The Great Hack (2019)

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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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You referred to having two sets
of business cards.

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Who did you work for?

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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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Hi. A small coffee, please?

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- Uh, $2.25.
- Great.

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All right.

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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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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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This is a Brooklyn-bound Q express train.

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The next stop is Canal Street.

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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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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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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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Go back to Washington.

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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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We saw the fallout
of our filtered realities

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in the 2016 election.

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...you were not offended
when Donald Trump said it!

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Get the fuck out!

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The real world became
a deeply divided wreckage site.

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Fuck those dirty beaners! Build the wall!

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Whoo!

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Fight!

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How did the dream
of the connected world tear us apart?

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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?"

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That's, like, the new way
I'm gonna be an annoying parent.

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Hey.

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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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...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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- This was the data center.
- Right.

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"We gotta target this state.
We gotta target that state."

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- So, within that...
- 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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- Paul-Olivier?
- I'm there.

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Okay. Let me just, uh, set up my screen.

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I connected with a mathematician
based out of Switzerland

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named Paul-Olivier Dehaye.

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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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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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That's the hardest part. Um...

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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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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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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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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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God bless the great state of Iowa.

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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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Let me first of all say...

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to God be the glory.

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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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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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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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Our movement is about replacing

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a failed
and corrupt political establishment.

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Why aren't I 50 points ahead,
you might ask?

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Do you really need to ask?

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A night that will go down in history,

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a stunning upset as Donald Trump
triumphs over Hillary Clinton,

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defying the polls, the pundits,
and the political class once again,

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this time elected president
of the United States.

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USA! USA!

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Thank you.

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Thank you very much, everybody.

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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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After the election,
it was really exciting.

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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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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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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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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.

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It was just after the Inauguration.

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So, Andy, he was just like sort of, like,
showing me all the photos on his phone.

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"This is the inauguration."

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Then, "Oh, it's such a laugh!

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We had such a good time. Oh, Donald..."

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And I was like, "How did the introduction
to Cambridge Analytica come out?"

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He was like, "You know, it's 'cause Nigel.
Nigel's friends with Steve Bannon."

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Ladies and gentlemen, Steve Bannon!

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Steve Bannon headed
the campaign for Trump.

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He's also the Vice President
of Cambridge Analytica.

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So he's like, "Yeah, there's this bunch
of billionaires in the States.

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We've all got the same aims,

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and Brexit was the petri dish for Trump."

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For most of my life,
America is the leader.

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Now, I would like to think,
in my own little way,

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that what we did with Brexit

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was the beginning
of what is gonna turn out to be

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a global revolution

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and that Trump's victory
is a part of that.

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Anyway, and then he told me
all sorts of other stuff

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about, you know, how they used
artificial intelligence,

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you know,
how they were mining details from Facebook

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and, um...

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And he was like... And he was like,
"It's creepy, Carole!" He said,

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"The amount of information
you can get on people...

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People just give it to you!"

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And he sort of said,
"It's just so creepy!"

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So, I just kind of kept going.

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The Brexit work.

250
00:19:32,462 --> 00:19:37,134
I'd started tracking down all these
Cambridge Analytica ex-employees.

251
00:19:40,470 --> 00:19:44,892
And, eventually, I got one guy
who was prepared to talk to me.

252
00:19:46,476 --> 00:19:47,519
Chris Wylie.

253
00:19:51,190 --> 00:19:54,735
We had this first telephone call,
which was insane.

254
00:19:54,818 --> 00:19:57,654
It was about eight hours long. And...

255
00:20:05,704 --> 00:20:08,373
My name is Christopher Wylie,
I'm a data scientist

256
00:20:08,457 --> 00:20:10,500
and I helped set up Cambridge Analytica.

257
00:20:12,044 --> 00:20:15,297
It's incorrect to call Cambridge Analytica

258
00:20:15,380 --> 00:20:19,551
a purely sort of data science company
or an algorithm, you know, company.

259
00:20:19,676 --> 00:20:22,930
You know, it is a full-service
propaganda machine.

260
00:20:26,516 --> 00:20:29,561
You were an investor
in Cambridge Analytica.

261
00:20:29,645 --> 00:20:32,624
- I helped put the company together.
- And... Yes, you did. And...

262
00:20:32,648 --> 00:20:34,733
And gave it...
And gave it that amazing name.

263
00:20:35,192 --> 00:20:38,111
Steve Bannon was the editor of Breitbart.

264
00:20:39,613 --> 00:20:42,366
He follows this idea
of the Breitbart doctrine,

265
00:20:42,449 --> 00:20:46,370
which is that, if you want
to fundamentally change society,

266
00:20:46,495 --> 00:20:48,121
you first have to break it.

267
00:20:48,455 --> 00:20:49,915
And it's only when you break it

268
00:20:49,998 --> 00:20:54,711
is when you can remold the pieces
into your vision of a new society.

269
00:20:58,257 --> 00:20:59,925
This was the weapon

270
00:21:00,008 --> 00:21:03,178
that Steve Bannon wanted to build
to fight his culture war.

271
00:21:04,179 --> 00:21:05,847
And we could build them for him.

272
00:21:06,431 --> 00:21:09,393
But I needed to figure out a way
of getting data,

273
00:21:09,476 --> 00:21:12,938
and so I went
to these Cambridge University profs

274
00:21:13,021 --> 00:21:14,606
and asked, "What do you think?"

275
00:21:28,328 --> 00:21:33,750
Kogan offered us apps on Facebook
that were given special permission

276
00:21:33,959 --> 00:21:39,756
to harvest data not from just the person
who used the app or joined the app,

277
00:21:41,049 --> 00:21:45,053
but also it would then go
into their entire friend network

278
00:21:45,637 --> 00:21:48,724
and pull out
all of the friends' data as well.

279
00:21:50,475 --> 00:21:53,061
If you were a friend of somebody
who used the app,

280
00:21:53,145 --> 00:21:56,148
you would have no idea
that I just pulled all of your data.

281
00:22:00,777 --> 00:22:03,780
We took things like status updates, likes,

282
00:22:03,864 --> 00:22:06,116
in some cases, private messages.

283
00:22:08,660 --> 00:22:10,954
We wouldn't just be targeting you
as a voter,

284
00:22:11,038 --> 00:22:14,333
we'd be targeting you as a personality.

285
00:22:16,460 --> 00:22:20,672
We would only need to touch
a couple hundred thousand people

286
00:22:20,756 --> 00:22:23,342
to build a psychological profile

287
00:22:23,425 --> 00:22:28,013
of each voter in all of the United States.

288
00:22:31,975 --> 00:22:33,244
And people had no idea

289
00:22:33,268 --> 00:22:35,354
that their data was being taken
in this way?

290
00:22:36,313 --> 00:22:37,314
No.

291
00:22:42,486 --> 00:22:44,363
You didn't ever stop and think,

292
00:22:44,446 --> 00:22:47,866
"Actually, this is people's
personal information,

293
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"?

294
00:22:53,288 --> 00:22:54,288
No.

295
00:22:56,375 --> 00:23:00,670
Throughout history, you have examples
of grossly unethical experiments.

296
00:23:01,129 --> 00:23:02,631
Is that what this was?

297
00:23:03,382 --> 00:23:07,636
I think that, yes,
it was a grossly unethical experiment.

298
00:23:08,970 --> 00:23:12,182
You are playing with the psychology
of an entire country

299
00:23:12,265 --> 00:23:14,434
without their consent or awareness.

300
00:23:15,769 --> 00:23:17,729
And not only are you, like,

301
00:23:17,813 --> 00:23:20,190
playing with the psychology
of an entire nation,

302
00:23:20,273 --> 00:23:22,377
you're playing with the psychology
of an entire nation

303
00:23:22,401 --> 00:23:24,111
in the context of the democratic process.

304
00:23:31,034 --> 00:23:33,578
The revelations have started to spill out.

305
00:23:34,663 --> 00:23:40,460
We're now not just threatening
to do things, but we're actually doing it.

306
00:23:42,671 --> 00:23:45,590
- Okay, we're ready, guys.
- One, two, three...

307
00:23:45,966 --> 00:23:48,093
We turn now to the burgeoning scandal

308
00:23:48,176 --> 00:23:51,054
around voter-profiling company
Cambridge Analytica.

309
00:23:51,388 --> 00:23:54,724
David Carroll filed a legal challenge
in Britain

310
00:23:54,808 --> 00:23:57,352
asking the court
to force Cambridge Analytica

311
00:23:57,436 --> 00:24:00,564
to turn over all the data it harvested
on him.

312
00:24:00,814 --> 00:24:02,816
Explain what you are demanding.

313
00:24:03,275 --> 00:24:05,402
Uh, full disclosure, so...

314
00:24:06,945 --> 00:24:08,780
where did they get our data,

315
00:24:08,864 --> 00:24:12,284
how did they process it,
who did they share it with,

316
00:24:12,576 --> 00:24:14,828
and do we have a right to opt out?

317
00:24:17,080 --> 00:24:18,331
Cambridge Analytica says

318
00:24:18,415 --> 00:24:19,541
it's got 5,000 data points

319
00:24:19,624 --> 00:24:21,668
on many, many millions
of people out there.

320
00:24:21,751 --> 00:24:22,836
That's right.

321
00:24:22,919 --> 00:24:26,298
When people can actually see
the extent of the surveillance,

322
00:24:26,381 --> 00:24:28,633
I think they're going to be shocked.

323
00:24:30,218 --> 00:24:33,430
We don't work with Facebook data.
We don't have Facebook data.

324
00:24:33,513 --> 00:24:36,766
Uh, we do use Facebook
as a platform, uh, to advertise.

325
00:24:37,184 --> 00:24:38,351
Mr. Nix, Channel 4 News.

326
00:24:38,560 --> 00:24:40,687
Did you mislead Parliament
over the Facebook issue?

327
00:24:40,770 --> 00:24:43,315
Absolutely not.

328
00:24:44,149 --> 00:24:47,736
It's crazy that I have to mount
a year-long,

329
00:24:47,819 --> 00:24:51,865
super risky legal challenge
in another country

330
00:24:51,990 --> 00:24:54,159
to get my voter profile.

331
00:24:54,326 --> 00:24:57,537
David, don't stop, don't relent.

332
00:24:58,955 --> 00:25:00,957
- Keep going. Good.
- I'm gonna do it, don't worry.

333
00:25:01,041 --> 00:25:02,876
Don't sleep!

334
00:25:05,670 --> 00:25:08,423
Facebook's down 6.35%.

335
00:25:08,715 --> 00:25:10,717
That's 120 billion dollars.

336
00:25:11,092 --> 00:25:12,219
This is huge.

337
00:25:14,387 --> 00:25:17,265
Officers working
for the UK Information Commissioner

338
00:25:17,349 --> 00:25:20,727
are searching the headquarters
of Cambridge Analytica, in London.

339
00:25:20,810 --> 00:25:22,872
They're inside,
they're looking at computers,

340
00:25:22,896 --> 00:25:24,523
they're looking for documents.

341
00:25:25,524 --> 00:25:29,486
Facebook knew about
that data collection over two years ago

342
00:25:29,569 --> 00:25:32,572
but did not go public
until three days ago.

343
00:25:33,365 --> 00:25:34,407
Really, Facebook?

344
00:25:34,491 --> 00:25:36,326
You forgot to mention
that 50 million people

345
00:25:36,409 --> 00:25:37,595
had their private data breached,

346
00:25:37,619 --> 00:25:40,455
but every time it's my uncle's friend's
sister's dog's birthday,

347
00:25:40,539 --> 00:25:41,873
I get a notification?

348
00:25:48,129 --> 00:25:50,298
You are taking on a giant,

349
00:25:50,382 --> 00:25:52,425
a Goliath of big data marketing.

350
00:25:53,343 --> 00:25:55,262
How hopeful are you of succeeding?

351
00:26:02,018 --> 00:26:04,688
People don't want to admit
that propaganda works.

352
00:26:05,480 --> 00:26:09,859
Because to admit it means confronting
our own susceptibilities,

353
00:26:10,193 --> 00:26:12,320
horrific lack of privacy,

354
00:26:12,612 --> 00:26:14,281
and hopeless dependency

355
00:26:14,364 --> 00:26:17,742
on tech platforms ruining our democracies

356
00:26:17,826 --> 00:26:19,619
on various attack surfaces.

357
00:26:20,370 --> 00:26:23,248
Join the struggle
to help get our data back.

358
00:26:37,345 --> 00:26:41,891
Welcome to our inquiry
into disinformation and fake news.

359
00:26:41,975 --> 00:26:45,520
I'd like to welcome Christopher Wylie
and Paul-Olivier Dehaye,

360
00:26:45,604 --> 00:26:48,231
uh, to the committee
to give evidence this morning.

361
00:26:49,190 --> 00:26:51,276
Have you or anybody else made
any assessment

362
00:26:51,359 --> 00:26:53,296
of actually whether any of this
made much difference

363
00:26:53,320 --> 00:26:56,364
to the final outcome of the EU Referendum?

364
00:26:59,618 --> 00:27:03,580
When... When you're caught
in the Olympics doping, right,

365
00:27:03,788 --> 00:27:08,668
there's not a debate about how much
illegal drug you took. Right?

366
00:27:08,752 --> 00:27:10,045
Or, "Well,

367
00:27:10,128 --> 00:27:11,808
he probably would've come in first
anyway,"

368
00:27:11,880 --> 00:27:14,758
or, you know,
"He only took half of the amount," or...

369
00:27:14,841 --> 00:27:17,719
Doesn't matter. If you're caught cheating,
you lose your medal. Right?

370
00:27:17,802 --> 00:27:18,928
Because...

371
00:27:19,304 --> 00:27:23,308
...if we allow cheating
in our democratic process,

372
00:27:23,683 --> 00:27:24,600
what about next time?

373
00:27:24,601 --> 00:27:28,146
What about the time after that?
Right? You shouldn't win by cheating.

374
00:27:29,648 --> 00:27:33,026
A lot of people will say,
and I'll say, um,

375
00:27:33,735 --> 00:27:36,464
that given that you're someone
who worked very closely with these people,

376
00:27:36,488 --> 00:27:37,656
uh, for a period of time,

377
00:27:37,739 --> 00:27:40,325
why have you decided to speak out
against it

378
00:27:40,408 --> 00:27:42,928
and give evidence against people
who used to be your colleagues?

379
00:27:43,286 --> 00:27:46,623
It's a process of coming to terms
with what you've created

380
00:27:46,706 --> 00:27:49,751
and the impact
that that... that... that has had.

381
00:27:49,834 --> 00:27:53,963
Um, I am incredibly remorseful
for my... my role in setting it up.

382
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...

383
00:27:59,427 --> 00:28:02,347
uh, you know, the face of it,
because I'm the one that's...

384
00:28:02,514 --> 00:28:04,557
come forward and put my name to it.

385
00:28:04,683 --> 00:28:06,363
But someone else
that you should be calling

386
00:28:06,434 --> 00:28:07,894
to the committee is Brittany Kaiser.

387
00:28:08,478 --> 00:28:09,813
Who's Brittany Kaiser?

388
00:28:27,789 --> 00:28:32,085
I'm not that interested in standing up
for powerful white men anymore

389
00:28:32,168 --> 00:28:35,505
who obviously don't have
everybody's best interests at heart.

390
00:28:39,384 --> 00:28:41,469
Brittany Kaiser,
once a key player

391
00:28:41,553 --> 00:28:43,513
inside Cambridge Analytica,

392
00:28:43,596 --> 00:28:45,765
casting herself as a whistle-blower.

