so if lately you’ve had the feeling that society is coming apart at the seams I’d
society is coming apart at the seams I’d
society is coming apart at the seams I’d like to offer you a simple explanation
like to offer you a simple explanation
like to offer you a simple explanation it’s because it is I’d like to share
it’s because it is I’d like to share
it’s because it is I’d like to share with you multiple ways in which we
with you multiple ways in which we
with you multiple ways in which we divide and dissects a society into
divide and dissects a society into
divide and dissects a society into different parts for the purposes of
different parts for the purposes of
different parts for the purposes of politics so just one brief technical
politics so just one brief technical
politics so just one brief technical note they were not able to update my
note they were not able to update my
note they were not able to update my slides to the most recent version so I’m
slides to the most recent version so I’m
slides to the most recent version so I’m going to skip a couple of slides in the
going to skip a couple of slides in the
going to skip a couple of slides in the interest of time so just don’t be
interest of time so just don’t be
interest of time so just don’t be alarmed when that happens
alarmed when that happens
alarmed when that happens so the first divide that I would like to
so the first divide that I would like to
so the first divide that I would like to share with you is the division between
share with you is the division between
share with you is the division between urban and rural and if you think about
urban and rural and if you think about
urban and rural and if you think about the politics of the United States are
the politics of the United States are
the politics of the United States are here in the UK this has become very
here in the UK this has become very
here in the UK this has become very clearly a divide that there are
clearly a divide that there are
clearly a divide that there are different sorts of populations in each
different sorts of populations in each
different sorts of populations in each of these areas and so I got interested
of these areas and so I got interested
of these areas and so I got interested in this a few years ago and started
in this a few years ago and started
in this a few years ago and started actually looking at the numbers of it
actually looking at the numbers of it
actually looking at the numbers of it and I went all the way back to the year
and I went all the way back to the year
and I went all the way back to the year 2000 presidential election which is kind
2000 presidential election which is kind
2000 presidential election which is kind of earliest that I was able to get data
of earliest that I was able to get data
of earliest that I was able to get data for and started looking at the dynamic
for and started looking at the dynamic
for and started looking at the dynamic of where voting behavior changes from
of where voting behavior changes from
of where voting behavior changes from Republican or Democrat at what
Republican or Democrat at what
Republican or Democrat at what population density so it turns out that
population density so it turns out that
population density so it turns out that in the 2000 presidential election that
in the 2000 presidential election that
in the 2000 presidential election that crossover point is at about a thousand
crossover point is at about a thousand
crossover point is at about a thousand 83 people per square mile and if we look
83 people per square mile and if we look
83 people per square mile and if we look at this again in 2004 it’s about a
at this again in 2004 it’s about a
at this again in 2004 it’s about a thousand eighty-five about the same and
thousand eighty-five about the same and
thousand eighty-five about the same and you’ll notice that it’s getting a little
you’ll notice that it’s getting a little
you’ll notice that it’s getting a little bit more extreme loo the redline Forbush
bit more extreme loo the redline Forbush
bit more extreme loo the redline Forbush getting a little higher percentage than
getting a little higher percentage than
getting a little higher percentage than in 2000 likewise in 2008 same divide
in 2000 likewise in 2008 same divide
in 2000 likewise in 2008 same divide 1024 people per-square-mile and in 2012
1024 people per-square-mile and in 2012
1024 people per-square-mile and in 2012 1100 and again at a stronger division
1100 and again at a stronger division
1100 and again at a stronger division and a 2016 the strongest division yet
and a 2016 the strongest division yet
and a 2016 the strongest division yet and at about 1,200 people per square
and at about 1,200 people per square
and at about 1,200 people per square mile so this brings to mind an
mile so this brings to mind an
mile so this brings to mind an interesting question if you know our
interesting question if you know our
interesting question if you know our politics are sort of centered around
politics are sort of centered around
politics are sort of centered around this model of urban versus rural when
this model of urban versus rural when
this model of urban versus rural when does it ever really change you can also
does it ever really change you can also
does it ever really change you can also see this represented in television and
see this represented in television and
see this represented in television and television over the last several decades
television over the last several decades
television over the last several decades has been one of the primary ways to
has been one of the primary ways to
has been one of the primary ways to segment and target portions of the
segment and target portions of the
segment and target portions of the population based on their interests so
population based on their interests so
population based on their interests so this just shows the difference between
this just shows the difference between
this just shows the difference between duck dynasty which is
duck dynasty which is
duck dynasty which is if Euler in rural areas and the Simpsons
if Euler in rural areas and the Simpsons
if Euler in rural areas and the Simpsons which is popular in more urban areas not
which is popular in more urban areas not
which is popular in more urban areas not surprisingly so a real question here is
surprisingly so a real question here is
surprisingly so a real question here is like what’s the actual cause of this and
like what’s the actual cause of this and
like what’s the actual cause of this and it one of the theories that I have is
it one of the theories that I have is
it one of the theories that I have is that it’s caused by the amount of
that it’s caused by the amount of
that it’s caused by the amount of infrastructure that’s required to serve
infrastructure that’s required to serve
infrastructure that’s required to serve a rural area with modern services and so
a rural area with modern services and so
a rural area with modern services and so I looked at the number of Road meters
I looked at the number of Road meters
I looked at the number of Road meters per person as population density
per person as population density
per person as population density increases and what do you want to know
increases and what do you want to know
increases and what do you want to know it crosses over at about a thousand
it crosses over at about a thousand
it crosses over at about a thousand people per square mile
people per square mile
people per square mile so we have very different political
so we have very different political
so we have very different political interests that are in play in this rural
interests that are in play in this rural
interests that are in play in this rural versus urban divide and according to the
versus urban divide and according to the
