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