good afternoon guys here today for us
to chat about algorithms of
recommendation and for this I’ll invite
You guys get up if we can.
move a little because I know that
after lunch is not easy and then the
people fill their energy auditorium
before we start talking
ah I chose here a very old song
school bit of the old ones I think
that the majority should know there that with
You sure know the choreography
also so we can dance together
beauty
come on
It was with joy Christmas that everything was
made on the line with his mother in line
joy marina group would score and
joy maracanã joy
it was a joy a brigade was great
They sent and there is clarity and until
I want to continue dancing here
I saw people then while you
seat and I take my breath back here
I also have a little secret to
tell you
Just put together a run here
algorithm series the definition of algorithm
is this here are finite sequences of
well defined instructions and not friends
each of which shall be
performed mechanically or electronically
in a finite time interval and how the
amount of finite effort space
that is, every time we perform a
choreography we are running a
algorithm the same thing when people
cooking following a cooking recipe
or even when we learn to use
new equipment following the
instructions
this means that the algorithms they
They are part of day-to-day you
regardless of whether you work with
technology or not
and why then the algorithms
has received so much
highlighted recently by a simple
We live in an age and are flooded.
data with the arrival of the internet at
information it started to circulate
freely in the world and in this new
the configuration in which we
fluidity through the interfaces of the physical world
and the digital world , we have
abundance of information
we have access to virtually
unlimited content on any
subject we are interested in
This is incredible, huh?
Yes it ‘s wonderful but it has a
story our brain it continues
with cognitive resources limited to
people can not handle the whole process
this information
not available so you think there are
of 20 years there was a certain
sense of idleness in relation to
content we had access to and the
amount of information to our
processing power
as this volume of information
it was increasing we went
experiencing the sensations of
excitement and even a sense of power
until we began to feel the
effects of this balance decided
the volume of information and our
human processing capacity and
this stress
we name it a fax complaint ‘ or
an overload due to the excess of
information that paralyzes our
mental activity and hampers our
decision-making
so if in the analogue era we read a
newspaper and felt that it was up to date.
about the news of the day
today we live the anguish of never gives
account to consume all content that
come to us
via news agencies networks
social or until the tap groups and
what are the projections for the future?
is there any chance of this
volume of information
it is clear that not as it expands
that the digital connection of the
humanity this avalanche of data she
specializes if one increases
exponentially and in this context the
algorithms and their evolution of
artificial intelligence they emerge as
heroes to help people filter
information and alleviate this
constant search and selection of content
relevant in this context the whole point is
that we do not have a problem in
truth of volume
no excess of information and
forms and failures in relation to
filtering that we make of these data
and in this way we begin to understand
the crucial social role that algorithms
of recommendation in this era of big
date
these are systems that have as behind
of hunger is the learning structure of
machine where from data
behavioral
they recognize patterns and repetitions and
so they give us recommendations
adhering to our profile for us
understand this better, let’s consider a
example as simple as a
trade
then from the shopping baskets of
different users
the algorithm it recognizes in the search for
patterns of behavior and then he
defines association notes between these
items and recommends those items
which have higher grades with each new
platform interaction
so the machine recognizes
that when users buy diamonds
they usually buy circles too
asterisks
eventually with triangles and
sometimes they buy too
squares and then it follows this
analytical structure at the time of
recommend a new product to the user in
systems but it is sophisticated
we can also include the interaction
between items and the occasion of consumption in
process that can recommend a movie
to watch a Saturday night being
different from a movie I go
watch on a Wednesday afternoon for
example and we can also think about
parameters that take into account the
description of attributes or tags
items
thinking for example of films with
ratings due to their level of
dramatic action or even with respect to
to the structure of the roadmap building
characters that is the whole system that
is porting is an algorithm
begin all the recommendations that come
of these algorithms they come from us
that is, the decoding of the
crystallized human behavior
through layers of science that
recognize our desires
and deliver us content qualification
and then it’s from that we start
receiving product indications
interesting to buy serials or
music to have fun and can roll
even a little help from a cupid
analytic when it comes to finding a new
love
between 75 and 80 percent of the product
content assisted within the
netflix platform
it originates from
recommendation while 35% of the
amazon purchases it comes from
data-driven indications and is
of course the content that we are
exposed in social networks also have
on the same type of systems in a
weighing the interests of individuals
of the platform and also of its
advertisers
in this environment it is very recently people
accompanied a very controversial case of use
data from Facebook users to
promote political engagement
directed in the united states in the kingdom
together a case in which the
users to authorize a
research team to collect your data
exchange a personality test
this company then from the data
