so if you’ve had the feeling over the last several months that society is
last several months that society is
last several months that society is being torn apart I’d like to offer you a
being torn apart I’d like to offer you a
being torn apart I’d like to offer you a simple explanation it actually is now
simple explanation it actually is now
simple explanation it actually is now you know we as humans divide ourselves
you know we as humans divide ourselves
you know we as humans divide ourselves into all sorts of interesting categories
into all sorts of interesting categories
into all sorts of interesting categories naturally one way that we do that is by
naturally one way that we do that is by
naturally one way that we do that is by organizing ourselves into cities and
organizing ourselves into cities and
organizing ourselves into cities and this actually is a visualization of the
this actually is a visualization of the
this actually is a visualization of the GDP of the United States split in half
GDP of the United States split in half
GDP of the United States split in half and what you can see here is that the
and what you can see here is that the
and what you can see here is that the most populated areas mostly on the
most populated areas mostly on the
most populated areas mostly on the coasts account for 50% of the GDP of the
coasts account for 50% of the GDP of the
coasts account for 50% of the GDP of the country while the entire rest of the
country while the entire rest of the
country while the entire rest of the country accounts for the rest and this
country accounts for the rest and this
country accounts for the rest and this is actually reflected in how the country
is actually reflected in how the country
is actually reflected in how the country voted back in November you can see that
voted back in November you can see that
voted back in November you can see that the bright blue areas there are areas
the bright blue areas there are areas
the bright blue areas there are areas that voted for Clinton and the areas in
that voted for Clinton and the areas in
that voted for Clinton and the areas in red where are people who voted for Trump
red where are people who voted for Trump
red where are people who voted for Trump and it was 2623 counties that voted for
and it was 2623 counties that voted for
and it was 2623 counties that voted for Trump and 489 for Clinton but yet
Trump and 489 for Clinton but yet
Trump and 489 for Clinton but yet Clinton got a majority of the vote so
Clinton got a majority of the vote so
Clinton got a majority of the vote so you know we see that this kind of rural
you know we see that this kind of rural
you know we see that this kind of rural divided rural urban divide happens in
divided rural urban divide happens in
divided rural urban divide happens in all sorts of political contexts around
all sorts of political contexts around
all sorts of political contexts around the world we saw it and brexit as well
the world we saw it and brexit as well
the world we saw it and brexit as well and so I’ve been digging into this to
and so I’ve been digging into this to
and so I’ve been digging into this to try to understand it a little bit better
try to understand it a little bit better
try to understand it a little bit better and so I went back to the year 2000 in
and so I went back to the year 2000 in
and so I went back to the year 2000 in the United States and tried to
the United States and tried to
the United States and tried to understand at what point people flipped
understand at what point people flipped
understand at what point people flipped over from voting from Republican to
over from voting from Republican to
over from voting from Republican to Democrat and it turns out that if you
Democrat and it turns out that if you
Democrat and it turns out that if you organize all of the counties in the
organize all of the counties in the
organize all of the counties in the country by their population density and
country by their population density and
country by their population density and then sort and group those you can see a
then sort and group those you can see a
then sort and group those you can see a clear crossover point and it turns out
clear crossover point and it turns out
clear crossover point and it turns out to be about a thousand people per square
to be about a thousand people per square
to be about a thousand people per square mile
mile
mile is when people flip their behavior from
is when people flip their behavior from
is when people flip their behavior from voting for a right-wing candidate to a
voting for a right-wing candidate to a
voting for a right-wing candidate to a left-wing candidate now we can see this
left-wing candidate now we can see this
left-wing candidate now we can see this again reflected in 2004 you can see the
again reflected in 2004 you can see the
again reflected in 2004 you can see the gray compared to 2000 and it sort of
gray compared to 2000 and it sort of
gray compared to 2000 and it sort of gets more extreme as we go over time but
gets more extreme as we go over time but
gets more extreme as we go over time but the crossover point still remains about
the crossover point still remains about
the crossover point still remains about the same about a thousand people per
the same about a thousand people per
the same about a thousand people per square mile so you can see that going
square mile so you can see that going
square mile so you can see that going all the way up into 2012 and 2016 and in
all the way up into 2012 and 2016 and in