versus urban divide and according to the UN by 2030 two thirds of the world will
UN by 2030 two thirds of the world will
UN by 2030 two thirds of the world will live in cities so what does this mean
live in cities so what does this mean
live in cities so what does this mean politically when our poles stop in our
politically when our poles stop in our
politically when our poles stop in our elections stop being really questions
elections stop being really questions
elections stop being really questions about ideas and they start being more in
about ideas and they start being more in
about ideas and they start being more in question of geography and a referendum
question of geography and a referendum
question of geography and a referendum based on you know where you happen to
based on you know where you happen to
based on you know where you happen to live you settle into a kind of permanent
live you settle into a kind of permanent
live you settle into a kind of permanent state of majority for rural area for
state of majority for rural area for
state of majority for rural area for urban areas potentially so there’s
urban areas potentially so there’s
urban areas potentially so there’s people that kind of wanted to figure out
people that kind of wanted to figure out
people that kind of wanted to figure out a way around that because you know if
a way around that because you know if
a way around that because you know if you really want to have a balance of
you really want to have a balance of
you really want to have a balance of ideas that’s not maybe a a destination
ideas that’s not maybe a a destination
ideas that’s not maybe a a destination end point that those folks like so
end point that those folks like so
end point that those folks like so people have started to look more how do
people have started to look more how do
people have started to look more how do we sort of pit tribe versus tribe and
we sort of pit tribe versus tribe and
we sort of pit tribe versus tribe and one of the things that I’ve looked at is
one of the things that I’ve looked at is
one of the things that I’ve looked at is mapping out cities using social media
mapping out cities using social media
mapping out cities using social media data so this is a map of my hometown of
data so this is a map of my hometown of
data so this is a map of my hometown of Baltimore Maryland in the United States
Baltimore Maryland in the United States
Baltimore Maryland in the United States using data from Twitter and you can see
using data from Twitter and you can see
using data from Twitter and you can see on the far right on the green end this
on the far right on the green end this
on the far right on the green end this is kind of where the geeks are so I’m
is kind of where the geeks are so I’m
is kind of where the geeks are so I’m kind of there and on the far other end
kind of there and on the far other end
kind of there and on the far other end in the pink side is more like young
in the pink side is more like young
in the pink side is more like young african-american folks and then in the
african-american folks and then in the
african-american folks and then in the middle is kind of sports people are
middle is kind of sports people are
middle is kind of sports people are connected by sports the main point that
connected by sports the main point that
connected by sports the main point that I want to make here is that this is a
I want to make here is that this is a
I want to make here is that this is a very divided city the people on the pink
very divided city the people on the pink
very divided city the people on the pink side of things don’t know most of the
side of things don’t know most of the
side of things don’t know most of the people on the green side of things at
people on the green side of things at
people on the green side of things at all and and just to be really clear here
all and and just to be really clear here
all and and just to be really clear here each dot here is a social is a Twitter
each dot here is a social is a Twitter
each dot here is a social is a Twitter user each line is a friend connection
user each line is a friend connection
user each line is a friend connection between them so you can also see this in
between them so you can also see this in
between them so you can also see this in other cities this is Saint Louis
other cities this is Saint Louis
other cities this is Saint Louis Missouri
Missouri
Missouri and you may have heard about some of the
and you may have heard about some of the
and you may have heard about some of the unrest in Ferguson there in 2014 so the
unrest in Ferguson there in 2014 so the
unrest in Ferguson there in 2014 so the same pattern applies here we’re on the
same pattern applies here we’re on the
same pattern applies here we’re on the far
far
far right you’ve got like TEDx geeky people
right you’ve got like TEDx geeky people
right you’ve got like TEDx geeky people and then on the far left you’ve got
and then on the far left you’ve got
and then on the far left you’ve got young african-americans and in the upper
young african-americans and in the upper
young african-americans and in the upper part you’ve got young white people and
part you’ve got young white people and
part you’ve got young white people and you can see that there’s a division
you can see that there’s a division
you can see that there’s a division between young white people and young
between young white people and young
between young white people and young black people really pronounced here and
black people really pronounced here and
black people really pronounced here and st. Louis and so if you think about you
st. Louis and so if you think about you
st. Louis and so if you think about you know targeting each of these different
know targeting each of these different
know targeting each of these different sub communities with different kinds of
sub communities with different kinds of
sub communities with different kinds of messaging if you had access to all of
messaging if you had access to all of
messaging if you had access to all of this kind of data you would be able to
this kind of data you would be able to
this kind of data you would be able to do that pretty effectively it’s very
do that pretty effectively it’s very
do that pretty effectively it’s very difficult to get access to all of this
difficult to get access to all of this
difficult to get access to all of this network data though I had to really
network data though I had to really
network data though I had to really fight to get this stuff and build it and
fight to get this stuff and build it and
fight to get this stuff and build it and it’s quite a bit of work you might
it’s quite a bit of work you might
it’s quite a bit of work you might recognize this map this is Oxford and
recognize this map this is Oxford and
recognize this map this is Oxford and guess what all the blue stuff is I don’t
guess what all the blue stuff is I don’t
guess what all the blue stuff is I don’t think you’re gonna be too surprised it’s
think you’re gonna be too surprised it’s
think you’re gonna be too surprised it’s Oxford University down here you’ve got
Oxford University down here you’ve got
Oxford University down here you’ve got arts culture and food which is also very
arts culture and food which is also very
arts culture and food which is also very obviously a big thing here government
obviously a big thing here government
obviously a big thing here government business and tourism
business and tourism
business and tourism oh you FC has its own little node down
oh you FC has its own little node down
oh you FC has its own little node down there Henley and ban ray so because I
there Henley and ban ray so because I
there Henley and ban ray so because I included all of Oxfordshire so point
included all of Oxfordshire so point
included all of Oxfordshire so point being with this and I could go into a
