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Herald (H): Yeah. Welcome to our next
talk, Social Cooling. You know, people say
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"I have no problem with surveillance. I
have nothing to hide," but then, you know,
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maybe the neighbors and maybe this and
maybe that. So, tonight we're going to
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hear Tijmen Schep who's from Holland. He's
a privacy designer and a freelance
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security researcher and he's gonna hold
a talk about how digital surveillance
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changes our social way of interacting. So,
please, let's have a hand for Tijmen Schep!
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Applause
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Tijmen Schep (TS): Hi everyone. Really
cool that you're all here and really happy
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to talk here. It's really an honor. My
name is Tijmen Schep and I am a technology
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critic. And that means that it's my job to
not believe [audio cuts out] tells us and
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that's really a lot of fun. [audio cuts
out] is, how do I get a wider audience
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involved in understanding technology and
the issues that are arising from
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technology? Because I believe that change
comes when the public demands it. I think
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that's really one of the important things
when change happens. And for me as a
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technology critic, for me words are very
much how I hack the system, how I try to
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hack this world. And so, tonight I'm going
to talk to you about one of these words
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that I think could help us. Framing the
issue is half the battle. [audio cuts out]
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and frame the problem - if we can explain,
what the problem is in a certain frame...
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that, you know, makes certain positions
already visible, that's really half the
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battle won. So, that frame is social
cooling. But before I go into it, I want
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to ask you a question. Who here recognizes
this? You're on Facebook or some other
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social site, and you click on the link
because you think "Oh I could [audio cuts
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out] listen [audio cuts out] could click
on this, but it might look bad. It might
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be remembered by someone. Some agency
might remember it, and I could click on
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it, but I'm hesitating to click."
Microphone buzzing
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laughter
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TS: That better? Can everyone hear me now?
Audience: No.
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TS: No. Okay, that... yeah. Should I start
again? Okay. So, you're on Facebook, and
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you're thinking "Oh, that's an interesting
link. I could click on that," but you're
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hesitating because maybe someone's gonna
remember
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that. And that might come back to me
later, and who here recognizes that
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feeling? So, pretty much almost everybody.
And that's increasingly what I find, when
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I talk about the issue, that people really
start to recognize this. And I think a
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word we could use to describe that is
"Click Fear." This hesitation, it could be
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click fear. And you're not alone.
Increasingly, we find that, research
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points that this is a wide problem, that
people are hesitating to click some of the
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links. For example, after the Snowden
revelations, people were less likely to
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research issues about terrorism and other
things on Wikipedia because they thought
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"Well, maybe the NSA wouldn't like it if I
[audio cuts out] that. Okay, not gonna
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move. And visiting Google as well. So this
is a pattern that there's research... are
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pointing to. And it's not very strange, of
course. I mean, we all understand that if
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you feel you're being
watched, you change your behavior. It's a
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very logical thing that we all understand.
And I believe that technology is really
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amplifying this effect. I think that's
something that we really have to come to
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grips with. And that's why I think social
cooling could be useful with that. Social
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cooling describes in a way how in
increasingly digital world, where our
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digital lives are increasingly digitized, it
becomes easier to feel this pressure, to
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feel these normative effects of these
systems. And very much you see that,
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because increasingly, your data is being
turned into thousands of scores by data
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brokers and other companies. And those
scores are increasing influences you're...
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influencing your chances in life. And this
is creating an engine of oppression, an
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engine of change that we have to
understand. And the fun thing is that in a
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way this idea is really being helped by
Silicon Valley, who for a long time has
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said "Data is the new gold," but they've
recently, in the last five years, changed
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that narrative. Now they're saying "Data
is the new oil," and that's really funny,
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because if data is the new oil, then
immediately you get the question "Wait,
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oil gave us global warming, so then, what
does data give us?" And I believe that if
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oil leads to global warming, then data
could lead to social cooling. That could
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be the word that we use for these negative
effects of big data. In order to really
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understand this, and go into it, we have
to look at three things. First, we're
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going to talk about the reputation
economy, how that system works. Second
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chapter, we're going to look at behavior
change, how it is influencing us and
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changing our behavior. And finally, to not
let you go home depressed, I'm gonna talk
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about how can we deal with this. So first.