all the way up into 2012 and 2016 and in 2016 indeed the division is greater in
2016 indeed the division is greater in
2016 indeed the division is greater in that in that year in last year’s
that in that year in last year’s
that in that year in last year’s election than it was in any previous
election than it was in any previous
election than it was in any previous year so I started to wonder well what
year so I started to wonder well what
year so I started to wonder well what might be driving
might be driving
might be driving some of this so I did another kind of
some of this so I did another kind of
some of this so I did another kind of visualization graph or what I do is took
visualization graph or what I do is took
visualization graph or what I do is took data from OpenStreetMap and looked at
data from OpenStreetMap and looked at
data from OpenStreetMap and looked at how much road mileage is necessary per
how much road mileage is necessary per
how much road mileage is necessary per person to support a specific population
person to support a specific population
person to support a specific population density and it turns out that when you
density and it turns out that when you
density and it turns out that when you get down to about a thousand people per
get down to about a thousand people per
get down to about a thousand people per square mile you end up kind of getting a
square mile you end up kind of getting a
square mile you end up kind of getting a flattening and the amount of road
flattening and the amount of road
flattening and the amount of road infrastructure that’s required and that
infrastructure that’s required and that
infrastructure that’s required and that of course also applies to sewers and
of course also applies to sewers and
of course also applies to sewers and other types of infrastructure it’s kind
other types of infrastructure it’s kind
other types of infrastructure it’s kind of the same as the physics of the you
of the same as the physics of the you
of the same as the physics of the you know circulatory system of an elephant
know circulatory system of an elephant
know circulatory system of an elephant versus a mouse that sort of thing it’s a
versus a mouse that sort of thing it’s a
versus a mouse that sort of thing it’s a similar kind of curve so you know that
similar kind of curve so you know that
similar kind of curve so you know that that sort of explains its some extent
that sort of explains its some extent
that sort of explains its some extent why we might be attenuated around this
why we might be attenuated around this
why we might be attenuated around this urban-rural divide and the idea that
urban-rural divide and the idea that
urban-rural divide and the idea that like people in cities are probably
like people in cities are probably
like people in cities are probably interested in different things in terms
interested in different things in terms
interested in different things in terms of their tax dollar spending you know
of their tax dollar spending you know
of their tax dollar spending you know things like public transportation or
things like public transportation or
things like public transportation or housing or health care versus people in
housing or health care versus people in
housing or health care versus people in remote areas who might be more
remote areas who might be more
remote areas who might be more interested in roads and gasoline and
interested in roads and gasoline and
interested in roads and gasoline and cars
cars
cars so I’ve also over the last few years
so I’ve also over the last few years
so I’ve also over the last few years been looking at other ways that we sort
been looking at other ways that we sort
been looking at other ways that we sort and divide ourselves this is a
and divide ourselves this is a
and divide ourselves this is a visualization of my hometown Baltimore
visualization of my hometown Baltimore
visualization of my hometown Baltimore Maryland in the United States you may
Maryland in the United States you may
Maryland in the United States you may know it from the wire it’s our little
know it from the wire it’s our little
know it from the wire it’s our little bit of marketing that we do for the city
bit of marketing that we do for the city
bit of marketing that we do for the city but what this is is a visualization of
but what this is is a visualization of
but what this is is a visualization of all the twitter users in the city that i
all the twitter users in the city that i
all the twitter users in the city that i could find at a specific point and each
could find at a specific point and each
could find at a specific point and each dot is a twitter user and each line is a
dot is a twitter user and each line is a
dot is a twitter user and each line is a relationship between them a friend
relationship between them a friend
relationship between them a friend follow relationship this is not a
follow relationship this is not a
follow relationship this is not a geographic map just a visualization of
geographic map just a visualization of
geographic map just a visualization of twitter users but what we find is that
twitter users but what we find is that
twitter users but what we find is that people sort themselves very neatly into
people sort themselves very neatly into
people sort themselves very neatly into kind of categories that are quite
kind of categories that are quite
kind of categories that are quite clearly identifiable so on the right
clearly identifiable so on the right
clearly identifiable so on the right where it says geeks and TEDx that’s kind