being with this and I could go into a
being with this and I could go into a lot more detail on this in another
lot more detail on this in another
lot more detail on this in another context but it is really possible if you
context but it is really possible if you
context but it is really possible if you have this kind of network data to group
have this kind of network data to group
have this kind of network data to group people by kind of their interests and
people by kind of their interests and
people by kind of their interests and start to target them with specific kinds
start to target them with specific kinds
start to target them with specific kinds of messages and I’m gonna skip Latvia
of messages and I’m gonna skip Latvia
of messages and I’m gonna skip Latvia you don’t get to see Lafayette sorry but
you don’t get to see Lafayette sorry but
you don’t get to see Lafayette sorry but it’s interesting though there you go
it’s interesting though there you go
it’s interesting though there you go Latvia
Latvia
Latvia so if you were going to attack Latvia
so if you were going to attack Latvia
so if you were going to attack Latvia everyone if if you were going to attack
everyone if if you were going to attack
everyone if if you were going to attack this kind of situation and you were also
this kind of situation and you were also
this kind of situation and you were also trying to get at that social media data
trying to get at that social media data
trying to get at that social media data but without necessarily having it what
but without necessarily having it what
but without necessarily having it what might you do
it’s a battle for social media supremacy
it’s a battle for social media supremacy that could define this year’s US
that could define this year’s US
that could define this year’s US presidential election Donald Trump’s
presidential election Donald Trump’s
presidential election Donald Trump’s campaign used a london-based data
campaign used a london-based data
campaign used a london-based data analytics company to help advise on
analytics company to help advise on
analytics company to help advise on strategy
September alone in the hope they
September alone in the hope they profiling
profiling
profiling since June a very sophisticated data
since June a very sophisticated data
since June a very sophisticated data analysis operation had been underway
analysis operation had been underway
analysis operation had been underway this involved a British data science
this involved a British data science
this involved a British data science turn in Cambridge analytical
turn in Cambridge analytical
turn in Cambridge analytical communication is fundamentally changing
communication is fundamentally changing
communication is fundamentally changing but if you’re gonna spend a billion
but if you’re gonna spend a billion
but if you’re gonna spend a billion dollars you want to be really ruthless
dollars you want to be really ruthless
dollars you want to be really ruthless about making sure that you’re focusing
about making sure that you’re focusing
about making sure that you’re focusing on the right people daily we’re updating
on the right people daily we’re updating
on the right people daily we’re updating or modeling with this data to show an
or modeling with this data to show an
or modeling with this data to show an accurate picture where the electorate
accurate picture where the electorate
accurate picture where the electorate stands that day today in the United
stands that day today in the United
stands that day today in the United States we have somewhere close to four
States we have somewhere close to four
States we have somewhere close to four five thousand data points on every
five thousand data points on every
five thousand data points on every individual app we re rated our polling
individual app we re rated our polling
individual app we re rated our polling and allowed us to see that a lot of
and allowed us to see that a lot of
and allowed us to see that a lot of these Midwestern Rust Belt states were
these Midwestern Rust Belt states were
these Midwestern Rust Belt states were one to three points closer than what
one to three points closer than what
one to three points closer than what most people thought how did you know
most people thought how did you know
most people thought how did you know what the voter was this year was not
what the voter was this year was not
what the voter was this year was not going to be what happened in 2012
going to be what happened in 2012
going to be what happened in 2012 clearly other groups weren’t as dynamic
clearly other groups weren’t as dynamic
clearly other groups weren’t as dynamic as you the ability to sort of shift the
as you the ability to sort of shift the
as you the ability to sort of shift the way you do what you do I think what we
way you do what you do I think what we
way you do what you do I think what we do differently is the combination of
do differently is the combination of
do differently is the combination of pulling of data science but these sorts
pulling of data science but these sorts
pulling of data science but these sorts of new technologies couple of social
of new technologies couple of social
of new technologies couple of social media incredibly powerful
become such a powerful tool in politics
become such a powerful tool in politics you did something that a lot of people
you did something that a lot of people
you did something that a lot of people who get paid a lot of money to do we’re
who get paid a lot of money to do we’re
who get paid a lot of money to do we’re not able to see and do which is you got
not able to see and do which is you got
not able to see and do which is you got this right Matt Donald Trump yet he
this right Matt Donald Trump yet he
this right Matt Donald Trump yet he should be kissing you today I love this
should be kissing you today I love this
should be kissing you today I love this quote there are no longer any experts
quote there are no longer any experts
quote there are no longer any experts except Cambridge analytical a were
except Cambridge analytical a were
except Cambridge analytical a were Trump’s digital team who figured out how
Trump’s digital team who figured out how
Trump’s digital team who figured out how to win it game over everyone I’m sorry
to win it game over everyone I’m sorry
to win it game over everyone I’m sorry these these other experts on anything so
these these other experts on anything so
these these other experts on anything so maybe a little hyperbole there just a
maybe a little hyperbole there just a
maybe a little hyperbole there just a little bit so the first thing I kind of
little bit so the first thing I kind of
little bit so the first thing I kind of want to show you here and I can’t go
want to show you here and I can’t go
want to show you here and I can’t go into this as in as much detail as I
into this as in as much detail as I
into this as in as much detail as I would like to I do intend to publish
would like to I do intend to publish
would like to I do intend to publish something on this on medium tomorrow
something on this on medium tomorrow
something on this on medium tomorrow this is the first time that this is
this is the first time that this is
this is the first time that this is being shown but this is basically a
being shown but this is basically a
being shown but this is basically a network map showing all of the
network map showing all of the
network map showing all of the interrelationships between Cambridge
interrelationships between Cambridge
interrelationships between Cambridge analytic
analytic
analytic the Trump campaign brexit and other
the Trump campaign brexit and other
the Trump campaign brexit and other players in that universe there’s a few
players in that universe there’s a few