raised from thousands of users
applied a segmentation methodology
known as steak
classifies people according to their
behavior rather than variables
demographic and from that
segmentation, news and
targeted posts
the interests are by profile of each one
of these user segments and with that
They were recommended and boosted
contents that generated this commitment
political directed to this if it in
suggests that it broadens the debate
about how our data is used
Makes people think about ethics
transparency and balance consciousness
the fact is that we exchange data for
value to be able to have content
custom we need to deliver
data on our expressions
individual and here and for that and when
more accurate information are these
recommendations that these structures
they all saw each other on top of
wishes
they have a scale that should weigh
the interests of people and business
systems that should balance is
bring a balance between offering us
more of the same than what has already
if you know that the user likes
while should open open
doors to diversity to instigate
new interests new visions are
questions about setting parameters that
should make it possible to exploit the known
at the same time as it launches into the
unknown
and then we need to question us
same
how much of plurality
we want in our lives or how much
that people prefer to stay
accommodated in our microcosm will be
even if you want to be asked to be
instigated by opinions
divergent news from your thinking
or do you prefer to say make friends with
those known on Facebook that have
opposite opinions to the streets
the fact is that the human being is by nature
a service used our behavior
in the digital sphere is simply a
reflection of who we are in the world
physical and we have to be yes
relate to people who follow lines
similar to our own and the
to reject those that are contradictory
and thus to each tanned in the same
content type for each share
from the same point of view
we reinforce our understanding of
algorithms about who we are
and we are closing in more and more in bubbles
created by ourselves
this clearly shows us the impact
that duality may have
in this age of the internet because we
our cognitive biases the
multiplier of algorithms
and it takes a lot of
attention especially in times of
collective decisions that shape the
directions of a nation
in the last presidential elections in
United States noticed what news
generated a greater engagement than
news from traditional media
in the run-up to voting in a
example of how the spirits inflame and
people craving get charged when
people’s eagerness to be able to
our point of view the people
simply loses reason
so the technology she needs
work to build algorithms
public life consensus
concerned to promote and deliver
interests of individuals
at the same time as promoting
diversity and transparency
we need is neutrality of
ethics of both developers and
of users and for this we need
to form analytical consciousness
our responsibility
providing data and sharing
content and we also need
distribute these conversations to
different layers of society so that
more people can understand this era
of changes that people are living
now we’re all together
building this new world
let’s act so it’s plural
thank you
to chat about algorithms of
recommendation and for this I’ll invite
You guys get up if we can.
move a little because I know that
after lunch is not easy and then the
people fill their energy auditorium
before we start talking
ah I chose here a very old song
school bit of the old ones I think
that the majority should know there that with
You sure know the choreography
also so we can dance together
beauty
come on
It was with joy Christmas that everything was
made on the line with his mother in line
joy marina group would score and
joy maracanã joy
it was a joy a brigade was great
They sent and there is clarity and until
I want to continue dancing here
I saw people then while you
seat and I take my breath back here
I also have a little secret to
tell you
Just put together a run here
algorithm series the definition of algorithm
is this here are finite sequences of
well defined instructions and not friends
each of which shall be
performed mechanically or electronically
in a finite time interval and how the
amount of finite effort space
that is, every time we perform a
choreography we are running a
algorithm the same thing when people
cooking following a cooking recipe
or even when we learn to use
new equipment following the
instructions
this means that the algorithms they
They are part of day-to-day you
regardless of whether you work with
technology or not
and why then the algorithms
has received so much
highlighted recently by a simple
We live in an age and are flooded.
data with the arrival of the internet at
information it started to circulate
freely in the world and in this new
the configuration in which we
fluidity through the interfaces of the physical world
and the digital world , we have
abundance of information
we have access to virtually
unlimited content on any
subject we are interested in
This is incredible, huh?
Yes it ‘s wonderful but it has a
story our brain it continues
with cognitive resources limited to
people can not handle the whole process
this information
not available so you think there are
of 20 years there was a certain
sense of idleness in relation to
content we had access to and the
amount of information to our
processing power
as this volume of information
it was increasing we went
experiencing the sensations of
excitement and even a sense of power
until we began to feel the
effects of this balance decided
the volume of information and our
human processing capacity and
this stress
we name it a fax complaint ‘ or
an overload due to the excess of
information that paralyzes our
mental activity and hampers our
decision-making
so if in the analogue era we read a
newspaper and felt that it was up to date.
about the news of the day
today we live the anguish of never gives
account to consume all content that
come to us
via news agencies networks
social or until the tap groups and
what are the projections for the future?
