Coding Like a Girl
This is a modal window.
Das Video konnte nicht geladen werden, da entweder ein Server- oder Netzwerkfehler auftrat oder das Format nicht unterstützt wird.
Formale Metadaten
Titel |
| |
Serientitel | ||
Teil | 43 | |
Anzahl der Teile | 46 | |
Autor | ||
Mitwirkende | ||
Lizenz | CC-Namensnennung 3.0 Unported: Sie dürfen das Werk bzw. den Inhalt zu jedem legalen Zweck nutzen, verändern und in unveränderter oder veränderter Form vervielfältigen, verbreiten und öffentlich zugänglich machen, sofern Sie den Namen des Autors/Rechteinhabers in der von ihm festgelegten Weise nennen. | |
Identifikatoren | 10.5446/32800 (DOI) | |
Herausgeber | ||
Erscheinungsjahr | ||
Sprache |
Inhaltliche Metadaten
Fachgebiet | ||
Genre | ||
Abstract |
|
00:00
Projektive EbeneGruppenoperationGeschlecht <Mathematik>MultiplikationsoperatorWellenpaketGewicht <Ausgleichsrechnung>Rechter WinkelOktaederResponse-ZeitGraphfärbungMAPFundamentalsatz der AlgebraParametersystemAnalogieschlussEreignisdatenanalyseTypentheorieDifferenteSprachsyntheseNP-hartes ProblemSchnittmengeMagnetbandlaufwerkDomain <Netzwerk>AssoziativgesetzART-NetzKlasse <Mathematik>ResultanteCASE <Informatik>FlächeninhaltInstantiierungOrtsoperatorBeobachtungsstudieMinimalgradSoftwareentwicklerEntscheidungstheorieVerkehrsinformationRegulator <Mathematik>EinflussgrößeWort <Informatik>Geneigte EbeneMessage-PassingSelbst organisierendes SystemÜberlagerung <Mathematik>Formation <Mathematik>Exogene VariableSoftwaretestDigitalisierungBenutzerbeteiligungSpieltheorieOpen SourceTaskFitnessfunktionOrientierung <Mathematik>ComputerspielComputeranimation
08:43
Web-DesignerMereologieMultiplikationsoperatorGeschlecht <Mathematik>ComputerspielHilfesystemArithmetisches MittelStapeldateiServerProdukt <Mathematik>FacebookZeichenketteRuhmasseProjektive EbeneAppletStandardabweichungExogene VariableSoftwareentwicklerEinfügungsdämpfungNeuroinformatikCASE <Informatik>DatenfeldPerfekte GruppeSoundverarbeitungBenutzerschnittstellenverwaltungssystemRechter WinkelFront-End <Software>AssoziativgesetzTouchscreenGefangenendilemmaMessage-PassingAnalysisFamilie <Mathematik>AggregatzustandErwartungswertDebuggingCodeSoftwaretestVerkehrsinformationGewicht <Ausgleichsrechnung>Twitter <Softwareplattform>Computeranimation
17:26
DifferenteDatenverwaltungMAPOrtsoperatorVerkehrsinformationResultanteLesezeichen <Internet>Web-SeiteTwitter <Softwareplattform>Güte der AnpassungBeobachtungsstudieParametersystemEndliche ModelltheorieZahlenbereichProgrammierumgebungMultiplikationsoperatorSoftwareentwicklerPunktFacebookProzess <Informatik>InformationsspeicherungMinimumNP-hartes ProblemStatistikMathematikSpieltheorieRechter WinkelGeradeBenutzerschnittstellenverwaltungssystemSoftwareProgrammierungFlächeninhaltMereologieAusnahmebehandlungRechenwerkEinfügungsdämpfungGebäude <Mathematik>Message-PassingDispersion <Welle>SystemaufrufElement <Gruppentheorie>SoundverarbeitungCASE <Informatik>Zellularer AutomatPerspektiveComputeranimation
26:09
OrtsoperatorMAPTaskMultiplikationsoperatorGesetz <Physik>GruppenoperationErwartungswertBeobachtungsstudieProzess <Informatik>Kategorie <Mathematik>SoftwareentwicklerVerkehrsinformationStabilitätstheorie <Logik>WhiteboardGüte der AnpassungBenutzerschnittstellenverwaltungssystemTeilbarkeitToken-RingSpiegelung <Mathematik>Arithmetisches MittelOvalFacebookHyperbelverfahrenFamilie <Mathematik>Exogene VariableMIDI <Musikelektronik>Metropolitan area networkFlächentheorieFreier LadungsträgerWellenpaketGeradeMonster-GruppeWort <Informatik>Befehl <Informatik>WinkelZahlenbereichSoundverarbeitungWorkstation <Musikinstrument>Materialisation <Physik>Abstimmung <Frequenz>InstantiierungWechselseitige InformationDialektComputeranimation
34:53
GruppenoperationBenutzerbeteiligungDivergente ReiheExogene VariableSchwarmintelligenzTaskPhysikalischer EffektGeschlecht <Mathematik>Physikalisches SystemSelbstrepräsentationQuaderBeobachtungsstudieWeb-SeiteUmsetzung <Informatik>Leistung <Physik>VerschlingungInteraktives FernsehenAuflösung <Mathematik>GenerizitätDifferenteMultiplikationsoperatorFamilie <Mathematik>SystemverwaltungNatürliche SpracheSoftwaretestZahlenbereichSolar-terrestrische PhysikSensitivitätsanalyseMetropolitan area networkQuellcodeMathematikt-TestHypermediaSummengleichungMomentenproblemZählenEndliche ModelltheorieProgrammschleifeAnalysisWärmeübergangGrundraumKorrelationsfunktionInstantiierungsinc-FunktionDatenfeldWeb SitePhysikerSoundverarbeitungOptimierungsproblemSchlüsselverwaltungSystemaufrufRuhmasseComputerspielComputeranimation
43:36
Projektive EbeneProzess <Informatik>ProgrammierungSoftwareentwicklerEinsOffice-PaketMAPCASE <Informatik>HilfesystemDeskriptive StatistikPunktMultiplikationsoperatorGeradeRandwertOrdnung <Mathematik>Minkowski-MetrikDienst <Informatik>BeobachtungsstudieGrundraumRechter WinkelIndexberechnungWeb-SeiteUmwandlungsenthalpieGroßrechnerZustandsmaschineWeb SiteComputeranimation
52:19
SchaltnetzComputeranimation
Transkript: Englisch(automatisch erzeugt)
00:20
It's Gabriela, but it's kind of hard to speak my name in English, so Gabi is fine.
