thank you thank you and hi everybody I me and mine who I am and I guess when we
me and mine who I am and I guess when we
me and mine who I am and I guess when we talk about data mining it’s not
talk about data mining it’s not
talk about data mining it’s not necessarily to talk about big data but
necessarily to talk about big data but
necessarily to talk about big data but we need to stress some information of
we need to stress some information of
we need to stress some information of what we mean by data mining data mining
what we mean by data mining data mining
what we mean by data mining data mining the way in which we search is different
the way in which we search is different
the way in which we search is different from what we are used to do we don’t
from what we are used to do we don’t
from what we are used to do we don’t search we don’t start from an hypothesis
search we don’t start from an hypothesis
search we don’t start from an hypothesis but we this data mining process search
but we this data mining process search
but we this data mining process search for a policies that there’s correlation
for a policies that there’s correlation
for a policies that there’s correlation among subsets of data and those
among subsets of data and those
among subsets of data and those correlations are somehow summarized in
correlations are somehow summarized in
correlations are somehow summarized in what is called a pattern and a pattern
what is called a pattern and a pattern
what is called a pattern and a pattern is basically a statement which is a sort
is basically a statement which is a sort
is basically a statement which is a sort of summary of all the instances there’s
of summary of all the instances there’s
of summary of all the instances there’s led to a sort of conclusion then a model
led to a sort of conclusion then a model
led to a sort of conclusion then a model is created and we are basically fitted
is created and we are basically fitted
is created and we are basically fitted to the model so a lot professor of
to the model so a lot professor of
to the model so a lot professor of giving a talk normally statistically
giving a talk normally statistically
giving a talk normally statistically wears a tie and it’s not dressed this
wears a tie and it’s not dressed this
wears a tie and it’s not dressed this way so I’m not fitting the model the key
way so I’m not fitting the model the key
way so I’m not fitting the model the key point here is that the pattern is not
point here is that the pattern is not
point here is that the pattern is not truthful across all data so I might not
truthful across all data so I might not
truthful across all data so I might not fit the pattern so I live in a networked
fit the pattern so I live in a networked
fit the pattern so I live in a networked Society so we live basically immersed in
Society so we live basically immersed in
Society so we live basically immersed in a number of connections all our data are
a number of connections all our data are
a number of connections all our data are we produce data data are produced on us
we produce data data are produced on us
we produce data data are produced on us data are referred on X so the part on it
data are referred on X so the part on it
data are referred on X so the part on it which is created on a number of other
which is created on a number of other
which is created on a number of other individuals a number of data maybe not
individuals a number of data maybe not
individuals a number of data maybe not personal identification information are
personal identification information are
personal identification information are referred to us no professor there for a
referred to us no professor there for a
referred to us no professor there for a time so we don’t talk about big data we
time so we don’t talk about big data we
time so we don’t talk about big data we moved to an interconnection in which
moved to an interconnection in which
moved to an interconnection in which basically all flows of information are
basically all flows of information are
basically all flows of information are continuously reshaped put
continuously reshaped put
continuously reshaped put later the pattern is changed we are fit
later the pattern is changed we are fit
later the pattern is changed we are fit and refit in the pattern and they are
and refit in the pattern and they are
and refit in the pattern and they are continuously changing we are even to the
continuously changing we are even to the
continuously changing we are even to the largest and forced to be permanently
largest and forced to be permanently
largest and forced to be permanently connected think about the switch to
connected think about the switch to
connected think about the switch to clouds services products basically John
clouds services products basically John
clouds services products basically John allows almost at all to have offline
allows almost at all to have offline
allows almost at all to have offline alternatives and in a sense this is a
alternatives and in a sense this is a
alternatives and in a sense this is a way in which the dynamic of our economy
way in which the dynamic of our economy
way in which the dynamic of our economy has been moving and transforming
has been moving and transforming
has been moving and transforming business in permanently connected people
business in permanently connected people
business in permanently connected people when I talk about permanently connected
when I talk about permanently connected
when I talk about permanently connected I’m not talking about only being