is there any chance of this
volume of information
it is clear that not as it expands
that the digital connection of the
humanity this avalanche of data she
specializes if one increases
exponentially and in this context the
algorithms and their evolution of
artificial intelligence they emerge as
heroes to help people filter
information and alleviate this
constant search and selection of content
relevant in this context the whole point is
that we do not have a problem in
truth of volume
no excess of information and
forms and failures in relation to
filtering that we make of these data
and in this way we begin to understand
the crucial social role that algorithms
of recommendation in this era of big
date
these are systems that have as behind
of hunger is the learning structure of
machine where from data
behavioral
they recognize patterns and repetitions and
so they give us recommendations
adhering to our profile for us
understand this better, let’s consider a
example as simple as a
trade
then from the shopping baskets of
different users
the algorithm it recognizes in the search for
patterns of behavior and then he
defines association notes between these
items and recommends those items
which have higher grades with each new
platform interaction
so the machine recognizes
that when users buy diamonds
they usually buy circles too
asterisks
eventually with triangles and
sometimes they buy too
squares and then it follows this
analytical structure at the time of
recommend a new product to the user in
systems but it is sophisticated
we can also include the interaction
between items and the occasion of consumption in
process that can recommend a movie
to watch a Saturday night being
different from a movie I go
watch on a Wednesday afternoon for
example and we can also think about
parameters that take into account the
description of attributes or tags
items
thinking for example of films with
ratings due to their level of
dramatic action or even with respect to
to the structure of the roadmap building
characters that is the whole system that
is porting is an algorithm
begin all the recommendations that come
of these algorithms they come from us
that is, the decoding of the
crystallized human behavior
through layers of science that
recognize our desires
and deliver us content qualification
and then it’s from that we start
receiving product indications
interesting to buy serials or
music to have fun and can roll
even a little help from a cupid
analytic when it comes to finding a new
love
between 75 and 80 percent of the product
content assisted within the
netflix platform
it originates from
recommendation while 35% of the
amazon purchases it comes from
data-driven indications and is
of course the content that we are
exposed in social networks also have
on the same type of systems in a
weighing the interests of individuals
of the platform and also of its
advertisers
in this environment it is very recently people
accompanied a very controversial case of use
data from Facebook users to
promote political engagement
directed in the united states in the kingdom
together a case in which the
users to authorize a
research team to collect your data
exchange a personality test
this company then from the data
raised from thousands of users
applied a segmentation methodology
known as steak
classifies people according to their
behavior rather than variables
demographic and from that
segmentation, news and
targeted posts
the interests are by profile of each one
of these user segments and with that
They were recommended and boosted
contents that generated this commitment
political directed to this if it in
suggests that it broadens the debate
about how our data is used
Makes people think about ethics
transparency and balance consciousness
the fact is that we exchange data for
value to be able to have content
custom we need to deliver
data on our expressions
individual and here and for that and when
more accurate information are these
recommendations that these structures
they all saw each other on top of
wishes
they have a scale that should weigh
the interests of people and business
systems that should balance is
bring a balance between offering us
more of the same than what has already
if you know that the user likes
while should open open
doors to diversity to instigate
new interests new visions are
questions about setting parameters that
should make it possible to exploit the known
at the same time as it launches into the
unknown
and then we need to question us
same
how much of plurality
we want in our lives or how much
that people prefer to stay
accommodated in our microcosm will be
even if you want to be asked to be
instigated by opinions
divergent news from your thinking
or do you prefer to say make friends with
those known on Facebook that have
opposite opinions to the streets
the fact is that the human being is by nature
a service used our behavior
in the digital sphere is simply a
reflection of who we are in the world
physical and we have to be yes
relate to people who follow lines
similar to our own and the
to reject those that are contradictory
and thus to each tanned in the same
content type for each share
from the same point of view
we reinforce our understanding of
algorithms about who we are
and we are closing in more and more in bubbles
created by ourselves
this clearly shows us the impact
that duality may have
in this age of the internet because we
our cognitive biases the
multiplier of algorithms
and it takes a lot of
attention especially in times of
collective decisions that shape the
directions of a nation
in the last presidential elections in
United States noticed what news
generated a greater engagement than
news from traditional media
in the run-up to voting in a
example of how the spirits inflame and
people craving get charged when
people’s eagerness to be able to
our point of view the people
simply loses reason
so the technology she needs
work to build algorithms
public life consensus
concerned to promote and deliver
interests of individuals
at the same time as promoting
diversity and transparency
we need is neutrality of
ethics of both developers and
of users and for this we need
to form analytical consciousness
our responsibility
providing data and sharing
content and we also need
distribute these conversations to
different layers of society so that
more people can understand this era
of changes that people are living
now we’re all together
building this new world
let’s act so it’s plural
thank you
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