Hello, everyone. So I'm Esther. I'm a web developer at Torchbox. And Torchbox, for those who don't know, is a digital agency creating web application and website, digital marketing strategy, and we also create a cool thing, a chain mess for Django,

called Wektail. And yeah, I'm also one of the organizers back in Italia and one of the strawberry graphical code. Oh yeah, I should mention that we are hiring Python developers worldwide and in Brazil, and we have also other positions open,

so check online if you are looking. Yeah, today I want to tell you a little story. So I was in Florence last year with a friend, one of my friends, Sabrina, and we went to a bookshop. And she suggested me a very interesting

reading, Invisible Woman, Exposing Data Bias in a World Designed for Men, written by Carolyn Parent. A very good reading, my opinion, but this talk basically talk about how gender bias affect in the use of data in our

society, healthcare, education, employment, etc. So yes, spoiler, we still have a little bit to do to fix gender gap. But today I don't want to talk about the book itself, but just about a particular chapter,

chapter four, that talks about the tech industry, so our industry. And I was particularly surprised and shocked to know that during the 40 and the 50, women, not men, were the dominant sex in programming,

so the opposite of what we have today. And of course, like many of you, I think, I already see the picture on books and all these women working on computer, a lot of cables, black and white, but I never truly realized

how many of them, so they were the majority. So much, there were pictures in magazine, like cosmopolitan, to encourage a woman to apply for jobs, so a typically more seminal magazine. So my question was, how that is possible?

How do we get from that situation to what we have today, that we are struggling so much to fix gender gap and increasing woman participation in tech? So first, we have to think about the historical reasons.

So during the Second World, men were called to arm and many women work in technical roles, including operating some early computer, like ENIAC in the US and Colossus in the UK. Those experience

paved the way for women to continue to work in technical roles also after the war. And the second reason is that the perception of programming was different. In the early day of computer, programming was thought to be like more a woman thing, and was less

prestigious than the hardware engineering, because hardware engineering was considered only a heavily-dominated male field, but programming was considered more like a clerical work, so typing, feeling that were

traditionally more female-dominated roles. So this perception made it acceptable for the society, for women to work in technical field, and continue. So there was already a gender gap that lead to

underestimated the women works, and the term programming was not yet mainstream, so there were many assumptions around it, well, about what it meant. And in fact, Ruth Lichterman, one of the girls that worked at ENIAC, in an interview was trying to clarify it.

And basically here, the interviewing is assuming that programming will just rearrange the cables. And actually, Ruth stopped him and started to say, no, it's actually more than that. It's about taking pen and paper,

start to do diagrams, and when the software was big, there were women specifying only a part, a portion of the software, and only after all these steps, then start to program me, or in this case, plug in the cables. So that sounds a bit familiar to me, but I don't know why. So we have to

consider that there were no programming languages, no operating system at the time, no best practicing, good lines, textbooks. So forget solving principle, forget design patterns. Every programming technique

must be evaluated and worked out for the first time. And these women at ENIAC made a lot of innovation, in fact, and inventors on programming techniques, like Betty Hoberton invented a special

technique that involved stop the machine in the middle of the program and look for the partial result. So yeah, when the next time you are debugging and you're struggling, think about her and say thank you, Betty. Yeah, to continue our story. So the computer became

commercial at the end of the 50s, and companies like EBM start to sell them massively, and companies with a brand new computer need programmers to start building their custom software. And good

programmers were hard to find, because nobody know how to program yet. So this is when the first software crisis was declared. And companies and industries start to use some aptitude test and personality profile to evaluate the candidates, so the potential

programmers. Because nobody know how to program yet, so it was a huge, huge investment. So they start to look at those skills that

they thought that was, they would have lead to be successful in programming. So the underlying assumption is that there were some innate qualities that will be correlated to the quality of the performance. So this test aimed to evaluate a specific skill like

verbal meaning, reasoning, and emotional stability. The test usually involved identify synonyms, completely number serious, answering questions related to personality traits or a

mix, mathematical trivia, logic puzzle, and war games. So they were already widely criticized. Study proved that there were no significant correlation between the test scores and the subsequent

job performance, and they were already what they criticized, they start to make jokes of them. But here is the important thing is some beliefs came out from this personality profile. Some were things like their belief of a relationship between programming

and musical ability. Why not? And other stuff like for most of the time programmers enjoyed their work, dislike routine, and they were particularly interested in problem solving, and they

really did interest in people. Programmers dislike activities involving close, partial interaction, they prefer work on things rather than with people. So these personality profiles formalize the stereotype that we all know, a male, typically wearing a hoodie,

always wearing a hoodie, they spend all this time behind a window which may not leave much time for socializing. So unfortunately these stereotypes has discouraged women from pursuing programmer careers, because they feel they must be

obsessed with the computers and work with them all the time to be successful in programming. So as a result from the 90s, women participation in tech started to decrease, both in education and in computer science. Moreover, males were

more likely to have a computer at home, because maybe someone gives them and they play with it and they look more confident with it and skilled, and this was reinforcing the stereotype that women were less capable of programming. So

these stereotypes and bias continue to affect the tech industry today, leading to lack of diversity and inclusion in the tech team. So addressing those biases is important, it's important to interrupt them and take action to build a more inclusive and diverse industry. There are several

factors that contribute to gender bias. One is unconscious bias. So from when we are young, we get our culture-based mental models for objects, systems, people around the world.

