanding.
343
00:24:03,275 --> 00:24:05,402
Uh, full disclosure, so...
344
00:24:06,945 --> 00:24:08,780
where did they get our data,
345
00:24:08,864 --> 00:24:12,284
how did they process it,
who did they share it with,
346
00:24:12,576 --> 00:24:14,828
and do we have a right to opt out?
347
00:24:17,080 --> 00:24:18,331
[man] Cambridge Analytica says
348
00:24:18,415 --> 00:24:19,541
it's got 5,000 data points
349
00:24:19,624 --> 00:24:21,668
on many, many millions
of people out there.
350
00:24:21,751 --> 00:24:22,836
[Carroll] That's right.
351
00:24:22,919 --> 00:24:26,298
When people can actually see
the extent of the surveillance,
352
00:24:26,381 --> 00:24:28,633
I think they're going to be shocked.
353
00:24:30,218 --> 00:24:33,430
We don't work with Facebook data.
We don't have Facebook data.
354
00:24:33,513 --> 00:24:36,766
Uh, we do use Facebook
as a platform, uh, to advertise.
355
00:24:37,184 --> 00:24:38,351
Mr. Nix, Channel 4 News.
356
00:24:38,560 --> 00:24:40,687
Did you mislead Parliament
over the Facebook issue?
357
00:24:40,770 --> 00:24:43,315
- Absolutely not.
- [reporter continues indistinctly]
358
00:24:44,149 --> 00:24:47,736
[Carroll] It's crazy that I have to mount
a year-long,
359
00:24:47,819 --> 00:24:51,865
super risky legal challenge
in another country
360
00:24:51,990 --> 00:24:54,159
to get my voter profile.
361
00:24:54,326 --> 00:24:57,537
David, don't stop, don't relent.
362
00:24:57,621 --> 00:24:58,872
[Carroll chuckles]
363
00:24:58,955 --> 00:25:00,957
- Keep going. Good.
- I'm gonna do it, don't worry.
364
00:25:01,041 --> 00:25:02,876
- [woman] Don't sleep!
- [Carroll laughs]
365
00:25:05,670 --> 00:25:08,423
Facebook's down 6.35%.
366
00:25:08,715 --> 00:25:10,717
That's 120 billion dollars.
367
00:25:11,092 --> 00:25:12,219
This is huge.
368
00:25:14,387 --> 00:25:17,265
[reporter 1] Officers working
for the UK Information Commissioner
369
00:25:17,349 --> 00:25:20,727
are searching the headquarters
of Cambridge Analytica, in London.
370
00:25:20,810 --> 00:25:22,872
[reporter 2] They're inside,
they're looking at computers,
371
00:25:22,896 --> 00:25:24,523
they're looking for documents.
372
00:25:25,524 --> 00:25:29,486
[reporter 3] Facebook knew about
that data collection over two years ago
373
00:25:29,569 --> 00:25:32,572
but did not go public
until three days ago.
374
00:25:33,365 --> 00:25:34,407
Really, Facebook?
375
00:25:34,491 --> 00:25:36,326
You forgot to mention
that 50 million people
376
00:25:36,409 --> 00:25:37,595
had their private data breached,
377
00:25:37,619 --> 00:25:40,455
but every time it's my uncle's friend's
sister's dog's birthday,
378
00:25:40,539 --> 00:25:41,873
I get a notification?
379
00:25:41,957 --> 00:25:44,167
[audience laughs]
380
00:25:48,129 --> 00:25:50,298
[reporter 4] You are taking on a giant,
381
00:25:50,382 --> 00:25:52,425
a Goliath of big data marketing.
382
00:25:53,343 --> 00:25:55,262
How hopeful are you of succeeding?
383
00:25:55,720 --> 00:26:00,850
- [woman makes indistinct introduction]
- [audience applauds]
384
00:26:02,018 --> 00:26:04,688
[Carroll] People don't want to admit
that propaganda works.
385
00:26:05,480 --> 00:26:09,859
Because to admit it means confronting
our own susceptibilities,
386
00:26:10,193 --> 00:26:12,320
horrific lack of privacy,
387
00:26:12,612 --> 00:26:14,281
and hopeless dependency
388
00:26:14,364 --> 00:26:17,742
on tech platforms ruining our democracies
389
00:26:17,826 --> 00:26:19,619
on various attack surfaces.
390
00:26:20,370 --> 00:26:23,248
Join the struggle
to help get our data back.
391
00:26:23,999 --> 00:26:26,585
[applause, cheering]
392
00:26:37,345 --> 00:26:41,891
Welcome to our inquiry
into disinformation and fake news.
393
00:26:41,975 --> 00:26:45,520
I'd like to welcome Christopher Wylie
and Paul-Olivier Dehaye,
394
00:26:45,604 --> 00:26:48,231
uh, to the committee
to give evidence this morning.
395
00:26:49,190 --> 00:26:51,276
[O'Hara] Have you or anybody else made
any assessment
396
00:26:51,359 --> 00:26:53,296
of actually whether any of this
made much difference
397
00:26:53,320 --> 00:26:56,364
to the final outcome of the EU Referendum?
398
00:26:59,618 --> 00:27:03,580
When... When you're caught
in the Olympics doping, right,
399
00:27:03,788 --> 00:27:08,668
there's not a debate about how much
illegal drug you took. Right?
400
00:27:08,752 --> 00:27:10,045
Or, "Well,
401
00:27:10,128 --> 00:27:11,808
he probably would've come in first
anyway,"
402
00:27:11,880 --> 00:27:14,758
or, you know,
"He only took half of the amount," or...
403
00:27:14,841 --> 00:27:17,719
Doesn't matter. If you're caught cheating,
you lose your medal. Right?
404
00:27:17,802 --> 00:27:18,928
Because...
405
00:27:19,304 --> 00:27:23,308
[stammers]...if we allow cheating
in our democratic process,
406
00:27:23,683 --> 00:27:24,600
what about next time?
407
00:27:24,601 --> 00:27:28,146
What about the time after that?
Right? You shouldn't win by cheating.
408
00:27:29,648 --> 00:27:33,026
A lot of people will say,
and I'll say, um,
409
00:27:33,735 --> 00:27:36,464
that given that you're someone
who worked very closely with these people,
410
00:27:36,488 --> 00:27:37,656
uh, for a period of time,
411
00:27:37,739 --> 00:27:40,325
why have you decided to speak out
against it
412
00:27:40,408 --> 00:27:42,928
and give evidence against people
who used to be your colleagues?
413
00:27:43,286 --> 00:27:46,623
It's a process of coming to terms
with what you've created
414
00:27:46,706 --> 00:27:49,751
and the impact
that that... that... that has had.
415
00:27:49,834 --> 00:27:53,963
Um, I am incredibly remorseful
for my... my role in setting it up.
416
00:27:54,214 --> 00:27:59,094
But there's been a lot of attention on me
because I'm sort of... I've become the...
417
00:27:59,427 --> 00:28:02,347
uh, you know, the face of it,
because I'm the one that's...
418
00:28:02,514 --> 00:28:04,557
come forward and put my name to it.
419
00:28:04,683 --> 00:28:06,363
But someone else
that you should be calling
420
00:28:06,434 --> 00:28:07,894
to the committee is Brittany Kaiser.
421
00:28:08,478 --> 00:28:09,813
Who's Brittany Kaiser?
422
00:28:27,789 --> 00:28:32,085
I'm not that interested in standing up
for powerful white men anymore
423
00:28:32,168 --> 00:28:35,505
who obviously don't have
everybody's best interests at heart.
424
00:28:39,384 --> 00:28:41,469
[reporter 1] Brittany Kaiser,
once a key player
425
00:28:41,553 --> 00:28:43,513
inside Cambridge Analytica,
426
00:28:43,596 --> 00:28:45,765
casting herself as a whistle-blower.
427
00:28:46,433 --> 00:28:49,269
[reporter 2] Until three weeks ago,
Brittany Kaiser, a top exec there,
428
00:28:49,352 --> 00:28:52,981
she had a key to Steve Bannon's townhouse
in Washington.
429
00:28:53,064 --> 00:28:56,151
She spoke at CPAC in 2016,
along with Kellyanne Conway,
430
00:28:56,234 --> 00:28:58,653
spent election night
at the Trump victory party
431
00:28:58,737 --> 00:29:01,364
with mega-donor Rebekah Mercer.
432
00:29:02,532 --> 00:29:04,743
[reporter 1]
Miss Kaiser was also closely involved
433
00:29:04,826 --> 00:29:07,537
with millionaire Brexit supporter
Arron Banks
434
00:29:07,620 --> 00:29:09,706
and his Leave. EU campaign.
435
00:29:18,173 --> 00:29:20,067
[reporter 3]
She's raising some interesting things.
436
00:29:20,091 --> 00:29:21,444
Why is she talking now, do you think?
437
00:29:21,468 --> 00:29:23,470
[man] Well, she only gave us
part of the picture.
438
00:29:23,553 --> 00:29:27,056
She's talking to investigators,
and so we'll know the full picture
439
00:29:27,140 --> 00:29:28,475
at some point later...
440
00:29:37,942 --> 00:29:39,944
[soft jazz playing]
441
00:29:51,456 --> 00:29:53,666
[Kaiser] I have evidence
442
00:29:53,750 --> 00:29:58,171
that the Brexit campaigns
and the Trump campaign
443
00:29:58,254 --> 00:30:00,423
could've been conducted illegally.
444
00:30:03,343 --> 00:30:07,514
And so, for my own safety,
I don't need geolocation of where this is.
445
00:30:07,680 --> 00:30:09,474
Just me sitting here...
446
00:30:11,434 --> 00:30:13,937
the person trying to overthrow
two administrations
447
00:30:14,020 --> 00:30:16,856
and all of the most powerful companies
in the world,
448
00:30:16,940 --> 00:30:18,858
all at once.
449
00:30:18,942 --> 00:30:20,527
[chuckles]
450
00:30:20,610 --> 00:30:25,240
With one disjointed
but hopefully-soon-seamless narrative.
451
00:30:25,323 --> 00:30:26,366
[chuckles]
452
00:30:27,784 --> 00:30:31,204
The wealthiest companies
are technology companies.
453
00:30:31,913 --> 00:30:34,999
Google, Facebook, Amazon, Tesla.
454
00:30:35,500 --> 00:30:37,710
And the reason why these companies
455
00:30:37,794 --> 00:30:40,547
are the most powerful companies
in the world
456
00:30:40,630 --> 00:30:45,343
is because, last year, data surpassed oil
in its value.
457
00:30:45,802 --> 00:30:48,388
Data is the most valuable asset on Earth.
458
00:30:49,430 --> 00:30:52,517
And these companies are valuable
459
00:30:52,600 --> 00:30:56,271
because they have been exploiting
people's assets.
460
00:30:57,939 --> 00:31:00,817
It wasn't until one of my friends
reached out to me
461
00:31:00,900 --> 00:31:03,945
to ask was I going to be all right
462
00:31:04,028 --> 00:31:07,740
with the way that my story would be seen
in history.
463
00:31:08,867 --> 00:31:11,452
And I thought, "No.
464
00:31:12,537 --> 00:31:14,414
I'm not okay, actually." [chuckles]
465
00:31:14,497 --> 00:31:18,042
And there's probably a lot of information
that I could give
466
00:31:18,126 --> 00:31:22,171
that would be helpful
to making things okay, possibly.
467
00:31:42,859 --> 00:31:44,611
[Hilder] I'm a political technologist
468
00:31:44,694 --> 00:31:47,989
who tries to shine a big light
469
00:31:48,072 --> 00:31:50,408
on how data's been used and abused.
470
00:31:52,535 --> 00:31:55,038
It's a moment where people have
that visceral sense.
471
00:31:55,121 --> 00:31:56,748
There is, you know,
472
00:31:57,332 --> 00:31:59,918
that there's something wrong here,
uh, that we need to fix.
473
00:32:00,919 --> 00:32:05,506
And so, I've dropped
pretty much everything I was doing
474
00:32:05,590 --> 00:32:07,967
to work on this with Brittany Kaiser.
475
00:32:10,345 --> 00:32:13,306
I went and found her and met her,
476
00:32:13,389 --> 00:32:15,642
and she was very forthcoming
477
00:32:16,267 --> 00:32:20,063
in a way which made me think,
[chuckles] "There's a lot here."
478
00:32:20,563 --> 00:32:24,025
[applause, scattered cheers]
479
00:32:26,861 --> 00:32:30,657
What we really need to be understanding
is people's levers of persuasion.
480
00:32:30,740 --> 00:32:34,118
How are we actually going to message
voters so that they can under...
481
00:32:34,202 --> 00:32:37,497
[man] Tina and I met with Brittany Kaiser.
482
00:32:37,580 --> 00:32:40,249
[Kaiser] We look very unlike
any other political
483
00:32:40,333 --> 00:32:42,001
and communications firm, so...
484
00:32:42,085 --> 00:32:44,045
[woman]
Do you work both sides of the aisle?
485
00:32:44,128 --> 00:32:46,523
Uh, no, we only work for the Republicans
in the United States.
486
00:32:46,547 --> 00:32:47,547
[woman] Okay.
487
00:32:48,341 --> 00:32:49,676
And in Britain?
488
00:32:49,842 --> 00:32:53,304
[Kaiser] Well, actually, right now
we're working on the Brexit campaign.
489
00:32:54,555 --> 00:32:57,767
At Leave. EU, we're going
to be running a large-scale research
490
00:32:57,850 --> 00:33:00,103
throughout the nation to really understand
491
00:33:00,186 --> 00:33:03,481
why people are interested in staying in
or out of the EU.
492
00:33:03,564 --> 00:33:07,652
And the answers to that will help inform
our policy and our communications,
493
00:33:07,735 --> 00:33:10,321
to make sure that we turn out
more first-time voters,
494
00:33:10,405 --> 00:33:14,200
more unregistered voters,
more apathetic voters than ever before.
495
00:33:31,009 --> 00:33:33,928
[Hilder] I think we now have
the foundations laid for...
496
00:33:34,554 --> 00:33:38,057
her to share what is
some reasonably explosive materials
497
00:33:38,224 --> 00:33:39,642
that we've been finding.
498
00:33:40,226 --> 00:33:46,024
Uh, and, uh...
her inbox and her hard drive,
499
00:33:46,733 --> 00:33:50,945
uh, really are a treasure trove
of... uh, sketchy information.
500
00:33:53,906 --> 00:33:56,075
And we're still
just scratching the surface.
501
00:33:59,454 --> 00:34:02,540
[dance music playing]
502
00:34:21,768 --> 00:34:24,520
[Hilder] Tell us about the first meeting
you had in Trump Tower.
503
00:34:24,812 --> 00:34:27,065
In November 2015,
504
00:34:27,148 --> 00:34:32,153
I went with Alexander Nix
to go see Corey Lewandowski,
505
00:34:32,236 --> 00:34:34,238
who was the campaign manager at the time.
506
00:34:34,489 --> 00:34:38,951
And I asked Corey, why could this place
possibly look so familiar?
507
00:34:39,118 --> 00:34:42,413
And he said,
"This is the set of The Apprentice.
508
00:34:42,789 --> 00:34:45,041
That's probably why you recognize it."
And...
509
00:34:45,541 --> 00:34:47,376
I was kind of shocked, you know?
510
00:34:48,127 --> 00:34:52,048
The Trump campaign HQ is a reality TV set.
511
00:34:52,131 --> 00:34:53,883
[Hilder] Yes. It is.
512
00:34:57,762 --> 00:35:00,765
And the idea of a company...
513
00:35:01,099 --> 00:35:04,143
conducting large-scale analysis
of a population...
514
00:35:04,227 --> 00:35:05,227
Mm-hmm.