where it says geeks and TEDx that’s kind
where it says geeks and TEDx that’s kind of where I’m at I’m a geek and I do TEDx
of where I’m at I’m a geek and I do TEDx
of where I’m at I’m a geek and I do TEDx so I’m kind of in the second e’en geeks
so I’m kind of in the second e’en geeks
so I’m kind of in the second e’en geeks there and then on the far left is mostly
there and then on the far left is mostly
there and then on the far left is mostly younger mostly african-american kids who
younger mostly african-american kids who
younger mostly african-american kids who are into hip-hop and stuff like that and
are into hip-hop and stuff like that and
are into hip-hop and stuff like that and what’s kind of startling about this map
what’s kind of startling about this map
what’s kind of startling about this map is it really shows the racial
is it really shows the racial
is it really shows the racial segregation that exists in the city
segregation that exists in the city
segregation that exists in the city people on the far left have almost no
people on the far left have almost no
people on the far left have almost no idea that the people on the far I even
idea that the people on the far I even
idea that the people on the far I even exist when I’ve shown this map to people
exist when I’ve shown this map to people
exist when I’ve shown this map to people on the city they kind of scratch their
on the city they kind of scratch their
on the city they kind of scratch their head and go wow this reshapes my mental
head and go wow this reshapes my mental
head and go wow this reshapes my mental model of how I thought the city worked
model of how I thought the city worked
model of how I thought the city worked so when you see this kind of segregation
so when you see this kind of segregation
so when you see this kind of segregation you can also kind of spot the same
you can also kind of spot the same
you can also kind of spot the same pattern in guess which city this is this
pattern in guess which city this is this
pattern in guess which city this is this is
is
is Louis Missouri in the United States and
Louis Missouri in the United States and
Louis Missouri in the United States and if you recall you know we had a lot of
if you recall you know we had a lot of
if you recall you know we had a lot of violence in both st. Louis first in st.
violence in both st. Louis first in st.
violence in both st. Louis first in st. Louis and then in Baltimore and I
Louis and then in Baltimore and I
Louis and then in Baltimore and I predicted that we would probably see
predicted that we would probably see
predicted that we would probably see some violence in Baltimore were there to
some violence in Baltimore were there to
some violence in Baltimore were there to be a catalyzing incident and indeed we
be a catalyzing incident and indeed we
be a catalyzing incident and indeed we have the same pattern there we’ve got
have the same pattern there we’ve got
have the same pattern there we’ve got kind of startup geeky people on the
kind of startup geeky people on the
kind of startup geeky people on the right TEDx and then on the far left it’s
right TEDx and then on the far left it’s
right TEDx and then on the far left it’s mostly younger black folks listening to
mostly younger black folks listening to
mostly younger black folks listening to rap music and there’s very little
rap music and there’s very little
rap music and there’s very little overlap between these worlds and indeed
overlap between these worlds and indeed
overlap between these worlds and indeed you can see similar patterns here in
you can see similar patterns here in
you can see similar patterns here in Norway but you guys are a little bit
Norway but you guys are a little bit
Norway but you guys are a little bit more cohesive than saying mr. Baltimore
more cohesive than saying mr. Baltimore
more cohesive than saying mr. Baltimore you can see groups that clearly identify
you can see groups that clearly identify
you can see groups that clearly identify around football and sports maybe not
around football and sports maybe not
around football and sports maybe not surprisingly a lot of places innovation
surprisingly a lot of places innovation
surprisingly a lot of places innovation tech and education the Norway diaspora
tech and education the Norway diaspora
tech and education the Norway diaspora and Europe there’s sort of Norwegians
and Europe there’s sort of Norwegians
and Europe there’s sort of Norwegians all scattered throughout Europe that are
all scattered throughout Europe that are
all scattered throughout Europe that are plugged into this and you can see them
plugged into this and you can see them
plugged into this and you can see them clustered there arts and culture
clustered there arts and culture
clustered there arts and culture politics and governance activism and
politics and governance activism and
politics and governance activism and commentary a lot of writers here in
commentary a lot of writers here in
commentary a lot of writers here in Norway I found and then kind of
Norway I found and then kind of
Norway I found and then kind of mainstream media in the centre so the
mainstream media in the centre so the
mainstream media in the centre so the point of kind of showing you these
point of kind of showing you these
point of kind of showing you these divisions is like you know we as humans
divisions is like you know we as humans
divisions is like you know we as humans we have there’s a principle called
we have there’s a principle called