I’m not talking about only being
I’m not talking about only being interconnected with Internet I mean that
interconnected with Internet I mean that
interconnected with Internet I mean that all our transactions all our
all our transactions all our
all our transactions all our interrelations are mostly computer
interrelations are mostly computer
interrelations are mostly computer mediated so even what we do in our real
mediated so even what we do in our real
mediated so even what we do in our real life and the physical life it’s computer
life and the physical life it’s computer
life and the physical life it’s computer mediated think about a credit card
mediated think about a credit card
mediated think about a credit card transaction as an example and think
transaction as an example and think
transaction as an example and think about what we basically do moving around
about what we basically do moving around
about what we basically do moving around through all the devices we are using and
through all the devices we are using and
through all the devices we are using and all this process is basically enabling
all this process is basically enabling
all this process is basically enabling what borrowing from geography we can
what borrowing from geography we can
what borrowing from geography we can call remote sensing so without even
call remote sensing so without even
call remote sensing so without even perceiving it data on us our producers
perceiving it data on us our producers
perceiving it data on us our producers are in further referred we give up data
are in further referred we give up data
are in further referred we give up data continuously and there is a permanent
continuously and there is a permanent
continuously and there is a permanent interconnection the results is basically
interconnection the results is basically
interconnection the results is basically that we are assuming that we give up
that we are assuming that we give up
that we are assuming that we give up data we don’t even perceive that data
data we don’t even perceive that data
data we don’t even perceive that data are generated on us without our
are generated on us without our
are generated on us without our contributing to those data think about
contributing to those data think about
contributing to those data think about behavioral patterns which are supposed
behavioral patterns which are supposed
behavioral patterns which are supposed when we are searching the web so we
when we are searching the web so we
when we are searching the web so we reached a point in which the economy has
reached a point in which the economy has
reached a point in which the economy has been named by Al Gore the stalker
been named by Al Gore the stalker
been named by Al Gore the stalker economy basically it’s the situation in
economy basically it’s the situation in
economy basically it’s the situation in which businesses
which businesses
which businesses and governments but mostly businesses
and governments but mostly businesses
and governments but mostly businesses know about us much more than we do know
know about us much more than we do know
know about us much more than we do know that is from big data analysis pattern
that is from big data analysis pattern
that is from big data analysis pattern are extracted that actually classify us
are extracted that actually classify us
are extracted that actually classify us according to subsets of data data which
according to subsets of data data which
according to subsets of data data which we might not be even aware I’m not aware
we might not be even aware I’m not aware
we might not be even aware I’m not aware they’re moving in a certain way my hands
they’re moving in a certain way my hands
they’re moving in a certain way my hands but the pattern can spot it and act
but the pattern can spot it and act
but the pattern can spot it and act accordingly I prefer to talk in terms of
accordingly I prefer to talk in terms of
accordingly I prefer to talk in terms of the classifying society what is the
the classifying society what is the
the classifying society what is the classifying society is basically dead
classifying society is basically dead
classifying society is basically dead our environment our decision-making
our environment our decision-making
our environment our decision-making environment is permanently shaped and
environment is permanently shaped and
environment is permanently shaped and reshaped by these flows of information
reshaped by these flows of information
reshaped by these flows of information to think in clear terms all our search
to think in clear terms all our search
to think in clear terms all our search on web are just not objective searches
on web are just not objective searches
on web are just not objective searches but are personalized results so we move
but are personalized results so we move
but are personalized results so we move we do a search and the results have been
we do a search and the results have been
we do a search and the results have been getting or you are getting or different
getting or you are getting or different
getting or you are getting or different because they are personalized according
because they are personalized according
because they are personalized according to what the algorithm think beliefs
to what the algorithm think beliefs
to what the algorithm think beliefs there is more suitable for me or for you
there is more suitable for me or for you
there is more suitable for me or for you so our contextual decision-making
so our contextual decision-making