515
00:35:05,269 --> 00:35:08,564
...and then identifying the triggers
that people have
516
00:35:08,648 --> 00:35:12,068
in terms of what's gonna move them
from one state to another state,
517
00:35:12,151 --> 00:35:15,113
that feels very challenging
518
00:35:15,196 --> 00:35:18,324
to the individual's sense of autonomy
and freedom...
519
00:35:18,407 --> 00:35:19,492
- Mm-hmm.
- ...uh...
520
00:35:19,575 --> 00:35:22,203
and to the idea of democracy.
521
00:35:22,662 --> 00:35:23,704
Doesn't it?
522
00:35:24,455 --> 00:35:28,000
I don't know. Um...
I would challenge that.
523
00:35:28,668 --> 00:35:31,420
What this strategy is mostly meant to do
524
00:35:31,504 --> 00:35:34,590
is to identify people
who are still considering
525
00:35:34,674 --> 00:35:36,384
- many different options...
- Yes.
526
00:35:36,467 --> 00:35:41,264
...and educate them
on some of the options that are out there,
527
00:35:41,347 --> 00:35:42,765
and if they're on the fence,
528
00:35:42,849 --> 00:35:45,893
then they can be persuaded
to go one way or the other.
529
00:35:45,977 --> 00:35:48,855
- Yes, they can.
- Uh, again, that is their own choice.
530
00:35:48,938 --> 00:35:50,398
- But a lot of the times...
- Is it?
531
00:35:50,481 --> 00:35:53,201
- ...these are individuals that...
- [Hilder] Is it their own choice?
532
00:35:54,569 --> 00:35:56,689
In the end, they're the ones
that go to the ballot box
533
00:35:56,737 --> 00:35:58,990
- and make their ch... decision.
- [Hilder] Yeah.
534
00:35:59,365 --> 00:36:02,368
I mean, I'm asking you these questions
as Brittany Kaiser.
535
00:36:02,451 --> 00:36:03,536
- [Kaiser] I know.
- Right?
536
00:36:03,619 --> 00:36:07,248
I'm not asking you these questions
as Cambridge Analytica or SCL,
537
00:36:07,331 --> 00:36:10,334
because that's not
who you are anymore. Right?
538
00:36:10,626 --> 00:36:12,545
I get it. I get it. But...
539
00:36:12,628 --> 00:36:14,748
[Hilder stammers]
And do you think Cambridge Analytica
540
00:36:14,797 --> 00:36:17,925
was ever involved in the contravention
of people's human rights?
541
00:36:18,009 --> 00:36:19,010
[Kaiser] No.
542
00:36:20,636 --> 00:36:25,766
But, [chuckles] again, I start to question
a lot of things the more I hear.
543
00:36:25,850 --> 00:36:26,800
[Hilder] Yeah.
544
00:36:26,809 --> 00:36:29,770
[Kaiser] I mean,
I had spent my entire career before that
545
00:36:29,854 --> 00:36:31,939
working for human rights.
546
00:36:33,900 --> 00:36:34,900
[Hilder] Okay.
547
00:36:35,318 --> 00:36:37,111
Let's go back to that. [chuckles]
548
00:36:38,196 --> 00:36:41,407
It wasn't that long ago. Just a decade.
549
00:36:43,159 --> 00:36:45,077
- [Hilder] It wasn't that long ago.
- Yeah.
550
00:36:50,541 --> 00:36:54,170
[Kaiser] I had worked in elections
since I was 14 or 15.
551
00:36:55,922 --> 00:36:59,842
I told my cousin I applied
to intern on the Obama campaign.
552
00:37:00,092 --> 00:37:01,302
She was like, "Oh, my God.
553
00:37:01,385 --> 00:37:03,721
You better get that internship,
or I'll die."
554
00:37:05,014 --> 00:37:07,767
I was part of the team
running Obama's Facebook.
555
00:37:09,310 --> 00:37:14,065
We invented the way social media is used
to communicate with voters.
556
00:37:19,820 --> 00:37:22,990
I then spent several years
working on human rights
557
00:37:23,074 --> 00:37:24,742
and international relations,
558
00:37:25,576 --> 00:37:27,328
first for Amnesty International,
559
00:37:27,411 --> 00:37:31,123
then lobbying at the United Nations
and European Parliament.
560
00:37:34,710 --> 00:37:38,214
And I used to always say
I love human rights campaigning,
561
00:37:38,923 --> 00:37:41,968
but sometimes I feel like
I'm banging my head against a brick wall
562
00:37:42,051 --> 00:37:44,387
because I can't see the results
of what I'm doing.
563
00:37:44,470 --> 00:37:46,889
I don't know
if I'm literally just wasting my time.
564
00:37:49,433 --> 00:37:52,144
And that's where I was
when I met Alexander Nix.
565
00:37:53,896 --> 00:37:56,524
- [low chatter]
- [cutlery clinking]
566
00:37:56,607 --> 00:37:59,487
[Kaiser] Friends of ours thought
it would be a good joke to introduce us.
567
00:38:00,486 --> 00:38:04,240
He was very interested in learning more
about my experience with the Democrats.
568
00:38:04,573 --> 00:38:06,367
He gave me his card and said,
569
00:38:06,450 --> 00:38:09,161
"Let me get you drunk
and steal your secrets."
570
00:38:12,248 --> 00:38:16,294
And in December 2014,
he offered me a job.
571
00:38:21,215 --> 00:38:24,927
Coming across a company
where you could actually see your impact
572
00:38:25,011 --> 00:38:27,346
was really exciting for me.
573
00:38:33,894 --> 00:38:36,564
I got a little more conservative or posh
574
00:38:36,647 --> 00:38:41,110
in terms of the way that I dressed
and the way that I spoke,
575
00:38:41,944 --> 00:38:46,532
and doing things
like going on shooting at the weekends
576
00:38:46,615 --> 00:38:47,992
and stuff like that.
577
00:38:48,409 --> 00:38:52,538
It's just very different to what
I would normally spend my time doing.
578
00:38:59,962 --> 00:39:01,881
[Hilder]
Must've been a hell of an adventure.
579
00:39:02,214 --> 00:39:05,343
It was really interesting.
I strapped on my cowboy boots,
580
00:39:05,426 --> 00:39:08,554
got into character,
got my NRA membership.
581
00:39:08,721 --> 00:39:11,140
- Yeah, you joined the NRA, right?
- I did, yeah.
582
00:39:11,223 --> 00:39:13,059
Just to understand
how these people think,
583
00:39:13,142 --> 00:39:14,142
- like...
- Uh-huh.
584
00:39:14,268 --> 00:39:15,686
I don't want to use guns.
585
00:39:15,770 --> 00:39:18,356
- I'm not really interested in guns at all.
- Yeah.
586
00:39:18,439 --> 00:39:20,316
I felt like I was getting to know...
587
00:39:21,233 --> 00:39:24,236
people that I used to disagree with a lot,
588
00:39:24,320 --> 00:39:27,281
like my grandparents, my aunts,
uncles, cousins.
589
00:39:28,532 --> 00:39:32,620
[Hilder] So this wasn't just an outfit
that you put on, and it felt important?
590
00:39:32,870 --> 00:39:35,498
It was important. It is important.
591
00:39:35,581 --> 00:39:37,833
- [Hilder] Yeah.
- I feel like the main problem
592
00:39:38,000 --> 00:39:39,210
in US politics
593
00:39:39,293 --> 00:39:43,130
is that people are so polarized
that they can't understand each other,
594
00:39:43,214 --> 00:39:46,092
and therefore they can't work together,
and therefore nothing gets done.
595
00:39:47,468 --> 00:39:51,138
- [PA chimes]
- [woman speaking indistinctly on PA]
596
00:39:59,647 --> 00:40:03,651
I am about to draft some questions
for a senator
597
00:40:03,734 --> 00:40:07,029
who will be able to ask them
to Mark Zuckerberg
598
00:40:07,113 --> 00:40:10,950
in the Senate Judiciary hearing
on Tuesday.
599
00:40:11,283 --> 00:40:14,829
"How much of Facebook's revenue
600
00:40:15,996 --> 00:40:19,375
comes directly from the monetization
601
00:40:20,000 --> 00:40:23,045
of users' personal data?"
602
00:40:24,713 --> 00:40:26,590
[chortles] All of it!
603
00:40:27,967 --> 00:40:29,552
Exactly.
604
00:40:30,386 --> 00:40:33,013
The reality is that Facebook knows more
about this
605
00:40:33,097 --> 00:40:34,974
than pretty much anyone in the world
606
00:40:35,057 --> 00:40:39,937
because Facebook is the best platform
on which to run experiments.
607
00:40:40,020 --> 00:40:41,939
- Yeah, it is. Um, it...
- [laughing]
608
00:40:42,022 --> 00:40:44,525
And it actually always gets you
the best engagement rates.
609
00:40:44,608 --> 00:40:46,735
We always spend the majority
amount of money
610
00:40:46,819 --> 00:40:49,613
on any commercial
or political campaign in Facebook.
611
00:40:50,156 --> 00:40:51,866
Always gets the majority of the ad budget.
612
00:40:51,949 --> 00:40:53,617
- It does, it does.
- Yep.
613
00:40:55,411 --> 00:40:58,956
[Hilder] There is at least the possibility
that the American public
614
00:40:59,039 --> 00:41:01,876
and publics in other countries
have been experimented on.
615
00:41:07,423 --> 00:41:09,484
[Kaiser] Remember those Facebook quizzes
that we used
616
00:41:09,508 --> 00:41:12,678
to form personality models
for all voters in the US?
617
00:41:15,556 --> 00:41:19,351
The truth is, we didn't target
every American voter equally.
618
00:41:20,519 --> 00:41:22,396
The bulk of our resources
619
00:41:22,480 --> 00:41:26,108
went into targeting those
whose minds we thought we could change.
620
00:41:26,901 --> 00:41:29,028
We called them "the persuadables."
621
00:41:31,238 --> 00:41:32,907
They're everywhere in the country,
622
00:41:32,990 --> 00:41:36,619
but the persuadables that mattered
were the ones in swing states
623
00:41:36,702 --> 00:41:40,873
like Michigan, Wisconsin,
Pennsylvania, and Florida.
624
00:41:44,001 --> 00:41:47,922
Now, each of these states were broken down
by precinct.
625
00:41:49,215 --> 00:41:53,093
So, you can say
there are 22,000 persuadable voters
626
00:41:53,302 --> 00:41:54,845
in this precinct,
627
00:41:55,971 --> 00:41:59,725
and if we target enough persuadable people
in the right precincts,
628
00:41:59,850 --> 00:42:03,479
then those states would turn red
instead of blue.
629
00:42:04,980 --> 00:42:07,942
Our creative team designed
personalized content
630
00:42:08,025 --> 00:42:09,693
to trigger those individuals.
631
00:42:09,777 --> 00:42:12,029
Terrorists love porous borders.
632
00:42:12,112 --> 00:42:15,324
Widespread gaps
in border security allow terrorists...
633
00:42:15,407 --> 00:42:19,745
[Kaiser] We bombarded them through blogs,
websites, articles, videos, ads,
634
00:42:19,828 --> 00:42:21,664
every platform you can imagine.
635
00:42:22,122 --> 00:42:24,959
Until they saw the world
the way we wanted them to.
636
00:42:27,920 --> 00:42:29,088
[emoji growls]
637
00:42:29,296 --> 00:42:31,590
[Kaiser] Until they voted
for our candidate.
638
00:42:33,384 --> 00:42:35,010
It's like a boomerang.
639
00:42:35,553 --> 00:42:37,137
You send your data out,
640
00:42:38,138 --> 00:42:39,807
it gets analyzed,
641
00:42:40,224 --> 00:42:43,727
and it comes back at you
as targeted messaging
642
00:42:44,311 --> 00:42:46,146
to change your behavior.
643
00:42:53,070 --> 00:42:55,072
[indistinct chatter]
644
00:43:00,744 --> 00:43:02,371
[indistinct announcement over PA]
645
00:43:02,454 --> 00:43:05,374
DCMS Committee announced
the future witnesses
646
00:43:05,457 --> 00:43:07,209
- for a fake news inquiry.
- Yes.
647
00:43:07,668 --> 00:43:09,712
- There you are. You're...
- Me.
648
00:43:09,795 --> 00:43:13,090
- [Hilder] You're the day before Alexander.
- [Kaiser] The former CEO.
649
00:43:13,966 --> 00:43:15,634
He's going the day after me.
650
00:43:16,844 --> 00:43:19,847
Yes. Is it... Is it all feeling a bit real?
651
00:43:19,930 --> 00:43:21,557
[chuckling] It's really intense.
652
00:43:22,266 --> 00:43:23,642
- [sniffles]
- [Hilder] It's real.
653
00:43:23,976 --> 00:43:26,437
- And it's big.
- [Kaiser sighs]
654
00:43:39,533 --> 00:43:42,578
[Cadwalladr] The first time
I wrote about Cambridge Analytica,
655
00:43:43,037 --> 00:43:45,497
it was December 2016.
656
00:43:47,291 --> 00:43:49,501
I said that they'd worked
for the Trump campaign
657
00:43:49,585 --> 00:43:51,587
and for the Brexit campaign.
658
00:43:54,465 --> 00:43:56,305
And I started getting letters
from them saying,
659
00:43:56,383 --> 00:43:58,218
"We never worked for the Leave campaign."
660
00:44:02,097 --> 00:44:04,725
And this was baffling
because on Leave. EU's website,
661
00:44:04,808 --> 00:44:07,019
it said, "We hired Cambridge Analytica."
662
00:44:08,896 --> 00:44:11,482
There were statements from Alexander Nix
about how they worked
663
00:44:11,565 --> 00:44:12,650
for the Leave campaign.
664
00:44:13,484 --> 00:44:17,112
Yeah, I'm afraid we don't talk
about that campaign. At all.
665
00:44:17,571 --> 00:44:19,365
[laughs]
666
00:44:19,448 --> 00:44:21,075
[woman] You didn't? Or you did?
667
00:44:21,158 --> 00:44:22,451
No, no, we don't discuss it.
668
00:44:22,534 --> 00:44:24,134
- [woman] Okay. Not at all.
- [Nix] Yeah.
669
00:44:24,703 --> 00:44:27,831
[Cadwalladr]
And that was when I discovered this video
670
00:44:27,915 --> 00:44:30,125
of Leave. EU's press launch.
671
00:44:32,628 --> 00:44:35,798
And I was like, well, there, look,
it's Brittany Kaiser!
672
00:44:35,881 --> 00:44:38,425
She works for Cambridge Analytica.
673
00:44:38,509 --> 00:44:40,552
She's at the press launch
674
00:44:40,636 --> 00:44:43,389
talking about all the clever things
675
00:44:43,472 --> 00:44:46,350
that they're going to do with data
for the Leave Campaign.
676
00:44:48,102 --> 00:44:50,979
Like, what the fuck?
677
00:44:51,063 --> 00:44:54,817
How can you carry on denying it?
This is nuts!
678
00:44:54,900 --> 00:44:57,945
[Russian national anthem playing]
679
00:44:58,779 --> 00:45:00,539
[Cadwalladr] And it was exactly
the same time
680
00:45:00,614 --> 00:45:02,408
that Leave. EU started posting
681
00:45:02,491 --> 00:45:04,243
the horrible videos of me.
682
00:45:04,326 --> 00:45:05,929
[woman panting]
I've gotta get out of here!
683
00:45:05,953 --> 00:45:08,747
[Cadwalladr] There was a spoof video
of a scene from Airplane!
684
00:45:08,831 --> 00:45:11,434
- [stewardess] Get a hold of yourself!
- [man] Please, let me handle this.
685
00:45:11,458 --> 00:45:14,604
[Cadwalladr] There was like a whole stream
of people going, "Don't be so hysterical!"