393
00:28:46,433 --> 00:28:49,269
Until three weeks ago,
Brittany Kaiser, a top exec there,

394
00:28:49,352 --> 00:28:52,981
she had a key to Steve Bannon's townhouse
in Washington.

395
00:28:53,064 --> 00:28:56,151
She spoke at CPAC in 2016,
along with Kellyanne Conway,

396
00:28:56,234 --> 00:28:58,653
spent election night
at the Trump victory party

397
00:28:58,737 --> 00:29:01,364
with mega-donor Rebekah Mercer.

398
00:29:02,532 --> 00:29:04,743
Miss Kaiser was also closely involved

399
00:29:04,826 --> 00:29:07,537
with millionaire Brexit supporter
Arron Banks

400
00:29:07,620 --> 00:29:09,706
and his Leave. EU campaign.

401
00:29:18,173 --> 00:29:20,067
She's raising some interesting things.

402
00:29:20,091 --> 00:29:21,444
Why is she talking now, do you think?

403
00:29:21,468 --> 00:29:23,470
Well, she only gave us
part of the picture.

404
00:29:23,553 --> 00:29:27,056
She's talking to investigators,
and so we'll know the full picture

405
00:29:27,140 --> 00:29:28,475
at some point later...

406
00:29:51,456 --> 00:29:53,666
I have evidence

407
00:29:53,750 --> 00:29:58,171
that the Brexit campaigns
and the Trump campaign

408
00:29:58,254 --> 00:30:00,423
could've been conducted illegally.

409
00:30:03,343 --> 00:30:07,514
And so, for my own safety,
I don't need geolocation of where this is.

410
00:30:07,680 --> 00:30:09,474
Just me sitting here...

411
00:30:11,434 --> 00:30:13,937
the person trying to overthrow
two administrations

412
00:30:14,020 --> 00:30:16,856
and all of the most powerful companies
in the world,

413
00:30:16,940 --> 00:30:18,858
all at once.

414
00:30:20,610 --> 00:30:25,240
With one disjointed
but hopefully-soon-seamless narrative.

415
00:30:27,784 --> 00:30:31,204
The wealthiest companies
are technology companies.

416
00:30:31,913 --> 00:30:34,999
Google, Facebook, Amazon, Tesla.

417
00:30:35,500 --> 00:30:37,710
And the reason why these companies

418
00:30:37,794 --> 00:30:40,547
are the most powerful companies
in the world

419
00:30:40,630 --> 00:30:45,343
is because, last year, data surpassed oil
in its value.

420
00:30:45,802 --> 00:30:48,388
Data is the most valuable asset on Earth.

421
00:30:49,430 --> 00:30:52,517
And these companies are valuable

422
00:30:52,600 --> 00:30:56,271
because they have been exploiting
people's assets.

423
00:30:57,939 --> 00:31:00,817
It wasn't until one of my friends
reached out to me

424
00:31:00,900 --> 00:31:03,945
to ask was I going to be all right

425
00:31:04,028 --> 00:31:07,740
with the way that my story would be seen
in history.

426
00:31:08,867 --> 00:31:11,452
And I thought, "No.

427
00:31:12,537 --> 00:31:14,414
I'm not okay, actually."

428
00:31:14,497 --> 00:31:18,042
And there's probably a lot of information
that I could give

429
00:31:18,126 --> 00:31:22,171
that would be helpful
to making things okay, possibly.

430
00:31:42,859 --> 00:31:44,611
I'm a political technologist

431
00:31:44,694 --> 00:31:47,989
who tries to shine a big light

432
00:31:48,072 --> 00:31:50,408
on how data's been used and abused.

433
00:31:52,535 --> 00:31:55,038
It's a moment where people have
that visceral sense.

434
00:31:55,121 --> 00:31:56,748
There is, you know,

435
00:31:57,332 --> 00:31:59,918
that there's something wrong here,
uh, that we need to fix.

436
00:32:00,919 --> 00:32:05,506
And so, I've dropped
pretty much everything I was doing

437
00:32:05,590 --> 00:32:07,967
to work on this with Brittany Kaiser.

438
00:32:10,345 --> 00:32:13,306
I went and found her and met her,

439
00:32:13,389 --> 00:32:15,642
and she was very forthcoming

440
00:32:16,267 --> 00:32:20,063
in a way which made me think,
"There's a lot here."

441
00:32:26,861 --> 00:32:30,657
What we really need to be understanding
is people's levers of persuasion.

442
00:32:30,740 --> 00:32:34,118
How are we actually going to message
voters so that they can under...

443
00:32:34,202 --> 00:32:37,497
Tina and I met with Brittany Kaiser.

444
00:32:37,580 --> 00:32:40,249
We look very unlike
any other political

445
00:32:40,333 --> 00:32:42,001
and communications firm, so...

446
00:32:42,085 --> 00:32:44,045
Do you work both sides of the aisle?

447
00:32:44,128 --> 00:32:46,523
Uh, no, we only work for the Republicans
in the United States.

448
00:32:46,547 --> 00:32:47,547
Okay.

449
00:32:48,341 --> 00:32:49,676
And in Britain?

450
00:32:49,842 --> 00:32:53,304
Well, actually, right now
we're working on the Brexit campaign.

451
00:32:54,555 --> 00:32:57,767
At Leave. EU, we're going
to be running a large-scale research

452
00:32:57,850 --> 00:33:00,103
throughout the nation to really understand

453
00:33:00,186 --> 00:33:03,481
why people are interested in staying in
or out of the EU.

454
00:33:03,564 --> 00:33:07,652
And the answers to that will help inform
our policy and our communications,

455
00:33:07,735 --> 00:33:10,321
to make sure that we turn out
more first-time voters,

456
00:33:10,405 --> 00:33:14,200
more unregistered voters,
more apathetic voters than ever before.

457
00:33:31,009 --> 00:33:33,928
I think we now have
the foundations laid for...

458
00:33:34,554 --> 00:33:38,057
her to share what is
some reasonably explosive materials

459
00:33:38,224 --> 00:33:39,642
that we've been finding.

460
00:33:40,226 --> 00:33:46,024
Uh, and, uh...
her inbox and her hard drive,

461
00:33:46,733 --> 00:33:50,945
uh, really are a treasure trove
of... uh, sketchy information.

462
00:33:53,906 --> 00:33:56,075
And we're still
just scratching the surface.

463
00:34:21,768 --> 00:34:24,520
Tell us about the first meeting
you had in Trump Tower.

464
00:34:24,812 --> 00:34:27,065
In November 2015,

465
00:34:27,148 --> 00:34:32,153
I went with Alexander Nix
to go see Corey Lewandowski,

466
00:34:32,236 --> 00:34:34,238
who was the campaign manager at the time.

467
00:34:34,489 --> 00:34:38,951
And I asked Corey, why could this place
possibly look so familiar?

468
00:34:39,118 --> 00:34:42,413
And he said,
"This is the set of The Apprentice.

469
00:34:42,789 --> 00:34:45,041
That's probably why you recognize it."
And...

470
00:34:45,541 --> 00:34:47,376
I was kind of shocked, you know?

471
00:34:48,127 --> 00:34:52,048
The Trump campaign HQ is a reality TV set.

472
00:34:52,131 --> 00:34:53,883
Yes. It is.

473
00:34:57,762 --> 00:35:00,765
And the idea of a company...

474
00:35:01,099 --> 00:35:04,143
conducting large-scale analysis
of a population...

475
00:35:04,227 --> 00:35:05,227
Mm-hmm.

476
00:35:05,269 --> 00:35:08,564
...and then identifying the triggers
that people have

477
00:35:08,648 --> 00:35:12,068
in terms of what's gonna move them
from one state to another state,

478
00:35:12,151 --> 00:35:15,113
that feels very challenging

479
00:35:15,196 --> 00:35:18,324
to the individual's sense of autonomy
and freedom...

480
00:35:18,407 --> 00:35:19,492
- Mm-hmm.
- ...uh...

481
00:35:19,575 --> 00:35:22,203
and to the idea of democracy.

482
00:35:22,662 --> 00:35:23,704
Doesn't it?

483
00:35:24,455 --> 00:35:28,000
I don't know. Um...
I would challenge that.

484
00:35:28,668 --> 00:35:31,420
What this strategy is mostly meant to do

485
00:35:31,504 --> 00:35:34,590
is to identify people
who are still considering

486
00:35:34,674 --> 00:35:36,384
- many different options...
- Yes.

487
00:35:36,467 --> 00:35:41,264
...and educate them
on some of the options that are out there,

488
00:35:41,347 --> 00:35:42,765
and if they're on the fence,

489
00:35:42,849 --> 00:35:45,893
then they can be persuaded
to go one way or the other.

490
00:35:45,977 --> 00:35:48,855
- Yes, they can.
- Uh, again, that is their own choice.

491
00:35:48,938 --> 00:35:50,398
- But a lot of the times...
- Is it?

492
00:35:50,481 --> 00:35:53,201
- ...these are individuals that...
- Is it their own choice?

493
00:35:54,569 --> 00:35:56,689
In the end, they're the ones
that go to the ballot box

494
00:35:56,737 --> 00:35:58,990
- and make their ch... decision.
- Yeah.

495
00:35:59,365 --> 00:36:02,368
I mean, I'm asking you these questions
as Brittany Kaiser.

496
00:36:02,451 --> 00:36:03,536
- I know.
- Right?

497
00:36:03,619 --> 00:36:07,248
I'm not asking you these questions
as Cambridge Analytica or SCL,

498
00:36:07,331 --> 00:36:10,334
because that's not
who you are anymore. Right?

499
00:36:10,626 --> 00:36:12,545
I get it. I get it. But...

500
00:36:12,628 --> 00:36:14,748
And do you think Cambridge Analytica

501
00:36:14,797 --> 00:36:17,925
was ever involved in the contravention
of people's human rights?

502
00:36:18,009 --> 00:36:19,010
No.

503
00:36:20,636 --> 00:36:25,766
But, again, I start to question
a lot of things the more I hear.

504
00:36:25,850 --> 00:36:26,800
Yeah.

505
00:36:26,809 --> 00:36:29,770
I mean,
I had spent my entire career before that

506
00:36:29,854 --> 00:36:31,939
working for human rights.

507
00:36:33,900 --> 00:36:34,900
Okay.

508
00:36:35,318 --> 00:36:37,111
Let's go back to that.

509
00:36:38,196 --> 00:36:41,407
It wasn't that long ago. Just a decade.

510
00:36:43,159 --> 00:36:45,077
- It wasn't that long ago.
- Yeah.

511
00:36:50,541 --> 00:36:54,170
I had worked in elections
since I was 14 or 15.

512
00:36:55,922 --> 00:36:59,842
I told my cousin I applied
to intern on the Obama campaign.

513
00:37:00,092 --> 00:37:01,302
She was like, "Oh, my God.

514
00:37:01,385 --> 00:37:03,721
You better get that internship,
or I'll die."

515
00:37:05,014 --> 00:37:07,767
I was part of the team
running Obama's Facebook.

516
00:37:09,310 --> 00:37:14,065
We invented the way social media is used
to communicate with voters.

517
00:37:19,820 --> 00:37:22,990
I then spent several years
working on human rights

518
00:37:23,074 --> 00:37:24,742
and international relations,

519
00:37:25,576 --> 00:37:27,328
first for Amnesty International,

520
00:37:27,411 --> 00:37:31,123
then lobbying at the United Nations
and European Parliament.

521
00:37:34,710 --> 00:37:38,214
And I used to always say
I love human rights campaigning,

522
00:37:38,923 --> 00:37:41,968
but sometimes I feel like
I'm banging my head against a brick wall

523
00:37:42,051 --> 00:37:44,387
because I can't see the results
of what I'm doing.

524
00:37:44,470 --> 00:37:46,889
I don't know
if I'm literally just wasting my time.

525
00:37:49,433 --> 00:37:52,144
And that's where I was
when I met Alexander Nix.

526
00:37:56,607 --> 00:37:59,487
Friends of ours thought
it would be a good joke to introduce us.

527
00:38:00,486 --> 00:38:04,240
He was very interested in learning more
about my experience with the Democrats.

528
00:38:04,573 --> 00:38:06,367
He gave me his card and said,

529
00:38:06,450 --> 00:38:09,161
"Let me get you drunk
and steal your secrets."

530
00:38:12,248 --> 00:38:16,294
And in December 2014,
he offered me a job.

531
00:38:21,215 --> 00:38:24,927
Coming across a company
where you could actually see your impact

532
00:38:25,011 --> 00:38:27,346
was really exciting for me.

533
00:38:33,894 --> 00:38:36,564
I got a little more conservative or posh

534
00:38:36,647 --> 00:38:41,110
in terms of the way that I dressed
and the way that I spoke,

535
00:38:41,944 --> 00:38:46,532
and doing things
like going on shooting at the weekends

536
00:38:46,615 --> 00:38:47,992
and stuff like that.

537
00:38:48,409 --> 00:38:52,538
It's just very different to what
I would normally spend my time doing.

538
00:38:59,962 --> 00:39:01,881
Must've been a hell of an adventure.

539
00:39:02,214 --> 00:39:05,343
It was really interesting.
I strapped on my cowboy boots,

540
00:39:05,426 --> 00:39:08,554
got into character,
got my NRA membership.

541
00:39:08,721 --> 00:39:11,140
- Yeah, you joined the NRA, right?
- I did, yeah.

542
00:39:11,223 --> 00:39:13,059
Just to understand
how these people think,

543
00:39:13,142 --> 00:39:14,142
- like...
- Uh-huh.

544
00:39:14,268 --> 00:39:15,686
I don't want to use guns.

545
00:39:15,770 --> 00:39:18,356
- I'm not really interested in guns at all.
- Yeah.

546
00:39:18,439 --> 00:39:20,316
I felt like I was getting to know...

547
00:39:21,233 --> 00:39:24,236
people that I used to disagree with a lot,

548
00:39:24,320 --> 00:39:27,281
like my grandparents, my aunts,
uncles, cousins.

549
00:39:28,532 --> 00:39:32,620
So this wasn't just an outfit
that you put on, and it felt important?

550
00:39:32,870 --> 00:39:35,498
It was important. It is important.

551
00:39:35,581 --> 00:39:37,833
- Yeah.
- I feel like the main problem

552
00:39:38,000 --> 00:39:39,210
in US politics

553
00:39:39,293 --> 00:39:43,130
is that people are so polarized
that they can't understand each other,

554
00:39:43,214 --> 00:39:46,092
and therefore they can't work together,
and therefore nothing gets done.

555
00:39:59,647 --> 00:40:03,651
I am about to draft some questions
for a senator

556
00:40:03,734 --> 00:40:07,029
who will be able to ask them
to Mark Zuckerberg

557
00:40:07,113 --> 00:40:10,950
in the Senate Judiciary hearing
on Tuesday.

558
00:40:11,283 --> 00:40:14,829
"How much of Facebook's revenue

559
00:40:15,996 --> 00:40:19,375
comes directly from the monetization

560
00:40:20,000 --> 00:40:23,045
of users' personal data?"

561
00:40:24,713 --> 00:40:26,590
All of it!

562
00:40:27,967 --> 00:40:29,552
Exactly.

563
00:40:30,386 --> 00:40:33,013
The reality is that Facebook knows more
about this

564
00:40:33,097 --> 00:40:34,974
than pretty much anyone in the world

565
00:40:35,057 --> 00:40:39,937
because Facebook is the best platform
on which to run experiments.

566
00:40:40,020 --> 00:40:41,939
Yeah, it is. Um, it...