we have there’s a principle called homophily which is basically the birds
homophily which is basically the birds
homophily which is basically the birds of a feather kind of flock together and
of a feather kind of flock together and
of a feather kind of flock together and we group into little subgroups kind of
we group into little subgroups kind of
we group into little subgroups kind of naturally but what if people started to
naturally but what if people started to
naturally but what if people started to take advantage of those divisions and
take advantage of those divisions and
take advantage of those divisions and maybe even try to make them worse let’s
maybe even try to make them worse let’s
maybe even try to make them worse let’s take a look at this
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 it by Dong
analytics company to help it by Dong
analytics company to help it by Dong strategy since June a very sophisticated
strategy since June a very sophisticated
strategy since June a very sophisticated data analysis operation had been
data analysis operation had been
data analysis operation had been underway this involves a British data
underway this involves a British data
underway this involves a British data science firm in Cambridge analytical
science firm in Cambridge analytical
science firm 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 our modelling with this data to show an
our modelling with this data to show an
our modelling 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 or five thousand data points on every
or five thousand data points on every
or five thousand data points on every individual a query rated our polling and
individual a query rated our polling and
individual a query rated our polling and allowed us to see that a lot of these
allowed us to see that a lot of these
allowed us to see that a lot of these Midwestern Rust Belt states were one to
Midwestern Rust Belt states were one to
Midwestern Rust Belt states were one to three points closer than what most
three points closer than what most
three points closer than what most people thought
people thought
people thought [Music]
[Music]
[Music] how did you know what the voter was this
how did you know what the voter was this
how did you know what the voter was this year was not going to be what happened
year was not going to be what happened
year was not going to be what happened in 2012 clearly other groups weren’t as
in 2012 clearly other groups weren’t as
in 2012 clearly other groups weren’t as dynamic as you the ability to sort of
dynamic as you the ability to sort of
dynamic as you the ability to sort of shift the way you do what you did I
shift the way you do what you did I
shift the way you do what you did I think what we do differently is the
think what we do differently is the
think what we do differently is the combination of pulling a data science
combination of pulling a data science
combination of pulling a data science but these sorts of new technologies
but these sorts of new technologies
but these sorts of new technologies couple of social media incredibly
couple of social media incredibly
couple of social media incredibly powerful you did something that a lot of
powerful you did something that a lot of
powerful you did something that a lot of people who get paid a lot of money to do
people who get paid a lot of money to do
people who get paid a lot of money to do were not able to see and do which is you
were not able to see and do which is you
were not able to see and do which is you got this right
got this right
got this right Matt Donald Trump yet he should be
Matt Donald Trump yet he should be
Matt Donald Trump yet he should be kissing you today yeah so Cambridge
kissing you today yeah so Cambridge
kissing you today yeah so Cambridge analytic oh I love this quote there are
analytic oh I love this quote there are
analytic oh I love this quote there are no longer any experts except Cambridge
no longer any experts except Cambridge
no longer any experts except Cambridge gentlemen ago they were Trump’s digital
gentlemen ago they were Trump’s digital
gentlemen ago they were Trump’s digital team and figured out how to win I mean
team and figured out how to win I mean
team and figured out how to win I mean this is from their website this is
this is from their website this is
this is from their website this is propaganda that they put out and I use
propaganda that they put out and I use
propaganda that they put out and I use that word for a specific purpose because
that word for a specific purpose because
that word for a specific purpose because this is an actual propaganda firm you
this is an actual propaganda firm you
this is an actual propaganda firm you may not know that Cambridge analytic is
may not know that Cambridge analytic is
may not know that Cambridge analytic is a subsidiary of a firm called strategic
a subsidiary of a firm called strategic
a subsidiary of a firm called strategic communication labs or SCL on that
communication labs or SCL on that
communication labs or SCL on that company has a 20-year background in
company has a 20-year background in
company has a 20-year background in running Psychological operations or
running Psychological operations or
running Psychological operations or psyops in military contexts around the
psyops in military contexts around the
psyops in military contexts around the world including in Afghanistan and other
world including in Afghanistan and other
world including in Afghanistan and other recent Wars so let’s take a little look