players in that universe there’s a few key things there that I wanted to show
key things there that I wanted to show
key things there that I wanted to show out to point out to you now though in
out to point out to you now though in
out to point out to you now though in 1993 a company called strategic
1993 a company called strategic
1993 a company called strategic communication labs was founded by a
communication labs was founded by a
communication labs was founded by a fellow named Nigel Oakes now Nigel Oakes
fellow named Nigel Oakes now Nigel Oakes
fellow named Nigel Oakes now Nigel Oakes was sort of an interesting character and
was sort of an interesting character and
was sort of an interesting character and then in the 80s he dated the daughter of
then in the 80s he dated the daughter of
then in the 80s he dated the daughter of the Queen’s cousin and got thrown out of
the Queen’s cousin and got thrown out of
the Queen’s cousin and got thrown out of Windsor Castle at a party and around a
Windsor Castle at a party and around a
Windsor Castle at a party and around a little few years after that he started a
little few years after that he started a
little few years after that he started a firm called the behavioral dynamics
firm called the behavioral dynamics
firm called the behavioral dynamics Institute which he claimed that he
Institute which he claimed that he
Institute which he claimed that he started while he was a student at
started while he was a student at
started while he was a student at University College of London the only
University College of London the only
University College of London the only thing is that University of College
thing is that University of College
thing is that University of College University College of London has no
University College of London has no
University College of London has no record of Nyjah Lopes ever having been
record of Nyjah Lopes ever having been
record of Nyjah Lopes ever having been there at all claimed he majored in
there at all claimed he majored in
there at all claimed he majored in psychology so SEL was started with the
psychology so SEL was started with the
psychology so SEL was started with the aim of really influencing elections and
aim of really influencing elections and
aim of really influencing elections and political situations around the world
political situations around the world
political situations around the world and he did work in Indonesia and some
and he did work in Indonesia and some
and he did work in Indonesia and some other places and really got embedded in
other places and really got embedded in
other places and really got embedded in that kind of universe around 2005 he
that kind of universe around 2005 he
that kind of universe around 2005 he wanted to kind of revamp his company and
wanted to kind of revamp his company and
wanted to kind of revamp his company and so he took Vince investment money from a
so he took Vince investment money from a
so he took Vince investment money from a fellow named Vincent Cheng who is who
fellow named Vincent Cheng who is who
fellow named Vincent Cheng who is who many of you may know as being a uk-based
many of you may know as being a uk-based
many of you may know as being a uk-based real estate investor but he actually is
real estate investor but he actually is
real estate investor but he actually is Iranian and has ties to Russia as well
Iranian and has ties to Russia as well
Iranian and has ties to Russia as well which is interesting until 2015 he was
which is interesting until 2015 he was
which is interesting until 2015 he was the primary shareholder of SCL and in
the primary shareholder of SCL and in
the primary shareholder of SCL and in 2013 they aimed to start working on
2013 they aimed to start working on
2013 they aimed to start working on pains in the UK and the US so they
pains in the UK and the US so they
pains in the UK and the US so they started the firm Cambridge analytic as a
started the firm Cambridge analytic as a
started the firm Cambridge analytic as a subsidiary of SCL Cambridge analytic I
subsidiary of SCL Cambridge analytic I
subsidiary of SCL Cambridge analytic I was sort of meant to be this sort of
was sort of meant to be this sort of
was sort of meant to be this sort of clean operation that could be used in
clean operation that could be used in
clean operation that could be used in these kinds of Western democracies and
these kinds of Western democracies and
these kinds of Western democracies and not say in developing parts of the world
not say in developing parts of the world
not say in developing parts of the world SCL by contrast had been doing work for
SCL by contrast had been doing work for
SCL by contrast had been doing work for NATO and for the UK Ministry of Defence
NATO and for the UK Ministry of Defence
NATO and for the UK Ministry of Defence and other parts of the world
and other parts of the world
and other parts of the world specifically with control with the goal
specifically with control with the goal
specifically with control with the goal in mind of controlling behaviors of
in mind of controlling behaviors of
in mind of controlling behaviors of populations so for instance in
populations so for instance in
populations so for instance in Afghanistan and we’ll get back to more
Afghanistan and we’ll get back to more
Afghanistan and we’ll get back to more about that later in 2014 they found out
about that later in 2014 they found out
about that later in 2014 they found out about some research being done by a
about some research being done by a
about some research being done by a fella named Michael kasinski at
fella named Michael kasinski at
fella named Michael kasinski at University of Cambridge wherein he had
University of Cambridge wherein he had
University of Cambridge wherein he had asked people to take social media
asked people to take social media
asked people to take social media personality quizzes in doing that he
personality quizzes in doing that he
personality quizzes in doing that he vacuumed up several hundred million
vacuumed up several hundred million
vacuumed up several hundred million profiles of Facebook users in the United
profiles of Facebook users in the United
profiles of Facebook users in the United States a researcher at University of
States a researcher at University of
States a researcher at University of Cambridge named Alexander Cogan found
Cambridge named Alexander Cogan found
Cambridge named Alexander Cogan found out about this and thought that might be
out about this and thought that might be
out about this and thought that might be potential to commercialize this and he
potential to commercialize this and he
potential to commercialize this and he connected up with SCO it’s unclear who
connected up with SCO it’s unclear who
connected up with SCO it’s unclear who contacted whom he founded a company
contacted whom he founded a company
contacted whom he founded a company called global science research
called global science research
called global science research laboratories which was aimed at
laboratories which was aimed at
laboratories which was aimed at monetizing this and turning it into a
monetizing this and turning it into a
monetizing this and turning it into a product and it was sold to Cambridge
product and it was sold to Cambridge
product and it was sold to Cambridge analytic as best as the records can show
analytic as best as the records can show
analytic as best as the records can show right now in 2016 that technology was
right now in 2016 that technology was
right now in 2016 that technology was used in brexit and it was also used in
used in brexit and it was also used in
used in brexit and it was also used in the Trump campaign it was previously
the Trump campaign it was previously
the Trump campaign it was previously used in the Ted Cruz campaign in the
used in the Ted Cruz campaign in the