686
00:45:14,628 --> 00:45:15,628
And, like, hitting her.
687
00:45:15,671 --> 00:45:17,589
Go back to your seat!
I'll take care of this.
688
00:45:17,673 --> 00:45:19,717
[Cadwalladr]
It was like, "Calm down! Calm down!"
689
00:45:19,800 --> 00:45:22,278
[makes slapping sound]
And, you know, so a whole line of people,
690
00:45:22,302 --> 00:45:24,638
and then the last person's carrying a gun.
691
00:45:26,390 --> 00:45:27,975
And the whole thing they had,
692
00:45:28,058 --> 00:45:30,936
it was set to the music
from the Russian national anthem.
693
00:45:31,019 --> 00:45:33,564
[anthem continues playing]
694
00:45:35,065 --> 00:45:36,400
Ugh.
695
00:45:38,110 --> 00:45:41,488
The day
after that Leave. EU video was put out,
696
00:45:41,572 --> 00:45:45,701
the editor of another news organization
that I was going to do a report for
697
00:45:46,201 --> 00:45:47,536
took me for lunch and said,
698
00:45:47,619 --> 00:45:50,579
"Actually, we think it's too much
of a risk having you present the report."
699
00:45:53,792 --> 00:45:58,046
It is this sort of visceral thing
of living with this disinformation
700
00:45:58,130 --> 00:46:00,924
and this propaganda every single day.
701
00:46:01,216 --> 00:46:04,887
And feeling the effects of it
and knowing that it does work,
702
00:46:04,970 --> 00:46:07,973
it does have an impact in real life,
whether people believe that or not.
703
00:46:13,437 --> 00:46:15,439
You know,
I'm used to just writing stories.
704
00:46:15,522 --> 00:46:18,025
You write it, and then you go on
to the next subject.
705
00:46:18,108 --> 00:46:21,445
I'm a feature writer, that's what I did.
But I was just like, "They've lied."
706
00:46:21,528 --> 00:46:24,168
And they're lying about something
which is actually really massive.
707
00:46:24,239 --> 00:46:26,533
'Cause it's, you know, the...
708
00:46:27,075 --> 00:46:29,953
rest of the future of our country.
709
00:46:30,662 --> 00:46:33,749
- [reporter 1] What do you think, Nigel?
- [reporters murmuring indistinctly]
710
00:46:35,584 --> 00:46:39,755
[Cadwalladr] In the referendum,
most people had very fixed views.
711
00:46:40,672 --> 00:46:44,218
But there was a tiny sliver of people
who didn't.
712
00:46:44,301 --> 00:46:46,345
These were "the persuadables."
713
00:46:46,678 --> 00:46:50,057
It was all about finding
these very few people
714
00:46:50,140 --> 00:46:52,810
and then bombarding them with ads.
715
00:46:55,020 --> 00:46:58,649
This is the thing
which was invisible to all of us.
716
00:47:00,442 --> 00:47:06,448
Let June the 23rd go down in our history
as our independence day!
717
00:47:06,532 --> 00:47:08,867
[loud cheering]
718
00:47:10,494 --> 00:47:13,705
[man 1] The British people have spoken,
and the answer is, "We're out."
719
00:47:13,789 --> 00:47:15,082
[woman 1] For good or for ill,
720
00:47:15,165 --> 00:47:18,043
this decision will define our politics
for years to come.
721
00:47:18,126 --> 00:47:22,256
[woman 2] This great country
has made a terrible mistake.
722
00:47:22,339 --> 00:47:24,174
[man 2]
It's an earthquake that has happened.
723
00:47:24,258 --> 00:47:27,553
And what happens after earthquakes?
We wait to see.
724
00:47:27,886 --> 00:47:30,013
[woman 3] People weren't agreed
on what Leave meant.
725
00:47:30,097 --> 00:47:32,992
- [man 3] It's simple: leave. Full stop.
- [woman 3] Was no manifesto for Leave.
726
00:47:33,016 --> 00:47:34,643
But there is no "leave, full stop..."
727
00:47:34,726 --> 00:47:37,604
[crowd chanting] Brexit! Brexit! Brexit!
728
00:47:38,730 --> 00:47:40,232
[PA chimes]
729
00:47:40,315 --> 00:47:41,995
[woman over PA] In the interest of safety,
730
00:47:42,067 --> 00:47:45,487
parents are advised not to carry children
on baggage trolleys
731
00:47:45,571 --> 00:47:47,573
or allow them to play on the escalators.
732
00:47:47,656 --> 00:47:49,575
- [Kaiser] Hi, Mama!
- [mother on phone] Hey!
733
00:47:50,784 --> 00:47:52,744
I'm through, I'm through,
I'm through, yeah.
734
00:47:52,828 --> 00:47:56,748
So, I managed to get
into the United Kingdom with no issues,
735
00:47:56,832 --> 00:47:59,251
which is really fantastic.
736
00:47:59,585 --> 00:48:02,379
[mother] Well, I just want you
to mentally be okay with this,
737
00:48:02,462 --> 00:48:06,091
'cause what you're doing
is a monumental undertaking.
738
00:48:06,174 --> 00:48:07,133
I know.
739
00:48:07,134 --> 00:48:08,719
And I still fear for your life.
740
00:48:08,802 --> 00:48:09,803
Yeah.
741
00:48:09,887 --> 00:48:12,097
With the powerful people
that are involved...
742
00:48:12,639 --> 00:48:13,807
[Kaiser] Yeah, I know.
743
00:48:13,891 --> 00:48:15,976
You just have to be careful all the time.
744
00:48:16,059 --> 00:48:17,853
[Kaiser] I know, but I can't keep quiet
745
00:48:17,936 --> 00:48:20,147
just because it'll make
powerful people mad.
746
00:48:20,230 --> 00:48:23,066
I know. I know, I know, I know. I know.
747
00:48:23,734 --> 00:48:26,111
I totally get that, you know.
748
00:48:26,862 --> 00:48:30,908
Somebody's always got to bring down
these jerks.
749
00:48:31,074 --> 00:48:32,200
Exactly.
750
00:48:32,284 --> 00:48:34,953
So, you know, anyway.
751
00:48:35,203 --> 00:48:37,039
When I have time off next month,
752
00:48:37,122 --> 00:48:40,667
I've gotta go and put deposits down
on electric and gas.
753
00:48:41,126 --> 00:48:44,379
I don't have $1,000 right now,
so I'll have to wait.
754
00:48:44,463 --> 00:48:47,382
[Kaiser] Well, I could...
I could pay for it. That means...
755
00:48:47,466 --> 00:48:49,885
Oh, don't worry,
I don't need it right now.
756
00:48:51,720 --> 00:48:53,472
All right, honey, you stay healthy.
757
00:48:53,555 --> 00:48:54,472
[Kaiser] Love you.
758
00:48:54,473 --> 00:48:55,599
Be safe, honey. I love you.
759
00:48:55,682 --> 00:48:56,599
[Kaiser] I love you. Bye-bye.
760
00:48:56,600 --> 00:48:57,809
Bye-bye, baby.
761
00:48:59,603 --> 00:49:00,604
[Kaiser sighs]
762
00:49:07,945 --> 00:49:09,821
[Kaiser] I'm really happy to be back,
763
00:49:09,905 --> 00:49:14,368
but I don't think I can really do much
going out in public while I'm here.
764
00:49:17,162 --> 00:49:18,664
Last time I left,
765
00:49:18,747 --> 00:49:23,627
I was in a very difficult situation
with a lot of my friends.
766
00:49:24,294 --> 00:49:25,934
- [Kaiser] So fire door number one?
- Yes.
767
00:49:26,004 --> 00:49:27,673
- [man murmurs indistinctly]
- What?
768
00:49:29,883 --> 00:49:33,345
[Kaiser] So many people were so angry
that I was working on the Brexit campaign,
769
00:49:33,428 --> 00:49:36,682
so angry I continued to work for a company
770
00:49:36,765 --> 00:49:39,601
that supported people
like Ted Cruz and Donald Trump.
771
00:49:42,312 --> 00:49:45,649
And there's still this whole group
of people that are wondering,
772
00:49:45,732 --> 00:49:49,361
am I taking the high road,
or am I doing something to protect myself?
773
00:49:56,368 --> 00:49:58,137
[reporter 1]
More news on Facebook over the weekend,
774
00:49:58,161 --> 00:50:00,580
as Mark Zuckerberg prepares to testify
before Congress
775
00:50:00,664 --> 00:50:01,957
tomorrow and Wednesday.
776
00:50:02,040 --> 00:50:03,851
Earlier this morning,
he announced some new measures
777
00:50:03,875 --> 00:50:06,670
in the company's efforts
to prevent interference in elections...
778
00:50:11,049 --> 00:50:13,051
[low chatter]
779
00:50:18,056 --> 00:50:20,684
[Kaiser gasps] It's today's FT.
780
00:50:20,767 --> 00:50:23,729
My name's at the top of the front page
of the FT.
781
00:50:23,812 --> 00:50:24,855
Oh, shit.
782
00:50:25,856 --> 00:50:27,566
[chuckles] There it is.
783
00:50:29,234 --> 00:50:31,111
"Zuckerberg braced for Congress grilling.
784
00:50:31,194 --> 00:50:34,573
Facebook chief will admit
that the social network did not do enough
785
00:50:34,656 --> 00:50:37,117
to stop its tools being used for harm."
786
00:50:37,826 --> 00:50:41,538
[Carroll] "Facebook should pay its
two billion users for their personal data.
787
00:50:41,788 --> 00:50:45,834
The big tech companies are evolving
into digital kleptocracies.
788
00:50:46,084 --> 00:50:47,294
Yesterday."
789
00:50:49,171 --> 00:50:50,797
[clicks tongue] Um...
790
00:50:51,590 --> 00:50:54,301
I sort of missed the paragraph of, like,
791
00:50:55,343 --> 00:50:57,554
"I helped build this monster
792
00:50:58,472 --> 00:50:59,472
that...
793
00:51:01,767 --> 00:51:05,395
wreaked havoc upon the world
and will take decades to recover from,
794
00:51:06,396 --> 00:51:10,025
and I feel really bad about that."
I don't see that here.
795
00:51:12,194 --> 00:51:14,071
[Kaiser] The data wars have begun.
796
00:51:15,572 --> 00:51:17,365
[camera shutters clicking]
797
00:51:24,498 --> 00:51:28,627
[Carroll] I mean, this is a company
that is a superstate,
798
00:51:28,919 --> 00:51:33,131
and the only nation
that has jurisdiction over it is ours.
799
00:51:33,215 --> 00:51:36,384
[gavel slams on video feed]
800
00:51:40,347 --> 00:51:44,810
[Grassley] The Committees on the Judiciary
and Commerce, Science and Transportation
801
00:51:44,893 --> 00:51:46,228
will come to order.
802
00:51:48,271 --> 00:51:51,024
[Zuckerberg] Chairman Grassley
and members of the committee:
803
00:51:52,192 --> 00:51:57,364
My top priority has always been
our social mission of connecting people,
804
00:51:57,447 --> 00:52:00,158
building community,
and bringing the world closer together.
805
00:52:01,243 --> 00:52:04,538
But it's clear now that we didn't
do enough to prevent these tools
806
00:52:04,621 --> 00:52:06,206
from being used for harm as well.
807
00:52:06,706 --> 00:52:09,417
Before I talk about the steps
we're taking to address them,
808
00:52:09,501 --> 00:52:10,981
I want to talk about how we got here.
809
00:52:11,545 --> 00:52:14,172
When we first contacted
Cambridge Analytica,
810
00:52:14,256 --> 00:52:16,466
they told us
that they had deleted the data.
811
00:52:16,842 --> 00:52:17,842
About a month ago,
812
00:52:17,884 --> 00:52:20,303
we heard new reports
that suggested that wasn't true.
813
00:52:21,054 --> 00:52:25,225
So, we're getting to the bottom
of exactly what Cambridge Analytica did.
814
00:52:25,767 --> 00:52:28,019
[Kaiser] Blame it on me, Mark. Go for it.
815
00:52:28,103 --> 00:52:30,689
...to address this and to prevent it
from happening again.
816
00:52:31,481 --> 00:52:35,318
Thank you for having me here today,
and I'm ready to take your questions.
817
00:52:36,444 --> 00:52:40,907
Well, Mr. Zuckerberg,
during the 2016 campaign,
818
00:52:41,032 --> 00:52:44,286
Cambridge Analytica worked
with the Trump campaign
819
00:52:44,369 --> 00:52:47,789
to refine tactics under Project Alamo.
820
00:52:47,873 --> 00:52:50,292
Were Facebook employees involved in that?
821
00:52:51,585 --> 00:52:54,480
Senator, I don't know that our employees
were involved with Cambridge Analytica.
822
00:52:54,504 --> 00:52:56,464
- Yes, they were.
- Whoa!
823
00:52:56,548 --> 00:52:57,591
[man] Oh, my God.
824
00:52:57,674 --> 00:53:00,468
The Republican team in DC was. I met them.
825
00:53:00,677 --> 00:53:03,680
...although I know that we did help out
the Trump campaign overall
826
00:53:03,763 --> 00:53:06,600
in sales support in the same way
that we do with other campaigns.
827
00:53:06,683 --> 00:53:08,560
So, they may have been involved
828
00:53:08,643 --> 00:53:11,271
and all working together
during that time period?
829
00:53:11,354 --> 00:53:14,107
Maybe that's something
your investigation will find out.
830
00:53:14,191 --> 00:53:16,818
Senator, I can certainly
have my team get back to you
831
00:53:16,902 --> 00:53:19,946
on any specifics there
that I don't know sitting here today.
832
00:53:20,030 --> 00:53:22,782
Oh, my God. This is the whole point
of the hearing, you...
833
00:53:22,866 --> 00:53:25,493
- [Cantwell] Know what I'm talking about?
- No, I do not.
834
00:53:25,577 --> 00:53:26,577
[Cantwell] Okay.
835
00:53:27,996 --> 00:53:29,122
[man] It can go to you.
836
00:53:29,789 --> 00:53:33,585
Do you think the 87 million users,
do you consider them victims?
837
00:53:34,628 --> 00:53:36,463
Uh, Senator, I think...
838
00:53:36,796 --> 00:53:38,048
Uh...
839
00:53:38,215 --> 00:53:42,010
Yes. I mean, they... they did not want
their information to be
840
00:53:42,219 --> 00:53:46,014
sold to Cambridge Analytica
by a developer. And... And...
841
00:53:46,348 --> 00:53:47,515
that happened.
842
00:53:47,682 --> 00:53:49,309
And it happened on our watch.
843
00:53:49,434 --> 00:53:50,936
So even though we didn't do it,
844
00:53:51,019 --> 00:53:53,563
I think we have a responsibility
to be able to prevent that
845
00:53:53,647 --> 00:53:55,190
and be able to take action sooner.
846
00:53:55,690 --> 00:53:57,734
One of the steps that we need to take now
847
00:53:57,817 --> 00:54:00,946
is go do a full audit
of all of Cambridge Analytica's systems
848
00:54:01,029 --> 00:54:04,449
to understand what they're doing,
whether they still have any data...
849
00:54:04,532 --> 00:54:08,411
[man 1] Obviously, Facebook has been done
considerable reputational damage
850
00:54:08,495 --> 00:54:10,956
by its association
with Cambridge Analytica.
851
00:54:11,039 --> 00:54:13,541
[woman 1]
...process by which Cambridge Analytica...
852
00:54:13,625 --> 00:54:15,228
[woman 2]
...relates to Cambridge Analytica...
853
00:54:15,252 --> 00:54:18,255
[man 2] The recent stories
about Cambridge Analytica
854
00:54:18,338 --> 00:54:19,941
- and data mining...