These schemas help us to navigate the world, but sometimes they lead to unconscious bias, causing us to miss some strengths and characteristics in people that don't fit for our mental image of a good leader or a good technical person looks like. Implicit bias are

nother of the human psychology, and we all have some degrees. The important is to recognize them and start to interrupt them. Gender biases. For example, a woman made me characterize as too aggressive, while the same

behavior is socially acceptable for a man, and sometimes even encourage. This bias influences promotion and hiring decisions, so resulting disparity in compensation is estimated that globally, women are paid 20% less

compared to males, and this data is even worse if we consider people of color. This means that women work for free two months a year. So gender bias can create hostile work environment, make it difficult for women

to continue in their careers, and make this problem even worse. Another thing. So we have to consider the platform, the software that we use, because some years ago, we found out that LinkedIn was suggesting more male candidates than female candidates, and they later

hired a diversity team that should have fixed this problem, some degrees, but the algorithm still has some kind of bias in their functions. And this platform is not open source, so we don't know how the

algorithm, how they are coded, and we rely on independent studies. Moreover, recently there was with all the layoff going on in the industry, that can be, I hope not, of course, that this diversity team

may be reduced, and the consequences will know only when it's too late. I hope not. Now let's see how meritocratic system can ironically perpetrate gender bias in the industry. Let's find out by a study that

when companies emphasized meritocracy in their core values, men were often more higher bonuses than women with equivalent performance. This is because meritocratic system devaluation of the performance is often based on

personal judgment and assumption that can be influenced by gender biases. So this study highlights the importance of being aware of the consequence of meritocracy and the need to establish a truly and fair objective valuation of the performance and

promotion, and companies should reflect very well on their core values, because they aren't just slogans or mottos, but they influence the entire organization. So there are many examples that I can talk about,

and I think the most famous ones are that in recent years there was a concern about the algorithm that recognized the face of people because it was failing on people of color with that skill, and it was found

out that the algorithm was not trained enough on those minorities. Another example, we have found out that some of the health trackers are less effective on women and people of color. So this lack of the

diversity in the tech industry had led to less problem solving and less innovation, and this is not a problem for the tech industry itself, but it became a problem from the whole society. Implicit biases are

natural of the human behavior, and we all have them. The importance is to interrupt, but it's not about blaming people, but rather working together to create a more inclusive and diverse tech industry.

So, yeah, I should already convince you that is important, but exclusion is not a low priority as a nice to have, it's a must, and if it's not enough, even the profitability of the company will benefit

from having a diverse team, because it brings innovation to help to better understand the client from different perspective. So we have to fix this problem as soon as possible, because discriminating people is just wrong, and it's not acceptable anymore

to continue to perpetuate these behaviors in 2023. I want to give you an example, if you're not convinced enough. This is Diana Tamina, she's a brilliant

mathematician, and her skills help to solve a question that was going on for centuries, how to draw the hyperbolic plane, and this is an example how combining the skill will end up in innovation.

Mathematicians could not solve this problem for centuries, and this sure reminds us that innovation many times came out from mixing the different skin perspective and experience and disciplines. So Houston, we have a problem, how can we fix

in practice? First, start from the job description. Words that are considered more masculine, women tend to believe that I don't belong to this position and find the job less appealing, so

develop a job advertisement that is without masculine gender words, for example, competitive, assertive, ambitious, and track if these good lines are followed. Some researchers have shown

that women are less likely to apply to a job if they don't meet 100% of the qualification. Instead, men, they will apply even if they only meet some of the qualification, and that can contribute to gender gap in the application.

To address this, we should consider to review our long and nice-to-have list of qualifications and keep only that are meaningful and important for the job, because that can discourage some good talent women to apply. And this is a little

real that I found very funny on Instagram, and nope, wrong button. Five years experience with Excel. I only have four years and three months. Well, I heard of Excel ten years ago, so that's

basically ten years experience. Attention to detail. I did make a typo last year. I always know when my mom moves my stuff. Great communicator. I've been working on my communications years in therapy. Yeah, I talk good. Works well with others. They're going to find out I had a friendship ruined over a project in

fifth grade. Others love me. Startup environment. Ugh, I hate playing ping-pong. Startups, no HR. Yeah, that is exactly the problem. Okay. And then the hiring process.