567
00:40:42,022 --> 00:40:44,525
And it actually always gets you
the best engagement rates.

568
00:40:44,608 --> 00:40:46,735
We always spend the majority
amount of money

569
00:40:46,819 --> 00:40:49,613
on any commercial
or political campaign in Facebook.

570
00:40:50,156 --> 00:40:51,866
Always gets the majority of the ad budget.

571
00:40:51,949 --> 00:40:53,617
- It does, it does.
- Yep.

572
00:40:55,411 --> 00:40:58,956
There is at least the possibility
that the American public

573
00:40:59,039 --> 00:41:01,876
and publics in other countries
have been experimented on.

574
00:41:07,423 --> 00:41:09,484
Remember those Facebook quizzes
that we used

575
00:41:09,508 --> 00:41:12,678
to form personality models
for all voters in the US?

576
00:41:15,556 --> 00:41:19,351
The truth is, we didn't target
every American voter equally.

577
00:41:20,519 --> 00:41:22,396
The bulk of our resources

578
00:41:22,480 --> 00:41:26,108
went into targeting those
whose minds we thought we could change.

579
00:41:26,901 --> 00:41:29,028
We called them "the persuadables."

580
00:41:31,238 --> 00:41:32,907
They're everywhere in the country,

581
00:41:32,990 --> 00:41:36,619
but the persuadables that mattered
were the ones in swing states

582
00:41:36,702 --> 00:41:40,873
like Michigan, Wisconsin,
Pennsylvania, and Florida.

583
00:41:44,001 --> 00:41:47,922
Now, each of these states were broken down
by precinct.

584
00:41:49,215 --> 00:41:53,093
So, you can say
there are 22,000 persuadable voters

585
00:41:53,302 --> 00:41:54,845
in this precinct,

586
00:41:55,971 --> 00:41:59,725
and if we target enough persuadable people
in the right precincts,

587
00:41:59,850 --> 00:42:03,479
then those states would turn red
instead of blue.

588
00:42:04,980 --> 00:42:07,942
Our creative team designed
personalized content

589
00:42:08,025 --> 00:42:09,693
to trigger those individuals.

590
00:42:09,777 --> 00:42:12,029
Terrorists love porous borders.

591
00:42:12,112 --> 00:42:15,324
Widespread gaps
in border security allow terrorists...

592
00:42:15,407 --> 00:42:19,745
We bombarded them through blogs,
websites, articles, videos, ads,

593
00:42:19,828 --> 00:42:21,664
every platform you can imagine.

594
00:42:22,122 --> 00:42:24,959
Until they saw the world
the way we wanted them to.

595
00:42:29,296 --> 00:42:31,590
Until they voted
for our candidate.

596
00:42:33,384 --> 00:42:35,010
It's like a boomerang.

597
00:42:35,553 --> 00:42:37,137
You send your data out,

598
00:42:38,138 --> 00:42:39,807
it gets analyzed,

599
00:42:40,224 --> 00:42:43,727
and it comes back at you
as targeted messaging

600
00:42:44,311 --> 00:42:46,146
to change your behavior.

601
00:43:02,454 --> 00:43:05,374
DCMS Committee announced
the future witnesses

602
00:43:05,457 --> 00:43:07,209
- for a fake news inquiry.
- Yes.

603
00:43:07,668 --> 00:43:09,712
- There you are. You're...
- Me.

604
00:43:09,795 --> 00:43:13,090
- You're the day before Alexander.
- The former CEO.

605
00:43:13,966 --> 00:43:15,634
He's going the day after me.

606
00:43:16,844 --> 00:43:19,847
Yes. Is it... Is it all feeling a bit real?

607
00:43:19,930 --> 00:43:21,557
It's really intense.

608
00:43:22,266 --> 00:43:23,642
It's real.

609
00:43:23,976 --> 00:43:26,437
And it's big.

610
00:43:39,533 --> 00:43:42,578
The first time
I wrote about Cambridge Analytica,

611
00:43:43,037 --> 00:43:45,497
it was December 2016.

612
00:43:47,291 --> 00:43:49,501
I said that they'd worked
for the Trump campaign

613
00:43:49,585 --> 00:43:51,587
and for the Brexit campaign.

614
00:43:54,465 --> 00:43:56,305
And I started getting letters
from them saying,

615
00:43:56,383 --> 00:43:58,218
"We never worked for the Leave campaign."

616
00:44:02,097 --> 00:44:04,725
And this was baffling
because on Leave. EU's website,

617
00:44:04,808 --> 00:44:07,019
it said, "We hired Cambridge Analytica."

618
00:44:08,896 --> 00:44:11,482
There were statements from Alexander Nix
about how they worked

619
00:44:11,565 --> 00:44:12,650
for the Leave campaign.

620
00:44:13,484 --> 00:44:17,112
Yeah, I'm afraid we don't talk
about that campaign. At all.

621
00:44:19,448 --> 00:44:21,075
You didn't? Or you did?

622
00:44:21,158 --> 00:44:22,451
No, no, we don't discuss it.

623
00:44:22,534 --> 00:44:24,134
- Okay. Not at all.
- Yeah.

624
00:44:24,703 --> 00:44:27,831
And that was when I discovered this video

625
00:44:27,915 --> 00:44:30,125
of Leave. EU's press launch.

626
00:44:32,628 --> 00:44:35,798
And I was like, well, there, look,
it's Brittany Kaiser!

627
00:44:35,881 --> 00:44:38,425
She works for Cambridge Analytica.

628
00:44:38,509 --> 00:44:40,552
She's at the press launch

629
00:44:40,636 --> 00:44:43,389
talking about all the clever things

630
00:44:43,472 --> 00:44:46,350
that they're going to do with data
for the Leave Campaign.

631
00:44:48,102 --> 00:44:50,979
Like, what the fuck?

632
00:44:51,063 --> 00:44:54,817
How can you carry on denying it?
This is nuts!

633
00:44:58,779 --> 00:45:00,539
And it was exactly
the same time

634
00:45:00,614 --> 00:45:02,408
that Leave. EU started posting

635
00:45:02,491 --> 00:45:04,243
the horrible videos of me.

636
00:45:04,326 --> 00:45:05,929
I've gotta get out of here!

637
00:45:05,953 --> 00:45:08,747
There was a spoof video
of a scene from Airplane!

638
00:45:08,831 --> 00:45:11,434
- Get a hold of yourself!
- Please, let me handle this.

639
00:45:11,458 --> 00:45:14,604
There was like a whole stream
of people going, "Don't be so hysterical!"

640
00:45:14,628 --> 00:45:15,628
And, like, hitting her.

641
00:45:15,671 --> 00:45:17,589
Go back to your seat!
I'll take care of this.

642
00:45:17,673 --> 00:45:19,717
It was like, "Calm down! Calm down!"

643
00:45:19,800 --> 00:45:22,278
And, you know, so a whole line of people,

644
00:45:22,302 --> 00:45:24,638
and then the last person's carrying a gun.

645
00:45:26,390 --> 00:45:27,975
And the whole thing they had,

646
00:45:28,058 --> 00:45:30,936
it was set to the music
from the Russian national anthem.

647
00:45:35,065 --> 00:45:36,400
Ugh.

648
00:45:38,110 --> 00:45:41,488
The day
after that Leave. EU video was put out,

649
00:45:41,572 --> 00:45:45,701
the editor of another news organization
that I was going to do a report for

650
00:45:46,201 --> 00:45:47,536
took me for lunch and said,

651
00:45:47,619 --> 00:45:50,579
"Actually, we think it's too much
of a risk having you present the report."

652
00:45:53,792 --> 00:45:58,046
It is this sort of visceral thing
of living with this disinformation

653
00:45:58,130 --> 00:46:00,924
and this propaganda every single day.

654
00:46:01,216 --> 00:46:04,887
And feeling the effects of it
and knowing that it does work,

655
00:46:04,970 --> 00:46:07,973
it does have an impact in real life,
whether people believe that or not.

656
00:46:13,437 --> 00:46:15,439
You know,
I'm used to just writing stories.

657
00:46:15,522 --> 00:46:18,025
You write it, and then you go on
to the next subject.

658
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."

659
00:46:21,528 --> 00:46:24,168
And they're lying about something
which is actually really massive.

660
00:46:24,239 --> 00:46:26,533
'Cause it's, you know, the...

661
00:46:27,075 --> 00:46:29,953
rest of the future of our country.

662
00:46:30,662 --> 00:46:33,749
What do you think, Nigel?

663
00:46:35,584 --> 00:46:39,755
In the referendum,
most people had very fixed views.

664
00:46:40,672 --> 00:46:44,218
But there was a tiny sliver of people
who didn't.

665
00:46:44,301 --> 00:46:46,345
These were "the persuadables."

666
00:46:46,678 --> 00:46:50,057
It was all about finding
these very few people

667
00:46:50,140 --> 00:46:52,810
and then bombarding them with ads.

668
00:46:55,020 --> 00:46:58,649
This is the thing
which was invisible to all of us.

669
00:47:00,442 --> 00:47:06,448
Let June the 23rd go down in our history
as our independence day!

670
00:47:10,494 --> 00:47:13,705
The British people have spoken,
and the answer is, "We're out."

671
00:47:13,789 --> 00:47:15,082
For good or for ill,

672
00:47:15,165 --> 00:47:18,043
this decision will define our politics
for years to come.

673
00:47:18,126 --> 00:47:22,256
This great country
has made a terrible mistake.

674
00:47:22,339 --> 00:47:24,174
It's an earthquake that has happened.

675
00:47:24,258 --> 00:47:27,553
And what happens after earthquakes?
We wait to see.

676
00:47:27,886 --> 00:47:30,013
People weren't agreed
on what Leave meant.

677
00:47:30,097 --> 00:47:32,992
- It's simple: leave. Full stop.
- Was no manifesto for Leave.

678
00:47:33,016 --> 00:47:34,643
But there is no "leave, full stop..."

679
00:47:34,726 --> 00:47:37,604
Brexit! Brexit! Brexit!

680
00:47:40,315 --> 00:47:41,995
In the interest of safety,

681
00:47:42,067 --> 00:47:45,487
parents are advised not to carry children
on baggage trolleys

682
00:47:45,571 --> 00:47:47,573
or allow them to play on the escalators.

683
00:47:47,656 --> 00:47:49,575
- Hi, Mama!
- Hey!

684
00:47:50,784 --> 00:47:52,744
I'm through, I'm through,
I'm through, yeah.

685
00:47:52,828 --> 00:47:56,748
So, I managed to get
into the United Kingdom with no issues,

686
00:47:56,832 --> 00:47:59,251
which is really fantastic.

687
00:47:59,585 --> 00:48:02,379
Well, I just want you
to mentally be okay with this,

688
00:48:02,462 --> 00:48:06,091
'cause what you're doing
is a monumental undertaking.

689
00:48:06,174 --> 00:48:07,133
I know.

690
00:48:07,134 --> 00:48:08,719
And I still fear for your life.

691
00:48:08,802 --> 00:48:09,803
Yeah.

692
00:48:09,887 --> 00:48:12,097
With the powerful people
that are involved...

693
00:48:12,639 --> 00:48:13,807
Yeah, I know.

694
00:48:13,891 --> 00:48:15,976
You just have to be careful all the time.

695
00:48:16,059 --> 00:48:17,853
I know, but I can't keep quiet

696
00:48:17,936 --> 00:48:20,147
just because it'll make
powerful people mad.

697
00:48:20,230 --> 00:48:23,066
I know. I know, I know, I know. I know.

698
00:48:23,734 --> 00:48:26,111
I totally get that, you know.

699
00:48:26,862 --> 00:48:30,908
Somebody's always got to bring down
these jerks.

700
00:48:31,074 --> 00:48:32,200
Exactly.

701
00:48:32,284 --> 00:48:34,953
So, you know, anyway.

702
00:48:35,203 --> 00:48:37,039
When I have time off next month,

703
00:48:37,122 --> 00:48:40,667
I've gotta go and put deposits down
on electric and gas.

704
00:48:41,126 --> 00:48:44,379
I don't have $1,000 right now,
so I'll have to wait.

705
00:48:44,463 --> 00:48:47,382
Well, I could...
I could pay for it. That means...

706
00:48:47,466 --> 00:48:49,885
Oh, don't worry,
I don't need it right now.

707
00:48:51,720 --> 00:48:53,472
All right, honey, you stay healthy.

708
00:48:53,555 --> 00:48:54,472
Love you.

709
00:48:54,473 --> 00:48:55,599
Be safe, honey. I love you.

710
00:48:55,682 --> 00:48:56,599
I love you. Bye-bye.

711
00:48:56,600 --> 00:48:57,809
Bye-bye, baby.

712
00:49:07,945 --> 00:49:09,821
I'm really happy to be back,

713
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.

714
00:49:17,162 --> 00:49:18,664
Last time I left,

715
00:49:18,747 --> 00:49:23,627
I was in a very difficult situation
with a lot of my friends.

716
00:49:24,294 --> 00:49:25,934
- So fire door number one?
- Yes.

717
00:49:26,004 --> 00:49:27,673
What?

718
00:49:29,883 --> 00:49:33,345
So many people were so angry
that I was working on the Brexit campaign,

719
00:49:33,428 --> 00:49:36,682
so angry I continued to work for a company

720
00:49:36,765 --> 00:49:39,601
that supported people
like Ted Cruz and Donald Trump.

721
00:49:42,312 --> 00:49:45,649
And there's still this whole group
of people that are wondering,

722
00:49:45,732 --> 00:49:49,361
am I taking the high road,
or am I doing something to protect myself?

723
00:49:56,368 --> 00:49:58,137
More news on Facebook over the weekend,

724
00:49:58,161 --> 00:50:00,580
as Mark Zuckerberg prepares to testify
before Congress

725
00:50:00,664 --> 00:50:01,957
tomorrow and Wednesday.

726
00:50:02,040 --> 00:50:03,851
Earlier this morning,
he announced some new measures

727
00:50:03,875 --> 00:50:06,670
in the company's efforts
to prevent interference in elections...

728
00:50:18,056 --> 00:50:20,684
It's today's FT.

729
00:50:20,767 --> 00:50:23,729
My name's at the top of the front page
of the FT.

730
00:50:23,812 --> 00:50:24,855
Oh, shit.

731
00:50:25,856 --> 00:50:27,566
There it is.

732
00:50:29,234 --> 00:50:31,111
"Zuckerberg braced for Congress grilling.

733
00:50:31,194 --> 00:50:34,573
Facebook chief will admit
that the social network did not do enough

734
00:50:34,656 --> 00:50:37,117
to stop its tools being used for harm."

735
00:50:37,826 --> 00:50:41,538
"Facebook should pay its
two billion users for their personal data.

736
00:50:41,788 --> 00:50:45,834
The big tech companies are evolving
into digital kleptocracies.

737
00:50:46,084 --> 00:50:47,294
Yesterday."

738
00:50:49,171 --> 00:50:50,797
Um...

739
00:50:51,590 --> 00:50:54,301
I sort of missed the paragraph of, like,

740
00:50:55,343 --> 00:50:57,554
"I helped build this monster

741
00:50:58,472 --> 00:50:59,472
that...

742
00:51:01,767 --> 00:51:05,395
wreaked havoc upon the world
and will take decades to recover from,

743
00:51:06,396 --> 00:51:10,025
and I feel really bad about that."
I don't see that here.

744
00:51:12,194 --> 00:51:14,071
The data wars have begun.