- [hearing continues indistinctly]
855
00:54:19,965 --> 00:54:23,176
[man] Look at how many people
are posting Zuckerberg...
856
00:54:23,260 --> 00:54:25,321
- [Kaiser] Everyone's watching this.
- [man] Oh, my God.
857
00:54:25,345 --> 00:54:27,281
- [Kaiser] And the whole thing just says...
- [man] Wow.
858
00:54:27,305 --> 00:54:29,307
[Kaiser]...Cambridge, Cambridge,
Cambridge.
859
00:54:29,391 --> 00:54:31,059
[no audible dialogue]
860
00:54:31,851 --> 00:54:33,687
[Kaiser] I never thought
everyone in the world
861
00:54:33,770 --> 00:54:36,064
would know who Cambridge Analytica was.
862
00:54:36,147 --> 00:54:38,942
[Zuckerberg hearing
continues indistinctly]
863
00:54:46,741 --> 00:54:49,536
[Wheatland]
I learnt many things from that period.
864
00:54:50,161 --> 00:54:53,707
I learnt, for example,
that when you're in a PR crisis,
865
00:54:53,790 --> 00:54:56,835
the one thing that you can't hire
is a PR crisis company.
866
00:54:57,168 --> 00:54:59,337
We spoke to...
867
00:55:00,630 --> 00:55:05,010
[sighs]...tens of PR crisis companies
that listened intently,
868
00:55:05,093 --> 00:55:07,220
went away to think about it,
and came back and said,
869
00:55:07,304 --> 00:55:10,557
"Sorry, we can't associate ourselves
with your brand." [chuckles]
870
00:55:10,640 --> 00:55:15,395
Um... And actually, I thought
that's what they were there, um, for.
871
00:55:15,770 --> 00:55:19,858
And so it became impossible to, um...
to get a voice.
872
00:55:26,072 --> 00:55:29,075
The reason that we've called
this news conference today
873
00:55:29,159 --> 00:55:33,913
is to begin to counter
some of the unfounded allegations
874
00:55:33,997 --> 00:55:38,168
and, frankly, the torrent of ill-informed
and inaccurate speculation.
875
00:55:47,135 --> 00:55:49,929
Do you think what was done was illegal?
876
00:55:50,013 --> 00:55:51,765
We think it is probably illegal
877
00:55:51,848 --> 00:55:54,517
according to UK law,
and that's what we're challenging.
878
00:55:54,601 --> 00:55:56,936
We do have a statement
from Cambridge Analytica.
879
00:55:57,020 --> 00:55:58,438
Cambridge said,
880
00:55:58,521 --> 00:56:01,775
"David Carroll has no more right
to submit this request
881
00:56:01,858 --> 00:56:05,737
than a member of the Taliban
sitting in a cave in Afghanistan."
882
00:56:08,615 --> 00:56:10,867
[Wheatland] And it came like a tsunami.
883
00:56:11,743 --> 00:56:16,331
There were 35,000 media stories per day.
884
00:56:19,459 --> 00:56:22,087
They wanted to discredit Trump,
885
00:56:22,420 --> 00:56:24,839
they wanted to discredit Brexit,
886
00:56:24,923 --> 00:56:26,841
and we were the vehicle for doing it.
887
00:56:27,634 --> 00:56:31,012
Do you feel
that you have skewed democracy?
888
00:56:31,388 --> 00:56:36,351
By providing campaign services
to a candidate who'd been fairly nominated
889
00:56:36,434 --> 00:56:39,646
as the Republican representative
of the United States?
890
00:56:40,105 --> 00:56:41,523
How is that possible?
891
00:56:43,191 --> 00:56:46,027
[Wheatland]
Cambridge Analytica became responsible
892
00:56:46,111 --> 00:56:49,864
for pretty much everything
that was wrong in the world.
893
00:56:55,078 --> 00:56:57,622
Are you saying
that Cambridge Analytica lies?
894
00:56:57,705 --> 00:57:00,417
They knowingly misrepresent the truth.
895
00:57:00,583 --> 00:57:02,168
What's your proof of that?
896
00:57:02,836 --> 00:57:04,087
I was there.
897
00:57:05,547 --> 00:57:08,133
[Wheatland]
Chris Wylie spoke with great authority
898
00:57:08,216 --> 00:57:11,094
about what had gone on
in Cambridge Analytica and SCL
899
00:57:11,177 --> 00:57:14,222
during 2015 and 2016,
900
00:57:14,305 --> 00:57:17,517
at a time when he was never there.
901
00:57:18,560 --> 00:57:22,939
He had worked for the company
for nine months, left in 2014.
902
00:57:23,231 --> 00:57:28,153
He then went out and pitched
the Trump campaign,
903
00:57:28,778 --> 00:57:31,281
and lost to us.
904
00:57:34,242 --> 00:57:37,328
Chris Wylie set out to kill the company.
905
00:57:39,998 --> 00:57:41,332
[man] And what about Brittany?
906
00:57:46,963 --> 00:57:48,965
I don't know what Brittany was doing.
907
00:57:54,387 --> 00:57:56,264
Brittany was someone that...
908
00:57:57,015 --> 00:58:00,185
I thought was a friend,
I know Alexander thought was a friend.
909
00:58:01,436 --> 00:58:02,562
But, you know,
910
00:58:04,105 --> 00:58:06,441
when the world gets turned upside down,
911
00:58:07,901 --> 00:58:11,738
people behave in different ways.
912
00:58:12,864 --> 00:58:15,450
Maybe even they don't understand
913
00:58:16,284 --> 00:58:18,495
why they're doing what they're doing
at the time.
914
00:58:24,959 --> 00:58:28,713
[Hilder] I would strongly recommend
that we start doing testimony prep.
915
00:58:30,131 --> 00:58:32,300
Uh, go through the emails together,
916
00:58:32,383 --> 00:58:35,720
maybe go through other stuff
and hash out what's there.
917
00:58:37,430 --> 00:58:39,557
[Kaiser]
Oh, my God. I have my entire calendar.
918
00:58:41,226 --> 00:58:43,144
[whispers] Shit. Shit.
919
00:58:43,228 --> 00:58:45,989
- [Hilder] You have your entire calendar?
- I have my entire calendar.
920
00:58:46,022 --> 00:58:47,273
Oh, my God.
921
00:58:47,524 --> 00:58:48,650
[Hilder] Downloaded?
922
00:58:48,733 --> 00:58:52,195
[Kaiser] I didn't think that
that was going to still link. [gasps]
923
00:58:52,278 --> 00:58:53,363
That's amazing.
924
00:58:53,446 --> 00:58:56,050
I can actually do an entire timeline
of everything, if that's the case.
925
00:58:56,074 --> 00:58:57,234
[Hilder] A timeline is great.
926
00:58:57,700 --> 00:58:59,160
[whispers] Fuck, look at this.
927
00:58:59,744 --> 00:59:02,580
[chuckles] September 2015.
928
00:59:04,749 --> 00:59:06,626
US Chamber of Commerce...
929
00:59:07,126 --> 00:59:08,211
Meeting at...
930
00:59:11,172 --> 00:59:13,883
Leave.EU. That was fun. Run-through.
931
00:59:13,967 --> 00:59:15,009
[Hilder] It's all here.
932
00:59:15,093 --> 00:59:17,762
I know exactly when everything happened.
933
00:59:17,845 --> 00:59:19,472
Always. Forever.
934
00:59:23,393 --> 00:59:25,186
[Kaiser] I didn't realize how much I had.
935
00:59:25,687 --> 00:59:27,021
I've got much more than that,
936
00:59:27,105 --> 00:59:30,108
it's just those are the things I forwarded
that I think are worthwhile.
937
00:59:33,444 --> 00:59:34,444
[elevator bell dings]
938
00:59:36,197 --> 00:59:38,783
[Kaiser] Did you get the chance
to look through all of that?
939
00:59:38,866 --> 00:59:41,666
[Hilder] I went through most of it.
I'll look through more of it today.
940
00:59:44,664 --> 00:59:47,417
[Kaiser] Let me get out
one of the pitches. Um...
941
00:59:47,667 --> 00:59:49,919
- [keyboard clacking]
- "CA Political."
942
00:59:52,171 --> 00:59:53,339
What is this?
943
00:59:54,257 --> 00:59:55,592
This looks mental.
944
00:59:57,343 --> 01:00:02,849
This is a list of, like,
the main sources of data.
945
01:00:04,017 --> 01:00:08,104
And look, it's got that fucking Facebook
data set of 30 million individuals.
946
01:00:08,187 --> 01:00:09,856
It just says it in there! [exclaims]
947
01:00:09,939 --> 01:00:11,608
What the fuck!
948
01:00:12,108 --> 01:00:13,401
[whispers] Oh, my God.
949
01:00:14,068 --> 01:00:16,738
- [Hilder] February...
- [Kaiser] Created February 4th, 2016!
950
01:00:16,821 --> 01:00:19,866
That was after we said to Facebook
that we deleted that shit!
951
01:00:20,992 --> 01:00:23,036
This is the 30 million individuals
952
01:00:23,119 --> 01:00:26,205
that we got their data
through Professor Kogan.
953
01:00:26,289 --> 01:00:27,498
That's that.
954
01:00:28,041 --> 01:00:31,794
And it admits to it right here,
"Our data makes us different,"
955
01:00:32,712 --> 01:00:36,174
because we're scraping people's profiles,
and other people are not.
956
01:00:37,967 --> 01:00:38,967
Fuck.
957
01:00:45,475 --> 01:00:47,977
[chuckles]
I forgot about this stuff, you know?
958
01:00:48,853 --> 01:00:50,772
There's just so much stuff.
959
01:01:02,241 --> 01:01:04,243
[Nix] ...we seek to do as a firm.
960
01:01:04,327 --> 01:01:06,788
We are a behavior change agency.
961
01:01:08,039 --> 01:01:11,125
The holy grail of communications is
962
01:01:11,209 --> 01:01:13,294
when you can start to change behavior.
963
01:01:15,171 --> 01:01:18,633
Uh, Trinidad. This is a great,
interesting case history
964
01:01:18,716 --> 01:01:20,218
of how we look at problems.
965
01:01:21,094 --> 01:01:23,346
[folk music playing]
966
01:01:23,680 --> 01:01:25,682
[Nix]
There are two main political parties,
967
01:01:25,890 --> 01:01:27,642
one for the blacks
and one for the Indians.
968
01:01:28,059 --> 01:01:29,727
And you know, they screw each other.
969
01:01:30,228 --> 01:01:33,064
So, we were working for the Indians.
970
01:01:34,399 --> 01:01:37,985
We went to the client and we said,
"We want to target the youth."
971
01:01:38,152 --> 01:01:42,365
And we try and increase apathy.
972
01:01:44,075 --> 01:01:45,910
The campaign had to be non-political,
973
01:01:45,993 --> 01:01:47,704
because the kids
don't care about politics.
974
01:01:47,787 --> 01:01:50,748
It had to be reactive,
because they're lazy.
975
01:01:51,582 --> 01:01:54,961
So we came up with this campaign,
which was all about:
976
01:01:55,044 --> 01:01:57,171
Be part of the gang. Do something cool.
977
01:01:57,255 --> 01:01:58,423
Be part of a movement.
978
01:01:58,715 --> 01:02:00,967
And it was called the "Do So!" campaign.
979
01:02:01,384 --> 01:02:03,024
[Kaiser]
It means "I'm not going to vote."
980
01:02:03,219 --> 01:02:04,887
[Nix] "Do so! Don't vote."
981
01:02:04,971 --> 01:02:06,973
[crowd cheering]
982
01:02:07,974 --> 01:02:09,726
[man] The salute of resistance
983
01:02:09,851 --> 01:02:12,729
that is known to all
across Trinidad and Tobago.
984
01:02:13,396 --> 01:02:15,481
Do So! Do So!
985
01:02:16,399 --> 01:02:18,484
- Do So!
- [crowd continues cheering]
986
01:02:18,776 --> 01:02:21,988
[Nix] It's a sign of resistance against,
not the government,
987
01:02:22,071 --> 01:02:24,574
against politics and voting.
988
01:02:24,949 --> 01:02:27,034
- ♪ Run with it, run with it ♪
- ♪ Run, run ♪
989
01:02:27,118 --> 01:02:28,762
- ♪ Run with it, run with it ♪
- ♪ Run, run ♪
990
01:02:28,786 --> 01:02:31,164
[Nix]
They're making their own YouTube videos.
991
01:02:31,247 --> 01:02:34,667
This is the prime minister's house
that's being graffitied.
992
01:02:34,751 --> 01:02:36,502
It was carnage.
993
01:02:38,296 --> 01:02:41,048
[Nix]
We knew that when it came to voting,
994
01:02:41,215 --> 01:02:44,177
all the Afro-Caribbean kids wouldn't vote,
995
01:02:44,260 --> 01:02:45,261
because they Do So!
996
01:02:45,344 --> 01:02:48,973
But all the Indian kids would do
what their parents told them to do,
997
01:02:49,223 --> 01:02:50,808
which is go out and vote.
998
01:02:51,434 --> 01:02:53,269
They had a lot of fun doing this,
999
01:02:53,352 --> 01:02:56,397
but they're not gonna go
against their parents' will.
1000
01:02:56,939 --> 01:02:58,024
[fireworks crackling]
1001
01:02:58,107 --> 01:03:00,526
[overlapping shouts]
1002
01:03:00,610 --> 01:03:05,072
Thank God for the guidance
that has brought us here to this victory.
1003
01:03:05,156 --> 01:03:07,492
Thank you. Thank you, God.
1004
01:03:07,575 --> 01:03:12,663
[Nix] And the difference in
18-to 35-year-old turnout was like 40%.
1005
01:03:13,372 --> 01:03:16,209
And that swung the election about 6%,
1006
01:03:16,292 --> 01:03:19,253
which was all we needed
in an election that's very close.
1007
01:03:22,256 --> 01:03:28,179
We now undertake ten national campaigns
for prime minister or president each year.
1008
01:03:28,805 --> 01:03:30,389
Malaysia, we're working in.
1009
01:03:30,473 --> 01:03:34,602
[Kaiser] We did Lithuania, Romania,
Kenya, Ghana.
1010
01:03:35,186 --> 01:03:37,266
- [Nix] So quite a few this year.
- [Kaiser] Nigeria.
1011
01:03:37,563 --> 01:03:40,650
- [man] The Brexit campaign?
- [Nix] Oh, and the Brexit campaign, yeah.
1012
01:03:41,067 --> 01:03:42,902
But we don't talk about that.
1013
01:03:42,985 --> 01:03:44,278
[Kaiser] Oops, we won!
1014
01:03:44,362 --> 01:03:45,738
[laughter]
1015
01:03:50,243 --> 01:03:52,912
[man] Do you worry at all
that she might let you down?
1016
01:03:54,539 --> 01:03:55,873
[sighs]
1017
01:03:56,541 --> 01:03:58,251
Look, um...
1018
01:04:01,254 --> 01:04:02,463
[sighs]
1019
01:04:06,843 --> 01:04:08,135
That is a good question.
1020
01:04:10,429 --> 01:04:15,184
I know already that she is
a complicated person, uh,
1021
01:04:15,268 --> 01:04:16,435
who has...
1022
01:04:18,521 --> 01:04:20,773
you know, done some complicated things.
1023
01:04:21,524 --> 01:04:22,608
Uh...
1024
01:04:23,734 --> 01:04:26,571
I believe in redemption.
1025
01:04:26,946 --> 01:04:28,239
[chuckles]
1026
01:04:28,948 --> 01:04:35,371
Uh, individual redemption
and collective... uh, social redemption.
1027
01:04:35,454 --> 01:04:39,041
Uh, I'm an idealist.
I think we can fix stuff that's broken,
1028
01:04:39,333 --> 01:04:42,962
uh, and, at the same time,
1029
01:04:43,045 --> 01:04:46,591
I am a realist about the fact
that you can't fix everything. Um...
