Good morning everyone.
Hope everyone is settling down.
We can get started with our first talk.
Our first talk is where have the women of tech history gone.
Our speaker is Laura Dury.
She has been a developer for six years and awarded at World Scales Belgium in Web Technologies category.
She has been doing monthly YouTube live discussions on latest tech developments in tech industry.
Additionally, she has also started a career of Fourier in France.
The talk is mostly about where have women of tech history gone.
Addaa Lovelace, Hedji Lamar, the Enoch Girls, Grace Hopper, John Clark.
Stemming from the role of calculator, the profession of developer has initially considered a woman's job while hardware design was seen as a man's job.
However, who are these women who have shaped the world in tech?
Why don't we hear more about them with Laura?
You'll attempt to see the record straight bit by bit and provide role models in the tech you've always needed.
Thank you.
Hi, can you hear me right?
Hi everyone, thank you so much for coming today.
I just wanted to say that at first I try to do my talk on Sunday because this is way too much for me to handle.
Please be kind to me, thank you so much.
We're going to talk today about the women in the tech history.
First of all, I wanted to talk to you about a little anecdote that happened to me when I was in college.
During my first year I had a North History class and I was kind of sad to see there were maximum two women represented.
I decided to send an email to my teacher and to ask him why he presented so few women.
He answered kindly, honestly, that he didn't have enough time to add more artists to his syllabus.
Because of that, some students may not have the required basis for their future career.
We think about students in illustration, in painting, art, etc.
At first I didn't really pay attention to it, I didn't really see the huge problem behind this.
Then when I started to realize that this is kind of weird, that this is not normal, this is not fair, I had two questions in my mind.
The first one is why are women not considered as the required basis? Why do they have less than men?
The second one is who is the person or the group of persons who decide what someone deserves more than another to be in a syllabus?
Spoiler alert, I don't have the answer to this question, I have ideas, I have theories.
This is not the aim of this talk, but I hope that this question you can yourself think about it and maybe try to think about it.
What I can do is to pay tribute and give a place to women who did a fantastic word to revolutionize the computer science field.
This is something I have had in my mind for many years, in fact it's only natural that I'm here today in front of you to speak about that.
The problem is present in the majority of fields, but today we're going to concentrate and talk only about computer science, the reason why we are all here today.
Of course we're going to do that.
Personally, if you go home and you remember two names of women you learned about today, it's a huge win for me.
What about you? Do you know some names of women in the tech history?
Adelovelle.
Kathleen Booth.
Margaret Hamilton.
Belinda Pearson.
Oh sorry I can't hear.
Belinda Pearson.
Belinda Pearson, yeah that's true.
I don't think you know anything about that.
Okay I have a lot of names, that's really nice.
Okay thank you so much for that.
So let's go discover together the stories through the computer science history.
And for that we need to go back in time and we're going to begin at the age of enlightenment.
So the ancestors of computing machines were human computers and especially in the astronomy fields.
So basically computer was a job.
And it was about mathematical calculations and very often the job was divided, the computers were divided into groups
to compute long and difficult calculations.
And the job was done in a way that the calculations were executed at the same time in parallel.
And I wanted to talk to you about that because this is really funny,
but because still today this is something that we are looking at in our computer.
How many operations my computer can execute at the same time.
And it was already something that people created, a way of working that was created a long time ago already.
So like every profession was dominated by the men.
However the first woman to be quoted in articles about the computer science history is Nicole Ren LePote, co-corrigor pour les Français.
So she is one of the most famous astronomers of the age of enlightenment.
And she is famous because with two other men she calculated the return date of the Hallease comet for April 13 in 1756, 59.
Almost exactly as it returned on March 13 in the same year.
So I don't know if you understand, we are in the 18th century and they calculated by hands the return date of the comet with only one month of error.
So it's really amazing.
Maria Mitchell also made a splash for discovering the first telescopic comet, which means it's invisible for the eyes.
It will be named after her and she will receive a gold medal for this achievement.
So during the 19th century there were a few barriers and contradictions regarding women in the scientific fields.
So despite the fact that they had access to degrees, they were forced to resign as soon as they get married.