745
00:51:24,498 --> 00:51:28,627
I mean, this is a company
that is a superstate,

746
00:51:28,919 --> 00:51:33,131
and the only nation
that has jurisdiction over it is ours.

747
00:51:40,347 --> 00:51:44,810
The Committees on the Judiciary
and Commerce, Science and Transportation

748
00:51:44,893 --> 00:51:46,228
will come to order.

749
00:51:48,271 --> 00:51:51,024
Chairman Grassley
and members of the committee:

750
00:51:52,192 --> 00:51:57,364
My top priority has always been
our social mission of connecting people,

751
00:51:57,447 --> 00:52:00,158
building community,
and bringing the world closer together.

752
00:52:01,243 --> 00:52:04,538
But it's clear now that we didn't
do enough to prevent these tools

753
00:52:04,621 --> 00:52:06,206
from being used for harm as well.

754
00:52:06,706 --> 00:52:09,417
Before I talk about the steps
we're taking to address them,

755
00:52:09,501 --> 00:52:10,981
I want to talk about how we got here.

756
00:52:11,545 --> 00:52:14,172
When we first contacted
Cambridge Analytica,

757
00:52:14,256 --> 00:52:16,466
they told us
that they had deleted the data.

758
00:52:16,842 --> 00:52:17,842
About a month ago,

759
00:52:17,884 --> 00:52:20,303
we heard new reports
that suggested that wasn't true.

760
00:52:21,054 --> 00:52:25,225
So, we're getting to the bottom
of exactly what Cambridge Analytica did.

761
00:52:25,767 --> 00:52:28,019
Blame it on me, Mark. Go for it.

762
00:52:28,103 --> 00:52:30,689
...to address this and to prevent it
from happening again.

763
00:52:31,481 --> 00:52:35,318
Thank you for having me here today,
and I'm ready to take your questions.

764
00:52:36,444 --> 00:52:40,907
Well, Mr. Zuckerberg,
during the 2016 campaign,

765
00:52:41,032 --> 00:52:44,286
Cambridge Analytica worked
with the Trump campaign

766
00:52:44,369 --> 00:52:47,789
to refine tactics under Project Alamo.

767
00:52:47,873 --> 00:52:50,292
Were Facebook employees involved in that?

768
00:52:51,585 --> 00:52:54,480
Senator, I don't know that our employees
were involved with Cambridge Analytica.

769
00:52:54,504 --> 00:52:56,464
- Yes, they were.
- Whoa!

770
00:52:56,548 --> 00:52:57,591
Oh, my God.

771
00:52:57,674 --> 00:53:00,468
The Republican team in DC was. I met them.

772
00:53:00,677 --> 00:53:03,680
...although I know that we did help out
the Trump campaign overall

773
00:53:03,763 --> 00:53:06,600
in sales support in the same way
that we do with other campaigns.

774
00:53:06,683 --> 00:53:08,560
So, they may have been involved

775
00:53:08,643 --> 00:53:11,271
and all working together
during that time period?

776
00:53:11,354 --> 00:53:14,107
Maybe that's something
your investigation will find out.

777
00:53:14,191 --> 00:53:16,818
Senator, I can certainly
have my team get back to you

778
00:53:16,902 --> 00:53:19,946
on any specifics there
that I don't know sitting here today.

779
00:53:20,030 --> 00:53:22,782
Oh, my God. This is the whole point
of the hearing, you...

780
00:53:22,866 --> 00:53:25,493
- Know what I'm talking about?
- No, I do not.

781
00:53:25,577 --> 00:53:26,577
Okay.

782
00:53:27,996 --> 00:53:29,122
It can go to you.

783
00:53:29,789 --> 00:53:33,585
Do you think the 87 million users,
do you consider them victims?

784
00:53:34,628 --> 00:53:36,463
Uh, Senator, I think...

785
00:53:36,796 --> 00:53:38,048
Uh...

786
00:53:38,215 --> 00:53:42,010
Yes. I mean, they... they did not want
their information to be

787
00:53:42,219 --> 00:53:46,014
sold to Cambridge Analytica
by a developer. And... And...

788
00:53:46,348 --> 00:53:47,515
that happened.

789
00:53:47,682 --> 00:53:49,309
And it happened on our watch.

790
00:53:49,434 --> 00:53:50,936
So even though we didn't do it,

791
00:53:51,019 --> 00:53:53,563
I think we have a responsibility
to be able to prevent that

792
00:53:53,647 --> 00:53:55,190
and be able to take action sooner.

793
00:53:55,690 --> 00:53:57,734
One of the steps that we need to take now

794
00:53:57,817 --> 00:54:00,946
is go do a full audit
of all of Cambridge Analytica's systems

795
00:54:01,029 --> 00:54:04,449
to understand what they're doing,
whether they still have any data...

796
00:54:04,532 --> 00:54:08,411
Obviously, Facebook has been done
considerable reputational damage

797
00:54:08,495 --> 00:54:10,956
by its association
with Cambridge Analytica.

798
00:54:11,039 --> 00:54:13,541
...process by which Cambridge Analytica...

799
00:54:13,625 --> 00:54:15,228
...relates to Cambridge Analytica...

800
00:54:15,252 --> 00:54:18,255
The recent stories
about Cambridge Analytica

801
00:54:18,338 --> 00:54:19,941
and data mining...

802
00:54:19,965 --> 00:54:23,176
Look at how many people
are posting Zuckerberg...

803
00:54:23,260 --> 00:54:25,321
- Everyone's watching this.
- Oh, my God.

804
00:54:25,345 --> 00:54:27,281
- And the whole thing just says...
- Wow.

805
00:54:27,305 --> 00:54:29,307
...Cambridge, Cambridge,
Cambridge.

806
00:54:31,851 --> 00:54:33,687
I never thought
everyone in the world

807
00:54:33,770 --> 00:54:36,064
would know who Cambridge Analytica was.

808
00:54:46,741 --> 00:54:49,536
I learnt many things from that period.

809
00:54:50,161 --> 00:54:53,707
I learnt, for example,
that when you're in a PR crisis,

810
00:54:53,790 --> 00:54:56,835
the one thing that you can't hire
is a PR crisis company.

811
00:54:57,168 --> 00:54:59,337
We spoke to...

812
00:55:00,630 --> 00:55:05,010
...tens of PR crisis companies
that listened intently,

813
00:55:05,093 --> 00:55:07,220
went away to think about it,
and came back and said,

814
00:55:07,304 --> 00:55:10,557
"Sorry, we can't associate ourselves
with your brand."

815
00:55:10,640 --> 00:55:15,395
Um... And actually, I thought
that's what they were there, um, for.

816
00:55:15,770 --> 00:55:19,858
And so it became impossible to, um...
to get a voice.

817
00:55:26,072 --> 00:55:29,075
The reason that we've called
this news conference today

818
00:55:29,159 --> 00:55:33,913
is to begin to counter
some of the unfounded allegations

819
00:55:33,997 --> 00:55:38,168
and, frankly, the torrent of ill-informed
and inaccurate speculation.

820
00:55:47,135 --> 00:55:49,929
Do you think what was done was illegal?

821
00:55:50,013 --> 00:55:51,765
We think it is probably illegal

822
00:55:51,848 --> 00:55:54,517
according to UK law,
and that's what we're challenging.

823
00:55:54,601 --> 00:55:56,936
We do have a statement
from Cambridge Analytica.

824
00:55:57,020 --> 00:55:58,438
Cambridge said,

825
00:55:58,521 --> 00:56:01,775
"David Carroll has no more right
to submit this request

826
00:56:01,858 --> 00:56:05,737
than a member of the Taliban
sitting in a cave in Afghanistan."

827
00:56:08,615 --> 00:56:10,867
And it came like a tsunami.

828
00:56:11,743 --> 00:56:16,331
There were 35,000 media stories per day.

829
00:56:19,459 --> 00:56:22,087
They wanted to discredit Trump,

830
00:56:22,420 --> 00:56:24,839
they wanted to discredit Brexit,

831
00:56:24,923 --> 00:56:26,841
and we were the vehicle for doing it.

832
00:56:27,634 --> 00:56:31,012
Do you feel
that you have skewed democracy?

833
00:56:31,388 --> 00:56:36,351
By providing campaign services
to a candidate who'd been fairly nominated

834
00:56:36,434 --> 00:56:39,646
as the Republican representative
of the United States?

835
00:56:40,105 --> 00:56:41,523
How is that possible?

836
00:56:43,191 --> 00:56:46,027
Cambridge Analytica became responsible

837
00:56:46,111 --> 00:56:49,864
for pretty much everything
that was wrong in the world.

838
00:56:55,078 --> 00:56:57,622
Are you saying
that Cambridge Analytica lies?

839
00:56:57,705 --> 00:57:00,417
They knowingly misrepresent the truth.

840
00:57:00,583 --> 00:57:02,168
What's your proof of that?

841
00:57:02,836 --> 00:57:04,087
I was there.

842
00:57:05,547 --> 00:57:08,133
Chris Wylie spoke with great authority

843
00:57:08,216 --> 00:57:11,094
about what had gone on
in Cambridge Analytica and SCL

844
00:57:11,177 --> 00:57:14,222
during 2015 and 2016,

845
00:57:14,305 --> 00:57:17,517
at a time when he was never there.

846
00:57:18,560 --> 00:57:22,939
He had worked for the company
for nine months, left in 2014.

847
00:57:23,231 --> 00:57:28,153
He then went out and pitched
the Trump campaign,

848
00:57:28,778 --> 00:57:31,281
and lost to us.

849
00:57:34,242 --> 00:57:37,328
Chris Wylie set out to kill the company.

850
00:57:39,998 --> 00:57:41,332
And what about Brittany?

851
00:57:46,963 --> 00:57:48,965
I don't know what Brittany was doing.

852
00:57:54,387 --> 00:57:56,264
Brittany was someone that...

853
00:57:57,015 --> 00:58:00,185
I thought was a friend,
I know Alexander thought was a friend.

854
00:58:01,436 --> 00:58:02,562
But, you know,

855
00:58:04,105 --> 00:58:06,441
when the world gets turned upside down,

856
00:58:07,901 --> 00:58:11,738
people behave in different ways.

857
00:58:12,864 --> 00:58:15,450
Maybe even they don't understand

858
00:58:16,284 --> 00:58:18,495
why they're doing what they're doing
at the time.

859
00:58:24,959 --> 00:58:28,713
I would strongly recommend
that we start doing testimony prep.

860
00:58:30,131 --> 00:58:32,300
Uh, go through the emails together,

861
00:58:32,383 --> 00:58:35,720
maybe go through other stuff
and hash out what's there.

862
00:58:37,430 --> 00:58:39,557
Oh, my God. I have my entire calendar.

863
00:58:41,226 --> 00:58:43,144
Shit. Shit.

864
00:58:43,228 --> 00:58:45,989
- You have your entire calendar?
- I have my entire calendar.

865
00:58:46,022 --> 00:58:47,273
Oh, my God.

866
00:58:47,524 --> 00:58:48,650
Downloaded?

867
00:58:48,733 --> 00:58:52,195
I didn't think that
that was going to still link.

868
00:58:52,278 --> 00:58:53,363
That's amazing.

869
00:58:53,446 --> 00:58:56,050
I can actually do an entire timeline
of everything, if that's the case.

870
00:58:56,074 --> 00:58:57,234
A timeline is great.

871
00:58:57,700 --> 00:58:59,160
Fuck, look at this.

872
00:58:59,744 --> 00:59:02,580
September 2015.

873
00:59:04,749 --> 00:59:06,626
US Chamber of Commerce...

874
00:59:07,126 --> 00:59:08,211
Meeting at...

875
00:59:11,172 --> 00:59:13,883
Leave.EU. That was fun. Run-through.

876
00:59:13,967 --> 00:59:15,009
It's all here.

877
00:59:15,093 --> 00:59:17,762
I know exactly when everything happened.

878
00:59:17,845 --> 00:59:19,472
Always. Forever.

879
00:59:23,393 --> 00:59:25,186
I didn't realize how much I had.

880
00:59:25,687 --> 00:59:27,021
I've got much more than that,

881
00:59:27,105 --> 00:59:30,108
it's just those are the things I forwarded
that I think are worthwhile.

882
00:59:36,197 --> 00:59:38,783
Did you get the chance
to look through all of that?

883
00:59:38,866 --> 00:59:41,666
I went through most of it.
I'll look through more of it today.

884
00:59:44,664 --> 00:59:47,417
Let me get out
one of the pitches. Um...

885
00:59:47,667 --> 00:59:49,919
"CA Political."

886
00:59:52,171 --> 00:59:53,339
What is this?

887
00:59:54,257 --> 00:59:55,592
This looks mental.

888
00:59:57,343 --> 01:00:02,849
This is a list of, like,
the main sources of data.

889
01:00:04,017 --> 01:00:08,104
And look, it's got that fucking Facebook
data set of 30 million individuals.

890
01:00:08,187 --> 01:00:09,856
It just says it in there!

891
01:00:09,939 --> 01:00:11,608
What the fuck!

892
01:00:12,108 --> 01:00:13,401
Oh, my God.

893
01:00:14,068 --> 01:00:16,738
- February...
- Created February 4th, 2016!

894
01:00:16,821 --> 01:00:19,866
That was after we said to Facebook
that we deleted that shit!

895
01:00:20,992 --> 01:00:23,036
This is the 30 million individuals

896
01:00:23,119 --> 01:00:26,205
that we got their data
through Professor Kogan.

897
01:00:26,289 --> 01:00:27,498
That's that.

898
01:00:28,041 --> 01:00:31,794
And it admits to it right here,
"Our data makes us different,"

899
01:00:32,712 --> 01:00:36,174
because we're scraping people's profiles,
and other people are not.

900
01:00:37,967 --> 01:00:38,967
Fuck.

901
01:00:45,475 --> 01:00:47,977
I forgot about this stuff, you know?

902
01:00:48,853 --> 01:00:50,772
There's just so much stuff.

903
01:01:02,241 --> 01:01:04,243
...we seek to do as a firm.

904
01:01:04,327 --> 01:01:06,788
We are a behavior change agency.

905
01:01:08,039 --> 01:01:11,125
The holy grail of communications is

906
01:01:11,209 --> 01:01:13,294
when you can start to change behavior.

907
01:01:15,171 --> 01:01:18,633
Uh, Trinidad. This is a great,
interesting case history

908
01:01:18,716 --> 01:01:20,218
of how we look at problems.

909
01:01:23,680 --> 01:01:25,682
There are two main political parties,

910
01:01:25,890 --> 01:01:27,642
one for the blacks
and one for the Indians.

911
01:01:28,059 --> 01:01:29,727
And you know, they screw each other.

912
01:01:30,228 --> 01:01:33,064
So, we were working for the Indians.

913
01:01:34,399 --> 01:01:37,985
We went to the client and we said,
"We want to target the youth."

914
01:01:38,152 --> 01:01:42,365
And we try and increase apathy.

915
01:01:44,075 --> 01:01:45,910
The campaign had to be non-political,

916
01:01:45,993 --> 01:01:47,704
because the kids
don't care about politics.

917
01:01:47,787 --> 01:01:50,748
It had to be reactive,
because they're lazy.

918
01:01:51,582 --> 01:01:54,961
So we came up with this campaign,
which was all about:

919
01:01:55,044 --> 01:01:57,171
Be part of the gang. Do something cool.

920
01:01:57,255 --> 01:01:58,423
Be part of a movement.

921
01:01:58,715 --> 01:02:00,967
And it was called the "Do So!" campaign.

922
01:02:01,384 --> 01:02:03,024
It means "I'm not going to vote."