1030
01:04:46,716 --> 01:04:49,176
You know, some things get broken
and stay broken.
1031
01:04:54,682 --> 01:04:57,018
Good morning,
welcome to this further session
1032
01:04:57,101 --> 01:05:00,104
of the Digital, Culture,
Media and Sport Select Committee.
1033
01:05:00,187 --> 01:05:02,773
Very pleased to welcome Brittany Kaiser
to give evidence to
1034
01:05:02,857 --> 01:05:04,442
the committee this morning.
1035
01:05:05,276 --> 01:05:09,739
Now, there was a contact between Facebook
and Cambridge Analytica
1036
01:05:09,822 --> 01:05:14,994
about the use of data in,
I think it was 2015, from memory.
1037
01:05:15,202 --> 01:05:18,205
Did you know about that at the time?
1038
01:05:18,414 --> 01:05:21,876
Uh, so Facebook had announced
to all of their clients
1039
01:05:21,959 --> 01:05:25,296
that they were going to close
their clients' access to this data,
1040
01:05:25,963 --> 01:05:27,673
so we agreed to delete it,
1041
01:05:27,757 --> 01:05:31,010
but in March 2016,
1042
01:05:31,093 --> 01:05:33,304
you know, six or eight weeks after
1043
01:05:33,387 --> 01:05:37,141
our chief data officer said
that those data sets were deleted,
1044
01:05:37,224 --> 01:05:40,227
I have an email from one
of our senior data scientists
1045
01:05:40,311 --> 01:05:44,941
that said that we were actually using
Facebook Like data in our modeling.
1046
01:05:45,024 --> 01:05:46,525
Ooh.
1047
01:05:46,609 --> 01:05:48,903
- [Kaiser] So that seems strange to me.
- Uh-oh.
1048
01:05:48,986 --> 01:05:51,131
[Kaiser] If we had deleted
all of the Facebook data sets,
1049
01:05:51,155 --> 01:05:53,491
how we were still using that
for modeling in March.
1050
01:05:54,700 --> 01:05:57,596
Ms. Kaiser, you seem to have traveled
a long way from an idealistic intern
1051
01:05:57,620 --> 01:05:59,288
in Barack Obama's campaign,
1052
01:05:59,372 --> 01:06:03,376
uh, to working for a company
that keeps pretty unsavory company,
1053
01:06:03,459 --> 01:06:07,213
uh, in wishing to make pitches
to far-right political parties.
1054
01:06:07,296 --> 01:06:09,799
- Mm-hmm.
- [man] Didn't that make you uncomfortable?
1055
01:06:09,966 --> 01:06:10,966
Uh, yes.
1056
01:06:11,717 --> 01:06:15,846
I would say questioning the ethics of it
is correct, definitely.
1057
01:06:15,930 --> 01:06:19,892
But I have been offered introductions
to clients
1058
01:06:19,976 --> 01:06:21,686
that I refused to meet with before,
1059
01:06:21,769 --> 01:06:25,940
um, such as the Alternative for Germany
and Marine Le Pen's campaign.
1060
01:06:26,023 --> 01:06:29,235
I refused to even get on a phone call
with them.
1061
01:06:30,361 --> 01:06:31,696
But not UKIP?
1062
01:06:31,988 --> 01:06:33,572
Not UKIP, no.
1063
01:06:35,116 --> 01:06:38,869
Um, did you appear and give a presentation
to the launch of Leave. EU?
1064
01:06:38,953 --> 01:06:40,121
Yes, I did.
1065
01:06:40,204 --> 01:06:42,999
[Matheson] Um, you must've been a bit, um,
disappointed then
1066
01:06:43,082 --> 01:06:45,501
when you subsequently
didn't do any work for them.
1067
01:06:45,793 --> 01:06:48,838
And we didn't do any further work for them
after that day, yes.
1068
01:06:48,921 --> 01:06:50,273
[Matheson] So you had done some work.
1069
01:06:50,297 --> 01:06:52,633
What was the nature of the work
that you had done so far?
1070
01:06:52,717 --> 01:06:53,968
We had taken receipt
1071
01:06:54,051 --> 01:06:57,388
of UK Independence Party data
and the survey data.
1072
01:06:57,471 --> 01:07:03,352
She's, like, contradicting Nix a lot,
what he said previously.
1073
01:07:03,436 --> 01:07:05,956
So, I think you've been quite clear,
as far as you're concerned,
1074
01:07:06,022 --> 01:07:10,026
you were working on the campaign,
but just not being paid for it?
1075
01:07:10,109 --> 01:07:12,069
- Mm-hmm.
- [Collins] You're pretty clear on that.
1076
01:07:12,862 --> 01:07:14,739
Just to clarify, for our benefit,
1077
01:07:14,822 --> 01:07:16,615
to be effective in this space,
1078
01:07:16,699 --> 01:07:18,951
how big a kind of working set do you need
1079
01:07:19,035 --> 01:07:22,163
to be able to then
use that to create the basis
1080
01:07:22,246 --> 01:07:24,790
for targeting the whole country
in terms of voting?
1081
01:07:25,082 --> 01:07:27,185
I'm not a data scientist,
so I wouldn't be able to say
1082
01:07:27,209 --> 01:07:29,712
the minimum number
of data points that you would require,
1083
01:07:29,795 --> 01:07:32,673
uh, but I do know
that their targeting tool
1084
01:07:32,757 --> 01:07:36,594
used to be export-controlled
by the British government,
1085
01:07:36,677 --> 01:07:39,930
so that would mean that
the methodology was considered a weapon.
1086
01:07:40,598 --> 01:07:43,267
Um, weapons-grade communications tactics.
1087
01:07:43,350 --> 01:07:46,896
What you're saying is that the proposal
was for Leave. EU to use what you call
1088
01:07:46,979 --> 01:07:50,858
weapons-grade communications techniques
against the UK population?
1089
01:07:51,942 --> 01:07:53,903
- [Kaiser] Yes, sir.
- It's crazy.
1090
01:07:54,236 --> 01:07:56,989
[O'Hara] Uh, I just want to get
your perspective as well.
1091
01:07:57,073 --> 01:07:59,158
What do you actually think
the legislators should do
1092
01:07:59,241 --> 01:08:01,368
in order to better protect people's data?
1093
01:08:01,911 --> 01:08:05,956
[Kaiser] Well, I'm very glad that
you asked that. Think about it right now.
1094
01:08:06,040 --> 01:08:08,459
The sole worth of Google and Facebook
1095
01:08:08,542 --> 01:08:12,046
is the fact that they own, and possess,
and hold, and use
1096
01:08:12,129 --> 01:08:14,249
the personal data
of people from all around the world.
1097
01:08:14,965 --> 01:08:17,218
So I think that the best way
to move forward
1098
01:08:17,301 --> 01:08:21,180
are for people to really possess
their data like their property.
1099
01:08:21,847 --> 01:08:23,825
- [O'Hara] Thank you, Chair.
- [Collins] Thank you.
1100
01:08:23,849 --> 01:08:26,602
Um, I think that concludes the questions
from us today.
1101
01:08:26,685 --> 01:08:28,005
Just before we close the session,
1102
01:08:28,062 --> 01:08:30,981
I just have to make a short announcement
about Alexander Nix.
1103
01:08:31,065 --> 01:08:34,193
He's now not able to give evidence
to the Committee tomorrow
1104
01:08:34,276 --> 01:08:37,321
as a consequence of him having been served
with an information notice
1105
01:08:37,404 --> 01:08:39,244
and being subject
to the criminal investigation
1106
01:08:39,323 --> 01:08:41,367
by the Information Commissioner's Office.
1107
01:08:41,450 --> 01:08:44,036
And I hope we'll be able to update people
1108
01:08:44,120 --> 01:08:46,413
about that early next week.
Thank you very much.
1109
01:08:47,081 --> 01:08:48,081
Thank you.
1110
01:08:48,749 --> 01:08:49,750
[Carroll] Shit!
1111
01:08:51,001 --> 01:08:53,045
[woman] The proceeding has ended.
1112
01:08:53,129 --> 01:08:54,129
Yes, it has!
1113
01:08:56,090 --> 01:08:57,091
[laughs]
1114
01:09:04,807 --> 01:09:06,809
[indistinct chatter]
1115
01:09:08,477 --> 01:09:10,479
[upbeat music playing over speakers]
1116
01:09:11,772 --> 01:09:13,732
I just got a text from Alexander.
1117
01:09:15,860 --> 01:09:17,486
[chuckles] Alexander Nix.
1118
01:09:20,447 --> 01:09:21,615
[man] What did he say?
1119
01:09:22,283 --> 01:09:25,619
"Well done, Britt.
Looked quite tough, and you did okay."
1120
01:09:26,453 --> 01:09:29,540
With a winky face little emoji.
1121
01:09:31,167 --> 01:09:33,794
It makes me kind of sad.
You know what I mean?
1122
01:09:33,878 --> 01:09:36,088
Like, it's not like he spent
three and a half years
1123
01:09:36,172 --> 01:09:37,923
being an asshole to me. He didn't.
1124
01:09:38,174 --> 01:09:40,443
[Hilder] He spent three and a half years
being nice to you
1125
01:09:40,467 --> 01:09:42,261
to get you to do what he wanted you to do.
1126
01:09:42,344 --> 01:09:46,473
Yeah. But he is rather fun. [laughs]
1127
01:09:46,557 --> 01:09:48,243
- [phone vibrates]
- [Hilder] I know, I know.
1128
01:09:48,267 --> 01:09:49,310
[Carroll] Hey, Justin.
1129
01:09:49,810 --> 01:09:52,146
[Justin over phone]
Hey, what's up? What did you think?
1130
01:09:52,646 --> 01:09:55,441
I'm processing it.
There were a lot of revelations.
1131
01:09:57,484 --> 01:10:00,988
SCL has to file its defense
at the end of the month,
1132
01:10:01,614 --> 01:10:04,200
so, it'll be really interesting
to see, like,
1133
01:10:04,283 --> 01:10:07,328
what they think they can do,
especially after this.
1134
01:10:07,995 --> 01:10:09,205
[Justin] That's right.
1135
01:10:10,206 --> 01:10:11,290
[Carroll] I mean, shit.
1136
01:10:11,373 --> 01:10:15,753
She said that basically psychographics
should be classified as a weapon.
1137
01:10:20,216 --> 01:10:23,719
It seems like Kaiser has
some moral compass in her.
1138
01:10:26,805 --> 01:10:30,392
But, so many times,
she knew that she was
1139
01:10:30,476 --> 01:10:32,061
in a dark world
1140
01:10:32,353 --> 01:10:33,896
and didn't step away.
1141
01:10:33,979 --> 01:10:37,191
And they... they got... got her on that
a couple of times.
1142
01:10:37,274 --> 01:10:38,274
Yeah.
1143
01:10:42,154 --> 01:10:45,157
[interviewer] You did work for a man who,
upon meeting you,
1144
01:10:45,241 --> 01:10:46,927
said to you, you know,
"Let me get you drunk
1145
01:10:46,951 --> 01:10:48,452
and steal your secrets."
1146
01:10:48,869 --> 01:10:51,789
You knew the kind of company
that you were working for.
1147
01:10:51,997 --> 01:10:54,208
I don't know. I guess I trusted him.
1148
01:10:54,500 --> 01:10:56,377
I worked for him
for three and a half years.
1149
01:10:56,460 --> 01:10:59,171
He was a friend and mentor. I mean...
1150
01:10:59,463 --> 01:11:01,465
He actually just sent me a text,
1151
01:11:01,548 --> 01:11:05,135
although I haven't spoken to him in,
I don't know, at least over a month.
1152
01:11:05,219 --> 01:11:06,696
[interviewer] So, he was watching you.
1153
01:11:06,720 --> 01:11:08,720
- He watched, yes.
- [interviewer] What did he say?
1154
01:11:09,056 --> 01:11:12,393
He said that it looked pretty tough
but that I did a good job.
1155
01:11:12,476 --> 01:11:14,520
- [interviewer] Did you reply?
- No.
1156
01:11:14,728 --> 01:11:15,854
[interviewer] Will you?
1157
01:11:15,938 --> 01:11:18,482
No, I don't think that's appropriate
at this time.
1158
01:11:18,565 --> 01:11:21,110
[interviewer]
So, there's no friendship there?
1159
01:11:21,777 --> 01:11:27,658
Well, I now question, you know,
how much of a friendship it actually was.
1160
01:11:49,722 --> 01:11:52,141
[Cadwalladr] The thing which
I give Brittany credit for...
1161
01:11:52,433 --> 01:11:56,520
it's really amazed me how many people
are just keeping their mouths shut.
1162
01:12:01,066 --> 01:12:03,485
I mean, it was a jaw-dropping moment
1163
01:12:03,569 --> 01:12:08,866
when Brittany said these are classified
as weapons-grade technology.
1164
01:12:09,199 --> 01:12:11,994
And it was actually illegal to use those
1165
01:12:12,077 --> 01:12:14,455
without the permission
of the British government.
1166
01:12:18,125 --> 01:12:19,710
It's psyops.
1167
01:12:20,961 --> 01:12:24,214
Psyops is psychological operations.
1168
01:12:24,298 --> 01:12:27,801
And it's a...
it's a term that the military uses
1169
01:12:27,885 --> 01:12:32,348
to describe what you do in warfare
which isn't warfare.
1170
01:12:32,431 --> 01:12:34,350
So, essentially, you know,
1171
01:12:34,433 --> 01:12:36,602
in a place like Afghanistan,
you've got a choice.
1172
01:12:36,685 --> 01:12:38,562
You either bomb the shit out of a village
1173
01:12:38,854 --> 01:12:41,398
or you try and use other techniques
1174
01:12:41,482 --> 01:12:44,943
to persuade them that actually,
"The Taliban's not very good,
1175
01:12:45,027 --> 01:12:46,862
and you'd be much better off
without them."
1176
01:12:51,033 --> 01:12:54,203
SCL started out as a military contractor.
1177
01:12:54,286 --> 01:12:55,454
SCL Defense.
1178
01:12:57,498 --> 01:13:00,417
[Nix] We have a fairly substantial
defense business.
1179
01:13:01,627 --> 01:13:03,837
We actually train the British Army,
the British Navy,
1180
01:13:03,921 --> 01:13:05,464
the U.S. Army, U.S. Special Forces.
1181
01:13:05,547 --> 01:13:09,009
We train NATO, the CIA,
State Department, Pentagon.
1182
01:13:09,718 --> 01:13:15,099
It's using research to influence behavior
of hostile audiences.
1183
01:13:15,766 --> 01:13:20,646
You know, how do you persuade
14-to 30-year-old Muslim boys
1184
01:13:20,729 --> 01:13:22,356
not to join Al-Qaeda?
1185
01:13:23,440 --> 01:13:24,942
Essentially communication warfare.
1186
01:13:25,025 --> 01:13:26,985
- [man] Allahu Akbar!
- [all] Allahu Akbar!
1187
01:13:27,486 --> 01:13:30,948
[Cadwalladr] They'd worked
in Afghanistan, they'd worked in Iraq,
1188
01:13:31,031 --> 01:13:34,576
they'd worked in various places
in Eastern Europe.
1189
01:13:34,993 --> 01:13:37,663
But the real game changer
1190
01:13:37,746 --> 01:13:42,918
was they started using information warfare
in elections.
1191
01:13:44,044 --> 01:13:47,714
[Nix] There's a lot of overlap,
because it's all the same methodology.
1192
01:13:50,843 --> 01:13:55,139
[Cadwalladr] All of the campaigns
which Cambridge Analytica/SCL did
1193
01:13:55,222 --> 01:13:57,599
for the developing world,
1194
01:13:57,808 --> 01:14:02,020
it was all about practicing
some new technology or trick.