used in the Ted Cruz campaign in the United States and it is now on track to
United States and it is now on track to
United States and it is now on track to be used in France so how does this work
be used in France so how does this work
be used in France so how does this work they basically take and map personality
they basically take and map personality
they basically take and map personality characteristics like openness
characteristics like openness
characteristics like openness conscientiousness extraversion and
conscientiousness extraversion and
conscientiousness extraversion and things like neuroticism and
things like neuroticism and
things like neuroticism and agreeableness so this Ocean score the
agreeableness so this Ocean score the
agreeableness so this Ocean score the big five this became popular in the 80s
big five this became popular in the 80s
big five this became popular in the 80s and they map this to your social media
and they map this to your social media
and they map this to your social media characteristics so they can tell that if
characteristics so they can tell that if
characteristics so they can tell that if you like certain types of magazines or
you like certain types of magazines or
you like certain types of magazines or if you’re connected with certain types
if you’re connected with certain types
if you’re connected with certain types of people you’re more than likely to
of people you’re more than likely to
of people you’re more than likely to fall into one of these personalities
fall into one of these personalities
fall into one of these personalities profiles why is this important so in
profiles why is this important so in
profiles why is this important so in order to really manipulate the behavior
order to really manipulate the behavior
order to really manipulate the behavior of people in a broad context you need to
of people in a broad context you need to
of people in a broad context you need to have a strategy this is a slide from one
have a strategy this is a slide from one
have a strategy this is a slide from one of SC LS decks that was used in
of SC LS decks that was used in
of SC LS decks that was used in Afghanistan and basically the you
Afghanistan and basically the you
Afghanistan and basically the you overall thought processes if you have an
overall thought processes if you have an
overall thought processes if you have an objective you need to come up with
objective you need to come up with
objective you need to come up with strategic communication to go with it
strategic communication to go with it
strategic communication to go with it which means analyzing your target
which means analyzing your target
which means analyzing your target audience and then campaigning an
audience and then campaigning an
audience and then campaigning an intervention strategy around that so
intervention strategy around that so
intervention strategy around that so pretty much coming up with specific
pretty much coming up with specific
pretty much coming up with specific targeted messages that you know are
targeted messages that you know are
targeted messages that you know are gonna make your target population behave
gonna make your target population behave
gonna make your target population behave in a certain way so this is an example
in a certain way so this is an example
in a certain way so this is an example of a dashboard that they used for one of
of a dashboard that they used for one of
of a dashboard that they used for one of their products at SCL where they’re
their products at SCL where they’re
their products at SCL where they’re targeting young unmarried males in Libya
targeting young unmarried males in Libya
targeting young unmarried males in Libya and you can see that there are a whole
and you can see that there are a whole
and you can see that there are a whole variety of different metrics things like
variety of different metrics things like
variety of different metrics things like you know behavior intent and ability how
you know behavior intent and ability how
you know behavior intent and ability how they respond to power structures whether
they respond to power structures whether
they respond to power structures whether they like the idea of a common enemy and
they like the idea of a common enemy and
they like the idea of a common enemy and you can fine tune how you want to get
you can fine tune how you want to get
you can fine tune how you want to get the behavior of these different groups
the behavior of these different groups
the behavior of these different groups to change and then design a campaign
to change and then design a campaign
to change and then design a campaign intervention around that so the other
intervention around that so the other
intervention around that so the other piece of this that’s really important to
piece of this that’s really important to
piece of this that’s really important to consider is fake news now you’ve all
consider is fake news now you’ve all
consider is fake news now you’ve all heard about fake news a lot lately and
heard about fake news a lot lately and
heard about fake news a lot lately and it’s certainly making the headlines but
it’s certainly making the headlines but
it’s certainly making the headlines but the thing you have to understand about
the thing you have to understand about
the thing you have to understand about fake news is that it’s not simply about
fake news is that it’s not simply about
fake news is that it’s not simply about spreading misinformation it’s about two
spreading misinformation it’s about two
spreading misinformation it’s about two things it’s about greed because people
things it’s about greed because people
things it’s about greed because people are motivated to figure out how to make
are motivated to figure out how to make
are motivated to figure out how to make money off of people’s weaknesses and
money off of people’s weaknesses and
money off of people’s weaknesses and then secondly it’s motivated by trying
then secondly it’s motivated by trying
then secondly it’s motivated by trying to identify target audiences that can be
to identify target audiences that can be
to identify target audiences that can be used in this sort of target audience
used in this sort of target audience
used in this sort of target audience analysis that we talked about for
analysis that we talked about for
analysis that we talked about for behavior change so how do you actually
behavior change so how do you actually
behavior change so how do you actually do this in practice there’s something
do this in practice there’s something
do this in practice there’s something called Facebook dark posts now most of
called Facebook dark posts now most of
called Facebook dark posts now most of you are probably not using Facebook dark
you are probably not using Facebook dark
you are probably not using Facebook dark posts most of you are probably putting
posts most of you are probably putting
posts most of you are probably putting pictures of kittens and kids onto your
pictures of kittens and kids onto your
pictures of kittens and kids onto your page and articles that you think are
page and articles that you think are
page and articles that you think are interesting and people like them and
interesting and people like them and
interesting and people like them and whatnot
whatnot
whatnot dark posts are different dark posts are
dark posts are different dark posts are
dark posts are different dark posts are when you basically pay to advertise to
when you basically pay to advertise to
when you basically pay to advertise to specific sub target audiences and these
specific sub target audiences and these
specific sub target audiences and these advertisements only appear to them so if
advertisements only appear to them so if
advertisements only appear to them so if you’re a political campaign you can