923
01:02:03,219 --> 01:02:04,887
"Do so! Don't vote."

924
01:02:07,974 --> 01:02:09,726
The salute of resistance

925
01:02:09,851 --> 01:02:12,729
that is known to all
across Trinidad and Tobago.

926
01:02:13,396 --> 01:02:15,481
Do So! Do So!

927
01:02:16,399 --> 01:02:18,484
Do So!

928
01:02:18,776 --> 01:02:21,988
It's a sign of resistance against,
not the government,

929
01:02:22,071 --> 01:02:24,574
against politics and voting.

930
01:02:24,949 --> 01:02:27,034
- ♪ Run with it, run with it ♪
- ♪ Run, run ♪

931
01:02:27,118 --> 01:02:28,762
- ♪ Run with it, run with it ♪
- ♪ Run, run ♪

932
01:02:28,786 --> 01:02:31,164
They're making their own YouTube videos.

933
01:02:31,247 --> 01:02:34,667
This is the prime minister's house
that's being graffitied.

934
01:02:34,751 --> 01:02:36,502
It was carnage.

935
01:02:38,296 --> 01:02:41,048
We knew that when it came to voting,

936
01:02:41,215 --> 01:02:44,177
all the Afro-Caribbean kids wouldn't vote,

937
01:02:44,260 --> 01:02:45,261
because they Do So!

938
01:02:45,344 --> 01:02:48,973
But all the Indian kids would do
what their parents told them to do,

939
01:02:49,223 --> 01:02:50,808
which is go out and vote.

940
01:02:51,434 --> 01:02:53,269
They had a lot of fun doing this,

941
01:02:53,352 --> 01:02:56,397
but they're not gonna go
against their parents' will.

942
01:03:00,610 --> 01:03:05,072
Thank God for the guidance
that has brought us here to this victory.

943
01:03:05,156 --> 01:03:07,492
Thank you. Thank you, God.

944
01:03:07,575 --> 01:03:12,663
And the difference in
18-to 35-year-old turnout was like 40%.

945
01:03:13,372 --> 01:03:16,209
And that swung the election about 6%,

946
01:03:16,292 --> 01:03:19,253
which was all we needed
in an election that's very close.

947
01:03:22,256 --> 01:03:28,179
We now undertake ten national campaigns
for prime minister or president each year.

948
01:03:28,805 --> 01:03:30,389
Malaysia, we're working in.

949
01:03:30,473 --> 01:03:34,602
We did Lithuania, Romania,
Kenya, Ghana.

950
01:03:35,186 --> 01:03:37,266
- So quite a few this year.
- Nigeria.

951
01:03:37,563 --> 01:03:40,650
- The Brexit campaign?
- Oh, and the Brexit campaign, yeah.

952
01:03:41,067 --> 01:03:42,902
But we don't talk about that.

953
01:03:42,985 --> 01:03:44,278
Oops, we won!

954
01:03:50,243 --> 01:03:52,912
Do you worry at all
that she might let you down?

955
01:03:56,541 --> 01:03:58,251
Look, um...

956
01:04:06,843 --> 01:04:08,135
That is a good question.

957
01:04:10,429 --> 01:04:15,184
I know already that she is
a complicated person, uh,

958
01:04:15,268 --> 01:04:16,435
who has...

959
01:04:18,521 --> 01:04:20,773
you know, done some complicated things.

960
01:04:21,524 --> 01:04:22,608
Uh...

961
01:04:23,734 --> 01:04:26,571
I believe in redemption.

962
01:04:28,948 --> 01:04:35,371
Uh, individual redemption
and collective... uh, social redemption.

963
01:04:35,454 --> 01:04:39,041
Uh, I'm an idealist.
I think we can fix stuff that's broken,

964
01:04:39,333 --> 01:04:42,962
uh, and, at the same time,

965
01:04:43,045 --> 01:04:46,591
I am a realist about the fact
that you can't fix everything. Um...

966
01:04:46,716 --> 01:04:49,176
You know, some things get broken
and stay broken.

967
01:04:54,682 --> 01:04:57,018
Good morning,
welcome to this further session

968
01:04:57,101 --> 01:05:00,104
of the Digital, Culture,
Media and Sport Select Committee.

969
01:05:00,187 --> 01:05:02,773
Very pleased to welcome Brittany Kaiser
to give evidence to

970
01:05:02,857 --> 01:05:04,442
the committee this morning.

971
01:05:05,276 --> 01:05:09,739
Now, there was a contact between Facebook
and Cambridge Analytica

972
01:05:09,822 --> 01:05:14,994
about the use of data in,
I think it was 2015, from memory.

973
01:05:15,202 --> 01:05:18,205
Did you know about that at the time?

974
01:05:18,414 --> 01:05:21,876
Uh, so Facebook had announced
to all of their clients

975
01:05:21,959 --> 01:05:25,296
that they were going to close
their clients' access to this data,

976
01:05:25,963 --> 01:05:27,673
so we agreed to delete it,

977
01:05:27,757 --> 01:05:31,010
but in March 2016,

978
01:05:31,093 --> 01:05:33,304
you know, six or eight weeks after

979
01:05:33,387 --> 01:05:37,141
our chief data officer said
that those data sets were deleted,

980
01:05:37,224 --> 01:05:40,227
I have an email from one
of our senior data scientists

981
01:05:40,311 --> 01:05:44,941
that said that we were actually using
Facebook Like data in our modeling.

982
01:05:45,024 --> 01:05:46,525
Ooh.

983
01:05:46,609 --> 01:05:48,903
- So that seems strange to me.
- Uh-oh.

984
01:05:48,986 --> 01:05:51,131
If we had deleted
all of the Facebook data sets,

985
01:05:51,155 --> 01:05:53,491
how we were still using that
for modeling in March.

986
01:05:54,700 --> 01:05:57,596
Ms. Kaiser, you seem to have traveled
a long way from an idealistic intern

987
01:05:57,620 --> 01:05:59,288
in Barack Obama's campaign,

988
01:05:59,372 --> 01:06:03,376
uh, to working for a company
that keeps pretty unsavory company,

989
01:06:03,459 --> 01:06:07,213
uh, in wishing to make pitches
to far-right political parties.

990
01:06:07,296 --> 01:06:09,799
- Mm-hmm.
- Didn't that make you uncomfortable?

991
01:06:09,966 --> 01:06:10,966
Uh, yes.

992
01:06:11,717 --> 01:06:15,846
I would say questioning the ethics of it
is correct, definitely.

993
01:06:15,930 --> 01:06:19,892
But I have been offered introductions
to clients

994
01:06:19,976 --> 01:06:21,686
that I refused to meet with before,

995
01:06:21,769 --> 01:06:25,940
um, such as the Alternative for Germany
and Marine Le Pen's campaign.

996
01:06:26,023 --> 01:06:29,235
I refused to even get on a phone call
with them.

997
01:06:30,361 --> 01:06:31,696
But not UKIP?

998
01:06:31,988 --> 01:06:33,572
Not UKIP, no.

999
01:06:35,116 --> 01:06:38,869
Um, did you appear and give a presentation
to the launch of Leave. EU?

1000
01:06:38,953 --> 01:06:40,121
Yes, I did.

1001
01:06:40,204 --> 01:06:42,999
Um, you must've been a bit, um,
disappointed then

1002
01:06:43,082 --> 01:06:45,501
when you subsequently
didn't do any work for them.

1003
01:06:45,793 --> 01:06:48,838
And we didn't do any further work for them
after that day, yes.

1004
01:06:48,921 --> 01:06:50,273
So you had done some work.

1005
01:06:50,297 --> 01:06:52,633
What was the nature of the work
that you had done so far?

1006
01:06:52,717 --> 01:06:53,968
We had taken receipt

1007
01:06:54,051 --> 01:06:57,388
of UK Independence Party data
and the survey data.

1008
01:06:57,471 --> 01:07:03,352
She's, like, contradicting Nix a lot,
what he said previously.

1009
01:07:03,436 --> 01:07:05,956
So, I think you've been quite clear,
as far as you're concerned,

1010
01:07:06,022 --> 01:07:10,026
you were working on the campaign,
but just not being paid for it?

1011
01:07:10,109 --> 01:07:12,069
- Mm-hmm.
- You're pretty clear on that.

1012
01:07:12,862 --> 01:07:14,739
Just to clarify, for our benefit,

1013
01:07:14,822 --> 01:07:16,615
to be effective in this space,

1014
01:07:16,699 --> 01:07:18,951
how big a kind of working set do you need

1015
01:07:19,035 --> 01:07:22,163
to be able to then
use that to create the basis

1016
01:07:22,246 --> 01:07:24,790
for targeting the whole country
in terms of voting?

1017
01:07:25,082 --> 01:07:27,185
I'm not a data scientist,
so I wouldn't be able to say

1018
01:07:27,209 --> 01:07:29,712
the minimum number
of data points that you would require,

1019
01:07:29,795 --> 01:07:32,673
uh, but I do know
that their targeting tool

1020
01:07:32,757 --> 01:07:36,594
used to be export-controlled
by the British government,

1021
01:07:36,677 --> 01:07:39,930
so that would mean that
the methodology was considered a weapon.

1022
01:07:40,598 --> 01:07:43,267
Um, weapons-grade communications tactics.

1023
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

1024
01:07:46,979 --> 01:07:50,858
weapons-grade communications techniques
against the UK population?

1025
01:07:51,942 --> 01:07:53,903
- Yes, sir.
- It's crazy.

1026
01:07:54,236 --> 01:07:56,989
Uh, I just want to get
your perspective as well.

1027
01:07:57,073 --> 01:07:59,158
What do you actually think
the legislators should do

1028
01:07:59,241 --> 01:08:01,368
in order to better protect people's data?

1029
01:08:01,911 --> 01:08:05,956
Well, I'm very glad that
you asked that. Think about it right now.

1030
01:08:06,040 --> 01:08:08,459
The sole worth of Google and Facebook

1031
01:08:08,542 --> 01:08:12,046
is the fact that they own, and possess,
and hold, and use

1032
01:08:12,129 --> 01:08:14,249
the personal data
of people from all around the world.

1033
01:08:14,965 --> 01:08:17,218
So I think that the best way
to move forward

1034
01:08:17,301 --> 01:08:21,180
are for people to really possess
their data like their property.

1035
01:08:21,847 --> 01:08:23,825
- Thank you, Chair.
- Thank you.

1036
01:08:23,849 --> 01:08:26,602
Um, I think that concludes the questions
from us today.

1037
01:08:26,685 --> 01:08:28,005
Just before we close the session,

1038
01:08:28,062 --> 01:08:30,981
I just have to make a short announcement
about Alexander Nix.

1039
01:08:31,065 --> 01:08:34,193
He's now not able to give evidence
to the Committee tomorrow

1040
01:08:34,276 --> 01:08:37,321
as a consequence of him having been served
with an information notice

1041
01:08:37,404 --> 01:08:39,244
and being subject
to the criminal investigation

1042
01:08:39,323 --> 01:08:41,367
by the Information Commissioner's Office.

1043
01:08:41,450 --> 01:08:44,036
And I hope we'll be able to update people

1044
01:08:44,120 --> 01:08:46,413
about that early next week.
Thank you very much.

1045
01:08:47,081 --> 01:08:48,081
Thank you.

1046
01:08:48,749 --> 01:08:49,750
Shit!

1047
01:08:51,001 --> 01:08:53,045
The proceeding has ended.

1048
01:08:53,129 --> 01:08:54,129
Yes, it has!

1049
01:09:11,772 --> 01:09:13,732
I just got a text from Alexander.

1050
01:09:15,860 --> 01:09:17,486
Alexander Nix.

1051
01:09:20,447 --> 01:09:21,615
What did he say?

1052
01:09:22,283 --> 01:09:25,619
"Well done, Britt.
Looked quite tough, and you did okay."

1053
01:09:26,453 --> 01:09:29,540
With a winky face little emoji.

1054
01:09:31,167 --> 01:09:33,794
It makes me kind of sad.
You know what I mean?

1055
01:09:33,878 --> 01:09:36,088
Like, it's not like he spent
three and a half years

1056
01:09:36,172 --> 01:09:37,923
being an asshole to me. He didn't.

1057
01:09:38,174 --> 01:09:40,443
He spent three and a half years
being nice to you

1058
01:09:40,467 --> 01:09:42,261
to get you to do what he wanted you to do.

1059
01:09:42,344 --> 01:09:46,473
Yeah. But he is rather fun.

1060
01:09:46,557 --> 01:09:48,243
I know, I know.

1061
01:09:48,267 --> 01:09:49,310
Hey, Justin.

1062
01:09:49,810 --> 01:09:52,146
Hey, what's up? What did you think?

1063
01:09:52,646 --> 01:09:55,441
I'm processing it.
There were a lot of revelations.

1064
01:09:57,484 --> 01:10:00,988
SCL has to file its defense
at the end of the month,

1065
01:10:01,614 --> 01:10:04,200
so, it'll be really interesting
to see, like,

1066
01:10:04,283 --> 01:10:07,328
what they think they can do,
especially after this.

1067
01:10:07,995 --> 01:10:09,205
That's right.

1068
01:10:10,206 --> 01:10:11,290
I mean, shit.

1069
01:10:11,373 --> 01:10:15,753
She said that basically psychographics
should be classified as a weapon.

1070
01:10:20,216 --> 01:10:23,719
It seems like Kaiser has
some moral compass in her.

1071
01:10:26,805 --> 01:10:30,392
But, so many times,
she knew that she was

1072
01:10:30,476 --> 01:10:32,061
in a dark world

1073
01:10:32,353 --> 01:10:33,896
and didn't step away.

1074
01:10:33,979 --> 01:10:37,191
And they... they got... got her on that
a couple of times.

1075
01:10:37,274 --> 01:10:38,274
Yeah.

1076
01:10:42,154 --> 01:10:45,157
You did work for a man who,
upon meeting you,

1077
01:10:45,241 --> 01:10:46,927
said to you, you know,
"Let me get you drunk

1078
01:10:46,951 --> 01:10:48,452
and steal your secrets."

1079
01:10:48,869 --> 01:10:51,789
You knew the kind of company
that you were working for.

1080
01:10:51,997 --> 01:10:54,208
I don't know. I guess I trusted him.

1081
01:10:54,500 --> 01:10:56,377
I worked for him
for three and a half years.

1082
01:10:56,460 --> 01:10:59,171
He was a friend and mentor. I mean...

1083
01:10:59,463 --> 01:11:01,465
He actually just sent me a text,

1084
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.

1085
01:11:05,219 --> 01:11:06,696
So, he was watching you.

1086
01:11:06,720 --> 01:11:08,720
- He watched, yes.
- What did he say?

1087
01:11:09,056 --> 01:11:12,393
He said that it looked pretty tough
but that I did a good job.

1088
01:11:12,476 --> 01:11:14,520
- Did you reply?
- No.

1089
01:11:14,728 --> 01:11:15,854
Will you?

1090
01:11:15,938 --> 01:11:18,482
No, I don't think that's appropriate
at this time.

1091
01:11:18,565 --> 01:11:21,110
So, there's no friendship there?

1092
01:11:21,777 --> 01:11:27,658
Well, I now question, you know,
how much of a friendship it actually was.

1093
01:11:49,722 --> 01:11:52,141
The thing which
I give Brittany credit for...

1094
01:11:52,433 --> 01:11:56,520
it's really amazed me how many people
are just keeping their mouths shut.

1095
01:12:01,066 --> 01:12:03,485
I mean, it was a jaw-dropping moment

1096
01:12:03,569 --> 01:12:08,866
when Brittany said these are classified
as weapons-grade technology.