1195
01:14:02,354 --> 01:14:04,106
How to persuade people,
1196
01:14:04,189 --> 01:14:07,943
how to suppress turnout,
or how to increase turnout.
1197
01:14:10,654 --> 01:14:11,654
And then it's like,
1198
01:14:11,697 --> 01:14:15,075
"Okay, now we've got the hang of it,
let's use it in Britain and America."
1199
01:14:24,751 --> 01:14:25,752
[Nix]
1200
01:14:37,014 --> 01:14:38,557
[overlapping restaurant chatter]
1201
01:14:42,269 --> 01:14:43,269
[man] Yes.
1202
01:15:19,306 --> 01:15:22,643
...and expands, but with no branding,
1203
01:15:22,893 --> 01:15:25,646
so it's unattributable, untrackable.
1204
01:15:26,396 --> 01:15:28,565
- [applause]
- And my view...
1205
01:15:29,441 --> 01:15:32,569
is that if you can't run your own house,
1206
01:15:32,778 --> 01:15:35,447
- you certainly can't run the White House.
- [crowd cheering]
1207
01:15:35,531 --> 01:15:36,990
- Can't do it.
- [cheering]
1208
01:15:38,158 --> 01:15:41,620
[Trump] Crooked Hillary, right? Crooked.
She's crooked as you can be.
1209
01:15:41,703 --> 01:15:43,413
[crowd chanting]
Lock her up! Lock her up!
1210
01:15:43,497 --> 01:15:45,415
[man] Yep, that's right, lock her up!
1211
01:15:45,499 --> 01:15:47,251
Lock her up! Lock her up!
1212
01:15:47,584 --> 01:15:49,920
Lock her up! Lock her up!
1213
01:15:50,003 --> 01:15:51,838
[crowd continues shouting]
1214
01:15:51,922 --> 01:15:54,424
Let's defeat her in November.
1215
01:16:08,105 --> 01:16:10,482
[man] What was it like for you to watch
1216
01:16:10,566 --> 01:16:12,526
the Channel 4 undercover video?
1217
01:16:14,069 --> 01:16:15,612
Nobody recognized it.
1218
01:16:18,407 --> 01:16:20,701
When we watched that video...
1219
01:16:21,118 --> 01:16:25,872
I watched it in the New York office
with, um, all the staff there.
1220
01:16:25,956 --> 01:16:27,791
And we knew it was coming out.
1221
01:16:28,000 --> 01:16:30,377
And I think everybody was...
1222
01:16:31,962 --> 01:16:33,255
in a state of shock.
1223
01:16:35,424 --> 01:16:40,095
Everybody walked away from the screen
in silence back to their desks.
1224
01:16:47,978 --> 01:16:51,398
[reporter 1] Tonight, an undercover
interview by Channel 4 News in London
1225
01:16:51,481 --> 01:16:52,983
shows Cambridge executives,
1226
01:16:53,066 --> 01:16:55,485
including CEO Alexander Nix,
1227
01:16:55,569 --> 01:16:58,030
boasting about the company's role
in Trump's win.
1228
01:16:58,488 --> 01:17:01,533
This series of undercover interviews
by Channel 4 News
1229
01:17:01,617 --> 01:17:03,076
also caught Nix on tape
1230
01:17:03,160 --> 01:17:06,038
talking about potential bribery
and entrapment.
1231
01:17:08,832 --> 01:17:10,334
[man] I don't understand.
1232
01:17:14,588 --> 01:17:16,798
[reporter 1] Mr. Nix, can I ask you
what your message is
1233
01:17:16,882 --> 01:17:19,217
to Cambridge Analytica employees today?
1234
01:17:22,220 --> 01:17:24,780
[reporter 2] We've just got a statement
from Cambridge Analytica.
1235
01:17:25,932 --> 01:17:29,686
Alexander Nix has been suspended
with immediate effect.
1236
01:17:29,770 --> 01:17:34,066
The company accused of harvesting the data
of more than 87 million Facebook users
1237
01:17:34,149 --> 01:17:35,484
says it is shutting down.
1238
01:17:35,817 --> 01:17:40,489
The company says it intends to file
for bankruptcy in the US and the UK.
1239
01:17:42,324 --> 01:17:44,576
[reporter]
Critics believe Cambridge Analytica
1240
01:17:44,660 --> 01:17:47,496
and SCL Elections
may be shutting operations
1241
01:17:47,579 --> 01:17:51,583
to limit or restrict the ability
of the authority's investigations
1242
01:17:51,667 --> 01:17:53,794
and also to get rid of evidence.
1243
01:18:02,678 --> 01:18:04,364
[Wheatland]
The Cambridge Analytica scandal,
1244
01:18:04,388 --> 01:18:05,972
is it now the Facebook scandal?
1245
01:18:08,100 --> 01:18:10,185
I mean, this is not about one company.
1246
01:18:11,436 --> 01:18:16,608
This technology is going on unabated
and will continue to go on.
1247
01:18:17,943 --> 01:18:19,653
But Cambridge Analytica's gone.
1248
01:18:20,696 --> 01:18:23,532
In some senses, I feel that, um...
1249
01:18:25,867 --> 01:18:30,038
that because of the way
that this technology is moving so fast,
1250
01:18:30,414 --> 01:18:34,710
and because people
don't really understand it,
1251
01:18:34,793 --> 01:18:37,170
and because there's a lot of concerns
about it,
1252
01:18:37,254 --> 01:18:40,215
there was always going to be
a Cambridge Analytica.
1253
01:18:40,632 --> 01:18:43,218
It just sucks for me
it was Cambridge Analytica.
1254
01:18:55,814 --> 01:18:57,733
[Cadwalladr]
After we dealt with the threats
1255
01:18:57,816 --> 01:19:00,527
from Cambridge Analytica
over the course of a year,
1256
01:19:01,027 --> 01:19:03,363
then the thing which made
our heads explode
1257
01:19:03,447 --> 01:19:06,283
was the day before publication,
when we got a letter from Facebook.
1258
01:19:06,992 --> 01:19:10,245
Yeah, it felt like an attempt
to... to cow us into submission.
1259
01:19:10,328 --> 01:19:11,747
It didn't feel like a sort of...
1260
01:19:11,830 --> 01:19:14,499
To me, it didn't feel like
a legitimate response...
1261
01:19:14,583 --> 01:19:18,462
And you sort of go, you know,
why is a great, big organization like you
1262
01:19:18,545 --> 01:19:20,130
using UK lawyers?
1263
01:19:20,213 --> 01:19:22,382
And again, a very aggressive threat
1264
01:19:22,466 --> 01:19:24,318
for which, actually, they then...
Didn't they apologize?
1265
01:19:24,342 --> 01:19:26,178
Yes,
they said it was not their finest hour.
1266
01:19:26,261 --> 01:19:27,888
- [all laugh]
- [Cadwalladr] Yeah.
1267
01:19:27,971 --> 01:19:29,473
And up until that point,
1268
01:19:29,556 --> 01:19:31,808
it was like the tech giants were still,
like,
1269
01:19:31,892 --> 01:19:33,727
the nice guys who wear hoodies,
1270
01:19:33,810 --> 01:19:35,562
- who connected the world.
- [Phillips] Yep.
1271
01:19:35,645 --> 01:19:37,898
And there was a shift away
1272
01:19:37,981 --> 01:19:39,983
from big tech being good
1273
01:19:40,066 --> 01:19:43,945
to saying well, actually,
we do need to start asking questions
1274
01:19:44,029 --> 01:19:46,364
about this and what it is.
1275
01:19:50,243 --> 01:19:52,245
[Cadwalladr] Cambridge Analytica is gone,
1276
01:19:52,829 --> 01:19:58,502
but it's really important to understand
that the Cambridge Analytica story
1277
01:19:58,668 --> 01:20:02,923
actually points to this much bigger,
more worrying story
1278
01:20:03,757 --> 01:20:08,637
which is that our personal data
is out there and being used against us
1279
01:20:08,720 --> 01:20:10,931
in ways we don't understand.
1280
01:20:14,643 --> 01:20:16,520
And if David gets his data back,
1281
01:20:16,812 --> 01:20:19,856
we can hopefully start
getting some answers.
1282
01:20:22,734 --> 01:20:26,780
[Carroll] The deadline is today for SCL
to comply with the law
1283
01:20:26,863 --> 01:20:28,615
and give me my data.
1284
01:20:30,659 --> 01:20:35,497
We're at the precipice of evasion
or accountability.
1285
01:20:38,583 --> 01:20:40,210
Carole tweeted,
1286
01:20:40,293 --> 01:20:43,421
"Prof. Carroll also giving evidence
to European Parliament today
1287
01:20:43,505 --> 01:20:47,634
on day of deadline for Cambridge Analytica
to turn over his data to him.
1288
01:20:47,717 --> 01:20:51,388
If it fails to do so, it becomes
a matter for criminal proceedings."
1289
01:20:55,934 --> 01:20:58,728
[Carroll]
"Hey Ravi, have you heard anything?"
1290
01:21:00,272 --> 01:21:01,356
"Not yet."
1291
01:21:07,445 --> 01:21:11,783
I've been waiting to hear from my lawyer,
and we have heard nothing.
1292
01:21:11,867 --> 01:21:14,244
And so they have not respected
the regulator.
1293
01:21:14,327 --> 01:21:16,788
They are not respecting the law.
1294
01:21:17,372 --> 01:21:19,666
So now that this is becoming
a criminal matter,
1295
01:21:19,749 --> 01:21:21,626
we are now in uncharted waters.
1296
01:21:22,711 --> 01:21:26,298
And I will continue to pursue it
1297
01:21:26,381 --> 01:21:30,051
because their model has the potential
to affect a population
1298
01:21:30,135 --> 01:21:32,596
even if it's just a tiny slice
of the population,
1299
01:21:32,679 --> 01:21:34,264
because in the United States,
1300
01:21:34,347 --> 01:21:39,436
only about 70,000 voters in three states
decided the election.
1301
01:21:42,188 --> 01:21:45,275
Thank you very much,
um, Professor Carroll. Um...
1302
01:21:45,609 --> 01:21:46,818
Mr. Batten.
1303
01:21:47,277 --> 01:21:51,281
[Batten] My question is
for Carole Cadwalladr from The Guardian.
1304
01:21:51,364 --> 01:21:56,077
Is The Guardian's stand
on this a purely politically partisan one
1305
01:21:56,161 --> 01:22:00,040
in its own intention to assist
in any way that it can
1306
01:22:00,123 --> 01:22:03,251
to reverse and overturn
the result of the referendum?
1307
01:22:05,420 --> 01:22:10,258
This is not a partisan issue,
I cannot say that more strongly.
1308
01:22:10,342 --> 01:22:14,304
This is about the integrity
of our democracy.
1309
01:22:14,387 --> 01:22:17,057
It's about our national sovereignty.
1310
01:22:17,599 --> 01:22:21,061
And I would think that you would have
an interest in that also.
1311
01:22:21,144 --> 01:22:23,146
[pounding applause]
1312
01:22:24,147 --> 01:22:28,234
I think that we desperately need
more information,
1313
01:22:28,652 --> 01:22:31,154
because we don't how people were targeted
1314
01:22:31,237 --> 01:22:33,782
and we don't know what data
that was based upon.
1315
01:22:34,157 --> 01:22:40,956
One thing we do know is that Facebook
has been obstructive in its efforts
1316
01:22:41,039 --> 01:22:43,708
to help the British Parliament
investigate this matter.
1317
01:22:44,084 --> 01:22:48,755
Uh, really, really, really,
you've got to, like, look higher
1318
01:22:48,838 --> 01:22:50,966
and really see the bigger issue here
1319
01:22:51,049 --> 01:22:53,635
and the bigger picture
and the bigger risks to us all.
1320
01:22:55,637 --> 01:22:57,973
[applause]
1321
01:23:04,771 --> 01:23:07,983
[reporter] Roger, even if, uh, Facebook
hasn't broken any laws,
1322
01:23:08,066 --> 01:23:12,320
have they broken a sort of moral trust
that they have with their consumers?
1323
01:23:12,404 --> 01:23:14,197
Well, I... They have with me.
1324
01:23:14,280 --> 01:23:18,743
I mean, I spent three months,
starting in October 2016, trying to say,
1325
01:23:18,827 --> 01:23:22,455
"Guys, I think you're killing democracy,
and you're gonna kill your business."
1326
01:23:22,539 --> 01:23:24,833
- Hi, how are you? I'm Roger.
- Hi, how are you?
1327
01:23:24,916 --> 01:23:26,811
- [McNamee] Pleasure to meet you.
- Pleasure to meet you.
1328
01:23:26,835 --> 01:23:31,131
Facebook is designed
to monopolize attention.
1329
01:23:31,589 --> 01:23:34,509
Just taking all of the basic tricks
of propaganda,
1330
01:23:34,592 --> 01:23:37,053
marrying them to the tricks
of casino gambling.
1331
01:23:37,137 --> 01:23:39,014
You know, slot machines and the like.
1332
01:23:39,264 --> 01:23:43,977
And basically playing on instincts,
1333
01:23:44,394 --> 01:23:47,772
and fear and anger are the two
most dependable ways of doing that.
1334
01:23:47,897 --> 01:23:50,483
And so, they created a set of tools
1335
01:23:50,567 --> 01:23:56,197
to allow advertisers to exploit
that emotional audience
1336
01:23:57,073 --> 01:24:00,368
with individual-level targeting, right?
1337
01:24:00,452 --> 01:24:05,623
There's 2.1 billion people,
each with their own reality.
1338
01:24:05,915 --> 01:24:08,251
And once everybody has their own reality,
1339
01:24:08,334 --> 01:24:11,463
- it's relatively easy to manipulate them.
- Mmm. Yeah.
1340
01:24:11,546 --> 01:24:16,926
And the other thing about this is,
they know that it's killing me...
1341
01:24:17,218 --> 01:24:18,678
- [Kaiser] Yeah.
- ...to be critical
1342
01:24:18,762 --> 01:24:20,597
of what I've viewed as my baby.
1343
01:24:20,680 --> 01:24:24,809
It is a lot easier to just sort of say,
"I'm not gonna think about it."
1344
01:24:24,893 --> 01:24:25,893
[Hilder] Yes.
1345
01:24:25,977 --> 01:24:27,645
- But...
- [Kaiser] Yeah.
1346
01:24:28,229 --> 01:24:31,191
...you get tested in your life
a few times, right? And...
1347
01:24:31,483 --> 01:24:33,151
for me, this was one of those moments.
1348
01:24:33,234 --> 01:24:35,004
I was either gonna stand up
and do something about this,
1349
01:24:35,028 --> 01:24:37,781
or I wasn't gonna stand up
and do anything about anything. Right?
1350
01:24:37,864 --> 01:24:40,533
Because my fingerprints are on this thing.
1351
01:24:41,034 --> 01:24:43,495
- [Kaiser] I know.
- I mean, I felt really guilty.
1352
01:24:44,621 --> 01:24:47,332
And I just want to be able to...
1353
01:24:48,458 --> 01:24:49,876
sleep at night.
1354
01:25:09,354 --> 01:25:12,774
[Hilder] One of the things
that I was really struck by was...
1355
01:25:13,066 --> 01:25:15,318
what happened with you
1356
01:25:15,401 --> 01:25:17,487
and the Obama people
and the Hillary people.
1357
01:25:18,863 --> 01:25:22,325
[Kaiser] Uh, none of them ever wanted
to offer to pay me.
1358
01:25:23,493 --> 01:25:27,497
And, um,
when your family loses all their money
1359
01:25:27,580 --> 01:25:30,375
and loses their family home
1360
01:25:30,458 --> 01:25:33,002
and your father,
who's the main breadwinner,
1361
01:25:33,086 --> 01:25:35,588
has brain surgery
and can never work again,
1362
01:25:36,214 --> 01:25:38,925
you have to work for people that pay you.