you’re a political campaign you can
you’re a political campaign you can basically target Facebook dark posts at
basically target Facebook dark posts at
basically target Facebook dark posts at people that have certain personality
people that have certain personality
people that have certain personality characteristics that you want to behave
characteristics that you want to behave
characteristics that you want to behave in a certain way now note that behavior
in a certain way now note that behavior
in a certain way now note that behavior doesn’t necessarily mean that you are
doesn’t necessarily mean that you are
doesn’t necessarily mean that you are trying to get them to vote for your
trying to get them to vote for your
trying to get them to vote for your candidate you may also be trying to
candidate you may also be trying to
candidate you may also be trying to suppress votes for other candidates so
suppress votes for other candidates so
suppress votes for other candidates so this is a really powerful tactic and if
this is a really powerful tactic and if
this is a really powerful tactic and if you think about it it’s unregulated
you think about it it’s unregulated
you think about it it’s unregulated political speech people are putting this
political speech people are putting this
political speech people are putting this kind of stuff out there and no one knows
kind of stuff out there and no one knows
kind of stuff out there and no one knows what’s being said to whom or why here’s
what’s being said to whom or why here’s
what’s being said to whom or why here’s an example of three different messages
an example of three different messages
an example of three different messages that are distributed using Facebook dark
that are distributed using Facebook dark
that are distributed using Facebook dark posts and other similar
posts and other similar
posts and other similar technologies that were prepared by the
technologies that were prepared by the
technologies that were prepared by the John Bolton super PAC in the United
John Bolton super PAC in the United
John Bolton super PAC in the United States and you can see that they each of
States and you can see that they each of
States and you can see that they each of them uses different kinds of imagery
them uses different kinds of imagery
them uses different kinds of imagery ideally we could play these ads but we
ideally we could play these ads but we
ideally we could play these ads but we don’t have time so you can see Islamic
don’t have time so you can see Islamic
don’t have time so you can see Islamic radicals are killing the innocent that’s
radicals are killing the innocent that’s
radicals are killing the innocent that’s going to respond to somebody who’s
going to respond to somebody who’s
going to respond to somebody who’s fear-driven and more neurotic the one on
fear-driven and more neurotic the one on
fear-driven and more neurotic the one on the right with the sort of science II
the right with the sort of science II
the right with the sort of science II approach that might be somebody who’s a
approach that might be somebody who’s a
approach that might be somebody who’s a little bit more open and agreeable the
little bit more open and agreeable the
little bit more open and agreeable the one down on the left this is somebody
one down on the left this is somebody
one down on the left this is somebody who’s into tradition and honor you know
who’s into tradition and honor you know
who’s into tradition and honor you know with military symbols and that sort of
with military symbols and that sort of
with military symbols and that sort of thing so the real question is does this
thing so the real question is does this
thing so the real question is does this really work a fellow named Paul Olivia
really work a fellow named Paul Olivia
really work a fellow named Paul Olivia dije in Zurich started to put together
dije in Zurich started to put together
dije in Zurich started to put together kind of a dossier on everything he knew
kind of a dossier on everything he knew
kind of a dossier on everything he knew from Cambridge analytic oh and that was
from Cambridge analytic oh and that was
from Cambridge analytic oh and that was the research that I relied upon for the
the research that I relied upon for the
the research that I relied upon for the visualization I showed you earlier this
visualization I showed you earlier this
visualization I showed you earlier this fellow on the right is Michael Kaczynski
fellow on the right is Michael Kaczynski
fellow on the right is Michael Kaczynski at University of Cambridge who initially
at University of Cambridge who initially
at University of Cambridge who initially did some of this research and his basic
did some of this research and his basic
did some of this research and his basic point was that he knew that this was
point was that he knew that this was
point was that he knew that this was dangerous and he did not permit Cogan
dangerous and he did not permit Cogan
dangerous and he did not permit Cogan who wanted to kind of build this product
who wanted to kind of build this product
who wanted to kind of build this product to take his research but it appears he
to take his research but it appears he
to take his research but it appears he may have used it anyway it’s unclear but
may have used it anyway it’s unclear but
may have used it anyway it’s unclear but anyway if an article came out about this
anyway if an article came out about this
anyway if an article came out about this a few days ago where in you know all of
a few days ago where in you know all of
a few days ago where in you know all of these problems were kind of explored and
these problems were kind of explored and
these problems were kind of explored and immediately some folks started to kind
immediately some folks started to kind
immediately some folks started to kind of deny that this was really an issue
of deny that this was really an issue
of deny that this was really an issue people said oh well you know Trump
people said oh well you know Trump
people said oh well you know Trump secret sauce is just more ketchup and
secret sauce is just more ketchup and
secret sauce is just more ketchup and then you know other people kind of copy
then you know other people kind of copy
then you know other people kind of copy blogging from that and the bottom line
blogging from that and the bottom line
blogging from that and the bottom line is that we really don’t know what the
is that we really don’t know what the
is that we really don’t know what the effects of this kind of thing were or
effects of this kind of thing were or
effects of this kind of thing were or are going to be going forward because no
are going to be going forward because no
are going to be going forward because no one’s really studied this in any detail
one’s really studied this in any detail
one’s really studied this in any detail and it’s really unclear how it works
and it’s really unclear how it works
and it’s really unclear how it works because there’s not very much
because there’s not very much
because there’s not very much transparency around it so if you really
transparency around it so if you really
transparency around it so if you really want to kind of find out whether it
want to kind of find out whether it
want to kind of find out whether it works or not one way to do it is to ask
works or not one way to do it is to ask
works or not one way to do it is to ask the people who have used it Aaron Banks
the people who have used it Aaron Banks
the people who have used it Aaron Banks one of the primary funders of brexit
one of the primary funders of brexit
one of the primary funders of brexit says we created 1 million online
says we created 1 million online
says we created 1 million online followers that reached upwards of 25
followers that reached upwards of 25
