[Music]
[Applause]
you
hi my name is Carolyn Shelley I am a
tech recruiter but I am NOT your typical
kind of recruiter fascinated by AI
diversity and ethics I am lucky to be
part of a global organization which is
called
women in machine learning and data
science we am LDS it will be way simpler
that way we NLDS aims at promoting and
supporting women and gender minorities
in the field of AI and we do free
technical events it's very important all
over the world in 2017
I created the Paris chapter and since
then we became the third largest chapter
in the world and we also won the science
and research award during the women in
tech challenge last year
we mailed yes on a global scale it's 48
thousand members we are present in six
continents and for instance in India we
are here Darabont
for New Delhi and maybe soon I hope my
talk will be watched maybe soon in
Ranchi before I start I have two
questions and I want you to be reactive
do you all know what AI stands for yes
okay
artificial intelligence do you know
Michael Jordan who is he
no is a Berkeley professor Michael
Jordan is hey I knew I would get you
Michael Jordan once said during a
fascinating talk that AI is a term we
overuse indeed no one really knows how
to define the human intelligence not
even the best psychologist so you will
hear me say machine learning instead of
AI but there's a trick even AI people
say AI machine learning is already part
of our job our daily lives Netflix
recommend movies Ola takes you to the
place you want to go to Spotify finds
new tracks for you and your phone
recognizes your face so no matter what
you think AI is already there and while
coming here I made a connection with
Shiva if I am NOT wrong Shiva is also
called the destroyer but Shiva creates
and transform and even if most of the
people think machine learning is going
to steal our jobs
I am hopeful in the same way as The
Economist Joseph Schumpeter theorized
the creative destruction I do believe
that if we use correctly the power of
computing and machine learning were
going to switch the way we deal with our
times and take activities but before we
all jump into the AI thingy there is a
problem we need to fix women are
underrepresented 3% of the Nobel prizes
in science are women 12% of the
researchers in AI are women we cannot
afford to deprive ourselves from 52% of
humanity's talent according to McKinsey
study the miss to win for economic
growth for India only has been estimated
at 200 million dollars if you take it to
a global scale it gives you a number of
12 trillion dollars so what if today you
had to tell someone why today's talk is
important just answer this increasing
the number of women modeling and
implementing machine learning algorithm
is a human rights issue
why machine learning are going to use
historical data and this data is biased
algorithms are not biased but humans are
and it's our responsibility not to
perpetrate these biases secondly
products of
designed do you remember when the Apple
health app got released it could track
every piece of data except a woman's
natural cycle do you think it's
acceptable I don't so today if I flew
all the way from Paris it's because I
want to share actionable items we can
set up in order to improve diversity in
AI but things too you can also go beyond
diversity is not an option it should be
an incarnated priority no matter what
your motivation in economic moral
whatever it has proven to improve of a
better our ourselves it increases by 30%
a team's productivity and once that has
been said I am much more interested in
coupling all the motivations together
in order to create real diverse team we
should value women empower them put them
in the spotlight promote them because if
we believe that meritocracy and
objectiveness are ruling the world we
are making a mistake thousands of social
science paper have proven it machine
learning algorithms are biased they are
conceived by a dominant population no
offense to you the man in the room but
the fact is that you are 78% to model it
and here allow me to quote the founder
of women yes dr. Aaron Liddell who
expressed an instrumental idea it's
important to have a diverse people
creating models and software because
once the Stauffer is created then you're
limited in terms of what it can do and
how it can be used so the more diverse
minds we have from the start the better
indeed if you hire a diverse team from
the very beginning your team is going to
be more creative your team is going to
attack problems in
a different way so I want you to
remember I am a recruiter hire diverse
team from the very beginning and beyond
hiring there is another critical issue
role models we need role models to
encourage to retain to keep women in
machine learning
well lacking role models in machine
learning and in science in general
so at women yes we did something quite
simple we offered women a safe place for
them to shine to present their work to
network but I can hear you
the other issue with role models is that
sometimes they're hard to reach let's
take an example if you're a physicist
it's hard to become yourself becoming
the next Mary Curie and get two Nobel
Prizes if I tell you being you Feifei
Ellie Tamara Broadwick Rachel Thomas
aneema Anant Kumar Kate Crawford Jimmy J
blue joy Balam Winnie Allah Wallach
Florence - epic do these names ring a
bell no and that's a shame because they
are the women leading the way in machine
learning
they are our current role models I have
been focusing my talk on women but they
are not the only population to be
underrepresented in machine learning
elders black Asian disabled queer people
- only quote them a highly
underrepresented
but I have a good news once you have
worked on improving and correcting your
biases prejudices or simply the way you
do things it gets easier to encourage
the other population to join your team
so it's really worth the effort and I
want also to correct something diversity
is not about gender
it might be the most visible thing you
see even if that can be discussed but
once you start on one topic it's easier
for the other ones and everything I've
just mentioned so far is no rocket
science it's common sense the changing
habits challenging the status quo
breaking the barriers it takes time it
takes effort it takes passion and let's
be pragmatic when you want to work on
diversity it never leaves you it's not
over when you go out of the office you
should read about unconscious biases you
should talk with people from
underrepresented groups you could test
and learn and be like and be like me
become an engineer you test learn and
you see if it works and if it doesn't
it's ok you do something else this is
super important because nobody will
criticize you if you try but we'll
remember you if you do nothing and I
have a personal role model her name is
Grace Hopper hope er sorry French accent
she was a pioneer in computer science
and she invented the concept of human
readable programming languages and she
used to say something quite simple but I
love if you have a good idea go ahead
and do it it's easier to apologize than
to add to get permission so I am begging
you be unapologetic make diversity your
priority and to conclude we all know
this song the world is changing
yes but machine learning is going to
take it at an unprecedented speed and so
yesterday when I was talking with Rajiv
he said something to me that
you know made me smile I was a recruiter
two years ago working in a company
focusing on machine learning and I was
pissed off because every day I was
picking up my phone and nine times out
of ten I was talking with a man I have
no problem with that but I was like
ladies are talented they are good in
science they kick ass in mathematics and
there is a problem and even if I'm
French and we know how to complain
instead of complaining
I did something I partnered with the
machine learning researchers and we
opened the Paris we an audience chatter
and today we have more than 3,500
members this is one of the thing I am
the most proud of and today if I had to
leave the stage and leave you with one
two ideas the fourth Industrial
Revolution is happening machine learning
is going to enable us to change our
habits we are going to automate things
we don't like to do but we will have the
time to spend more time on creative
projects thoughts it's exciting but we
need to include everyone
so my last sentence will be nobody will
criticize you if you try but we'll
remember you if you do nothing thank you
[Applause]
[Music]
[Applause]