1363
01:25:40,718 --> 01:25:42,220
[thunder rumbles]
1364
01:25:42,303 --> 01:25:45,265
[Hilder]
Your family lost their money in 2008?
1365
01:25:45,682 --> 01:25:49,519
Um, yeah, but it took a while
for it all to really fall apart.
1366
01:25:49,602 --> 01:25:50,854
- [man] Yeah.
- Um...
1367
01:25:52,147 --> 01:25:57,026
We lost our family home in 2014,
when I started working for Cambridge.
1368
01:26:09,497 --> 01:26:12,375
[reporter 1] Alexander Nix appears
before Parliament's Media Committee
1369
01:26:12,458 --> 01:26:14,460
after previously refusing to testify
1370
01:26:14,544 --> 01:26:17,338
due to law enforcement investigations
into the firm.
1371
01:26:19,924 --> 01:26:22,260
[overlapping questions]
1372
01:26:22,343 --> 01:26:23,887
- Hi, Jo, how are you?
- Hello.
1373
01:26:27,223 --> 01:26:29,058
[Carroll] The last time I was in London,
1374
01:26:29,142 --> 01:26:33,188
I remember considering challenging SCL
1375
01:26:34,522 --> 01:26:38,651
and running through my head, like,
how scary it was.
1376
01:26:40,195 --> 01:26:42,572
The Committee's very grateful, uh,
to Alexander Nix
1377
01:26:42,655 --> 01:26:45,408
for agreeing to come back
in front of the committee today
1378
01:26:45,491 --> 01:26:47,243
to answer our questions...
1379
01:26:47,327 --> 01:26:49,120
[Carroll] Now, to be back here and, uh...
1380
01:26:49,204 --> 01:26:52,457
these guys are down for the count and...
1381
01:26:52,540 --> 01:26:54,876
the villain is up against the wall.
1382
01:26:56,336 --> 01:26:59,505
[chuckles] You know,
does he have any allies left in the world
1383
01:27:00,298 --> 01:27:02,634
or has everybody turned against him?
1384
01:27:04,385 --> 01:27:05,720
[sighs] Right.
1385
01:27:06,763 --> 01:27:09,849
I'd like to make
a few short clarifications.
1386
01:27:09,933 --> 01:27:12,560
Um, these will only take a few minutes,
1387
01:27:12,644 --> 01:27:17,273
uh, but it is important
to be able to frame, uh, my answers.
1388
01:27:17,357 --> 01:27:18,358
He's so nervous.
1389
01:27:18,441 --> 01:27:20,461
Mr. Nix, I'd be grateful if you'd start
with the committee's questions
1390
01:27:20,485 --> 01:27:22,087
and then see how we go
through the hearing.
1391
01:27:22,111 --> 01:27:26,449
Ordinarily, uh, I would respect that,
but these aren't ordinary circumstances,
1392
01:27:26,532 --> 01:27:30,203
and so, if I may, I'd like to start
with a very brief statement
1393
01:27:30,286 --> 01:27:31,663
just to set out my position.
1394
01:27:31,746 --> 01:27:34,332
I would rather take this
on a question by question basis
1395
01:27:34,415 --> 01:27:37,126
rather than being dealt with
as a statement at the beginning.
1396
01:27:37,377 --> 01:27:39,587
Mr. Collins,
you'll have plenty of opportunity,
1397
01:27:39,671 --> 01:27:43,174
as will all the Committee,
to ask me as many questions as you want,
1398
01:27:43,258 --> 01:27:45,134
but I have to insist on...
1399
01:27:45,218 --> 01:27:48,614
- How could you possibly start like that...
- [Collins] It's not your place to insist.
1400
01:27:48,638 --> 01:27:51,724
"I accept that some of my answers
could have been clearer..."
1401
01:27:51,808 --> 01:27:54,560
[Collins] So, instead,
you're just reading out the statement.
1402
01:27:54,644 --> 01:27:58,189
- Can you answer the first question...
- Why is he doing that?
1403
01:27:59,816 --> 01:28:02,456
- Could you repeat your first question?
- [Collins] Yes, thank you.
1404
01:28:02,527 --> 01:28:05,238
You did pitch to work on the Referendum,
1405
01:28:05,321 --> 01:28:09,284
and I don't want to dwell on Leave. EU
because you've made your position clear.
1406
01:28:09,534 --> 01:28:12,912
We're really scratching around here,
Mr. Farrelly. Um...
1407
01:28:13,329 --> 01:28:17,417
We've been working, or I've been working
with this company for 15 years. Um...
1408
01:28:17,500 --> 01:28:20,086
We've never undertaken an election
in the UK.
1409
01:28:20,253 --> 01:28:21,462
[Collins] Well, I was...
1410
01:28:21,546 --> 01:28:23,732
- I hope I wasn't scratching around.
- That is not true.
1411
01:28:23,756 --> 01:28:26,759
[Collins] I was comparing what you told us
with the evidence
1412
01:28:26,843 --> 01:28:28,344
that's subsequently emerged,
1413
01:28:28,428 --> 01:28:30,468
- and you clearly felt...
- [phone chimes, vibrates]
1414
01:28:30,513 --> 01:28:33,641
...that the work that you've done, uh...
[stammers, continues indistinctly]
1415
01:28:33,725 --> 01:28:37,186
[Kaiser] So, I got an email from Carole.
1416
01:28:37,270 --> 01:28:40,315
She knows that I met Julian Assange
in February.
1417
01:28:40,398 --> 01:28:42,025
[chuckles] Um...
1418
01:28:42,108 --> 01:28:47,155
And she knows that I donated to WikiLeaks
at some point in Bitcoin.
1419
01:28:49,073 --> 01:28:52,076
If she prints something about it today,
it's going to make...
1420
01:28:53,202 --> 01:28:56,372
my conversations with my own government
really difficult.
1421
01:28:56,914 --> 01:28:59,059
[Collins] Um, it came up
in Brittany Kaiser's evidence,
1422
01:28:59,083 --> 01:29:02,628
because you spoke to us about, uh,
Julian Assange the last time you came,
1423
01:29:02,712 --> 01:29:06,049
saying that you made an attempt
to gain access to the emails
1424
01:29:06,132 --> 01:29:08,092
that Julian Assange had, um,
1425
01:29:08,176 --> 01:29:11,554
the Hillary Clinton emails,
in order to benefit your client,
1426
01:29:11,637 --> 01:29:12,554
the Trump campaign.
1427
01:29:12,555 --> 01:29:15,099
Well, these were very contentious emails,
potentially...
1428
01:29:15,183 --> 01:29:17,602
- [Collins] Yeah.
- ...and we wanted to understand...
1429
01:29:17,685 --> 01:29:19,812
as did every journalist
1430
01:29:19,896 --> 01:29:22,565
and, I would say,
most political consultants
1431
01:29:22,648 --> 01:29:25,109
on both sides of the aisle
in the United States,
1432
01:29:25,193 --> 01:29:26,778
um, what was contained in them.
1433
01:29:26,861 --> 01:29:32,492
[stammers] I don't think that curiosity
is indicative of anything nefarious.
1434
01:29:32,575 --> 01:29:36,245
- [hearing continues indistinctly]
- Oh, my God. Carole published the article.
1435
01:29:38,122 --> 01:29:40,666
I didn't discuss the US election!
1436
01:29:40,750 --> 01:29:43,086
- Oh, my God, this is insane!
- [phone ringing]
1437
01:29:43,169 --> 01:29:44,337
Paul!
1438
01:29:44,420 --> 01:29:46,964
- [Paul] Hello, how are you!
- Paul!
1439
01:29:47,507 --> 01:29:50,051
I have said to you, it's all coming out,
1440
01:29:50,134 --> 01:29:51,469
and the question is how.
1441
01:29:51,552 --> 01:29:54,347
I didn't conspire
to leak Hillary's emails,
1442
01:29:54,430 --> 01:29:58,184
and I have nothing... [clears throat]
...to do with Russia, so...
1443
01:29:58,267 --> 01:29:59,267
[Paul] Yes.
1444
01:29:59,435 --> 01:30:01,020
The fact is...
1445
01:30:01,104 --> 01:30:02,104
[clears throat]
1446
01:30:02,522 --> 01:30:05,233
- ...it looks like I did both.
- Does it look like you did both?
1447
01:30:05,316 --> 01:30:08,694
If I wasn't me, I would say yes,
that's what it looks like!
1448
01:30:08,778 --> 01:30:10,446
- [chuckles nervously]
- [Paul laughs]
1449
01:30:11,155 --> 01:30:12,698
That's why I'm freaking out.
1450
01:30:12,782 --> 01:30:15,535
There's gonna be so many people
that literally never believe me.
1451
01:30:15,952 --> 01:30:18,496
I will die
with people still not believing me.
1452
01:30:18,579 --> 01:30:21,374
- Uh, that is possible.
- [chuckles]
1453
01:30:21,624 --> 01:30:24,043
- That is definitely possible. [laughs]
- I know!
1454
01:30:24,794 --> 01:30:26,170
Agh! [slams table]
1455
01:30:27,380 --> 01:30:28,423
All right...
1456
01:30:29,006 --> 01:30:31,446
[Kaiser sniffles] I think I need
to get the fuck out of here.
1457
01:30:34,887 --> 01:30:37,807
[O'Hara] From where I'm sitting,
since you've come here today,
1458
01:30:37,890 --> 01:30:41,686
you have attempted to paint yourself
as the victim here,
1459
01:30:41,769 --> 01:30:46,566
though, by no stretch of the imagination
can you be seen as a victim.
1460
01:30:46,858 --> 01:30:50,194
Surely you can see that
you are not the victim here.
1461
01:30:51,028 --> 01:30:52,864
[Nix] What if I was the victim?
1462
01:30:52,947 --> 01:30:56,868
What happens if, as some
of these investigations are concluded,
1463
01:30:56,951 --> 01:30:59,787
people realize
that actually we were simply...
1464
01:31:00,371 --> 01:31:04,917
the guys who were, uh,
perceived to have contributed
1465
01:31:05,001 --> 01:31:06,711
to the Trump campaign
1466
01:31:06,794 --> 01:31:10,923
and were wrongly accredited
with being the architects of Brexit
1467
01:31:11,340 --> 01:31:15,636
and as a result of the polarizing nature
of those two political campaigns,
1468
01:31:15,720 --> 01:31:18,723
the global liberal media took umbrage
1469
01:31:18,806 --> 01:31:21,684
and decided to put us in their crosshairs
1470
01:31:21,767 --> 01:31:26,147
and launch a coordinated attack on us
as a company
1471
01:31:26,230 --> 01:31:29,317
in order to destroy our reputations
and our business,
1472
01:31:29,400 --> 01:31:34,405
and all of this was underpinned
by a stream of allegations,
1473
01:31:34,489 --> 01:31:37,867
unfounded, groundless allegations
that came from Mr. Wylie,
1474
01:31:37,950 --> 01:31:41,287
who gave the media
the ammunition that they needed...
1475
01:31:41,662 --> 01:31:43,164
that they wanted,
1476
01:31:43,247 --> 01:31:46,417
to be able to attack us for something
that, in the case of Brexit,
1477
01:31:46,501 --> 01:31:47,502
we simply didn't do.
1478
01:31:47,585 --> 01:31:49,504
[O'Hara]
So you are the victim in all of this.
1479
01:31:50,796 --> 01:31:54,717
Well, if you're sitting where I am
right now, you'd probably feel...
1480
01:31:54,800 --> 01:31:56,177
uh... [stammers]
1481
01:31:56,260 --> 01:31:57,470
...quite victimized.
1482
01:31:57,845 --> 01:31:59,514
Where the fuck is my passport?
1483
01:32:00,348 --> 01:32:01,348
[exhales]
1484
01:32:01,766 --> 01:32:03,809
Not having a good day right now.
1485
01:32:04,352 --> 01:32:05,645
Did I put it somewhere else?
1486
01:32:08,731 --> 01:32:09,857
[sighs] Oh, my God.
1487
01:32:10,149 --> 01:32:12,568
I've never put it there before in my life.
1488
01:32:13,110 --> 01:32:15,613
Not that I'm thinking straight today,
so...
1489
01:32:17,615 --> 01:32:18,741
[sighs]
1490
01:32:19,992 --> 01:32:22,662
I'm flustered. Sorry, guys.
1491
01:32:27,416 --> 01:32:29,460
Coco Mademoiselle makes me feel better.
1492
01:32:30,503 --> 01:32:32,171
At least I smell good.
1493
01:32:38,678 --> 01:32:41,639
I have no idea what's gonna happen
in the next coming days.
1494
01:32:43,015 --> 01:32:46,352
I literally came back here
because I wanted to be cooperative,
1495
01:32:47,562 --> 01:32:48,938
I want to help.
1496
01:32:49,438 --> 01:32:51,440
[low, indistinct radio chatter]
1497
01:33:15,047 --> 01:33:17,192
[reporter] Today, The Guardian newspaper
in Britain reports
1498
01:33:17,216 --> 01:33:19,468
that a senior executive
at Cambridge Analytica
1499
01:33:19,552 --> 01:33:22,305
met with Julian Assange from WikiLeaks,
1500
01:33:22,555 --> 01:33:25,933
which is the entity that distributed
the documents that Russia had stolen.
1501
01:33:27,935 --> 01:33:31,022
She says they discussed the US election.
1502
01:33:49,498 --> 01:33:52,585
[Kaiser] The Mueller investigation called
when I booked my flight
1503
01:33:52,668 --> 01:33:55,087
and they decided to issue a subpoena.
1504
01:33:56,380 --> 01:34:00,635
We were talking to them
in a very, like, friendly, cooperative way
1505
01:34:00,718 --> 01:34:05,097
and then Carole's article completely
changed the way that they see me.
1506
01:34:06,557 --> 01:34:09,518
And, yeah, I...
1507
01:34:10,144 --> 01:34:12,438
worked at Cambridge Analytica
1508
01:34:12,521 --> 01:34:15,399
while they had Facebook data sets.
1509
01:34:16,400 --> 01:34:18,110
And, you know, I...
1510
01:34:19,612 --> 01:34:23,074
went to Russia one time
while I worked for Cambridge.
1511
01:34:23,157 --> 01:34:25,743
I visited Julian Assange
while I worked for Cambridge.
1512
01:34:25,951 --> 01:34:27,787
I once donated to WikiLeaks.
1513
01:34:27,870 --> 01:34:32,416
I pitched the Trump campaign
and wrote the first contract.
1514
01:34:33,167 --> 01:34:36,170
Like, all of these things
make it look like I am...
1515
01:34:36,504 --> 01:34:40,049
at the center of some big, crazy thing.
1516
01:34:41,258 --> 01:34:44,178
And I see that,
and I can't argue with that.
1517
01:34:46,055 --> 01:34:49,392
I might need to rethink the way
that I've been doing things
1518
01:34:49,475 --> 01:34:50,810
for the past few years.
1519
01:35:05,032 --> 01:35:08,661
[Cadwalladr] This is a story
which we haven't published yet
1520
01:35:08,744 --> 01:35:11,288
talking about all the investigations
1521
01:35:11,372 --> 01:35:14,333
which have been kicked off
in Britain and the US
1522
01:35:14,417 --> 01:35:16,168
since the story came out.
1523
01:35:16,252 --> 01:35:19,630
So, there's an investigation by the FBI,
1524
01:35:19,714 --> 01:35:22,675
by the US, the SEC,
1525
01:35:22,758 --> 01:35:24,260
by the Department of Justice,
1526
01:35:24,343 --> 01:35:25,928
by Robert Mueller,
1527
01:35:26,011 --> 01:35:28,556
and by the Senate Intelligence Committee,
1528
01:35:28,639 --> 01:35:31,016
the Judiciary Committee,
the House Intelligence Committee.