1097
01:12:09,199 --> 01:12:11,994
And it was actually illegal to use those

1098
01:12:12,077 --> 01:12:14,455
without the permission
of the British government.

1099
01:12:18,125 --> 01:12:19,710
It's psyops.

1100
01:12:20,961 --> 01:12:24,214
Psyops is psychological operations.

1101
01:12:24,298 --> 01:12:27,801
And it's a...
it's a term that the military uses

1102
01:12:27,885 --> 01:12:32,348
to describe what you do in warfare
which isn't warfare.

1103
01:12:32,431 --> 01:12:34,350
So, essentially, you know,

1104
01:12:34,433 --> 01:12:36,602
in a place like Afghanistan,
you've got a choice.

1105
01:12:36,685 --> 01:12:38,562
You either bomb the shit out of a village

1106
01:12:38,854 --> 01:12:41,398
or you try and use other techniques

1107
01:12:41,482 --> 01:12:44,943
to persuade them that actually,
"The Taliban's not very good,

1108
01:12:45,027 --> 01:12:46,862
and you'd be much better off
without them."

1109
01:12:51,033 --> 01:12:54,203
SCL started out as a military contractor.

1110
01:12:54,286 --> 01:12:55,454
SCL Defense.

1111
01:12:57,498 --> 01:13:00,417
We have a fairly substantial
defense business.

1112
01:13:01,627 --> 01:13:03,837
We actually train the British Army,
the British Navy,

1113
01:13:03,921 --> 01:13:05,464
the U.S. Army, U.S. Special Forces.

1114
01:13:05,547 --> 01:13:09,009
We train NATO, the CIA,
State Department, Pentagon.

1115
01:13:09,718 --> 01:13:15,099
It's using research to influence behavior
of hostile audiences.

1116
01:13:15,766 --> 01:13:20,646
You know, how do you persuade
14-to 30-year-old Muslim boys

1117
01:13:20,729 --> 01:13:22,356
not to join Al-Qaeda?

1118
01:13:23,440 --> 01:13:24,942
Essentially communication warfare.

1119
01:13:25,025 --> 01:13:26,985
- Allahu Akbar!
- Allahu Akbar!

1120
01:13:27,486 --> 01:13:30,948
They'd worked
in Afghanistan, they'd worked in Iraq,

1121
01:13:31,031 --> 01:13:34,576
they'd worked in various places
in Eastern Europe.

1122
01:13:34,993 --> 01:13:37,663
But the real game changer

1123
01:13:37,746 --> 01:13:42,918
was they started using information warfare
in elections.

1124
01:13:44,044 --> 01:13:47,714
There's a lot of overlap,
because it's all the same methodology.

1125
01:13:50,843 --> 01:13:55,139
All of the campaigns
which Cambridge Analytica/SCL did

1126
01:13:55,222 --> 01:13:57,599
for the developing world,

1127
01:13:57,808 --> 01:14:02,020
it was all about practicing
some new technology or trick.

1128
01:14:02,354 --> 01:14:04,106
How to persuade people,

1129
01:14:04,189 --> 01:14:07,943
how to suppress turnout,
or how to increase turnout.

1130
01:14:10,654 --> 01:14:11,654
And then it's like,

1131
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."

1132
01:14:42,269 --> 01:14:43,269
Yes.

1133
01:15:19,306 --> 01:15:22,643
...and expands, but with no branding,

1134
01:15:22,893 --> 01:15:25,646
so it's unattributable, untrackable.

1135
01:15:26,396 --> 01:15:28,565
And my view...

1136
01:15:29,441 --> 01:15:32,569
is that if you can't run your own house,

1137
01:15:32,778 --> 01:15:35,447
you certainly can't run the White House.

1138
01:15:35,531 --> 01:15:36,990
Can't do it.

1139
01:15:38,158 --> 01:15:41,620
Crooked Hillary, right? Crooked.
She's crooked as you can be.

1140
01:15:41,703 --> 01:15:43,413
Lock her up! Lock her up!

1141
01:15:43,497 --> 01:15:45,415
Yep, that's right, lock her up!

1142
01:15:45,499 --> 01:15:47,251
Lock her up! Lock her up!

1143
01:15:47,584 --> 01:15:49,920
Lock her up! Lock her up!

1144
01:15:51,922 --> 01:15:54,424
Let's defeat her in November.

1145
01:16:08,105 --> 01:16:10,482
What was it like for you to watch

1146
01:16:10,566 --> 01:16:12,526
the Channel 4 undercover video?

1147
01:16:14,069 --> 01:16:15,612
Nobody recognized it.

1148
01:16:18,407 --> 01:16:20,701
When we watched that video...

1149
01:16:21,118 --> 01:16:25,872
I watched it in the New York office
with, um, all the staff there.

1150
01:16:25,956 --> 01:16:27,791
And we knew it was coming out.

1151
01:16:28,000 --> 01:16:30,377
And I think everybody was...

1152
01:16:31,962 --> 01:16:33,255
in a state of shock.

1153
01:16:35,424 --> 01:16:40,095
Everybody walked away from the screen
in silence back to their desks.

1154
01:16:47,978 --> 01:16:51,398
Tonight, an undercover
interview by Channel 4 News in London

1155
01:16:51,481 --> 01:16:52,983
shows Cambridge executives,

1156
01:16:53,066 --> 01:16:55,485
including CEO Alexander Nix,

1157
01:16:55,569 --> 01:16:58,030
boasting about the company's role
in Trump's win.

1158
01:16:58,488 --> 01:17:01,533
This series of undercover interviews
by Channel 4 News

1159
01:17:01,617 --> 01:17:03,076
also caught Nix on tape

1160
01:17:03,160 --> 01:17:06,038
talking about potential bribery
and entrapment.

1161
01:17:08,832 --> 01:17:10,334
I don't understand.

1162
01:17:14,588 --> 01:17:16,798
Mr. Nix, can I ask you
what your message is

1163
01:17:16,882 --> 01:17:19,217
to Cambridge Analytica employees today?

1164
01:17:22,220 --> 01:17:24,780
We've just got a statement
from Cambridge Analytica.

1165
01:17:25,932 --> 01:17:29,686
Alexander Nix has been suspended
with immediate effect.

1166
01:17:29,770 --> 01:17:34,066
The company accused of harvesting the data
of more than 87 million Facebook users

1167
01:17:34,149 --> 01:17:35,484
says it is shutting down.

1168
01:17:35,817 --> 01:17:40,489
The company says it intends to file
for bankruptcy in the US and the UK.

1169
01:17:42,324 --> 01:17:44,576
Critics believe Cambridge Analytica

1170
01:17:44,660 --> 01:17:47,496
and SCL Elections
may be shutting operations

1171
01:17:47,579 --> 01:17:51,583
to limit or restrict the ability
of the authority's investigations

1172
01:17:51,667 --> 01:17:53,794
and also to get rid of evidence.

1173
01:18:02,678 --> 01:18:04,364
The Cambridge Analytica scandal,

1174
01:18:04,388 --> 01:18:05,972
is it now the Facebook scandal?

1175
01:18:08,100 --> 01:18:10,185
I mean, this is not about one company.

1176
01:18:11,436 --> 01:18:16,608
This technology is going on unabated
and will continue to go on.

1177
01:18:17,943 --> 01:18:19,653
But Cambridge Analytica's gone.

1178
01:18:20,696 --> 01:18:23,532
In some senses, I feel that, um...

1179
01:18:25,867 --> 01:18:30,038
that because of the way
that this technology is moving so fast,

1180
01:18:30,414 --> 01:18:34,710
and because people
don't really understand it,

1181
01:18:34,793 --> 01:18:37,170
and because there's a lot of concerns
about it,

1182
01:18:37,254 --> 01:18:40,215
there was always going to be
a Cambridge Analytica.

1183
01:18:40,632 --> 01:18:43,218
It just sucks for me
it was Cambridge Analytica.

1184
01:18:55,814 --> 01:18:57,733
After we dealt with the threats

1185
01:18:57,816 --> 01:19:00,527
from Cambridge Analytica
over the course of a year,

1186
01:19:01,027 --> 01:19:03,363
then the thing which made
our heads explode

1187
01:19:03,447 --> 01:19:06,283
was the day before publication,
when we got a letter from Facebook.

1188
01:19:06,992 --> 01:19:10,245
Yeah, it felt like an attempt
to... to cow us into submission.

1189
01:19:10,328 --> 01:19:11,747
It didn't feel like a sort of...

1190
01:19:11,830 --> 01:19:14,499
To me, it didn't feel like
a legitimate response...

1191
01:19:14,583 --> 01:19:18,462
And you sort of go, you know,
why is a great, big organization like you

1192
01:19:18,545 --> 01:19:20,130
using UK lawyers?

1193
01:19:20,213 --> 01:19:22,382
And again, a very aggressive threat

1194
01:19:22,466 --> 01:19:24,318
for which, actually, they then...
Didn't they apologize?

1195
01:19:24,342 --> 01:19:26,178
Yes,
they said it was not their finest hour.

1196
01:19:26,261 --> 01:19:27,888
Yeah.

1197
01:19:27,971 --> 01:19:29,473
And up until that point,

1198
01:19:29,556 --> 01:19:31,808
it was like the tech giants were still,
like,

1199
01:19:31,892 --> 01:19:33,727
the nice guys who wear hoodies,

1200
01:19:33,810 --> 01:19:35,562
- who connected the world.
- Yep.

1201
01:19:35,645 --> 01:19:37,898
And there was a shift away

1202
01:19:37,981 --> 01:19:39,983
from big tech being good

1203
01:19:40,066 --> 01:19:43,945
to saying well, actually,
we do need to start asking questions

1204
01:19:44,029 --> 01:19:46,364
about this and what it is.

1205
01:19:50,243 --> 01:19:52,245
Cambridge Analytica is gone,

1206
01:19:52,829 --> 01:19:58,502
but it's really important to understand
that the Cambridge Analytica story

1207
01:19:58,668 --> 01:20:02,923
actually points to this much bigger,
more worrying story

1208
01:20:03,757 --> 01:20:08,637
which is that our personal data
is out there and being used against us

1209
01:20:08,720 --> 01:20:10,931
in ways we don't understand.

1210
01:20:14,643 --> 01:20:16,520
And if David gets his data back,

1211
01:20:16,812 --> 01:20:19,856
we can hopefully start
getting some answers.

1212
01:20:22,734 --> 01:20:26,780
The deadline is today for SCL
to comply with the law

1213
01:20:26,863 --> 01:20:28,615
and give me my data.

1214
01:20:30,659 --> 01:20:35,497
We're at the precipice of evasion
or accountability.

1215
01:20:38,583 --> 01:20:40,210
Carole tweeted,

1216
01:20:40,293 --> 01:20:43,421
"Prof. Carroll also giving evidence
to European Parliament today

1217
01:20:43,505 --> 01:20:47,634
on day of deadline for Cambridge Analytica
to turn over his data to him.

1218
01:20:47,717 --> 01:20:51,388
If it fails to do so, it becomes
a matter for criminal proceedings."

1219
01:20:55,934 --> 01:20:58,728
"Hey Ravi, have you heard anything?"

1220
01:21:00,272 --> 01:21:01,356
"Not yet."

1221
01:21:07,445 --> 01:21:11,783
I've been waiting to hear from my lawyer,
and we have heard nothing.

1222
01:21:11,867 --> 01:21:14,244
And so they have not respected
the regulator.

1223
01:21:14,327 --> 01:21:16,788
They are not respecting the law.

1224
01:21:17,372 --> 01:21:19,666
So now that this is becoming
a criminal matter,

1225
01:21:19,749 --> 01:21:21,626
we are now in uncharted waters.

1226
01:21:22,711 --> 01:21:26,298
And I will continue to pursue it

1227
01:21:26,381 --> 01:21:30,051
because their model has the potential
to affect a population

1228
01:21:30,135 --> 01:21:32,596
even if it's just a tiny slice
of the population,

1229
01:21:32,679 --> 01:21:34,264
because in the United States,

1230
01:21:34,347 --> 01:21:39,436
only about 70,000 voters in three states
decided the election.

1231
01:21:42,188 --> 01:21:45,275
Thank you very much,
um, Professor Carroll. Um...

1232
01:21:45,609 --> 01:21:46,818
Mr. Batten.

1233
01:21:47,277 --> 01:21:51,281
My question is
for Carole Cadwalladr from The Guardian.

1234
01:21:51,364 --> 01:21:56,077
Is The Guardian's stand
on this a purely politically partisan one

1235
01:21:56,161 --> 01:22:00,040
in its own intention to assist
in any way that it can

1236
01:22:00,123 --> 01:22:03,251
to reverse and overturn
the result of the referendum?

1237
01:22:05,420 --> 01:22:10,258
This is not a partisan issue,
I cannot say that more strongly.

1238
01:22:10,342 --> 01:22:14,304
This is about the integrity
of our democracy.

1239
01:22:14,387 --> 01:22:17,057
It's about our national sovereignty.

1240
01:22:17,599 --> 01:22:21,061
And I would think that you would have
an interest in that also.

1241
01:22:24,147 --> 01:22:28,234
I think that we desperately need
more information,

1242
01:22:28,652 --> 01:22:31,154
because we don't how people were targeted

1243
01:22:31,237 --> 01:22:33,782
and we don't know what data
that was based upon.

1244
01:22:34,157 --> 01:22:40,956
One thing we do know is that Facebook
has been obstructive in its efforts

1245
01:22:41,039 --> 01:22:43,708
to help the British Parliament
investigate this matter.

1246
01:22:44,084 --> 01:22:48,755
Uh, really, really, really,
you've got to, like, look higher

1247
01:22:48,838 --> 01:22:50,966
and really see the bigger issue here

1248
01:22:51,049 --> 01:22:53,635
and the bigger picture
and the bigger risks to us all.

1249
01:23:04,771 --> 01:23:07,983
Roger, even if, uh, Facebook
hasn't broken any laws,

1250
01:23:08,066 --> 01:23:12,320
have they broken a sort of moral trust
that they have with their consumers?

1251
01:23:12,404 --> 01:23:14,197
Well, I... They have with me.

1252
01:23:14,280 --> 01:23:18,743
I mean, I spent three months,
starting in October 2016, trying to say,

1253
01:23:18,827 --> 01:23:22,455
"Guys, I think you're killing democracy,
and you're gonna kill your business."

1254
01:23:22,539 --> 01:23:24,833
- Hi, how are you? I'm Roger.
- Hi, how are you?

1255
01:23:24,916 --> 01:23:26,811
- Pleasure to meet you.
- Pleasure to meet you.

1256
01:23:26,835 --> 01:23:31,131
Facebook is designed
to monopolize attention.

1257
01:23:31,589 --> 01:23:34,509
Just taking all of the basic tricks
of propaganda,

1258
01:23:34,592 --> 01:23:37,053
marrying them to the tricks
of casino gambling.

1259
01:23:37,137 --> 01:23:39,014
You know, slot machines and the like.

1260
01:23:39,264 --> 01:23:43,977
And basically playing on instincts,

1261
01:23:44,394 --> 01:23:47,772
and fear and anger are the two
most dependable ways of doing that.

1262
01:23:47,897 --> 01:23:50,483
And so, they created a set of tools

1263
01:23:50,567 --> 01:23:56,197
to allow advertisers to exploit
that emotional audience

1264
01:23:57,073 --> 01:24:00,368
with individual-level targeting, right?