followers that reached upwards of 25 million in most weeks the engagement was
million in most weeks the engagement was
million in most weeks the engagement was huge and our Facebook page gross still
huge and our Facebook page gross still
huge and our Facebook page gross still grows at 3 K a week so he’s funding it
grows at 3 K a week so he’s funding it
grows at 3 K a week so he’s funding it he thinks this works and if you think
he thinks this works and if you think
he thinks this works and if you think about it if you look at the results on
about it if you look at the results on
about it if you look at the results on the right you know really zero point
the right you know really zero point
the right you know really zero point nine seven percent of the population is
nine seven percent of the population is
nine seven percent of the population is what determined the difference between
what determined the difference between
what determined the difference between leave and remain so it doesn’t take a
leave and remain so it doesn’t take a
leave and remain so it doesn’t take a very big margin to influence behavior to
very big margin to influence behavior to
very big margin to influence behavior to change a major outcome like potentially
change a major outcome like potentially
change a major outcome like potentially the unraveling of the
the unraveling of the
the unraveling of the you can see in the United States a
you can see in the United States a
you can see in the United States a similar kind of result happened Trump
similar kind of result happened Trump
similar kind of result happened Trump won with minus two million eight hundred
won with minus two million eight hundred
won with minus two million eight hundred and sixty-four thousand nine hundred and
and sixty-four thousand nine hundred and
and sixty-four thousand nine hundred and seventy four votes amazing right our
seventy four votes amazing right our
seventy four votes amazing right our system is interesting we know and but he
system is interesting we know and but he
system is interesting we know and but he did prevail in the electoral college
did prevail in the electoral college
did prevail in the electoral college which is what enabled it but if you see
which is what enabled it but if you see
which is what enabled it but if you see this vector map that the the New York
this vector map that the the New York
this vector map that the the New York Times prepared the people that were in
Times prepared the people that were in
Times prepared the people that were in rural areas moved more to the right and
rural areas moved more to the right and
rural areas moved more to the right and people that were in urban areas moved
people that were in urban areas moved
people that were in urban areas moved more to the left so they exploited this
more to the left so they exploited this
more to the left so they exploited this divide between urban and rural to great
divide between urban and rural to great
divide between urban and rural to great ends and again it only took a tiny small
ends and again it only took a tiny small
ends and again it only took a tiny small change to have a dramatic effect on the
change to have a dramatic effect on the
change to have a dramatic effect on the outcome so what can we do about this
outcome so what can we do about this
outcome so what can we do about this going forward so I want to introduce you
going forward so I want to introduce you
going forward so I want to introduce you to three folks one of whom you know it’s
to three folks one of whom you know it’s
to three folks one of whom you know it’s the other two I’m not sure you do yet
the other two I’m not sure you do yet
the other two I’m not sure you do yet Steven K Bannon is Donald Trump’s chief
Steven K Bannon is Donald Trump’s chief
Steven K Bannon is Donald Trump’s chief political strategist and he’s also the
political strategist and he’s also the
political strategist and he’s also the former ahead of Breitbart news and he is
former ahead of Breitbart news and he is
former ahead of Breitbart news and he is really intent on building up a global
really intent on building up a global
really intent on building up a global audience of people that follow this kind
audience of people that follow this kind
audience of people that follow this kind of alt-right messaging and I could go
of alt-right messaging and I could go
of alt-right messaging and I could go into a great deal of detail about him
into a great deal of detail about him
into a great deal of detail about him but the thing you need to understand
but the thing you need to understand
but the thing you need to understand about Steven Bannon is that he is a
about Steven Bannon is that he is a
about Steven Bannon is that he is a believer in a book called the fourth
believer in a book called the fourth
believer in a book called the fourth turning the fourth turning basically
turning the fourth turning basically
turning the fourth turning basically pauses that there’s a generational model
pauses that there’s a generational model
pauses that there’s a generational model to history and that we can predict
to history and that we can predict
to history and that we can predict what’s going to happen at this moment in
what’s going to happen at this moment in
what’s going to happen at this moment in history by reading that book I won’t go
history by reading that book I won’t go
history by reading that book I won’t go into it now but he basically predicts a
into it now but he basically predicts a
into it now but he basically predicts a major crisis and a potential global war
major crisis and a potential global war
major crisis and a potential global war which he calls decisive okay so let’s
which he calls decisive okay so let’s
which he calls decisive okay so let’s keep that in mind second person is
keep that in mind second person is
keep that in mind second person is Vladislav Surkov he is the equivalent of
Vladislav Surkov he is the equivalent of
Vladislav Surkov he is the equivalent of Bannon to Vladimir Putin under the
Bannon to Vladimir Putin under the
Bannon to Vladimir Putin under the pseudonym of nettan dubov it’s key he
pseudonym of nettan dubov it’s key he
pseudonym of nettan dubov it’s key he wrote a straight short story called
wrote a straight short story called
wrote a straight short story called without sky I encourage you to google it
without sky I encourage you to google it
without sky I encourage you to google it and look it up it’s a short read but
and look it up it’s a short read but
and look it up it’s a short read but basically in that story which was
basically in that story which was
basically in that story which was published around the same time as the
published around the same time as the
published around the same time as the invasion of Ukraine or whatever that was
invasion of Ukraine or whatever that was
invasion of Ukraine or whatever that was in Ukraine it posits that there’s a
in Ukraine it posits that there’s a
in Ukraine it posits that there’s a concept called nonlinear war where there
concept called nonlinear war where there
concept called nonlinear war where there are no sides where we’re just in
are no sides where we’re just in
are no sides where we’re just in conflict all the time so I would argue
conflict all the time so I would argue
conflict all the time so I would argue that these three are the architects of
that these three are the architects of
that these three are the architects of the moment that we live in now and it is
the moment that we live in now and it is
the moment that we live in now and it is a very very very perilous time so in a
a very very very perilous time so in a
a very very very perilous time so in a few weeks we have the selection
few weeks we have the selection
few weeks we have the selection happening in
happening in