The reputation economy. Already we've seen
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today that China is building this new
system, the social credit system. It's a
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system that will give every citizen in
China a score that basically represents
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how well-behaved they are. And it
will influence your ability to get a job,
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a loan, a visum and even a date. And for
example, the current version of the
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system, Sesame Credit, one of the early
prototypes, already gives everybody that
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wants to a score, but it also is connected
to the largest dating website in China.
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So, you can kind of find out "Is this
person that I'm dating... what kind of
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person is this? Is this something who's,
you know, well viewed by Chinese society?"
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This is where it gets really heinous for
me, because until now you could say "Well,
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these reputation systems, they're fair, if
you're a good person, you get a higher
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score. If you're bad person, you get a
lower score," but it's not that simple. I
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mean, your friends' score influences your
score, and your score influences your
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friends' score, and that's where you
really start to see how complex social
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pressures arrive, and where we can see the
effects of data stratification, where
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people are starting to think "Hey, who are
my friends, and who should I be friends
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with?" You could think "That only happens
in China. Those Chinese people are, you
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know, different." But the exact
same thing is happening here in the West,
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except we're letting the market build it.
I'll give you an example. This is a
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company called "deemly" - a Danish company
- and this is their video for their
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service.
Video narrator (VN): ... renting
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apartments from others, and she loves to
swap trendy clothes and dresses. She's
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looking to capture her first lift from a
RideShare app, but has no previous reviews
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to help support her.
Video background voices: Awww.
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VN: Luckily, she's just joined deemly,
where her positive feedback from the other
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sites appears as a deemly score, helping
her to win a RideShare in no time. Deemly
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is free to join and supports users across
many platforms, helping you to share and
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benefit from the great reputation you've
earned. Imagine the power of using your
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deemly score alongside your CV for a job
application...
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TS: Like in China.
VN: ... perhaps to help get a bank loan...
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TS: Like...
VN: or even to link to from your dating
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profile.
TS: Like in China!
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VN: Sign up now at deemly.co. Deemly:
better your sharing.
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Applause
TS: Thanks. There is a change. There is
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difference, though. The funny thing about
here is that it's highly invisible to us.
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The Chinese government is very open about
what they're building, but here we are
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very blind to what's going on. Mostly,
when we talk about these things, then
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we're talking about these systems that
give us a very clear rating, like Airbnb,
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Uber, and of course the Chinese system.
The thing is, most of these systems are
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invisible to us. There's a huge market of
data brokers who are, you know, not
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visible to you, because you are not the
customer. You are the product. And these
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data brokers, well, what they do is, they
gather as much data as possible about you.
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And that's not all. They then create up to
eight thousand scores about you. In the
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United States, these companies have up to
8,000 scores, and in Europe it's a little
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less, around 600. These are scores about
things like your IQ, your psychological
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profile, your gullibility, your religion,
your estimated life span. 8,000 of these
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different things about you. And how does
that work? Well, it works by machine
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learning. So, machine learning algorithms
can find patterns in society that we can
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really not anticipate. For example, let's
say you're a diabetic, and, well, let's
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say this data broker company has a mailing
list, or has an app, that diabetic
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patients use. And they also have the data
of these diabetic patients about what they
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do on Facebook. Well, there you can start
to see correlations. So, if diabetic
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patients more often like gangster-rap and
pottery on Facebook, well, then you could
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deduce from that if you also like
gangster-rap or pottery on Facebook, then
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perhaps you also are more likely to have
or get diabetes. It is highly
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unscientific, but this is how the system
works. And this is an example of how that
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works with just your Facebook scores.
Woman in the video: ... see was lowest about
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60% when it came to predicting whether a
user's parents were still together when
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they were 21. People whose parents
divorced before they were 21 tended to
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like statements about relationships. Drug
users were ID'd with about 65% accuracy.
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Smokers with 73%, and drinkers with 70%.
Sexual orientation was also easier to
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distinguish among men. 88% right there.
For women, it was about 75%. Gender, by
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the way, race, religion, and political
views, were predicted with high accuracy
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as well. For instance: White versus black:
95%.
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TS: So, the important thing to understand
here is that this isn't really about your
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data anymore. Like, oftentimes when we
talk about data protection, we talk about
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"Oh, I want to keep control of my data."