1265
01:24:00,452 --> 01:24:05,623
There's 2.1 billion people,
each with their own reality.

1266
01:24:05,915 --> 01:24:08,251
And once everybody has their own reality,

1267
01:24:08,334 --> 01:24:11,463
- it's relatively easy to manipulate them.
- Mmm. Yeah.

1268
01:24:11,546 --> 01:24:16,926
And the other thing about this is,
they know that it's killing me...

1269
01:24:17,218 --> 01:24:18,678
- Yeah.
- ...to be critical

1270
01:24:18,762 --> 01:24:20,597
of what I've viewed as my baby.

1271
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."

1272
01:24:24,893 --> 01:24:25,893
Yes.

1273
01:24:25,977 --> 01:24:27,645
- But...
- Yeah.

1274
01:24:28,229 --> 01:24:31,191
...you get tested in your life
a few times, right? And...

1275
01:24:31,483 --> 01:24:33,151
for me, this was one of those moments.

1276
01:24:33,234 --> 01:24:35,004
I was either gonna stand up
and do something about this,

1277
01:24:35,028 --> 01:24:37,781
or I wasn't gonna stand up
and do anything about anything. Right?

1278
01:24:37,864 --> 01:24:40,533
Because my fingerprints are on this thing.

1279
01:24:41,034 --> 01:24:43,495
- I know.
- I mean, I felt really guilty.

1280
01:24:44,621 --> 01:24:47,332
And I just want to be able to...

1281
01:24:48,458 --> 01:24:49,876
sleep at night.

1282
01:25:09,354 --> 01:25:12,774
One of the things
that I was really struck by was...

1283
01:25:13,066 --> 01:25:15,318
what happened with you

1284
01:25:15,401 --> 01:25:17,487
and the Obama people
and the Hillary people.

1285
01:25:18,863 --> 01:25:22,325
Uh, none of them ever wanted
to offer to pay me.

1286
01:25:23,493 --> 01:25:27,497
And, um,
when your family loses all their money

1287
01:25:27,580 --> 01:25:30,375
and loses their family home

1288
01:25:30,458 --> 01:25:33,002
and your father,
who's the main breadwinner,

1289
01:25:33,086 --> 01:25:35,588
has brain surgery
and can never work again,

1290
01:25:36,214 --> 01:25:38,925
you have to work for people that pay you.

1291
01:25:42,303 --> 01:25:45,265
Your family lost their money in 2008?

1292
01:25:45,682 --> 01:25:49,519
Um, yeah, but it took a while
for it all to really fall apart.

1293
01:25:49,602 --> 01:25:50,854
- Yeah.
- Um...

1294
01:25:52,147 --> 01:25:57,026
We lost our family home in 2014,
when I started working for Cambridge.

1295
01:26:09,497 --> 01:26:12,375
Alexander Nix appears
before Parliament's Media Committee

1296
01:26:12,458 --> 01:26:14,460
after previously refusing to testify

1297
01:26:14,544 --> 01:26:17,338
due to law enforcement investigations
into the firm.

1298
01:26:22,343 --> 01:26:23,887
- Hi, Jo, how are you?
- Hello.

1299
01:26:27,223 --> 01:26:29,058
The last time I was in London,

1300
01:26:29,142 --> 01:26:33,188
I remember considering challenging SCL

1301
01:26:34,522 --> 01:26:38,651
and running through my head, like,
how scary it was.

1302
01:26:40,195 --> 01:26:42,572
The Committee's very grateful, uh,
to Alexander Nix

1303
01:26:42,655 --> 01:26:45,408
for agreeing to come back
in front of the committee today

1304
01:26:45,491 --> 01:26:47,243
to answer our questions...

1305
01:26:47,327 --> 01:26:49,120
Now, to be back here and, uh...

1306
01:26:49,204 --> 01:26:52,457
these guys are down for the count and...

1307
01:26:52,540 --> 01:26:54,876
the villain is up against the wall.

1308
01:26:56,336 --> 01:26:59,505
You know,
does he have any allies left in the world

1309
01:27:00,298 --> 01:27:02,634
or has everybody turned against him?

1310
01:27:04,385 --> 01:27:05,720
Right.

1311
01:27:06,763 --> 01:27:09,849
I'd like to make
a few short clarifications.

1312
01:27:09,933 --> 01:27:12,560
Um, these will only take a few minutes,

1313
01:27:12,644 --> 01:27:17,273
uh, but it is important
to be able to frame, uh, my answers.

1314
01:27:17,357 --> 01:27:18,358
He's so nervous.

1315
01:27:18,441 --> 01:27:20,461
Mr. Nix, I'd be grateful if you'd start
with the committee's questions

1316
01:27:20,485 --> 01:27:22,087
and then see how we go
through the hearing.

1317
01:27:22,111 --> 01:27:26,449
Ordinarily, uh, I would respect that,
but these aren't ordinary circumstances,

1318
01:27:26,532 --> 01:27:30,203
and so, if I may, I'd like to start
with a very brief statement

1319
01:27:30,286 --> 01:27:31,663
just to set out my position.

1320
01:27:31,746 --> 01:27:34,332
I would rather take this
on a question by question basis

1321
01:27:34,415 --> 01:27:37,126
rather than being dealt with
as a statement at the beginning.

1322
01:27:37,377 --> 01:27:39,587
Mr. Collins,
you'll have plenty of opportunity,

1323
01:27:39,671 --> 01:27:43,174
as will all the Committee,
to ask me as many questions as you want,

1324
01:27:43,258 --> 01:27:45,134
but I have to insist on...

1325
01:27:45,218 --> 01:27:48,614
- How could you possibly start like that...
- It's not your place to insist.

1326
01:27:48,638 --> 01:27:51,724
"I accept that some of my answers
could have been clearer..."

1327
01:27:51,808 --> 01:27:54,560
So, instead,
you're just reading out the statement.

1328
01:27:54,644 --> 01:27:58,189
- Can you answer the first question...
- Why is he doing that?

1329
01:27:59,816 --> 01:28:02,456
- Could you repeat your first question?
- Yes, thank you.

1330
01:28:02,527 --> 01:28:05,238
You did pitch to work on the Referendum,

1331
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.

1332
01:28:09,534 --> 01:28:12,912
We're really scratching around here,
Mr. Farrelly. Um...

1333
01:28:13,329 --> 01:28:17,417
We've been working, or I've been working
with this company for 15 years. Um...

1334
01:28:17,500 --> 01:28:20,086
We've never undertaken an election
in the UK.

1335
01:28:20,253 --> 01:28:21,462
Well, I was...

1336
01:28:21,546 --> 01:28:23,732
- I hope I wasn't scratching around.
- That is not true.

1337
01:28:23,756 --> 01:28:26,759
I was comparing what you told us
with the evidence

1338
01:28:26,843 --> 01:28:28,344
that's subsequently emerged,

1339
01:28:28,428 --> 01:28:30,468
and you clearly felt...

1340
01:28:30,513 --> 01:28:33,641
...that the work that you've done, uh...

1341
01:28:33,725 --> 01:28:37,186
So, I got an email from Carole.

1342
01:28:37,270 --> 01:28:40,315
She knows that I met Julian Assange
in February.

1343
01:28:40,398 --> 01:28:42,025
Um...

1344
01:28:42,108 --> 01:28:47,155
And she knows that I donated to WikiLeaks
at some point in Bitcoin.

1345
01:28:49,073 --> 01:28:52,076
If she prints something about it today,
it's going to make...

1346
01:28:53,202 --> 01:28:56,372
my conversations with my own government
really difficult.

1347
01:28:56,914 --> 01:28:59,059
Um, it came up
in Brittany Kaiser's evidence,

1348
01:28:59,083 --> 01:29:02,628
because you spoke to us about, uh,
Julian Assange the last time you came,

1349
01:29:02,712 --> 01:29:06,049
saying that you made an attempt
to gain access to the emails

1350
01:29:06,132 --> 01:29:08,092
that Julian Assange had, um,

1351
01:29:08,176 --> 01:29:11,554
the Hillary Clinton emails,
in order to benefit your client,

1352
01:29:11,637 --> 01:29:12,554
the Trump campaign.

1353
01:29:12,555 --> 01:29:15,099
Well, these were very contentious emails,
potentially...

1354
01:29:15,183 --> 01:29:17,602
- Yeah.
- ...and we wanted to understand...

1355
01:29:17,685 --> 01:29:19,812
as did every journalist

1356
01:29:19,896 --> 01:29:22,565
and, I would say,
most political consultants

1357
01:29:22,648 --> 01:29:25,109
on both sides of the aisle
in the United States,

1358
01:29:25,193 --> 01:29:26,778
um, what was contained in them.

1359
01:29:26,861 --> 01:29:32,492
I don't think that curiosity
is indicative of anything nefarious.

1360
01:29:32,575 --> 01:29:36,245
Oh, my God. Carole published the article.

1361
01:29:38,122 --> 01:29:40,666
I didn't discuss the US election!

1362
01:29:40,750 --> 01:29:43,086
Oh, my God, this is insane!

1363
01:29:43,169 --> 01:29:44,337
Paul!

1364
01:29:44,420 --> 01:29:46,964
- Hello, how are you!
- Paul!

1365
01:29:47,507 --> 01:29:50,051
I have said to you, it's all coming out,

1366
01:29:50,134 --> 01:29:51,469
and the question is how.

1367
01:29:51,552 --> 01:29:54,347
I didn't conspire
to leak Hillary's emails,

1368
01:29:54,430 --> 01:29:58,184
and I have nothing...
...to do with Russia, so...

1369
01:29:58,267 --> 01:29:59,267
Yes.

1370
01:29:59,435 --> 01:30:01,020
The fact is...

1371
01:30:02,522 --> 01:30:05,233
- ...it looks like I did both.
- Does it look like you did both?

1372
01:30:05,316 --> 01:30:08,694
If I wasn't me, I would say yes,
that's what it looks like!

1373
01:30:11,155 --> 01:30:12,698
That's why I'm freaking out.

1374
01:30:12,782 --> 01:30:15,535
There's gonna be so many people
that literally never believe me.

1375
01:30:15,952 --> 01:30:18,496
I will die
with people still not believing me.

1376
01:30:18,579 --> 01:30:21,374
Uh, that is possible.

1377
01:30:21,624 --> 01:30:24,043
- That is definitely possible.
- I know!

1378
01:30:24,794 --> 01:30:26,170
Agh!

1379
01:30:27,380 --> 01:30:28,423
All right...

1380
01:30:29,006 --> 01:30:31,446
I think I need
to get the fuck out of here.

1381
01:30:34,887 --> 01:30:37,807
From where I'm sitting,
since you've come here today,

1382
01:30:37,890 --> 01:30:41,686
you have attempted to paint yourself
as the victim here,

1383
01:30:41,769 --> 01:30:46,566
though, by no stretch of the imagination
can you be seen as a victim.

1384
01:30:46,858 --> 01:30:50,194
Surely you can see that
you are not the victim here.

1385
01:30:51,028 --> 01:30:52,864
What if I was the victim?

1386
01:30:52,947 --> 01:30:56,868
What happens if, as some
of these investigations are concluded,

1387
01:30:56,951 --> 01:30:59,787
people realize
that actually we were simply...

1388
01:31:00,371 --> 01:31:04,917
the guys who were, uh,
perceived to have contributed

1389
01:31:05,001 --> 01:31:06,711
to the Trump campaign

1390
01:31:06,794 --> 01:31:10,923
and were wrongly accredited
with being the architects of Brexit

1391
01:31:11,340 --> 01:31:15,636
and as a result of the polarizing nature
of those two political campaigns,

1392
01:31:15,720 --> 01:31:18,723
the global liberal media took umbrage

1393
01:31:18,806 --> 01:31:21,684
and decided to put us in their crosshairs

1394
01:31:21,767 --> 01:31:26,147
and launch a coordinated attack on us
as a company

1395
01:31:26,230 --> 01:31:29,317
in order to destroy our reputations
and our business,

1396
01:31:29,400 --> 01:31:34,405
and all of this was underpinned
by a stream of allegations,

1397
01:31:34,489 --> 01:31:37,867
unfounded, groundless allegations
that came from Mr. Wylie,

1398
01:31:37,950 --> 01:31:41,287
who gave the media
the ammunition that they needed...

1399
01:31:41,662 --> 01:31:43,164
that they wanted,

1400
01:31:43,247 --> 01:31:46,417
to be able to attack us for something
that, in the case of Brexit,

1401
01:31:46,501 --> 01:31:47,502
we simply didn't do.

1402
01:31:47,585 --> 01:31:49,504
So you are the victim in all of this.

1403
01:31:50,796 --> 01:31:54,717
Well, if you're sitting where I am
right now, you'd probably feel...

1404
01:31:54,800 --> 01:31:56,177
uh...

1405
01:31:56,260 --> 01:31:57,470
...quite victimized.

1406
01:31:57,845 --> 01:31:59,514
Where the fuck is my passport?

1407
01:32:01,766 --> 01:32:03,809
Not having a good day right now.

1408
01:32:04,352 --> 01:32:05,645
Did I put it somewhere else?

1409
01:32:08,731 --> 01:32:09,857
Oh, my God.

1410
01:32:10,149 --> 01:32:12,568
I've never put it there before in my life.

1411
01:32:13,110 --> 01:32:15,613
Not that I'm thinking straight today,
so...

1412
01:32:19,992 --> 01:32:22,662
I'm flustered. Sorry, guys.

1413
01:32:27,416 --> 01:32:29,460
Coco Mademoiselle makes me feel better.

1414
01:32:30,503 --> 01:32:32,171
At least I smell good.

1415
01:32:38,678 --> 01:32:41,639
I have no idea what's gonna happen
in the next coming days.

1416
01:32:43,015 --> 01:32:46,352
I literally came back here
because I wanted to be cooperative,

1417
01:32:47,562 --> 01:32:48,938
I want to help.

1418
01:33:15,047 --> 01:33:17,192
Today, The Guardian newspaper
in Britain reports

1419
01:33:17,216 --> 01:33:19,468
that a senior executive
at Cambridge Analytica

1420
01:33:19,552 --> 01:33:22,305
met with Julian Assange from WikiLeaks,

1421
01:33:22,555 --> 01:33:25,933
which is the entity that distributed
the documents that Russia had stolen.

1422
01:33:27,935 --> 01:33:31,022
She says they discussed the US election.

1423
01:33:49,498 --> 01:33:52,585
The Mueller investigation called
when I booked my flight

1424
01:33:52,668 --> 01:33:55,087
and they decided to issue a subpoena.

1425
01:33:56,380 --> 01:34:00,635
We were talking to them
in a very, like, friendly, cooperative way

1426
01:34:00,718 --> 01:34:05,097
and then Carole's article completely
changed the way that they see me.

1427
01:34:06,557 --> 01:34:09,518
And, yeah, I...

1428
01:34:10,144 --> 01:34:12,438
worked at Cambridge Analytica

1429
01:34:12,521 --> 01:34:15,399
while they had Facebook data sets.

1430
01:34:16,400 --> 01:34:18,110
And, you know, I...

1431
01:34:19,612 --> 01:34:23,074
went to Russia one time
while I worked for Cambridge.

1432
01:34:23,157 --> 01:34:25,743
I visited Julian Assange
while I worked for Cambridge.

1433
01:34:25,951 --> 01:34:27,787
I once donated to WikiLeaks.

1434
01:34:27,870 --> 01:34:32,416
I pitched the Trump campaign
and wrote the first contract.

1435
01:34:33,167 --> 01:34:36,170
Like, all of these things
make it look like I am...