so our contextual decision-making environment is continuously changed and
environment is continuously changed and
environment is continuously changed and altered in this change so classify
altered in this change so classify
altered in this change so classify normally meant to a range in category
normally meant to a range in category
normally meant to a range in category and Google has clearly changed it and
and Google has clearly changed it and
and Google has clearly changed it and it’s just an example in classify
it’s just an example in classify
it’s just an example in classify arranging people or things never before
arranging people or things never before
arranging people or things never before was used for people the terms classified
was used for people the terms classified
was used for people the terms classified in categories according to shared
in categories according to shared
in categories according to shared qualities or characteristics and this
qualities or characteristics and this
qualities or characteristics and this shared qualities or characteristics
shared qualities or characteristics
shared qualities or characteristics which are gathered which are in third
which are gathered which are in third
which are gathered which are in third may not entirely correspond what we
may not entirely correspond what we
may not entirely correspond what we think we are and sometimes they even
think we are and sometimes they even
think we are and sometimes they even take priority I mean in the classifying
take priority I mean in the classifying
take priority I mean in the classifying society something more tricky if you
society something more tricky if you
society something more tricky if you want is happening we are used to more
want is happening we are used to more
want is happening we are used to more stable and less dynamic classification
stable and less dynamic classification
stable and less dynamic classification white man
white man
white man white women black men black women in all
white women black men black women in all
white women black men black women in all the time we have spots that some of them
the time we have spots that some of them
the time we have spots that some of them were too discriminatory so they are not
were too discriminatory so they are not
were too discriminatory so they are not acceptable in legal or ethical terms it
acceptable in legal or ethical terms it
acceptable in legal or ethical terms it took a number of years but we are living
took a number of years but we are living
took a number of years but we are living now it’s something different in which
now it’s something different in which
now it’s something different in which the pigeonholing is more transient so
the pigeonholing is more transient so
the pigeonholing is more transient so for a number of reasons we are pigeon
for a number of reasons we are pigeon
for a number of reasons we are pigeon holed in a number of cluster according
holed in a number of cluster according
holed in a number of cluster according to a number of data points results we
to a number of data points results we
to a number of data points results we don’t even know why a part of a woman
don’t even know why a part of a woman
don’t even know why a part of a woman would be in a specific cluster getting a
would be in a specific cluster getting a
would be in a specific cluster getting a specific context in real and digital
specific context in real and digital
specific context in real and digital life and this is all changing
life and this is all changing
life and this is all changing continuously adapting we have just heard
continuously adapting we have just heard
continuously adapting we have just heard about the machine learning and all those
about the machine learning and all those
about the machine learning and all those beautiful technologies advances up to
beautiful technologies advances up to
beautiful technologies advances up to the point that we don’t actually know
the point that we don’t actually know
the point that we don’t actually know and it’s not clearly readable which are
and it’s not clearly readable which are
and it’s not clearly readable which are the set of facts the data which gathered
the set of facts the data which gathered
the set of facts the data which gathered together lead to a pattern a statement
together lead to a pattern a statement
together lead to a pattern a statement which is user as a knowledge that is to
which is user as a knowledge that is to
which is user as a knowledge that is to act in the action it’s actually
act in the action it’s actually
act in the action it’s actually surrounding us think about personalized
surrounding us think about personalized
surrounding us think about personalized advertising think about the search and
advertising think about the search and
advertising think about the search and things similar to that so we are now
things similar to that so we are now
things similar to that so we are now living in a world in which the
living in a world in which the
living in a world in which the pigeonholing the classification are more
pigeonholing the classification are more
pigeonholing the classification are more dynamic continuously change and
dynamic continuously change and
dynamic continuously change and transient after five minutes or a few
transient after five minutes or a few
transient after five minutes or a few seconds we can be pigeonholed in
seconds we can be pigeonholed in
seconds we can be pigeonholed in different ways according to different
different ways according to different