recent Wars so let’s take a little look
recent Wars so let’s take a little look at what Cambridge analytically is doing
at what Cambridge analytically is doing
at what Cambridge analytically is doing in order to try to tip elections both in
in order to try to tip elections both in
in order to try to tip elections both in their US and brexit and in Kenya and in
their US and brexit and in Kenya and in
their US and brexit and in Kenya and in other places where they’ve been involved
other places where they’ve been involved
other places where they’ve been involved so what they do is they try to derive an
so what they do is they try to derive an
so what they do is they try to derive an ocean score this is a personality score
ocean score this is a personality score
ocean score this is a personality score for every adult that they can sort of
for every adult that they can sort of
for every adult that they can sort of cram into their database and ocean is
cram into their database and ocean is
cram into their database and ocean is another another word for is the Big Five
another another word for is the Big Five
another another word for is the Big Five personality score and it stands for
personality score and it stands for
personality score and it stands for openness concierge conscientiousness
openness concierge conscientiousness
openness concierge conscientiousness extraversion agreeableness and
extraversion agreeableness and
extraversion agreeableness and neuroticism and depending on how each
neuroticism and depending on how each
neuroticism and depending on how each individual kind of score is on each of
individual kind of score is on each of
individual kind of score is on each of these axes you can create targeted
these axes you can create targeted
these axes you can create targeted advertising that will modify your
advertising that will modify your
advertising that will modify your behavior now that’s an important point
behavior now that’s an important point
behavior now that’s an important point we’re not talking about necessarily
we’re not talking about necessarily
we’re not talking about necessarily changing your opinion about what
changing your opinion about what
changing your opinion about what candidate to vote for we’re talking
candidate to vote for we’re talking
candidate to vote for we’re talking about modifying your behavior and that
about modifying your behavior and that
about modifying your behavior and that might include getting you to argue with
might include getting you to argue with
might include getting you to argue with people it might include getting you not
people it might include getting you not
people it might include getting you not to vote and a whole variety of other
to vote and a whole variety of other
to vote and a whole variety of other potential behaviors so if we take a look
potential behaviors so if we take a look
potential behaviors so if we take a look at some other materials that SCO has put
at some other materials that SCO has put
at some other materials that SCO has put out over time this is a slide that was
out over time this is a slide that was
out over time this is a slide that was included in a
included in a
included in a talking about work that they were doing
talking about work that they were doing
talking about work that they were doing in Afghanistan and sort of complicated
in Afghanistan and sort of complicated
in Afghanistan and sort of complicated mumbo-jumbo on here but the key thing to
mumbo-jumbo on here but the key thing to
mumbo-jumbo on here but the key thing to kind of recognize with this is this one
kind of recognize with this is this one
kind of recognize with this is this one element here taa target audience
element here taa target audience
element here taa target audience analysis and what they’re doing there is
analysis and what they’re doing there is
analysis and what they’re doing there is basically saying there’s a slice of the
basically saying there’s a slice of the
basically saying there’s a slice of the population that we would like to get to
population that we would like to get to
population that we would like to get to behave in a certain way how do we send
behave in a certain way how do we send
behave in a certain way how do we send them messaging how do we give them
them messaging how do we give them
them messaging how do we give them information that’s going to get them to
information that’s going to get them to
information that’s going to get them to behave the way that we want them to
behave the way that we want them to
behave the way that we want them to behave okay so this is the technology
behave okay so this is the technology
behave okay so this is the technology that’s being deployed in elections in
that’s being deployed in elections in
that’s being deployed in elections in open democracies so this is another kind
open democracies so this is another kind
open democracies so this is another kind of a dashboard from an SEL piece that
of a dashboard from an SEL piece that
of a dashboard from an SEL piece that shows how they’re addressing able to
shows how they’re addressing able to
shows how they’re addressing able to address with very fine kind of
address with very fine kind of
address with very fine kind of granularity different aspects of a young
granularity different aspects of a young
granularity different aspects of a young unmarried males population in
unmarried males population in
unmarried males population in Afghanistan and of course that would be
Afghanistan and of course that would be