happening in France with marine lepen it’s you know
France with marine lepen it’s you know
France with marine lepen it’s you know according to this article from two days
according to this article from two days
according to this article from two days ago lepen is likely to win the first
ago lepen is likely to win the first
ago lepen is likely to win the first round of the presidential election but
round of the presidential election but
round of the presidential election but then losing the runoff two weeks later
then losing the runoff two weeks later
then losing the runoff two weeks later well we don’t know that we don’t know
well we don’t know that we don’t know
well we don’t know that we don’t know what’s gonna happen in France or in the
what’s gonna happen in France or in the
what’s gonna happen in France or in the Netherlands or in Germany or in
Netherlands or in Germany or in
Netherlands or in Germany or in Switzerland in Italy over the course of
Switzerland in Italy over the course of
Switzerland in Italy over the course of the next two years so I’d like to offer
the next two years so I’d like to offer
the next two years so I’d like to offer these items as a bit of a remedy or at
these items as a bit of a remedy or at
these items as a bit of a remedy or at least some things that we can all be
least some things that we can all be
least some things that we can all be doing to be on guard about this and if
doing to be on guard about this and if
doing to be on guard about this and if you’d like to take a photo of this slide
you’d like to take a photo of this slide
you’d like to take a photo of this slide I recommend it because it’s just a good
I recommend it because it’s just a good
I recommend it because it’s just a good checklist but I think we all need to be
checklist but I think we all need to be
checklist but I think we all need to be worried about exposing fake news
worried about exposing fake news
worried about exposing fake news especially fake news that’s being
especially fake news that’s being
especially fake news that’s being generated really just for greed we need
generated really just for greed we need
generated really just for greed we need to think about regulating election
to think about regulating election
to think about regulating election communications especially things like
communications especially things like
communications especially things like dark posts we need to develop a
dark posts we need to develop a
dark posts we need to develop a framework of data protections and ethics
framework of data protections and ethics
framework of data protections and ethics how are we going to use data we need to
how are we going to use data we need to
how are we going to use data we need to inoculate ourselves against the
inoculate ourselves against the
inoculate ourselves against the potential misuse of data for
potential misuse of data for
potential misuse of data for manipulating our political structures we
manipulating our political structures we
manipulating our political structures we need to fight societal fragmentation we
need to fight societal fragmentation we
need to fight societal fragmentation we should consider things like a national
should consider things like a national
should consider things like a national service program that can expose people
service program that can expose people
service program that can expose people with different backgrounds to each other
with different backgrounds to each other
with different backgrounds to each other so that they can become more accepting
so that they can become more accepting
so that they can become more accepting of their views and we should all be
of their views and we should all be
of their views and we should all be committing acts of journalism I’m not a
committing acts of journalism I’m not a
committing acts of journalism I’m not a journalist I’m a software developer but
journalist I’m a software developer but
journalist I’m a software developer but I care about the fate of the world and
I care about the fate of the world and
I care about the fate of the world and I’m really interested in figuring out
I’m really interested in figuring out
I’m really interested in figuring out how we can use all the data that we have
how we can use all the data that we have
how we can use all the data that we have to understand what’s going on better and
to understand what’s going on better and
to understand what’s going on better and the beauty is so much of it is available
the beauty is so much of it is available
the beauty is so much of it is available to all of us so we should be doing more
to all of us so we should be doing more
to all of us so we should be doing more of that to kind of develop our
of that to kind of develop our
of that to kind of develop our understanding of the world around us the
understanding of the world around us the
understanding of the world around us the other thing we need to consider is
other thing we need to consider is
other thing we need to consider is developing mimetic warfare counter
developing mimetic warfare counter
developing mimetic warfare counter response to some of these tactics the
response to some of these tactics the
response to some of these tactics the Albright has been very good at
Albright has been very good at
Albright has been very good at developing the mimetic warfare and if
developing the mimetic warfare and if
developing the mimetic warfare and if you see a lot of memes on the internet a
you see a lot of memes on the internet a
you see a lot of memes on the internet a lot of that is the product of a lot of
lot of that is the product of a lot of
lot of that is the product of a lot of experimentation and I won’t get into all
experimentation and I won’t get into all
experimentation and I won’t get into all of that now but if you want to learn
of that now but if you want to learn
of that now but if you want to learn more about mimetics check out Rickard
more about mimetics check out Rickard
more about mimetics check out Rickard Richard Dawkins book from 1976 called
Richard Dawkins book from 1976 called
Richard Dawkins book from 1976 called The Selfish Gene and he basically posits
The Selfish Gene and he basically posits
The Selfish Gene and he basically posits that memes work a lot like genes and the
that memes work a lot like genes and the
that memes work a lot like genes and the ideas that survive when I would also say
ideas that survive when I would also say
ideas that survive when I would also say we need to own our symbols of national
we need to own our symbols of national
we need to own our symbols of national unity and not surrender them to people
unity and not surrender them to people
unity and not surrender them to people on one side or the other so in closing I
on one side or the other so in closing I
on one side or the other so in closing I just want to remind us all that our
just want to remind us all that our
just want to remind us all that our democracies are incredibly fragile
democracies are incredibly fragile
democracies are incredibly fragile they’re incredibly vulnerable and
they’re incredibly vulnerable and
they’re incredibly vulnerable and they’ve never been more of all
they’ve never been more of all
they’ve never been more of all than they are right now we all have to
than they are right now we all have to
than they are right now we all have to take a stand and understand what’s
take a stand and understand what’s
take a stand and understand what’s actually happening in them and preserve
actually happening in them and preserve
actually happening in them and preserve the values that we all care about for
the values that we all care about for
the values that we all care about for future generations thank you
future generations thank you
future generations thank you [Applause]
”
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