A kindly reminder that a woman that is not married at that time doesn't exist in the eyes of society.
So yeah.
The history of computer science starts in 1840 with a woman that you obviously know and if you don't know her you should ask yourself some serious questions.
Who is that Pokemon? Well of course it's Ada Lovelace.
So I think that everyone in this room know who is Ada Lovelace.
But for me she is not only the first programmer and this is my thought and I wanted to speak to you with you about that.
So for that I need to explain you something.
So Charles Babbage is the person who built the difference engine and the analytical engine.
However he was messy and he couldn't stand back from his machine he was building.
So he had ideas but he didn't have a concept that embraced his machine.
Hence the arrival of our sweet and dear Ada.
She invented the concepts behind the analytical engine by providing the first algorithms.
And I have something to say more and I forgot about it.
So she invented the concept of the analytical engine by providing the first algorithm.
And ladies and gentlemen computer science was born.
So this is why I think for me that Ada Lovelace isn't just the first programmer but she is the mother of computer science by giving these first algorithms.
And by the way you can find the first notions of loops and functions in these algorithms.
So despite this extraordinary invention it was way too innovative for that time.
I remind you to tell you again where we are in 1840.
So it was way too innovative and the analytical engine was forgotten for lack of funding.
Before being rediscovered in 1937 to inspire the Mach 1 the first general purpose electromechanical computer.
But let's take it easy.
Alright we are in the end of 19th century and Edward Charles Pickering is the founder of a group of women called the Harvard computers.
These women listed over 10,000 stars and developed a system to describe them.
But a woman, a particular woman stood out, Aynie Jump Cannon.
So she pioneered, this is hard to remember this one, she pioneered a new spectral type classification system
and she developed the Harvard classification scheme which is still in use today.
No sorry, which is the basis of the system used today.
Between 1911 and 1915 she classified over 5,000 stars a month at a rate of one star per 3 seconds.
I don't know what you can do in 3 seconds.
I mean I can chug a beer in 3 seconds but that's all I can do, right?
Okay girl, you have my respect.
And in the 19th century the growth of industries opened up opportunities for women to join the field of technology.
One notable woman, Great Hermann, made significant contributions with her advanced work in mathematics and physics.
She played a key role in her early philosophical work on the foundation of quantum mechanics.
But in 1920s her doctoral thesis led the groundwork for computer algebra and it first established the existence of algorithms for many of the basic problems of abstract algebra.
So we are going to see a little more of computing here.
I promise it's coming.
Between computer algebra, I don't know if you know this app or a definition over there if you want to look at that after.
So between the 1940s and the 1970s women were widely hired as coders and there are numbers of reasons.
The first one is that coding programming was an emerging field so you didn't need a diploma to be hired.
As new hires only had to pass a straightforward test, logic test, sorry, to work in a computer science job.
Another factor was that despite the fact that women had diplomas degrees in scientific field, they faced a lot of challenges like finding a job or even advancing in their career.
So they decided to turn to opportunities in the IT field.
The last one is the shortage of manpower during this time and the fact that women cost very little.
Grace Hopper.
So during the World War II Grace Hopper, a 36 years old mathematician, decided to serve her country.
This is very American.
I'm sorry for the Americans over there.
She decided to let her job, her teaching position at Vassar College to enroll in the US Navy expecting to decode enemy messages and serve her country.
Surprisingly, the US Navy sent her to Harvard where she became the third programmer of the Mark I.
If you remember, earlier I mentioned the analytical engine and how it was rediscovered to inspire Howard Aiken to create the Mark I in 1937.
Well, the Mark I is a versatile, punchcard, programmable calculator and it was Grace who has the honor or rather the heavy burden of taming this machine.
She wrote her 521 page user manual from scratch with any help of nobody.
Like they said, okay, this is the machine. Go yourself and yeah.
See you next time.
Okay.
So this is really impressive to know that and with her work she was engaged in top secret calculation crucial to the war efforts.
Involving past like determining rocket trajectories, generating range tables for new anti aircraft guns and calibrating minesweepers.
Now look at your computer.
Look how easy it is to code.