different ways according to different criteria and those data that pigeon all
criteria and those data that pigeon all
criteria and those data that pigeon all may not even be strictly related as we
may not even be strictly related as we
may not even be strictly related as we shall see to us at all so
[Laughter]
[Laughter] I think this basically tell us much more
I think this basically tell us much more
I think this basically tell us much more than a long talk we react to context we
than a long talk we react to context we
than a long talk we react to context we react to stimulus and a number of you
react to stimulus and a number of you
react to stimulus and a number of you began to laugh or smile just watching
began to laugh or smile just watching
began to laugh or smile just watching this movies and abstracted from a
this movies and abstracted from a
this movies and abstracted from a commercial so this switch from more
commercial so this switch from more
commercial so this switch from more transient dynamic mostly unnoticed not
transient dynamic mostly unnoticed not
transient dynamic mostly unnoticed not visible classifications that reshape our
visible classifications that reshape our
visible classifications that reshape our decision-making context are the seminal
decision-making context are the seminal
decision-making context are the seminal switching to more natural life in which
switching to more natural life in which
switching to more natural life in which our right to be divergent if you want to
our right to be divergent if you want to
our right to be divergent if you want to be to react differently from what the
be to react differently from what the
be to react differently from what the pattern is suggesting you should do
pattern is suggesting you should do
pattern is suggesting you should do wearing a tie it’s becoming more and
wearing a tie it’s becoming more and
wearing a tie it’s becoming more and more problematic we’re of course we are
more problematic we’re of course we are
more problematic we’re of course we are used to systems in which we are somehow
used to systems in which we are somehow
used to systems in which we are somehow coerced forced to behave in a certain
coerced forced to behave in a certain
coerced forced to behave in a certain ways but we are moving away from that
ways but we are moving away from that
ways but we are moving away from that and we are now moving in a completely
and we are now moving in a completely
and we are now moving in a completely different environment in which the shape
different environment in which the shape
different environment in which the shape of the information the contextual
of the information the contextual
of the information the contextual decision-making is continually
decision-making is continually
decision-making is continually personalised honest and it’s changing so
personalised honest and it’s changing so
personalised honest and it’s changing so we switched from just a reshaping of the
we switched from just a reshaping of the
we switched from just a reshaping of the amount the quality quantity kind of
amount the quality quantity kind of
amount the quality quantity kind of information we add or at least we are
information we add or at least we are
information we add or at least we are thinking we have to what is suggestion
thinking we have to what is suggestion
thinking we have to what is suggestion it’s presented as personalization of
it’s presented as personalization of
it’s presented as personalization of services those are the suggestions that
services those are the suggestions that
services those are the suggestions that we
we
we should maybe begin to wonder whether we
should maybe begin to wonder whether we
should maybe begin to wonder whether we actually correspond to what this
actually correspond to what this
actually correspond to what this continuous pattern is suggesting to us
continuous pattern is suggesting to us
continuous pattern is suggesting to us so whether or not we know all of people
so whether or not we know all of people
so whether or not we know all of people or we don’t know any of them the system
or we don’t know any of them the system
or we don’t know any of them the system and this system confused interaction is
and this system confused interaction is
and this system confused interaction is a service allows you to interact with
a service allows you to interact with
a service allows you to interact with your friends yet the point is who are my
your friends yet the point is who are my
your friends yet the point is who are my friends
friends
friends this is friends for Facebook but these
this is friends for Facebook but these
this is friends for Facebook but these are subsets of friends for you and you
are subsets of friends for you and you
are subsets of friends for you and you might not want to mix your family with
might not want to mix your family with
might not want to mix your family with college friends with Santana friends and
college friends with Santana friends and
college friends with Santana friends and some of them not even your friends but
some of them not even your friends but
some of them not even your friends but still the system is suggesting you that
still the system is suggesting you that
still the system is suggesting you that those people should be your friends
those people should be your friends
those people should be your friends so the impact also in social life is
so the impact also in social life is
so the impact also in social life is becoming to be a little bit more complex
becoming to be a little bit more complex