Start giving managers blind resume, so remove all the personal detail of the applicant, name, gender, date of birth, picture, all this stuff. And track if these changes change the hiring number. Use a structured interview process to find some

set of questions to ask to all the candidates to assure more fairness and consistency and provide unconscionable training to hiring managers regularly. Encourage STEM education for young girls is

very, very important to increase participation in tech and enforce that there is more than one way to be interested in computer science. We don't have to be obsessed with the computer. We don't have to conform to the boy-hacker stereotype to be good and

appreciate the field. Representation, our role model and mentors play a crucial role in inspiring us and guiding people in their life, in their career. And one of the key note of Paeko Mitalia had an entire talk about the power of representation.

And here there is the link of my land talk. And if you're interested in the topic, put in your watch later YouTube list. Mentorship program are a beautiful example how to increase women participation. So define some position that don't require

an experience before. For example, we have the torch ball academy when we take union developer without experience. Or there is Google Summer of Code, for example. This allow people want, for example, to switch career also to start.

And it's a good way to find new talent. So preaching diversity is not enough. We have to create a safe and supportive work environment where everyone regarding their background or identity feel valued and included and heard.

To achieve this, we need to build a culture of open communication and feedbacks. Everyone should feel comfortable speaking up, bringing new ideas or report issue when they happen without the fear of backslash. Ensure there are procedures in place to report where something bad happens.

It's not enough to just listen. We must also to act. So when issue like harassment happen or discrimination occur, we should not look on the other way just because the people involved are strategic in the organization.

But instead we have to have like procedure in place, talk with HR and to address this problem. Do the training and be sure that it doesn't happen again. So an inclusive workplace is more than just a diverse workplace. It's a place where everyone feels

safe, heard and respected. And when we build such a workplace, we force a better idea and a stronger environment. And I talk about workplace culture at PyCon Italia. It's another 30-minute talk.

And I have only two minutes left. So if you are interested in continuing with this topic, this is the video. And we will upload soon. This is the streaming. And Marco over there will upload the video later. But we are enjoying the conference, so we didn't have too much time

to split in them. But they will be there soon. There are some resources that I used while I was researching for this topic and other resources. And that was it.

The slides are available on Discord and on my website, this link. Thank you. We will now have five minutes of Q&A. Please use the microphones to

ask questions. My first question is, somebody has a thing to open the bottle. Next question. Hi, thank you for the talk. I just want to ask you a bit

more about the Torchbox Academy program that you mentioned. And how do you select people for that to ensure that you're not just taking those with the most advantage already who apply, who perhaps can present their applications a bit better and things like that? I'm not involved in the organization or the program,

because I've been there only for five months. There is a day where we bring all the applications at the office and they will do workshops. We will do some talks as well. We will tell them the whole thing and then they will do a task,

I'm pretty sure. And then we will evaluate based on the performance, basically. So you bring everyone who applies to the office first? Yeah. That's really good. Thank you very much for the talk as well.

Hello. Thank you so much for the talk, that was pretty interesting and pretty much confirmed what I have been talking about since university with assumptions. One point is something I noticed from since I started programming in school with like 15, and I'm trying to apply to university, to jobs,

and now as an adult applying to jobs is, one expectation that I meet explicitly and implicitly all the time is, did you have some private projects? What did you do in your private projects? Are you always reading these tech magazines? And I sit there and think, sorry, that's my free time. Do you have, and yes, sometimes I do, but even then

what I do has nothing to do with what I do in work. Like I love embedded systems, and that's what I do in private time, and I'm a Python developer in the back end. So do you have an idea how to raise awareness in the people hiring and being the team leads that, while that is a cool thing to have and

to do, it has nothing to do if the person will be a good programmer for you, especially not in the very beginning when you're hiring juniors from university. Yeah. Okay, the question will be really long, can you say? Do you have a chance how to raise awareness for the fact

that this exists and it doesn't mean the person is a worse programmer, it just means it's not their hobby? Yeah, yes. I think when a company wants to look here and see some side projects, if you have it that is fine, but they should offer an alternative and

doesn't have to be some code specifically. Maybe just talk about your passion, but it's not about the job, so I agree to you that it doesn't matter. I would like that them will

understand that it doesn't matter. It's kind of a challenge. I hope that they will watch my video. Hi. When talking about gender bias in tech and work, I've had previous issues where people

maybe don't understand, like at a fundamental level, like the gender pay gap, or like alternatively, like anecdotal evidence of saying, oh, well, I've never had an issue being a woman in tech, so yeah. So how would you recommend talking about those issues in an informal way in work,

especially without mansplaining? It's a tricky way, because when someone has a strong belief, it's hard to convince that actually the reality is not in that way, because if it didn't happen to you, it's not true that it's

not happening. And maybe bring this topic from time to time, hey, look at this cool article or something, or sometimes it's even in the

news. I mean, recently in Italy there was kind of an harassment issue in the agency. So if you know something that happened, it can be a good way to start the conversation. Look, this is real. And start from there.

Thank you, Esther. Unfortunately, we don't have more time for questions here, but please talk to Esther after the talk. Thank you so much. Thank you, Esther. Thank you, folks from this room. Thank you.