Now imagine doing this with a big, big computer like doing this for day long, for day long and for night long also.
This is not the right page.
Yeah, this is.
We continue in the history and we are in 1940 and this year marks a milestone in the history of computing.
The first fully electronic computer, the ENIAC.
It was developed to automate and speed up the work of calculators and computers who was first humans.
Right.
But even if it was faster, it still needed a human intervention called the operator.
And this job was largely performed by women.
So the operator is the person who will enter manually questions into the machine through switches and cables.
So you have a little, I don't know, overview.
Can you see it?
Well, it's kind of dark.
I'm sorry about that.
Yeah, you have a lot of cables over there.
And six astounding women, Kathleen, Marlene, Betty, Francis, Betty and Ruth were the first six ENIAC programmer and the first programmer by extension also.
So they had to install and assembling this machine.
You have to know that the operator was the programmer of today.
And even if this is the case, even if this is the programmer of today, at that time it was, it didn't receive a lot of credits.
And it was very often belittled because it was performed by women.
And hardware was the main job.
Yet the line between these two jobs wasn't really clear cuts because women, so operators, needed to have little or in depth hardware knowledge to do it.
To control this machine, to program these machines.
Because this is still hardware.
We didn't have in graphic interface or things like that.
You needed to touch the hardware to use the cables, the switches.
So this is where we see there is a big difference between a job description and what these women really had to do.
Hello.
I have a little anecdote.
So first of all ENIAC for those who didn't know, means Electronical, Numerical, Integrator and Computer.
So all these six women had a mathematics degree in common.
They were responsible for installing and assembling the ENIAC.
And the most important thing, they were the ancestors of the debugger.
So look again to this machine and imagine you have a bug but you don't know where it is.
So there were six.
There were a group, so they had to work together to try to understand where a bug come from.
And why is it a bug?
So they created a system to work together as a debugger when there is a bug.
And this is quite impressive.
I don't know if there is people in this room already saw a machine like that or not.
Yeah, okay.
That's so nice.
I'm jealous.
So now we are in 1942 and a significant innovation emerged unintentionally driven by Hedila Marm, a renowned movie star.
So to understand what happened, we need to rewind a little bit and delve into her background.
So Hedila Marm is really famous for her role in the first non-pornographic film featuring a nude orgasm scene,
which is really like, people were, oh my God, oh my God, this is so, yeah.
And she also recognized, she recognized as the face of Disney's animated film Snow White.
I don't know if it made sense.
So, yeah.
But she was facing a troubled marriage and Lamar decided to fled from Austria.
But she had a really interesting alter ego.
Like she was super duper into war and technologies, advancements.
Well, it was influenced by her former husband who was a prominent Austrian art manufacturer.
And during that time, she crossed path with a pianist named George Entail.
And together they created, they invented top secret communication for radio-controlled torpedoes called, if I remember,
Frequency Hoping Spread Spectrum.
Is it right?
Yes, it is right.
Okay, Arda FHSS.
Thank you, thank you.
Okay, let me correct this.
And so they patented this idea in 1942 and what is surprising, singly,
what is really awesome is that to see that this technology is still in use today.
And for all those who are on social network right now on the web, you can think,
Adi Lamar, because of her that we have Wi-Fi and Bluetooth today.
And a little thing that I have to say is that when it comes to unusual career changes,
I think that we are reaching new heights.
At the same time, a new way of thinking could emerge in the 50s.
So the programming was involving way faster than hardware, which is still the case today.
And so they begin to think because they had to begin to optimize their algorithm.
And this lead to an image of the singular creative genius who wielding a form of black magic.
And with that, the first stereotypical of the programmer emerged.
So the white, hairy, antisocial men.
And even if this is more to the realm of fantasy,
studies in the 60s showed that it was a profile sewed after
and it was more easily hired by companies.
So you thought you were done with Grace Hopper?
Now she's back.
And you have to know that after the war, she worked on the Univac.
So it was the more powerful computer at that time.
And when she was put in charge of the automatic department, sorry,
when she was put in charge of the automatic programming department,
she had the idea of the compiler.
So this person, this one there, she saved our life
because now our computer can understand languages that we can read.