becoming to be a little bit more complex and complicated so this has been with us
and complicated so this has been with us
and complicated so this has been with us for a number of years with a lot of
for a number of years with a lot of
for a number of years with a lot of impacts with scoring and other
impacts with scoring and other
impacts with scoring and other implications what we are now looking at
implications what we are now looking at
implications what we are now looking at is something different once it is not
is something different once it is not
is something different once it is not necessary anymore to identify you as
necessary anymore to identify you as
necessary anymore to identify you as high who you are Giovanni kimande and
high who you are Giovanni kimande and
high who you are Giovanni kimande and it’s more and more possible to target
it’s more and more possible to target
it’s more and more possible to target individuals or better way to target
individuals or better way to target
individuals or better way to target devices used or even better groups of
devices used or even better groups of
devices used or even better groups of data points of information things begin
data points of information things begin
data points of information things begin to change and all the data which are
to change and all the data which are
to change and all the data which are referred to us may be somehow misleading
referred to us may be somehow misleading
referred to us may be somehow misleading let me give you a may be hilarious
let me give you a may be hilarious
let me give you a may be hilarious example think about an individual that
example think about an individual that
example think about an individual that for personal reasons for work or any
for personal reasons for work or any
for personal reasons for work or any other reason is somehow forced at the
other reason is somehow forced at the
other reason is somehow forced at the regular times to go through an area
regular times to go through an area
regular times to go through an area where the capo prostitutes is going on
where the capo prostitutes is going on
where the capo prostitutes is going on and this traffic stop and go
and this traffic stop and go
and this traffic stop and go and this process of stopping and go it’s
and this process of stopping and go it’s
and this process of stopping and go it’s gathered from the devices mobile phone
gathered from the devices mobile phone
gathered from the devices mobile phone tablets computer that brings with him
tablets computer that brings with him
tablets computer that brings with him it’s not interconnected it’s not
it’s not interconnected it’s not
it’s not interconnected it’s not connected to internet but those devices
connected to internet but those devices
connected to internet but those devices are Jo located temporal is partially
are Jo located temporal is partially
are Jo located temporal is partially dimensionally located and their movement
dimensionally located and their movement
dimensionally located and their movement is tracked stop and go in it is clearly
is tracked stop and go in it is clearly
is tracked stop and go in it is clearly a pattern which is compatible with
a pattern which is compatible with
a pattern which is compatible with picking up prostitute what actually then
picking up prostitute what actually then
picking up prostitute what actually then is the result is that one of those
is the result is that one of those
is the result is that one of those advices once is connected the
advices once is connected the
advices once is connected the information about those devices those
information about those devices those
information about those devices those movements are related to a pattern
movements are related to a pattern
movements are related to a pattern result not individual but the set of
result not individual but the set of
result not individual but the set of devices which have been experiencing
devices which have been experiencing
devices which have been experiencing that stop and go at regular chiming are
that stop and go at regular chiming are
that stop and go at regular chiming are considered sex addicts or interested in
considered sex addicts or interested in
considered sex addicts or interested in drugs in specific directions and
drugs in specific directions and
drugs in specific directions and dimension well clearly we don’t need to
dimension well clearly we don’t need to
dimension well clearly we don’t need to identify and connect the device with an
identify and connect the device with an
identify and connect the device with an individual so for instance the car or
individual so for instance the car or
individual so for instance the car or the notebook or the tablet with me or
the notebook or the tablet with me or
the notebook or the tablet with me or with a specific gender because in the
with a specific gender because in the
with a specific gender because in the internet of things a pink cover can
internet of things a pink cover can
internet of things a pink cover can signal that most probably that
signal that most probably that
signal that most probably that individual is female not male therefore
individual is female not male therefore
individual is female not male therefore making it different in the pattern so
making it different in the pattern so
making it different in the pattern so not picking up prostitute that would be
not picking up prostitute that would be
not picking up prostitute that would be the pattern not always true and changing
the pattern not always true and changing