But this is their data. This data that
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they deduce, that they derive from your
data. These are opinions about you. And
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these things are what, you know, make it
so that even though you never filled in a
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psychological test, they'd have one. A
great example of that, how that's used, is
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a company called Cambridge Analytica. This
company has created detailed profiles
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about us through what they call
psychographics and I'll let them explain
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it themselves.
Man in the video: By having hundreds and
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hundreds of thousands of Americans
undertake this survey, we were able to
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form a
model to predict the personality of every
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single adult in the United States of
America. If you know the personality of
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the people you're targeting you can nuance
your messaging to resonate more
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effectively with those key audience
groups. So, for a highly neurotic and
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conscientious audience, you're going to
need a message that is rational and fair-
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based, or emotionally-based. In this case,
the threat of a burglary, and the
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insurance policy of a gun is very
persuasive. And we can see where these
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people are on the map. If we wanted to
drill down further, we could resolve the
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data to an individual level, where we have
somewhere close to four or five thousand
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data points on every adult in the United
States.
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TS: So, yeah. This is the company that
worked with both the... for the Brexit
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campaign and with the Trump campaign. Of
course, little after Trump campaign, all
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the data was leaked, so data on 200
million Americans was leaked, And
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increasingly, you can see
this data described as "modeled voter
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ethnicities and religions." So, this is
this derived data. You might think that
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when you go online and use Facebook and
use all these services, that advertisers
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are paying for you. That's a common
misperception. That's not really the case.
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What's really going on is that, according
to SSC research, the majority of the
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money made in this data broker market is
made from risk management. All right, so,
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in a way you could say that it's not
really marketers that are paying for you,
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it's your bank. It's ensurers. It's your
employer. It's governments. These kind of
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organizations are the ones who buy these
profiles. The most. More than the other
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ones. Of course, the promise of big data
is that you can then manage risk. Big data
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is the idea that with data you can
understand things and then manage them.
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So what really is innovation in this big
data world, this data economy, is the
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democratization of the background check.
That's really the core of this, this market
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that now you can find out everything about
everyone.
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So, yeah, now your... in past, only perhaps
your bank could know your credit score but
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now your green grocer knows your
psychological profile.
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Right that's a new level of, yeah, what's
going on here. It's not only inv... not
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only invisible but it's also huge
according to the same research by the FCC
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this market was already worth 150 billion
dollars in 2015. So, it's invisible, it's
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huge and hardly anyone knows about it. But
that's probably going to change. And that
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brings us to the second part: Behavioral
change. We already see this first part of
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this, how behavioral change is happening
through these systems. That's through outside
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influence and we've, we've talked a lot
about this in this conference. For example
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we see how Facebook and advertisers try to
do that. We've also seen how China is
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doing that, trying to influence you. Russia
has recently tried to use Facebook to
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influence the elections and of course
companies like Cambridge Analytica try to
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do the same thing.
And here you can have a debate on, you
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know, to what extent are they really
influencing us, but I think that's not
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actually the really, the most interesting
question. What interests me most of all is
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how we are doing it ourselves, how we are
creating new forms of self-censorship and
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and are proactively anticipating these
systems. Because once you realize that
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this is really about risk management you
start... and this is about banks and
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employers trying to understand you, people
start to understand that this will go beyond
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click fear, if you remember. This will go
beyond, this will become, you know,
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when people find out this will be, you
know, not getting a job for example.
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This'll be about getting really expensive
insurance. It'll be about all these kinds
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of problems and people are increasingly
finding this out. So for example in the
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United States if you... the IRS might now
use data profile... are now using data
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profiles to find out who they should
audit. So I was talking recently to a girl
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and and she said: "Oh I recently tweeted
about... a negative tweet about the IRS," and
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she immediately grabbed her phone to
delete it.
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When she realized that, you know, this
could now be used against her in a way.
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And that's the problem. Of course we see all
kinds of other crazy examples that the big...
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the audience that we measure... the wider public
is picking up on, like who... so we now have
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algorithms that can find out if you're gay
or not. And these things scare people and
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these things are something we have to
understand. So, chilling effects this what
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this boils down to. For me, more importantly
than these influences of these big
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companies and nation states is how people
themselves are experiencing these chilling
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effects like you yourself have as well.
That brings us back to social cooling. For
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me, social cooling is about these two
things combined at once and this
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increasing ability of agents and... and groups
to influence you and on the other hand the
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increasing willingness of people
themselves to change their own behavior to
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proactively engage with this issue.