We don't have zeroes, one or very low, low, low level languages.
So thank you, thank you Grace Hopper for that.
And as the idea was revolutionary,
she started to observe that every manufacturer,
every brand of computer was started to develop their own compilers.
So in 1969, sorry, this is not the right date.
In 1959, almost, in 1959, she faced a potential chaos that it could be.
She decided to call on her old Navy connections to organize a meeting
with every manufacturer of the country.
And when they came out of the meeting, they all agreed on a simple universal language.
The common oriented business language or COBOL was invented,
which is still in use today in banks.
Who do COBOL? Who can code in COBOL?
Here, some people not a lot, okay.
Are you happy with that?
Okay, that's nice, the love man is in there, thank you.
So I have two little anecdotes about Grace Hopper.
I mean like this woman, like who didn't know Grace Hopper before coming today?
You're gonna love her, okay?
I mean, I already, we can love her, but the first anecdote I have about her is that
she was also the person who think about the software portability.
So before, we had to rewrite every program on every computer.
And she then had the idea of why?
Why we couldn't compile the code to just put a software in between computers
without having to rewrite them?
Thank you Grace, thank you so much, oh my god.
And the second thing is like a little bit funny is that she is the one who decided to call
the process of writing instruction, coding, coding, coding, coding, coding.
And it's funny to know that this term replaced by programming
because you know this is a woman, so no coding, we're gonna say programming.
Today is coming back to our vocabulary and today is way more cool,
cooler to say coding than programming.
Okay, now look at this graph.
So this is the percentage of women majors by field.
So we have the medical school, low school, physical sciences and computer science.
And what we can see, I was going to speak in French,
what we can see is that there is a kind of rupture between women and computer science
between 1980 and 1995.
So this is a big question and I think that if you are interested in,
by women in computer science, I think that you already heard about that,
about this thing and what happened and why.
This is not the aim of the speak but I think it's still important to speak about that.
And this is, so there are a lot of reasons, there are a lot of theories about that.
And I really invite you to discuss about that with people, older people, younger people
and to see what can be done to try to make this curve up again, really higher.
But today one of the reasons I saw when I did my research is the arrival of the personal computer in 1981.
Woohoo, PC.
Before the PC, the thing is that university students had little to no exposure to computer
because they were rare, expensive and oh my god, it was like the size of a house.
So they were relatively on equal foot.
However, with the introduction of the PC, a new stereotype emerged and I love this one.
This is a joke.
The perception arose that to be a proficient programmer, you have to spend countless hours obsessively on a computer,
which is still the case today.
So leading to the notion of the real programmer who sported a computer screen tan from constant screen time.
This is my case.
I don't know if I'm good, but this is my case though, sadly.
Funny thing is many men in the business didn't even fit the stereotypes and it could be a little bit controversial.
And however for the women it was different.
You couldn't have this kind of stereotype on women because either they were not tough enough
or they were too tough and then annoying.
So many women begin to doubt about their ability to code and dropped out school.
And the last thing I have to say about that is the fact that when households acquired a PC, a personal computer,
it was mostly put in the boys room with the father taking a coach role and trying to push his son to explore programming.
Does people here live that?
Or not?
Yeah?
Okay.
And this is one of the multiple reasons why there is the wear, sorry, a gap gender who began.
It's not the only one.
I'm not saying that because people after my conference were, no, this is not the only reason.
No, I know I didn't say that.
I'm sorry.
And so before I said, like they were relatively on the equal foot and with that they weren't because the women, the girls,
wasn't pushed to, not a majority, so there are exceptions, all right?
A majority of girls wasn't pushed to try the computer or programming.
And so at the end, before university, the boys were more experienced than women.
So today we hear every day, we hear every day about Chagipiti and AI.
That's so cool.
I'm sick of it.
Thank you.
That's cute.
And during my research, I discovered several women who have advanced the field of artificial intelligence,
including Alice Chocock and Karen Spark Jones.
And today we're going to speak about Karen Spark Jones because I had to do a choice.
Scientists and researchers in computer science, Karen Spark Jones' work focuses on natural language processing
or NLP and information retrieval.