the pattern not always true and changing the results and of course the individual
the results and of course the individual
the results and of course the individual with the pink cover with not picking up
with the pink cover with not picking up
with the pink cover with not picking up the prostitute might end up with a wrong
the prostitute might end up with a wrong
the prostitute might end up with a wrong inference of course and bronc
inference of course and bronc
inference of course and bronc suggestive which of course makes us
suggestive which of course makes us
suggestive which of course makes us laughing and makes us thinking that well
laughing and makes us thinking that well
laughing and makes us thinking that well this is not really happening and we do
this is not really happening and we do
this is not really happening and we do know that it’s actually happening
know that it’s actually happening
know that it’s actually happening already it’s already happening because
already it’s already happening because
already it’s already happening because for instance cross matching
for instance cross matching
for instance cross matching for devices it’s a huge market in which
for devices it’s a huge market in which
for devices it’s a huge market in which basically devices are linked either
basically devices are linked either
basically devices are linked either because you are connected with your
because you are connected with your
because you are connected with your unique identifier your many unique
unique identifier your many unique
unique identifier your many unique identifiers you are connected with your
identifiers you are connected with your
identifiers you are connected with your Apple ID your Google ID or whatever
Apple ID your Google ID or whatever
Apple ID your Google ID or whatever other ID you are connected or because
other ID you are connected or because
other ID you are connected or because your device which is a bundle of other
your device which is a bundle of other
your device which is a bundle of other devices with unique identifiers for
devices with unique identifiers for
devices with unique identifiers for instance the MAC address can be
instance the MAC address can be
instance the MAC address can be probabilistically related with each
probabilistically related with each
probabilistically related with each other and this is something continuously
other and this is something continuously
other and this is something continuously epping there is plenty of companies
epping there is plenty of companies
epping there is plenty of companies which make a large plus large profits
which make a large plus large profits
which make a large plus large profits just making offline and online
just making offline and online
just making offline and online identities through probabilistic
identities through probabilistic
identities through probabilistic matching that trust me works very very
matching that trust me works very very
matching that trust me works very very very well now we moved from I I am Joe
very well now we moved from I I am Joe
very well now we moved from I I am Joe Bendigo Monday I but I am supposed to
Bendigo Monday I but I am supposed to
Bendigo Monday I but I am supposed to wear a tie I’m not wearing a tie but the
wear a tie I’m not wearing a tie but the
wear a tie I’m not wearing a tie but the inference on me is that I should wear a
inference on me is that I should wear a
inference on me is that I should wear a tie and we reach the point in which
tie and we reach the point in which
tie and we reach the point in which basically it’s not anymore me targeted
basically it’s not anymore me targeted
basically it’s not anymore me targeted in this some devices some objects which
in this some devices some objects which
in this some devices some objects which doesn’t really matter whether or not
doesn’t really matter whether or not
doesn’t really matter whether or not they are related to me so we are a step
they are related to me so we are a step
they are related to me so we are a step ahead even beyond the idea of data
ahead even beyond the idea of data
ahead even beyond the idea of data protection so the frontiers between my
protection so the frontiers between my
protection so the frontiers between my data the data in further me and the data
data the data in further me and the data
data the data in further me and the data of the things which some house are
of the things which some house are
of the things which some house are surrounding me are once again sailing
surrounding me are once again sailing
surrounding me are once again sailing away and and blurring and it’s much much
away and and blurring and it’s much much
away and and blurring and it’s much much much easier and effective to target
much easier and effective to target
much easier and effective to target devices which are matched
devices which are matched
devices which are matched among themselves because it’s much more
among themselves because it’s much more
among themselves because it’s much more accurate than targeting me think about
accurate than targeting me think about
accurate than targeting me think about the different objects in the daily life
the different objects in the daily life
the different objects in the daily life between 9:30 a.m. and 5:30 and finally
between 9:30 a.m. and 5:30 and finally
between 9:30 a.m. and 5:30 and finally the fitting model they
the fitting model they
the fitting model they those devices create is that you are a
those devices create is that you are a
those devices create is that you are a professional female age 42 and then