There are three long-term consequences
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that I want to dive into. The first is how
this affects the individual, the second is
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how it affects society, and the third is
how it affects the market. So let's look
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the individual. Here we've seen, there's a
rising culture of self-censorship. It
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started for me with an article that I read in
New York Times, where a student was saying:
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"Well we're very very reserved." She's
going to do things like spring break.
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I said: "Well you don't have to defend
yourself later," so you don't do it.
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And what she's talking about, she's
talking about doing crazy things, you
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know, letting go, having fun. She's
worried that the next day it'll be on
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Facebook.
So what's happening here is that you do
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have all kinds of freedoms: You have the
freedom to look up things, you have the
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freedom to to say things, but you're
hesitating to use it. And that's really
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insidious. That has an effect on a wider
society and here we really see the
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societal value of privacy. Because in
society often minority values later become
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majority values. An example is... is weed.
I'm from... I'm from the Netherlands and
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there you see, you know, at first it's
something that you just don't do and it's
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you know a bit of a "uhh", but then "Oh, maybe
yeah, you should... you should try it as well," and
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people try it and slowly under the surface
of the society, people change their minds
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about these things. And then, after a while
it's like, you know, "What are we still
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worried about?"
How the same pattern help it happens of
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course with way bigger things like this:
Martin Luther King: "I must honestly say to
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you that I never intend to adjust myself
to racial segregation and discrimination."
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TS: This is the same pattern
that's happening
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for all kinds of things that that change
in society, and that's what privacy is so
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important for, and that's why it's so
important that people have the ability to
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look things up and to change their minds
and to talk about each other without
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feeling so watched all the time.
The third thing is how this impacts the
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market. Here we see very much the rise of
a culture of risk avoidance. An example
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here is that in
1995 already, doctors in New York were
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given scores, and what happened was that
the doctors who try to help advanced
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stage cancer patients, complex patients, who
try to do the operation, difficult
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operations, got a low score, because these
people more often died, while doctors that
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didn't lift a finger and didn't try to
help got a high score. Because, well, people
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didn't die. So you see here that these
systems that, they bring all kinds of
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perverse incentives. They, you know, they're
they lower the willingness for everybody
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to take a risk and in some areas of
society we really like people to take
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risks. They're like entrepreneurs, doctors.
So in the whole part you could say that
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this, what we're seeing here, is some kind
of trickle-down risk aversion, where
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the willing, the... the way that
companies and governments want to
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manage risk, that's trickling down to us.
And we're we of course want them to like
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us, want to have a job, we want to have
insurance, and then we increasingly start
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to think "Oh, maybe I should not do this." It's
a subtle effect. So how do we deal with
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this?
Well, together. I think this is a really
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big problem. I think this is such a big
problem that, that it can't be managed by
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just some, some hackers or nerds, building
something, or by politicians, making a law.
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This is a really a society-wide problem.
So I want to talk about all these groups
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that should get into this: the public,
politicians, business, and us.
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So the public. I think we have to talk
about and maybe extend the metaphor of the
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cloud and say we have to learn to see the
stars behind the cloud. Alright, that's one
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way that we could... that's a narrative we
could use. I really like to use humor to
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explain this to a wider audience, so for
example, last year I was part of an
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exhibits... helped develop exhibits about
dubious devices and one of the devices
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there was called "Taste your status"
which was a coffee machine that gave you
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coffee based on your area code. So if you
live in a good area code, you get nice coffee.
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You live in a bad area code, you get bad
coffee.
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music
laugher
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applause
I'll go into it but... these... often times
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you can use humor to explain these things
to a wider audience. I really like that
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method, that approach.
We've got a long way to go though. I mean,
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if we look at the long, you know, how long
it took for us to understand global
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warming, to really, you know, come to a stage
where most people understand what it is
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and care about it except Donald Trump.
Well, with data we really got a long way to
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go, we're really at the beginning of
understanding this issue like this.
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Okay, so the second group that has to
really wake up is politicians. And they have
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to understand that this is really about the
balance of power. This is really about
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power. And if you permit me, I'll go into
the big picture a little bit, as a media
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theorist. So this is called Giles Deleuze.
he's a French philosopher and he explained
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in his work something that I find really
useful, He said you have two systems of
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control in society and the one is the
institutional one and that's the one we
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all know.