So this is a good anecdote to say when you are with your friends in a party with your friends from programming and everything.
She developed the, you know, to seem intelligent, smart.
She developed the TF IDF.
I don't know if people know that.
Perfect.
Yes, some of you.
Okay, nice.
Okay.
So this is the term frequency, inverse document frequency.
And if you may let me read this because this is impossible to read by heart because this is not my field.
This is a weighted relevance measure that is still used today by most search engines.
And it's an important tool for SEO.
So if you are doing web, if you are web developers,
it's kind of important to know it.
And this is this woman who developed it.
This method combined the physical presence of a word in a text with the weight of its importance in general.
It does make it possible to define the relevance of a specific keyword in a text.
So finally, this is kind of charge PD due to understand what you're saying when you are writing a prompt in big.
I don't know.
I'm bigger.
Oh my God.
What did I say?
And then after she decided to work with Margaret mastermind and they wanted to do, to have a little challenge to challenge themselves.
So she decided to program a computer to understand words with multiple meaning.
And the result of that was a dictionary of synonyms.
Karen published an article in 1964 that is considered as a fundamental document and the foundation in the field of natural language processing.
I think that if you are interesting in that, if you are working, if you are coding in this field or just interested,
I think this is really, could be really nice to read more about her and to let people know about her work.
So her ideas was little appreciated at that time, but they are implemented today and continue to inspire.
Okay, I'm going to say something now.
Please don't stay here.
Okay.
People go out because I'm saying that is going to be a little bit.
She also mentored a generation of researchers, both men and women, and she coined the slogan, computer is too important to be left to men.
Thank you.
Thank you to her.
Nobody is living?
Perfect.
Okay.
I also discovered something really interesting is that there are no sexism in hacking.
Why?
Because the philosophy of the hacker is that only the work of the hacker is judged in the hacker itself and not the hacker itself.
So it means that we don't care about where you come from, your age, your gender, what you look like, or anything, or your orientation.
It's hard to say this one.
This is, you are only judged by your work.
However, I had the luck to type, to do a research on Google in French and trying to search the top 10 female hackers of the world.
So, yeah.
The funny thing is that if they are French speakers here, it's written,
Le dit plus belle accuse du monde qui te font chaud, which is a literal translation from another language.
So it makes sense, but a half is not really making sense.
So this is the 10 hottest female hacker in the world.
So I watched the article and they were quite impressive for their work.
Well, this is true they were impressive for their work, but sad to be to finish inside that.
And what I wanted to say is that, yeah.
So we see a will of progress, of progressments in, is it English?
No, we see a will of doing better about all these ethics things.
But, however, we see that in the society, the female hacker still is a fantasy, like this, or we have a lot of stereotypes of women female hackers.
So the woman I would like to highlight here is Joanna Ruckowski, sorry for my pronunciation, a Polish computer scientist and security expert.
She's best known for her research on low level security and still malware.
This is a conclusion.
So I can go hours and hours about women.
To be honest with you, my first version of this conference, I think I had like 20 women.
And they said to me, come down, okay, okay, okay.
So today, many actions and associations are being set up to give a place and a voice to women in IT.
And this conference is one of them.
The reason I'm glad, no, this is not, I'm glad, but no, okay.
I have some questions, like have you ever had a role model in your life?
And this, sorry, I don't remember.
And did this role model help you to dream and give you the motivation to project yourself and believe in your dreams?
Yes, no, okay.
Yes, okay.
Did it allow you to say to yourself, I can do it?
Well, role model, like I would like now to speak a little bit about my own experience.
Sorry, this is my conference, okay, so you're here to hear me now.
I would like to talk a little bit about my experience of discovering my own role model.
So this is really weird to say like that.
The role model have a lot of consequences and all of them are positive.
Not only they can make us think that we can have that kind of dream, dream of reaching great heights, just as they do,
but above all, we allow ourselves to think that we have the right to do so.
It may sound weird and simplistic, you know.
Often when I suggest to my friends, female friends, you know, because I'm passionate of what I'm doing
and I don't have a lot of co-dra friends.