Afghanistan and of course that would be an important population to be able to
an important population to be able to
an important population to be able to kind of manipulate in a war context so
kind of manipulate in a war context so
kind of manipulate in a war context so how did they take this and apply it to
how did they take this and apply it to
how did they take this and apply it to kind of elections and everyday stuff
kind of elections and everyday stuff
kind of elections and everyday stuff that we do in our democracies what
that we do in our democracies what
that we do in our democracies what they’re doing is using what’s called
they’re doing is using what’s called
they’re doing is using what’s called Facebook dark posts now you’ve all seen
Facebook dark posts now you’ve all seen
Facebook dark posts now you’ve all seen Facebook advertising where you know
Facebook advertising where you know
Facebook advertising where you know you’ll see an ad for a product or
you’ll see an ad for a product or
you’ll see an ad for a product or something dark posts are a little bit
something dark posts are a little bit
something dark posts are a little bit different they’re an advertisement but
different they’re an advertisement but
different they’re an advertisement but it’s sent specifically to a very tiny
it’s sent specifically to a very tiny
it’s sent specifically to a very tiny targeted micro audience and no one else
targeted micro audience and no one else
targeted micro audience and no one else can see those except you and the
can see those except you and the
can see those except you and the advertiser so as political speech it’s
advertiser so as political speech it’s
advertiser so as political speech it’s completely unregulated no one knows what
completely unregulated no one knows what
completely unregulated no one knows what even messages have been sent out and
even messages have been sent out and
even messages have been sent out and indeed yesterday if you saw the news
indeed yesterday if you saw the news
indeed yesterday if you saw the news facebook under testimony to Congress
facebook under testimony to Congress
facebook under testimony to Congress admitted that they had received over a
admitted that they had received over a
admitted that they had received over a hundred thousand dollars in payments
hundred thousand dollars in payments
hundred thousand dollars in payments from Russian based companies to
from Russian based companies to
from Russian based companies to influence the US election that doesn’t
influence the US election that doesn’t
influence the US election that doesn’t even include the sort of work that
even include the sort of work that
even include the sort of work that Cambridge analytic acclaims to have been
Cambridge analytic acclaims to have been
Cambridge analytic acclaims to have been doing that’s just Russian companies
doing that’s just Russian companies
doing that’s just Russian companies trying to influence Americans so what
trying to influence Americans so what
trying to influence Americans so what does this look like in practice well it
does this look like in practice well it
does this look like in practice well it allows you to create different kinds of
allows you to create different kinds of
allows you to create different kinds of messaging that you can send to different
messaging that you can send to different
messaging that you can send to different people depending on you know sort of
people depending on you know sort of
people depending on you know sort of what their inclinations are so for
what their inclinations are so for
what their inclinations are so for somebody that’s driven by fear you can
somebody that’s driven by fear you can
somebody that’s driven by fear you can say Islamic radicals are killing the
say Islamic radicals are killing the
say Islamic radicals are killing the innocent or maybe somebody that’s going
innocent or maybe somebody that’s going
innocent or maybe somebody that’s going to respond to tradition and patriotism
to respond to tradition and patriotism
to respond to tradition and patriotism will respond to patriotic symbols well
will respond to patriotic symbols well
will respond to patriotic symbols well somebody else might be more convinced by
somebody else might be more convinced by
somebody else might be more convinced by a sort of a science logic reason based
a sort of a science logic reason based
a sort of a science logic reason based argument so it doesn’t work well erin
argument so it doesn’t work well erin
argument so it doesn’t work well erin banks one of the chief funders of brexit
banks one of the chief funders of brexit
banks one of the chief funders of brexit made claims that they created a one
made claims that they created a one
made claims that they created a one online followers that reached upwards of
online followers that reached upwards of
online followers that reached upwards of 25 millions on most week the engagement
25 millions on most week the engagement
25 millions on most week the engagement level was huge and our FB page still
level was huge and our FB page still
level was huge and our FB page still grows the 3k a week the key thing here
grows the 3k a week the key thing here
grows the 3k a week the key thing here is that all it took was six hundred and
is that all it took was six hundred and
is that all it took was six hundred and fifty thousand votes to sway the result
fifty thousand votes to sway the result
fifty thousand votes to sway the result in the brexit election and that’s zero
in the brexit election and that’s zero