You know that the judicial system so
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you're free to do what you want but then
you cross a line you cross a law and the
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police get you you go for every charge you
go to prison. That's the system we
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understand.
But he says there's another system which
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is the social system this is a social
pressure system and this for a long time
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wasn't really designed.
But now increasingly we are able to do
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that so this is the system where you
perform suboptimal behavior and then that
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gets measured and judged and then you get
subtly nudged in the right direction. And
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there's some very important differences
between these 2 systems. The institutional
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system you know it has this idea that
you're a free citizen that makes up your
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own mind and you know what social system
is like that's working all the time,
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constantly it doesn't matter if you're
guilty or innocent it's always trying to
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push you. The old system, the institutional
system is very much about punishment so if
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you
break the rules you get punishment but
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people sometimes don't really care about
punishment sometimes it's cool to get
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punishment. But the social system uses
something way more powerful which is the
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fear of exclusion. We are social animals
and we really care to belong to a group.
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The other difference is that it's very
important that the institutional system is
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accountable. You know democratically to us
how the social system at the moment is
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really really invisible like these
algorithms how they work where the data is
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going it's very hard to understand and of
course it's exactly what China loved so
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much about it right there's no you can
stand in front of a tank but you can't
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really stand in front of the cloud. So
yeah that's that's great it also helps me
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to understand when people say I have
nothing to hide. I really understand that
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because when people say I have nothing to
hide what they're saying is I have nothing
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to hide from the old system from the
classic system from the institutional
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system. They're saying I want to help the
police I trust our gover
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nment I trust our institutions and that's
actually really a positive thing to say.
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The thing is they don't really see the other
part of the system how increasingly there
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are parts that are not in your control
they're not democratically checked and that's
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really a problem. So the third thing that
I think we have to wake up is business,
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business has to see that this is not so
much a problem perhaps but that it could
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be an opportunity. I think I'm still
looking for a metaphor here but perhaps,
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if we you know again, compare this issue
to global warming we say that we need
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something like ecological food for data.
And but I don't know what that's gonna
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look like or how we're gonna explain that
maybe we have to talk about fast food
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versus fast data versus ecological data
but we need a metaphor here. Of course
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laws are also really helpful. So we might
get things like this. I'm actually working
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on this is funny. Or if things get really
out of hand we might get here, right?
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So luckily we see that in Europe
the the politicians are awake and are
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really trying to push this market I think
that's really great, so I think in the
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future we'll get to a moment where people
say well I prefer European smart products
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for example, I think that's a good thing I
think this is really positive. Finally I
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want to get to all of us what each of us
can do. I think here again there's a
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parallel to global warming where at its
core it's not so much about the new
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technology and all the issues, it's about
a new mindset, a new way of looking at the
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world. And I here think we have to stop
saying that we have nothing to hide for
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example. If I've learned anything in the
past years understanding and researching
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privacy and this big trade data market is
privacy is the right to be imperfect. All
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right increasing there's pressure to be
the perfect citizen to be the perfect
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consumer and privacy is a way of getting
out of that. So this is how I would
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reframe privacy it's not just being about
which bits and bytes go where but it's
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about you know the human right to be
imperfect cause course we are human we are
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all imperfect. Sometimes when I talk at
technology conference people say well
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privacy was just a phase. You know, it's
like ebb and flood in and we got it and
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it's gonna go away again, that's crazy you
know, you don't say women's rights were
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just a phase we had it for a while and
it's gonna go again. Right? And of course
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Edward Snowden explains it way better. He
says arguing that you don't care about the
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right to privacy because you have nothing
to hide it's no different than saying you
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don't care about free speech because you
have nothing to say. What an eloquent
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system admin. So I think what we have to
do strive for here is that we develop for
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more nuanced understanding of all these
issues. I think we have to go away from
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this idea that data more data is better,
data is automatically progress. No it's
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not data is a trade-off for example for
the individual more data might mean less
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psychological security, less willingness
to share, less willing to try things. For
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a country it might mean less autonomy for
citizens and citizens need their own
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autonomy they need to know what's going on
they need to be able to vote in their own
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autonomous way and decide what's what they
want. In business you could say more data
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might lead to less creativity right less
willingness to share new ideas to come up
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with new ideas - that's again an issue
there. So in conclusion social cooling is
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a way of understanding these issues or a
way of framing these issues that I think
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could be useful for us. That could help us
understand and engage with these issues.