1436
01:34:36,504 --> 01:34:40,049
at the center of some big, crazy thing.

1437
01:34:41,258 --> 01:34:44,178
And I see that,
and I can't argue with that.

1438
01:34:46,055 --> 01:34:49,392
I might need to rethink the way
that I've been doing things

1439
01:34:49,475 --> 01:34:50,810
for the past few years.

1440
01:35:05,032 --> 01:35:08,661
This is a story
which we haven't published yet

1441
01:35:08,744 --> 01:35:11,288
talking about all the investigations

1442
01:35:11,372 --> 01:35:14,333
which have been kicked off
in Britain and the US

1443
01:35:14,417 --> 01:35:16,168
since the story came out.

1444
01:35:16,252 --> 01:35:19,630
So, there's an investigation by the FBI,

1445
01:35:19,714 --> 01:35:22,675
by the US, the SEC,

1446
01:35:22,758 --> 01:35:24,260
by the Department of Justice,

1447
01:35:24,343 --> 01:35:25,928
by Robert Mueller,

1448
01:35:26,011 --> 01:35:28,556
and by the Senate Intelligence Committee,

1449
01:35:28,639 --> 01:35:31,016
the Judiciary Committee,
the House Intelligence Committee.

1450
01:35:31,100 --> 01:35:33,060
And then these are all the ones
which are going on

1451
01:35:33,102 --> 01:35:34,770
which are connected in Britain.

1452
01:35:38,274 --> 01:35:41,277
Parliament spent 18 months investigating.

1453
01:35:42,403 --> 01:35:44,572
They called in all these witnesses.

1454
01:35:48,284 --> 01:35:52,037
And at the end of it,
their report says very clearly,

1455
01:35:52,121 --> 01:35:54,623
"Our electoral laws are not fit
for purpose."

1456
01:35:56,417 --> 01:36:00,421
We literally cannot have
a free and fair election in this country.

1457
01:36:01,881 --> 01:36:04,759
And we can't have it because of Facebook,

1458
01:36:04,925 --> 01:36:08,846
because of the tech giants
who are still completely unaccountable.

1459
01:36:13,058 --> 01:36:15,478
It sounds, like, quite apocalyptic.

1460
01:36:15,644 --> 01:36:19,815
But it does feel like we are entering
into a whole new era.

1461
01:36:20,858 --> 01:36:24,945
We can see that authoritarian governments
are on the rise.

1462
01:36:25,362 --> 01:36:31,243
And they're all using these politics
of hate and fear on Facebook.

1463
01:36:33,370 --> 01:36:34,765
Look at Brazil.

1464
01:36:34,789 --> 01:36:38,501
There's this right-wing extremist

1465
01:36:38,584 --> 01:36:39,919
who's been elected.

1466
01:36:40,002 --> 01:36:44,048
And we know that WhatsApp,
which is a part of Facebook,

1467
01:36:44,131 --> 01:36:49,929
was really clearly implicated
in the dissemination of fake news there.

1468
01:36:51,263 --> 01:36:53,474
And look at what happened in Myanmar.

1469
01:36:54,350 --> 01:36:56,727
There is evidence that Facebook was used

1470
01:36:56,811 --> 01:36:58,604
to incite racial hatred

1471
01:36:58,687 --> 01:37:00,731
which caused a genocide.

1472
01:37:07,488 --> 01:37:13,327
We also know that the Russian government
was using Facebook's tools in the US.

1473
01:37:17,081 --> 01:37:24,046
There's evidence that Russian intelligence
created fake Black Lives Matter memes.

1474
01:37:24,755 --> 01:37:28,509
And when people clicked on them,
they were taken to pages

1475
01:37:28,592 --> 01:37:32,388
where they were actually invited
to protests

1476
01:37:32,471 --> 01:37:35,724
that were organized
by the Russian government.

1477
01:37:35,808 --> 01:37:37,911
- Justice! Now!
- When do we want it?

1478
01:37:37,935 --> 01:37:40,080
At the same time,
they were setting up pages

1479
01:37:40,104 --> 01:37:44,191
targeting adversary groups,
like Blue Lives Matter.

1480
01:37:45,818 --> 01:37:48,696
It's about stoking fear and hate

1481
01:37:48,779 --> 01:37:51,657
to turn the country against itself.

1482
01:37:52,700 --> 01:37:54,493
Divide and conquer.

1483
01:37:57,329 --> 01:37:58,998
White power!

1484
01:37:59,456 --> 01:38:01,333
Fascist and proud!

1485
01:38:04,461 --> 01:38:07,965
Fuck Donald Trump! Fuck Donald Trump!

1486
01:38:08,883 --> 01:38:12,136
These platforms
which were created to connect us

1487
01:38:12,553 --> 01:38:14,847
have now been weaponized.

1488
01:38:16,765 --> 01:38:20,227
And it's impossible to know what is what

1489
01:38:20,311 --> 01:38:24,315
because it's happening
on exactly the same platforms

1490
01:38:24,398 --> 01:38:27,985
that we chat to our friends
or share baby photos.

1491
01:38:30,404 --> 01:38:32,489
Nothing is what it seems.

1492
01:38:45,127 --> 01:38:47,567
- Hi, how are you?
- Doing wonderful, yourself?

1493
01:38:47,671 --> 01:38:48,923
I'm all right.

1494
01:38:49,006 --> 01:38:55,012
Um, I stayed here last week
and I checked in a suitcase and two bags.

1495
01:38:55,095 --> 01:38:58,474
And I had to go to the airport and just,
like, left.

1496
01:38:58,557 --> 01:39:00,434
So my bags have been here for a week.

1497
01:39:06,941 --> 01:39:08,984
My guest, Carole Cadwalladr,

1498
01:39:09,068 --> 01:39:12,363
writes for the British newspapers
The Observer and The Guardian.

1499
01:39:12,863 --> 01:39:15,282
Can you just say a little bit more
about the Facebook data?

1500
01:39:15,824 --> 01:39:20,871
This thing of the data,
so how Americans were targeted,

1501
01:39:20,955 --> 01:39:22,998
and what they were targeted with,

1502
01:39:23,290 --> 01:39:27,544
is a sort of key part
of Mueller's investigation.

1503
01:39:30,839 --> 01:39:34,718
I am headed to Washington, DC,

1504
01:39:34,969 --> 01:39:38,430
for my testimony
for the Mueller investigation.

1505
01:39:41,767 --> 01:39:45,270
I definitely didn't think
that while we're sitting there

1506
01:39:45,354 --> 01:39:47,898
counting votes on our data screen

1507
01:39:47,982 --> 01:39:50,401
that some of those votes

1508
01:39:50,484 --> 01:39:56,281
were made by people
who had seen fake news stories

1509
01:39:56,365 --> 01:39:59,451
paid for by Russia on their Facebook page.

1510
01:40:01,120 --> 01:40:02,413
Maybe I wanted to believe

1511
01:40:02,496 --> 01:40:05,749
that Cambridge Analytica
was just the best.

1512
01:40:07,376 --> 01:40:09,586
It's a convenient story to believe.

1513
01:40:25,060 --> 01:40:28,731
...service down to our nation's capital,
Washington Reagan DC airport.

1514
01:40:35,195 --> 01:40:37,656
I don't think it's possible
to shed any of this.

1515
01:40:40,075 --> 01:40:42,911
You can't really
put something like this behind you.

1516
01:40:58,510 --> 01:41:01,805
"Youth engagement, persuasion...

1517
01:41:03,140 --> 01:41:04,516
apathy."

1518
01:41:04,600 --> 01:41:05,920
Malaysia, we're working in.

1519
01:41:05,976 --> 01:41:10,105
We did Lithuania, Romania,
Kenya, Ghana.

1520
01:41:10,689 --> 01:41:12,816
Oh, and the Brexit campaign, yeah.

1521
01:41:12,900 --> 01:41:14,693
But we don't talk about that.

1522
01:41:14,777 --> 01:41:17,821
Oops, we won!

1523
01:41:18,655 --> 01:41:20,949
Listening to this now,
it just sounds like...

1524
01:41:21,784 --> 01:41:25,913
a criminal admitting to everything
he’s done wrong around the world.

1525
01:41:27,498 --> 01:41:28,540
You know?

1526
01:41:29,291 --> 01:41:32,002
I'm just there,
nervously laughing along with him,

1527
01:41:32,086 --> 01:41:33,170
letting it happen.

1528
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.

1529
01:41:47,601 --> 01:41:48,727
So...

1530
01:41:51,814 --> 01:41:55,192
it makes me angry at myself that
I could sit through a meeting like that...

1531
01:41:55,943 --> 01:41:58,153
and not quit directly afterwards,

1532
01:41:59,321 --> 01:42:00,572
basically.

1533
01:42:04,243 --> 01:42:05,619
What was I doing?

1534
01:42:06,411 --> 01:42:08,664
What investigators
have you been talking to?

1535
01:42:09,623 --> 01:42:13,710
I'm currently working
to be as helpful as possible

1536
01:42:13,794 --> 01:42:17,422
to any government investigations
where I can provide assistance,

1537
01:42:17,506 --> 01:42:20,092
but I can't comment on that right now
while they're ongoing.

1538
01:42:28,725 --> 01:42:31,270
At this time,
you may use your cellular service.

1539
01:42:31,353 --> 01:42:35,023
However, larger electronic devices
must remain stowed.

1540
01:42:35,232 --> 01:42:37,109
Brittany made mistakes.

1541
01:42:38,819 --> 01:42:41,155
But I think it was very brave of her

1542
01:42:41,238 --> 01:42:44,199
to come out and then to keep cooperating

1543
01:42:44,283 --> 01:42:45,826
and not to walk away.

1544
01:42:48,620 --> 01:42:51,665
She is one of two people

1545
01:42:51,748 --> 01:42:56,378
who has blown the whistle
in any serious way on Cambridge Analytica.

1546
01:43:00,465 --> 01:43:01,967
We're all responsible.

1547
01:43:04,928 --> 01:43:07,806
So the question is,
what do we do with that responsibility?

1548
01:43:08,348 --> 01:43:09,683
Can we embrace it?

1549
01:43:12,394 --> 01:43:14,521
Happy that it's finally happening

1550
01:43:14,605 --> 01:43:18,275
so that I can just tell people
what happened and get everything...

1551
01:43:19,943 --> 01:43:20,944
on record

1552
01:43:22,154 --> 01:43:25,199
for this government, my government.

1553
01:43:47,095 --> 01:43:49,181
You remember, though,
Cambridge Analytica.

1554
01:43:49,431 --> 01:43:51,391
Its big claim in 2016

1555
01:43:51,475 --> 01:43:53,477
was that it had access to voter data

1556
01:43:53,685 --> 01:43:56,688
on all of the people voting
in the US election.

1557
01:43:58,273 --> 01:44:02,402
Well, just one of the 157 million people
who voted in that election,

1558
01:44:02,486 --> 01:44:06,365
a man called David Carroll,
asked them a very simple question:

1559
01:44:06,990 --> 01:44:09,826
"Can I see the data you have on me?"

1560
01:44:10,661 --> 01:44:12,621
And they refused to give it to him.

1561
01:44:14,248 --> 01:44:18,335
But crucially, today,
Cambridge Analytica pled guilty

1562
01:44:18,418 --> 01:44:22,422
at Hendon Magistrates' Court
for failing to comply with the ICO notice.

1563
01:44:40,482 --> 01:44:43,277
The Cambridge Analytica case
is behind me now.

1564
01:44:43,860 --> 01:44:46,738
They pleaded guilty
for not giving me my data,

1565
01:44:47,739 --> 01:44:50,242
and I'll probably never get it back.

1566
01:44:53,120 --> 01:44:55,330
By the time my daughter is 18,

1567
01:44:55,414 --> 01:44:58,750
she'll have 70,000 data points
defining her,

1568
01:44:58,917 --> 01:45:01,295
and currently she has no rights,

1569
01:45:01,628 --> 01:45:03,839
no control over that at all.

1570
01:45:06,216 --> 01:45:07,551
But the battle continues.

1571
01:45:13,432 --> 01:45:15,100
I don't have to tell you

1572
01:45:15,183 --> 01:45:17,102
that there is this dark undertow

1573
01:45:17,185 --> 01:45:19,563
which is connecting us all globally.

1574
01:45:19,646 --> 01:45:23,567
And it is flowing
via the technology platforms.

1575
01:45:24,026 --> 01:45:26,236
And that is why I am here

1576
01:45:26,320 --> 01:45:31,450
to address you directly,
the Gods of Silicon Valley.

1577
01:45:35,245 --> 01:45:36,997
Mark Zuckerberg,

1578
01:45:38,206 --> 01:45:40,000
and Sheryl Sandberg,

1579
01:45:40,083 --> 01:45:43,170
and Larry Page, and Sergey Brin,

1580
01:45:43,253 --> 01:45:44,671
and Jack Dorsey.

1581
01:45:46,381 --> 01:45:49,301
Because you set out to connect people

1582
01:45:49,801 --> 01:45:51,803
and you are refusing to acknowledge

1583
01:45:51,887 --> 01:45:55,682
that this same technology
is now driving us apart.

1584
01:45:56,767 --> 01:45:59,478
And what you don't seem to understand

1585
01:45:59,561 --> 01:46:03,357
is that this is bigger than you,
and it's bigger than any of us.

1586
01:46:03,440 --> 01:46:08,779
And it is not about left or right,
or leave or remain, or Trump or not.

1587
01:46:09,363 --> 01:46:11,281
It's about whether it's actually possible

1588
01:46:11,365 --> 01:46:13,742
to have a free and fair election
ever again.

1589
01:46:14,368 --> 01:46:18,038
And so my question to you is:
Is this what you want?

1590
01:46:19,247 --> 01:46:22,209
Is this how you want history
to remember you?

1591
01:46:23,293 --> 01:46:26,922
As the handmaidens to authoritarianism?

1592
01:46:27,464 --> 01:46:31,510
And my question to everybody else is,
is this what we want?

1593
01:46:31,968 --> 01:46:36,181
To sit back and play with our phones
as this darkness falls?

1594
01:46:41,770 --> 01:46:44,272
Who is logged into Facebook right now?

1595
01:46:46,274 --> 01:46:47,359
Almost everybody.

1596
01:46:49,069 --> 01:46:50,779
So, as individuals,

1597
01:46:50,862 --> 01:46:55,534
we can limit the flood of data
that we're leaking all over the place.

1598
01:46:55,617 --> 01:46:59,496
But there's no silver bullet.
There's no way to go off the grid.

1599
01:46:59,579 --> 01:47:02,207
So, you have to understand

1600
01:47:02,874 --> 01:47:05,877
how your data is affecting your life.

1601
01:47:07,087 --> 01:47:10,841
Our dignity as humans is at stake.

1602
01:47:20,434 --> 01:47:22,314
But the hardest part in all of this...

1603
01:47:22,394 --> 01:47:25,355
Got a lot of rough people
in those caravans. They are not a...

1604
01:47:25,439 --> 01:47:27,899
...is that these wreckage sites...

1605
01:47:27,983 --> 01:47:31,069
...and crippling divisions...

1606
01:47:33,989 --> 01:47:37,742
begin with the manipulation
of one individual.

1607
01:47:39,369 --> 01:47:40,537
Then another.

1608
01:47:42,164 --> 01:47:43,248
And another.

1609
01:47:47,794 --> 01:47:50,213
So, I can't help but ask myself:

1610
01:47:52,132 --> 01:47:53,758
Can I be manipulated?

1611
01:47:57,387 --> 01:47:58,388
Can you?