in the brexit election and that’s zero point nine seven percent of the UK
point nine seven percent of the UK
point nine seven percent of the UK population likewise in the u.s. Trump
population likewise in the u.s. Trump
population likewise in the u.s. Trump lost by almost three million votes if
lost by almost three million votes if
lost by almost three million votes if you just looked at the popular vote but
you just looked at the popular vote but
you just looked at the popular vote but by targeting specific counties in
by targeting specific counties in
by targeting specific counties in specific states he was able to get the
specific states he was able to get the
specific states he was able to get the 70 thousand vote margin that was
70 thousand vote margin that was
70 thousand vote margin that was required in order to win the electoral
required in order to win the electoral
required in order to win the electoral college by 306 votes to 232 votes so
college by 306 votes to 232 votes so
college by 306 votes to 232 votes so I’ve been using some of this same
I’ve been using some of this same
I’ve been using some of this same methodology to try to study the news and
methodology to try to study the news and
methodology to try to study the news and to get a sense of what’s going on with
to get a sense of what’s going on with
to get a sense of what’s going on with this whole Trump Russia situation and
this whole Trump Russia situation and
this whole Trump Russia situation and SEL and Cambridge analytic and
SEL and Cambridge analytic and
SEL and Cambridge analytic and everything else and it’s it’s definitely
everything else and it’s it’s definitely
everything else and it’s it’s definitely overwhelming and I’m not going to go
overwhelming and I’m not going to go
overwhelming and I’m not going to go into the details of this map here
into the details of this map here
into the details of this map here because you can’t really read it but you
because you can’t really read it but you
because you can’t really read it but you know the idea here is that we can
know the idea here is that we can
know the idea here is that we can actually study what the relationships
actually study what the relationships
actually study what the relationships between all of these different entities
between all of these different entities
between all of these different entities and get some sense that kind of where
and get some sense that kind of where
and get some sense that kind of where things are going so on the left side of
things are going so on the left side of
things are going so on the left side of this graph is actually a lot of
this graph is actually a lot of
this graph is actually a lot of transactions involving Azerbaijani and
transactions involving Azerbaijani and
transactions involving Azerbaijani and Kazakhstan e financial transactions that
Kazakhstan e financial transactions that
Kazakhstan e financial transactions that Trump’s been engaged in and it’s very
Trump’s been engaged in and it’s very
Trump’s been engaged in and it’s very likely that that’s where the
likely that that’s where the
likely that that’s where the investigation is gonna go next and it’s
investigation is gonna go next and it’s
investigation is gonna go next and it’s very likely that he may be taken down by
very likely that he may be taken down by
very likely that he may be taken down by this so a lot of people ask me you know
this so a lot of people ask me you know
this so a lot of people ask me you know what’s going to happen and I think that
what’s going to happen and I think that
what’s going to happen and I think that at this stage you know we’ve got a
at this stage you know we’ve got a
at this stage you know we’ve got a tremendous conflict that’s been set up
tremendous conflict that’s been set up
tremendous conflict that’s been set up clearly you know there’s a lot of forces
clearly you know there’s a lot of forces
clearly you know there’s a lot of forces that are sort of moving in on Trump and
that are sort of moving in on Trump and
that are sort of moving in on Trump and he’s feeling threatened and you know
he’s feeling threatened and you know
he’s feeling threatened and you know whether you agree with right-wing or
whether you agree with right-wing or
whether you agree with right-wing or left-wing politics isn’t the point we
left-wing politics isn’t the point we
left-wing politics isn’t the point we just sort of have an attack on the
just sort of have an attack on the
just sort of have an attack on the system right now and whenever a conflict
system right now and whenever a conflict
system right now and whenever a conflict like this is resolved there’s a good
like this is resolved there’s a good
like this is resolved there’s a good chance that it could be dangerous and
chance that it could be dangerous and
chance that it could be dangerous and messy so I think we need to be able to
messy so I think we need to be able to
messy so I think we need to be able to expect that in addition to that I think
expect that in addition to that I think
expect that in addition to that I think we should probably expect to see kind of
we should probably expect to see kind of
we should probably expect to see kind of a continued assault on consensus reality
a continued assault on consensus reality
a continued assault on consensus reality the things that we all believe to be
the things that we all believe to be
the things that we all believe to be true will be tempted to fight with each
true will be tempted to fight with each