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And yes social cooling is an alarm, it's
alarmist - it is we're trying to say this
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is the problem and we have to deal with
this. But it's also really about hope. All
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right. I trust not so much in technology I
trust in us in people that we can fix this
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once we understand the issue in the same
way that when we understood the problem
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with global warming we started to deal
with it. Where do it's
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gonna it's slow progress we're doing that
and we can do the same thing with data.
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It'll take a while but we'll get there.
And finally this is about starting to
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understand the difference between shallow
optimism and deep optimism. All right,
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oftentimes technology sectors right cool
into technology and we're going to fix
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this by creating an app and for me that's
you know ,They: "we have to be
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optimistic", that's very shallow optimism
the TEDx make optimism. Like true optimism
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recognizes that each technology comes with
a downside and we have to recognize that
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thats it's, that thats not a problem to,
to point out these problems it's a good
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thing if once you understand the problems
you can deal with them - and you know come
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up with better solutions. If we don't
change in this mindset then we might
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create the world where we're all more well
behaved but perhaps also a little bit
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less human. Thank you.
Applause
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H: Thank You Devin.
TS: You are welcome.
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Applause
H: We still have five more minutes we'll
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take some questions if you like. First
microphone number 2.
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Microphone 2 (M2): Hello, thanks that was
a really interesting talk. I have a
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question that I hope will work it's a bit
complicated there's a project called indie
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by a foundation called a sovereign
foundation do you know about it? Okay very
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great perfect so to just to quickly
explain these people want to create an
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identity layer that will be self sovereign
which means people can reveal what they
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want about themselves only when they want
but is one unique identity on the entire
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internet so that can potentially be very
liberating because you control all your
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identity and individual data. But at the
same time it could be used to enable
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something like the personal scores we were
showing earlier on so made me think about
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that and I wanted to know if you had an
opinion on this.
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TS: Yes well um the first thing I think
about is that as I try to explain you see
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a lot of initiatives have tried to be
about: "Oo you have to control your own
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data". But that's really missing the point
that it's no longer really about your data
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it's about this derived data and of course
it can help to to manage what you share
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you know then they can't derive anything
from it. But to little I see that
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awareness. Second of all this is very much
for me an example of what nerds and
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technologies are really good at it's like:
"oh we've got a social problem let's
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create a technology app and then we'll fix
it". Well what I'm trying to explain is
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that this is such a big problem that we
cannot fix this with just one group alone
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- not the politicians, not the designers,
not the Nerds this is something that we
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have to really get together you know grab
- fix together because this is such a
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fundamental issue right. The idea that
risk is a problem that we want to manage
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risk is such so deeply ingrained in people
you know such stuff based in fear is
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fundamental and it's everywhere so it's
not enough for one group to try to fix
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that it's something that we have to come
to grips with together.
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M2: Thanks a lot.
H: Ok there is a signal angel has a
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question from the internet I think.
Signal Angel (SigA): Yes and BarkingSheep
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is asking: "do you think there's a
relationship between self-censorship and
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echo chambers in a sense that people
become afraid to challenge their own
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belief and thus isolate themselves in
groups with the same ideology?".
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TS: That's, a that's a, that's a really
big answer to that one.
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pauses
TS: Actually, I was e-mailing Vince Cerf,
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00:30:31,440 --> 00:30:35,610
and miraculously he, he responded, and he
said what you really have to look for is
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this, not just a reputation economy, but
also the attention economy and how they're
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linked. So for a while I've been looking
for that, that link and there's a lot to
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00:30:45,280 --> 00:30:49,990
say there and there definitely is a link.
I think important to understand over to
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00:30:49,990 --> 00:30:53,540
get new ones here is that, I'm not saying
that everybody will become really well
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00:30:53,540 --> 00:30:59,700
behaved and gray book worm people. The
thing is that what this situation's
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00:30:59,700 --> 00:31:03,230
creating, is that we're all becoming
theater players while playing in identity
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00:31:03,230 --> 00:31:06,230
more and more, because we're watched more
of the time. And for some people that
404
00:31:06,230 --> 00:31:10,660
might mean that they're, you know, I think
most people will be more conservative and
405
00:31:10,660 --> 00:31:15,400
more careful, some people will go really
all out and they all enjoy the stage! You
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00:31:15,400 --> 00:31:18,850
know? We have those people as well, and I
think those people could really benefit
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00:31:18,850 --> 00:31:23,800
and that the attention economy could
really you know give them a lot of
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00:31:23,800 --> 00:31:26,859
attention through that. So I think
there's, there's a link there but I could
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00:31:26,859 --> 00:31:29,549
go on more but I think it's for now, where
I'm aware.