1529
01:35:31,100 --> 01:35:33,060
And then these are all the ones
which are going on
1530
01:35:33,102 --> 01:35:34,770
which are connected in Britain.
1531
01:35:38,274 --> 01:35:41,277
Parliament spent 18 months investigating.
1532
01:35:42,403 --> 01:35:44,572
They called in all these witnesses.
1533
01:35:48,284 --> 01:35:52,037
And at the end of it,
their report says very clearly,
1534
01:35:52,121 --> 01:35:54,623
"Our electoral laws are not fit
for purpose."
1535
01:35:56,417 --> 01:36:00,421
We literally cannot have
a free and fair election in this country.
1536
01:36:01,881 --> 01:36:04,759
And we can't have it because of Facebook,
1537
01:36:04,925 --> 01:36:08,846
because of the tech giants
who are still completely unaccountable.
1538
01:36:13,058 --> 01:36:15,478
It sounds, like, quite apocalyptic.
1539
01:36:15,644 --> 01:36:19,815
But it does feel like we are entering
into a whole new era.
1540
01:36:20,858 --> 01:36:24,945
We can see that authoritarian governments
are on the rise.
1541
01:36:25,362 --> 01:36:31,243
And they're all using these politics
of hate and fear on Facebook.
1542
01:36:33,370 --> 01:36:34,765
- Look at Brazil.
- [crowd cheering]
1543
01:36:34,789 --> 01:36:38,501
[Cadwalladr]
There's this right-wing extremist
1544
01:36:38,584 --> 01:36:39,919
who's been elected.
1545
01:36:40,002 --> 01:36:44,048
And we know that WhatsApp,
which is a part of Facebook,
1546
01:36:44,131 --> 01:36:49,929
was really clearly implicated
in the dissemination of fake news there.
1547
01:36:51,263 --> 01:36:53,474
And look at what happened in Myanmar.
1548
01:36:54,350 --> 01:36:56,727
There is evidence that Facebook was used
1549
01:36:56,811 --> 01:36:58,604
to incite racial hatred
1550
01:36:58,687 --> 01:37:00,731
which caused a genocide.
1551
01:37:07,488 --> 01:37:13,327
We also know that the Russian government
was using Facebook's tools in the US.
1552
01:37:17,081 --> 01:37:24,046
There's evidence that Russian intelligence
created fake Black Lives Matter memes.
1553
01:37:24,755 --> 01:37:28,509
And when people clicked on them,
they were taken to pages
1554
01:37:28,592 --> 01:37:32,388
where they were actually invited
to protests
1555
01:37:32,471 --> 01:37:35,724
that were organized
by the Russian government.
1556
01:37:35,808 --> 01:37:37,911
- [crowd chants] Justice! Now!
- [man] When do we want it?
1557
01:37:37,935 --> 01:37:40,080
[Cadwalladr] At the same time,
they were setting up pages
1558
01:37:40,104 --> 01:37:44,191
targeting adversary groups,
like Blue Lives Matter.
1559
01:37:45,818 --> 01:37:48,696
It's about stoking fear and hate
1560
01:37:48,779 --> 01:37:51,657
to turn the country against itself.
1561
01:37:52,700 --> 01:37:54,493
Divide and conquer.
1562
01:37:54,910 --> 01:37:57,246
[overlapping shouts]
1563
01:37:57,329 --> 01:37:58,998
White power!
1564
01:37:59,456 --> 01:38:01,333
Fascist and proud!
1565
01:38:01,417 --> 01:38:04,378
[overlapping protests]
1566
01:38:04,461 --> 01:38:07,965
[chanting]
Fuck Donald Trump! Fuck Donald Trump!
1567
01:38:08,883 --> 01:38:12,136
[Cadwalladr] These platforms
which were created to connect us
1568
01:38:12,553 --> 01:38:14,847
have now been weaponized.
1569
01:38:16,765 --> 01:38:20,227
And it's impossible to know what is what
1570
01:38:20,311 --> 01:38:24,315
because it's happening
on exactly the same platforms
1571
01:38:24,398 --> 01:38:27,985
that we chat to our friends
or share baby photos.
1572
01:38:30,404 --> 01:38:32,489
Nothing is what it seems.
1573
01:38:45,127 --> 01:38:47,567
- [Kaiser] Hi, how are you?
- [man] Doing wonderful, yourself?
1574
01:38:47,671 --> 01:38:48,923
I'm all right.
1575
01:38:49,006 --> 01:38:55,012
Um, I stayed here last week
and I checked in a suitcase and two bags.
1576
01:38:55,095 --> 01:38:58,474
And I had to go to the airport and just,
like, left.
1577
01:38:58,557 --> 01:39:00,434
So my bags have been here for a week.
1578
01:39:06,941 --> 01:39:08,984
[reporter] My guest, Carole Cadwalladr,
1579
01:39:09,068 --> 01:39:12,363
writes for the British newspapers
The Observer and The Guardian.
1580
01:39:12,863 --> 01:39:15,282
Can you just say a little bit more
about the Facebook data?
1581
01:39:15,824 --> 01:39:20,871
[Cadwalladr] This thing of the data,
so how Americans were targeted,
1582
01:39:20,955 --> 01:39:22,998
and what they were targeted with,
1583
01:39:23,290 --> 01:39:27,544
is a sort of key part
of Mueller's investigation.
1584
01:39:30,839 --> 01:39:34,718
[Kaiser] I am headed to Washington, DC,
1585
01:39:34,969 --> 01:39:38,430
for my testimony
for the Mueller investigation.
1586
01:39:38,514 --> 01:39:40,516
[indistinct radio chatter]
1587
01:39:41,767 --> 01:39:45,270
[Kaiser] I definitely didn't think
that while we're sitting there
1588
01:39:45,354 --> 01:39:47,898
counting votes on our data screen
1589
01:39:47,982 --> 01:39:50,401
that some of those votes
1590
01:39:50,484 --> 01:39:56,281
were made by people
who had seen fake news stories
1591
01:39:56,365 --> 01:39:59,451
paid for by Russia on their Facebook page.
1592
01:40:01,120 --> 01:40:02,413
Maybe I wanted to believe
1593
01:40:02,496 --> 01:40:05,749
that Cambridge Analytica
was just the best.
1594
01:40:07,376 --> 01:40:09,586
It's a convenient story to believe.
1595
01:40:21,515 --> 01:40:23,517
[indistinct announcement over PA]
1596
01:40:25,060 --> 01:40:28,731
...service down to our nation's capital,
Washington Reagan DC airport.
1597
01:40:35,195 --> 01:40:37,656
[Kaiser] I don't think it's possible
to shed any of this.
1598
01:40:40,075 --> 01:40:42,911
You can't really
put something like this behind you.
1599
01:40:58,510 --> 01:41:01,805
"Youth engagement, persuasion...
1600
01:41:03,140 --> 01:41:04,516
apathy."
1601
01:41:04,600 --> 01:41:05,920
[Nix] Malaysia, we're working in.
1602
01:41:05,976 --> 01:41:10,105
[Kaiser] We did Lithuania, Romania,
Kenya, Ghana.
1603
01:41:10,689 --> 01:41:12,816
[Nix] Oh, and the Brexit campaign, yeah.
1604
01:41:12,900 --> 01:41:14,693
But we don't talk about that.
1605
01:41:14,777 --> 01:41:17,821
- [Kaiser] Oops, we won!
- [laughter on recording]
1606
01:41:18,655 --> 01:41:20,949
Listening to this now,
it just sounds like...
1607
01:41:21,784 --> 01:41:25,913
a criminal admitting to everything
he’s done wrong around the world.
1608
01:41:27,498 --> 01:41:28,540
You know?
1609
01:41:29,291 --> 01:41:32,002
I'm just there,
nervously laughing along with him,
1610
01:41:32,086 --> 01:41:33,170
letting it happen.
1611
01:41:34,630 --> 01:41:35,631
[chuckles]
1612
01:41:41,386 --> 01:41:46,058
As I said, it's the opposite of what
I've worked my whole life to do.
1613
01:41:47,601 --> 01:41:48,727
So...
1614
01:41:51,814 --> 01:41:55,192
it makes me angry at myself that
I could sit through a meeting like that...
1615
01:41:55,943 --> 01:41:58,153
and not quit directly afterwards,
1616
01:41:59,321 --> 01:42:00,572
basically.
1617
01:42:04,243 --> 01:42:05,619
What was I doing?
1618
01:42:06,411 --> 01:42:08,664
[reporter] What investigators
have you been talking to?
1619
01:42:09,623 --> 01:42:13,710
I'm currently working
to be as helpful as possible
1620
01:42:13,794 --> 01:42:17,422
to any government investigations
where I can provide assistance,
1621
01:42:17,506 --> 01:42:20,092
but I can't comment on that right now
while they're ongoing.
1622
01:42:28,725 --> 01:42:31,270
[woman over PA] At this time,
you may use your cellular service.
1623
01:42:31,353 --> 01:42:35,023
However, larger electronic devices
must remain stowed.
1624
01:42:35,232 --> 01:42:37,109
[Hilder] Brittany made mistakes.
1625
01:42:38,819 --> 01:42:41,155
But I think it was very brave of her
1626
01:42:41,238 --> 01:42:44,199
to come out and then to keep cooperating
1627
01:42:44,283 --> 01:42:45,826
and not to walk away.
1628
01:42:48,620 --> 01:42:51,665
She is one of two people
1629
01:42:51,748 --> 01:42:56,378
who has blown the whistle
in any serious way on Cambridge Analytica.
1630
01:43:00,465 --> 01:43:01,967
We're all responsible.
1631
01:43:04,928 --> 01:43:07,806
So the question is,
what do we do with that responsibility?
1632
01:43:08,348 --> 01:43:09,683
Can we embrace it?
1633
01:43:12,394 --> 01:43:14,521
[Kaiser] Happy that it's finally happening
1634
01:43:14,605 --> 01:43:18,275
so that I can just tell people
what happened and get everything...
1635
01:43:19,943 --> 01:43:20,944
on record
1636
01:43:22,154 --> 01:43:25,199
for this government, my government.
[chuckles]
1637
01:43:47,095 --> 01:43:49,181
[reporter] You remember, though,
Cambridge Analytica.
1638
01:43:49,431 --> 01:43:51,391
Its big claim in 2016
1639
01:43:51,475 --> 01:43:53,477
was that it had access to voter data
1640
01:43:53,685 --> 01:43:56,688
on all of the people voting
in the US election.
1641
01:43:58,273 --> 01:44:02,402
Well, just one of the 157 million people
who voted in that election,
1642
01:44:02,486 --> 01:44:06,365
a man called David Carroll,
asked them a very simple question:
1643
01:44:06,990 --> 01:44:09,826
"Can I see the data you have on me?"
1644
01:44:10,661 --> 01:44:12,621
And they refused to give it to him.
1645
01:44:14,248 --> 01:44:18,335
But crucially, today,
Cambridge Analytica pled guilty
1646
01:44:18,418 --> 01:44:22,422
at Hendon Magistrates' Court
for failing to comply with the ICO notice.
1647
01:44:40,482 --> 01:44:43,277
[Carroll] The Cambridge Analytica case
is behind me now.
1648
01:44:43,860 --> 01:44:46,738
They pleaded guilty
for not giving me my data,
1649
01:44:47,739 --> 01:44:50,242
and I'll probably never get it back.
1650
01:44:53,120 --> 01:44:55,330
By the time my daughter is 18,
1651
01:44:55,414 --> 01:44:58,750
she'll have 70,000 data points
defining her,
1652
01:44:58,917 --> 01:45:01,295
and currently she has no rights,
1653
01:45:01,628 --> 01:45:03,839
no control over that at all.
1654
01:45:06,216 --> 01:45:07,551
But the battle continues.
1655
01:45:08,176 --> 01:45:10,887
[applause]
1656
01:45:13,432 --> 01:45:15,100
I don't have to tell you
1657
01:45:15,183 --> 01:45:17,102
that there is this dark undertow
1658
01:45:17,185 --> 01:45:19,563
which is connecting us all globally.
1659
01:45:19,646 --> 01:45:23,567
And it is flowing
via the technology platforms.
1660
01:45:24,026 --> 01:45:26,236
And that is why I am here
1661
01:45:26,320 --> 01:45:31,450
to address you directly,
the Gods of Silicon Valley.
1662
01:45:31,533 --> 01:45:33,535
[audience cheers and applauds]
1663
01:45:35,245 --> 01:45:36,997
Mark Zuckerberg,
1664
01:45:38,206 --> 01:45:40,000
and Sheryl Sandberg,
1665
01:45:40,083 --> 01:45:43,170
and Larry Page, and Sergey Brin,
1666
01:45:43,253 --> 01:45:44,671
and Jack Dorsey.
1667
01:45:46,381 --> 01:45:49,301
Because you set out to connect people
1668
01:45:49,801 --> 01:45:51,803
and you are refusing to acknowledge
1669
01:45:51,887 --> 01:45:55,682
that this same technology
is now driving us apart.
1670
01:45:56,767 --> 01:45:59,478
And what you don't seem to understand
1671
01:45:59,561 --> 01:46:03,357
is that this is bigger than you,
and it's bigger than any of us.
1672
01:46:03,440 --> 01:46:08,779
And it is not about left or right,
or leave or remain, or Trump or not.
1673
01:46:09,363 --> 01:46:11,281
It's about whether it's actually possible
1674
01:46:11,365 --> 01:46:13,742
to have a free and fair election
ever again.
1675
01:46:14,368 --> 01:46:18,038
And so my question to you is:
Is this what you want?
1676
01:46:19,247 --> 01:46:22,209
Is this how you want history
to remember you?
1677
01:46:23,293 --> 01:46:26,922
As the handmaidens to authoritarianism?
1678
01:46:27,464 --> 01:46:31,510
And my question to everybody else is,
is this what we want?
1679
01:46:31,968 --> 01:46:36,181
To sit back and play with our phones
as this darkness falls?
1680
01:46:41,770 --> 01:46:44,272
Who is logged into Facebook right now?
1681
01:46:46,274 --> 01:46:47,359
Almost everybody.
1682
01:46:49,069 --> 01:46:50,779
So, as individuals,
1683
01:46:50,862 --> 01:46:55,534
we can limit the flood of data
that we're leaking all over the place.
1684
01:46:55,617 --> 01:46:59,496
But there's no silver bullet.
There's no way to go off the grid.
1685
01:46:59,579 --> 01:47:02,207
So, you have to understand
1686
01:47:02,874 --> 01:47:05,877
how your data is affecting your life.
1687
01:47:07,087 --> 01:47:10,841
Our dignity as humans is at stake.
1688
01:47:11,091 --> 01:47:13,844
[overlapping shouts of protest]
1689
01:47:20,434 --> 01:47:22,314
[Carroll]
But the hardest part in all of this...
1690
01:47:22,394 --> 01:47:25,355
[Trump] Got a lot of rough people
in those caravans. They are not a...
1691
01:47:25,439 --> 01:47:27,899
[Carroll]
...is that these wreckage sites...
1692
01:47:27,983 --> 01:47:31,069
- [people screaming]
- ...and crippling divisions...
1693
01:47:33,989 --> 01:47:37,742
begin with the manipulation
of one individual.
1694
01:47:39,369 --> 01:47:40,537
Then another.
1695
01:47:42,164 --> 01:47:43,248
And another.
1696
01:47:47,794 --> 01:47:50,213
So, I can't help but ask myself:
1697
01:47:52,132 --> 01:47:53,758
Can I be manipulated?
1698
01:47:57,387 --> 01:47:58,388
Can you?