professional female age 42 and then
professional female age 42 and then times pass along the day goes on and we
times pass along the day goes on and we
times pass along the day goes on and we have a different moment in time a
have a different moment in time a
have a different moment in time a different connection or a different
different connection or a different
different connection or a different spatial location of those devices and
spatial location of those devices and
spatial location of those devices and clearly some devices come in some other
clearly some devices come in some other
clearly some devices come in some other devices come out and another fitting
devices come out and another fitting
devices come out and another fitting model tends to be applied and at that
model tends to be applied and at that
model tends to be applied and at that fitting model in that fitting model you
fitting model in that fitting model you
fitting model in that fitting model you are a child male age eight just because
are a child male age eight just because
are a child male age eight just because maybe your son is using at that regular
maybe your son is using at that regular
maybe your son is using at that regular time your iPad or your computer and
time your iPad or your computer and
time your iPad or your computer and therefore it’s a specific target
therefore it’s a specific target
therefore it’s a specific target therefore the search ranking will be
therefore the search ranking will be
therefore the search ranking will be tailored for a child male aged eight not
tailored for a child male aged eight not
tailored for a child male aged eight not a female 8 42 the results the
a female 8 42 the results the
a female 8 42 the results the suggestions the results in the search
suggestions the results in the search
suggestions the results in the search the banners the commercials the filters
the banners the commercials the filters
the banners the commercials the filters and so on so forth these are just
and so on so forth these are just
and so on so forth these are just example that if we move along during the
example that if we move along during the
example that if we move along during the day you might realize at a certain point
day you might realize at a certain point
day you might realize at a certain point the fitting model is not anymore
the fitting model is not anymore
the fitting model is not anymore 15:42 but it’s a teenager age 15 right
15:42 but it’s a teenager age 15 right
15:42 but it’s a teenager age 15 right and if you begin to think about and for
and if you begin to think about and for
and if you begin to think about and for instance this happens only on wetness d
instance this happens only on wetness d
instance this happens only on wetness d and on every other week on during
and on every other week on during
and on every other week on during weekdays on every other week you can
weekdays on every other week you can
weekdays on every other week you can easily think without being a smart
easily think without being a smart
easily think without being a smart algorithm Lee you have a shared custody
algorithm Lee you have a shared custody
algorithm Lee you have a shared custody of the child
of the child
of the child so at that point another pattern applies
so at that point another pattern applies
so at that point another pattern applies the child is with mommy or with daddy
the child is with mommy or with daddy
the child is with mommy or with daddy and therefore we could somehow
and therefore we could somehow
and therefore we could somehow manipulate the environment knowing that
manipulate the environment knowing that
manipulate the environment knowing that the eight-year-old child is with the
the eight-year-old child is with the
the eight-year-old child is with the father or with the mother to
father or with the mother to
father or with the mother to contextualise
contextualise
contextualise even more personalizing is
even more personalizing is
even more personalizing is decision-making and environment and
decision-making and environment and
decision-making and environment and interfering with the decision-making
interfering with the decision-making
interfering with the decision-making environment of the adult which is
environment of the adult which is
environment of the adult which is present at the same time of course times
present at the same time of course times
present at the same time of course times past alone and
past alone and
past alone and at a certain moment in time the fitting
at a certain moment in time the fitting
at a certain moment in time the fitting model is telling to you that you are who
model is telling to you that you are who
model is telling to you that you are who you are and then at the very end of the
you are and then at the very end of the
you are and then at the very end of the day you’d realize that you are your wife
day you’d realize that you are your wife
day you’d realize that you are your wife and doesn’t really make a difference
and doesn’t really make a difference
and doesn’t really make a difference whether or not you are your wives
whether or not you are your wives
whether or not you are your wives if the system is contextualizing all
if the system is contextualizing all
if the system is contextualizing all your decision-making environment in that
your decision-making environment in that
your decision-making environment in that direction so we reach I guess and I up
direction so we reach I guess and I up
direction so we reach I guess and I up the frontiers we want to reach so in the