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00:31:29,549 --> 00:31:33,819
H: Okay, we're short on time, we'll take,
I'm sorry one more question. The number
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00:31:33,819 --> 00:31:36,850
one?
Microphone 1 (M1): So, the, I think the
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00:31:36,850 --> 00:31:38,710
audience you're talking about, ...
H: Louder, please.
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00:31:38,710 --> 00:31:44,350
M1: The the audience you're talking to
here, is already very aware but I'm asking
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00:31:44,350 --> 00:31:50,210
for, like tactics, or your tips, to spread
your message and to talk to people that
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00:31:50,210 --> 00:31:55,440
are in this, they say: "Uh, I don't care
they can surveil me.", like what's, what's
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00:31:55,440 --> 00:32:01,430
your approach, like in a practical way?
How do you actually do this?
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00:32:01,430 --> 00:32:08,230
TS: Yeah, so, I'm really glad to be here
because I am, yes, I am a nerd, but I'm
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00:32:08,230 --> 00:32:11,539
also a philosopher or thinker, you know
and, and that means that
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00:32:11,539 --> 00:32:15,820
for me what I work with, it's not just odd
Rhinos, but words and ideas. I think those
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00:32:15,820 --> 00:32:18,860
I've been trying to show can be really
powerful, like a word can be a really
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00:32:18,860 --> 00:32:29,229
powerful way to frame a debate or engage
people. So, I haven't found yet a way to
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00:32:29,229 --> 00:32:33,030
push all this tar. Like, I was making joke
that I can tell you in one sentence, what
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00:32:33,030 --> 00:32:36,500
privacy is and why it matters but I have
to give a whole talk before that, all
424
00:32:36,500 --> 00:32:39,530
right? Privacy is a right to be imperfect
but in order to understand that you have
425
00:32:39,530 --> 00:32:42,710
to understand the rise of the reputation
economy, and how it affects your chances
426
00:32:42,710 --> 00:32:47,061
in life. The fun thing is, that, that that
will happen by itself that people will
427
00:32:47,061 --> 00:32:50,700
become more aware of that, they will run
into these problems. They will not get a
428
00:32:50,700 --> 00:32:55,660
job or they might get other issues, and
then they will start to see the problem.
429
00:32:55,660 --> 00:32:59,150
And so my question not so much to help
people understand it, but to help them
430
00:32:59,150 --> 00:33:02,980
understand it before they run into the
wall, right? That's how usually society at
431
00:33:02,980 --> 00:33:06,530
the moment deals with technology problems.
It's like "Oh we'll, we'll, oh ... Oh?
432
00:33:06,530 --> 00:33:10,820
it's a problem? Oh well, now we'll try to
fix it." Well, I believe you can really
433
00:33:10,820 --> 00:33:15,020
see these problems come way earlier and I
think the humanity's, to come around from,
434
00:33:15,020 --> 00:33:19,630
is really helpful in that, and trying to
you know like, the lows are really,
435
00:33:19,630 --> 00:33:28,040
really clearly explaining what the problem
is in 1995. So yeah, that I think that, I
436
00:33:28,040 --> 00:33:32,530
don't have a short way of explaining, you
know, why privacy matters but I think
437
00:33:32,530 --> 00:33:38,220
it'll become easier over time as people
start to really feel these pressures.
438
00:33:38,220 --> 00:33:42,530
H: Sorry, thank you very much for the
question. I think we all should go out and
439
00:33:42,530 --> 00:33:49,320
spread the message. This talk is over, I'm
awfully sorry. When you people leave,
440
00:33:49,320 --> 00:33:51,620
please take your bottles, and your cups,
...
441
00:33:51,620 --> 00:33:54,190
applause
H: ... and all your junk, and thank you
442
00:33:54,190 --> 00:34:05,500
very much again Tijmen Schep!
applause
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00:34:05,500 --> 00:34:09,899
music
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00:34:09,899 --> 00:34:27,000
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