I don't know, I have Twitch, okay, it's good.
So I'm like, oh, do you want to learn a little bit?
You know, HTML, CSS, it's really funny.
You don't have to, you know, to do a trigger warning is going to be a lot of flash colors, okay, trigger warning.
You know, the little rotations and colors, CSS animation, this is so funny.
I love to do that.
And this is really funny.
Okay, it's going away, trigger warning is done.
And they always said to me like, oh, no, no, I don't want to because I'm not good at math.
So even if computer science have a basis of mathematics, depending on the field,
it doesn't like require a lot of mathematics, depending on the field.
And I love this sentence and you'd be surprised by how many of my buddies who were not brilliant at math at all
have gone on to study computer science or engineering without ever asking themselves whether they're good or not at math.
I love that, I love that.
And this is kind of a sad situation, all right.
So now we all agree and I think we all agree in the room here today that the fact that women and men are smart to do mathematics.
I don't know.
What did I write?
Okay, stereotypes linked to women in mathematics no longer put people in agreement.
And I think that we are all agreed today to say that.
But the fact is that they persist unconsciously in society.
A woman will often feel inferior to her male peers in math because of conditionings and stereotypes that persist.
I know that this is not the case of everyone.
So I had this case, I felt that until maybe I was 15 and then after I met people who let me learn math and say,
okay, no, I'm good at math and I love it.
So personally, when I discovered my role model, it was maybe two years ago and her name is Aureligeant.
I don't know if you know her here in the room.
Okay, so yeah, she's from France and she, I never know how to describe what she's doing, all right.
She's a numerical physicist.
I don't know how to explain.
She's doing AI.
She's a physicist.
She's doing a lot of things and she's really impressive.
She wrote a lot of books.
She's like trying to help people to understand the AI.
And I just fell in love with what she's done, her background, her career.
When I read her book, I don't have the translation.
If you want to read the book, you should really read her book, her first book.
Where is the mic over there?
Okay, and if you want to know a little bit more, like for the book, don't hesitate to come after and to ask me.
I can show you the book.
So like that you can see if you want to buy it or not.
And discovering this woman let me think that, okay, no, even if I was already a programmer, you know, I was already working.
I was already having, did my studies and everything.
But it made me think that I can do more because I wanted to do more, but I was afraid.
I was like, what do I have to say?
What can I say?
I'm like, I mean, I'm a woman.
I'm afraid.
It's sad, but I think that this is what I thought unconsciously before.
And meeting this woman, like being in the highlights, being in front of people, writing books and being known,
and give me the courage, give me the, it opened the door for me to go in to say, okay, I can do it too, and I have the right to do it.
So the aim of this conference is to highlight women who have changed the course of IT history
and who can inspire young girls today or women or all the people like.
But I ask you to those who have patiently listened to these stories,
when you get home to write down at least two names you discovered today and spread the word, the word, the word.
To share the stories of these women with your daughters, with your students, with your friends, with your cousins,
your niece, with the people in the street.
I don't know, your bar mate, well, I don't know.
And create them to show these women.
These girls don't have to become, they don't have to become programmers,
but you can open their horizon and show that being a girl, being a girl doesn't have to limit the choices and their dream.
So please narrate and create and propagate.
Thank you.
It's literal translation of French, so if you have better translation, don't hesitate to tell me.
So to finish my talk, my, why, I didn't, oh no, this is internet.
Oh no, oh no internet.
Go buddy.
Okay, try again.
So I know you have talk to see, I hope I'm gonna do it faster.
Oh.
Okay, we're gonna do it like that.
So, nice to meet you, my name is Laura Durieux, a.k.a. Deaf Girl.
So I'm a full stack web developer, WorldSkills Belgium Gold Medal in 2020 and 2021.
I am a streamer on Twitch and we are doing code on Twitch, so don't hesitate to come and say hi.
I'm also the show presenter of On est pas des Yankees on RTBS X-Pay, which is the national media of Belgium.
So here you can take a picture and see, and come to see me on my social media.
So the slide gonna be available for after.
Thank you, if you have questions, don't hesitate.
Thank you so much.
Thank you, thank you.