true will be tempted to fight with each other will be prompted to fight with
other will be prompted to fight with
other will be prompted to fight with each other and we should resist those
each other and we should resist those
each other and we should resist those temptations wherever we can and indeed
temptations wherever we can and indeed
temptations wherever we can and indeed you know we’ve already seen divisions in
you know we’ve already seen divisions in
you know we’ve already seen divisions in the right and left with the emergence of
the right and left with the emergence of
the right and left with the emergence of neo-nazi groups on the right and then
neo-nazi groups on the right and then
neo-nazi groups on the right and then increasing arguments on the left about
increasing arguments on the left about
increasing arguments on the left about whether it’s appropriate to use violence
whether it’s appropriate to use violence
whether it’s appropriate to use violence to fight such neo-nazi groups in
to fight such neo-nazi groups in
to fight such neo-nazi groups in addition to the other question that
addition to the other question that
addition to the other question that people ask me a lot is what should we be
people ask me a lot is what should we be
people ask me a lot is what should we be doing about this and you know I think
doing about this and you know I think
doing about this and you know I think clearly we need to protect our
clearly we need to protect our
clearly we need to protect our vulnerable democracies they are
vulnerable democracies they are
vulnerable democracies they are extremely vulnerable to attack as a
extremely vulnerable to attack as a
extremely vulnerable to attack as a technology and we need to be aware of
technology and we need to be aware of
technology and we need to be aware of that but a lot of the solutions that are
that but a lot of the solutions that are
that but a lot of the solutions that are being proposed really amount to kind of
being proposed really amount to kind of
being proposed really amount to kind of blaming the victim and saying like you
blaming the victim and saying like you
blaming the victim and saying like you know you need to be better educated you
know you need to be better educated you
know you need to be better educated you need to have browser plug-ins that are
need to have browser plug-ins that are
need to have browser plug-ins that are lurk people to spurious information and
lurk people to spurious information and
lurk people to spurious information and while that might be a reasonable
while that might be a reasonable
while that might be a reasonable approach it’s kind of the same as saying
approach it’s kind of the same as saying
approach it’s kind of the same as saying that our democracies are being attacked
that our democracies are being attacked
that our democracies are being attacked because they’re wearing a short skirt
because they’re wearing a short skirt
because they’re wearing a short skirt and that’s not OK we need to deal with
and that’s not OK we need to deal with
and that’s not OK we need to deal with the aggressors in this case and that
the aggressors in this case and that
the aggressors in this case and that includes Russia it includes SCL and
includes Russia it includes SCL and
includes Russia it includes SCL and Cambridge analytical and also the Mercer
Cambridge analytical and also the Mercer
Cambridge analytical and also the Mercer family that’s been funding Cambridge
family that’s been funding Cambridge
family that’s been funding Cambridge analytic equai tab it so you know I
analytic equai tab it so you know I
analytic equai tab it so you know I think we really have to you know start
think we really have to you know start
think we really have to you know start to focus on how do we attack the people
to focus on how do we attack the people
to focus on how do we attack the people who are would be attacking our
who are would be attacking our
who are would be attacking our democracies you know during peacetime
democracies you know during peacetime
democracies you know during peacetime and some people have even asked me like
and some people have even asked me like
and some people have even asked me like you know are we gonna be at war soon and
you know are we gonna be at war soon and
you know are we gonna be at war soon and I actually think we’re kind of at war
I actually think we’re kind of at war
I actually think we’re kind of at war now and you know whether it’s a new kind
now and you know whether it’s a new kind
now and you know whether it’s a new kind of cool war or a continuation of the
of cool war or a continuation of the
of cool war or a continuation of the Cold War I can’t say but I do believe
Cold War I can’t say but I do believe
Cold War I can’t say but I do believe that this war will be resolved the way
that this war will be resolved the way
that this war will be resolved the way that other wars have been in the past
that other wars have been in the past
that other wars have been in the past openness will assert itself over
openness will assert itself over
openness will assert itself over nationalism and fear and indeed it must
nationalism and fear and indeed it must
nationalism and fear and indeed it must because that is our one great prayer and
because that is our one great prayer and
because that is our one great prayer and true hope for a prosperous shared future
true hope for a prosperous shared future
true hope for a prosperous shared future thank you
thank you
thank you [Applause]
”
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