the frontiers we want to reach so in the
the frontiers we want to reach so in the classifying society in this way in the
classifying society in this way in the
classifying society in this way in the way in which our economy has been is
way in which our economy has been is
way in which our economy has been is being shaved thanks to technology with
being shaved thanks to technology with
being shaved thanks to technology with doing Marlo’s things and not saying that
doing Marlo’s things and not saying that
doing Marlo’s things and not saying that all this is wrong but I’m trying to
all this is wrong but I’m trying to
all this is wrong but I’m trying to stress one point that is we are in a
stress one point that is we are in a
stress one point that is we are in a moment in time and moment in the
moment in time and moment in the
moment in time and moment in the development of the economy and
development of the economy and
development of the economy and technology in which I our real-life
technology in which I our real-life
technology in which I our real-life identities are becoming less important
identities are becoming less important
identities are becoming less important if you want to a large extent even in
if you want to a large extent even in
if you want to a large extent even in relevant and this irrelevance is
relevant and this irrelevance is
relevant and this irrelevance is strictly related to the fact that all
strictly related to the fact that all
strictly related to the fact that all the products and services we receive are
the products and services we receive are
the products and services we receive are contributing to shape our environment in
contributing to shape our environment in
contributing to shape our environment in a specific environment our
a specific environment our
a specific environment our decision-making environment so we are at
decision-making environment so we are at
decision-making environment so we are at the point in which we have to decide
the point in which we have to decide
the point in which we have to decide whether or not it is legally permissible
whether or not it is legally permissible
whether or not it is legally permissible or ethically acceptable and to what
or ethically acceptable and to what
or ethically acceptable and to what extent of withdrawal of information so
extent of withdrawal of information so
extent of withdrawal of information so the ranking the results which have been
the ranking the results which have been
the ranking the results which have been taking away from your search to what
taking away from your search to what
taking away from your search to what extent this is something we do want and
extent this is something we do want and
extent this is something we do want and to what extent withdrawing information
to what extent withdrawing information
to what extent withdrawing information reducing filtering information or
reducing filtering information or
reducing filtering information or results or possibilities or alternatives
results or possibilities or alternatives
results or possibilities or alternatives or suggestions Sandman is reaching a
or suggestions Sandman is reaching a
or suggestions Sandman is reaching a point in which is
point in which is
point in which is too much altering pre defining our
too much altering pre defining our
too much altering pre defining our decision-making context it’s how to draw
decision-making context it’s how to draw
decision-making context it’s how to draw the border between the marvelous results
the border between the marvelous results
the border between the marvelous results of taking away of the noise in the
of taking away of the noise in the
of taking away of the noise in the search to remain in the example and to
search to remain in the example and to
search to remain in the example and to not receive any further information on
not receive any further information on
not receive any further information on that well almost twenty five years ago
that well almost twenty five years ago
that well almost twenty five years ago or even more there was this picture
or even more there was this picture
or even more there was this picture paper and the idea was on the internet
paper and the idea was on the internet
paper and the idea was on the internet nobody knows you are dog well with on
nobody knows you are dog well with on
nobody knows you are dog well with on sites we might begin to think that
sites we might begin to think that
sites we might begin to think that certainly on internet nobody knows you
certainly on internet nobody knows you
certainly on internet nobody knows you are a dog but it might be relevant if
are a dog but it might be relevant if
are a dog but it might be relevant if you are treated like a dog despite the
you are treated like a dog despite the
you are treated like a dog despite the fact you might be the owner or you might
fact you might be the owner or you might
fact you might be the owner or you might not be the owner of a specific kind of
not be the owner of a specific kind of
not be the owner of a specific kind of dog and this might be relevant if your
dog and this might be relevant if your
dog and this might be relevant if your decision making context is shaped by
decision making context is shaped by
decision making context is shaped by that well I think these are frontiers
that well I think these are frontiers
that well I think these are frontiers words to be explored
words to be explored
words to be explored thank you
thank you
thank you [Applause]
”
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