00:26
I'm Brazilian. I came from Sao Paulo. I was the only dot on the world map from Jackie's talk, from Brazil there, so that's me. I would like first to thank the organizers for being so aware of diversity that they
00:43
bring me here to help you to improve the discussion. I must say I'm pretty impressed about the amount of women that I saw on this conference. I used to see 10 women out of 200 in some conference that I went to, and Jeff just
01:02
showed me that we have almost 21% of women. I think it's almost 90 women here, so that's nice, nice to see there. So, thank you again, and congratulations for the effort. A little about me. You don't know me. I'm not a Django developer, not a Python developer.
01:23
I'm a PHP developer. I work sometimes with Node, too. I also don't have a degree in women's studies or anthropology. All of this is my own interest in the subject. I have a passion in technology. I'm majoring in digital game development, but I don't work with that.
01:43
I'm a web developer, as I said, and I usually, in my spare time, I play with Legos. I have, like, 25,000 pieces, so, yeah, yeah, that's a lot. I'm a little overboard on that, but there's this new Lego set that's from Simpsons.
02:04
I want to buy it, but I'm trying not to. It's hard. But let's see. So, what do I expect from this talk? I want to talk about diversity and how bias can influence our decisions and what do I
02:22
mean like a girl? Some companies' diversity reports and how diversity is important to a company is some I don't want to talk about how one gender is different from another.
02:43
That's not what this is about. And this is about how both genders working together can make a better workplace. So diversity. When I was a teenager in my biology class, one of the few things I learned because I'm
03:03
not really going to biology was that about DNA diversity. You see, species that have the most diverse DNA have better chance of survival. We can see that in bacteria, for instance, where they can appropriate other DNA from
03:21
other bacterias to improve their own survivability. Although this is not 100% analogy, I think the idea is the same. The more diverse you are, the more chance you have to do something great. You have different types of diversity.
03:41
You have gender diversity, you have racial. In gender, I don't just mean male or female, you have a lot of transgender people, too. And ethnic diversity, also sexual orientation diversity. I was at Apple Store last year and I saw a girl working there.
04:01
I think she was Muslim. I think she was using the hijab. I think that's the name. And I thought that's awesome because they're not discriminating her because she's female and not because of her religion. She's just working there like anyone else. And I think that's great because you're not limiting someone in what they believe
04:24
or what they are, but in what they can do to help you. I think that's the thing that people should look for. What you can do to a team to help you improve. Bias is the, we all have it.
04:44
It's the notion that what we believe that people shouldn't or shouldn't do. We have this set of parameters that we build through our life experience. And sometimes if a person doesn't fit the parameters, you get like confrontation or even get anger towards someone or get some kind of hatred.
05:06
This, it is in a fundamental level what prejudice is like. You get, your bias can cause you prejudice. And this preconcept, concepts that reminds your actions. So even though you think you have any prejudice, you may be discriminating someone
05:26
because they are fat or because they are old. And you don't even notice it. You just do it without noticing. Some time ago someone, I noticed that people wouldn't sit down to me on the train.
05:41
At the time I was weighing way more than I do today. But because I was fat, nobody would sit down next to me on the train. And I noticed when I lost weight that people not sit down next to me. But I don't think they were like, I'm not going to sit next to the fat girl. I think maybe they did, but okay, some people don't even think.
06:02
And you can maybe do that to people of color or people from other religions, for instance. And sometimes it's so deep inside us that it may be disguised as a compliment. You know, you're pretty competent for a developer girl.
06:22
The person who said that was trying to make a compliment, but why? Because I'm a developer girl, are you implying that I'm not good enough to be competent? What do you mean? So because of that, there is this project for Harvard University called Project Implicit.
06:42
They researched the gap between intentions and actions by measuring the response time between proposed situations. For instance, they have a task that you can measure the gender versus the science
07:02
to see where your inclinations are. So they put a couple words that are female or male and a couple words that are science or liberal arts, and you have to associate them. And according to your time response, they will tell you how aligned you are.
07:22
For instance, these are the kind of tasks they have, they have a lot more. I just, this is the one that fits the slides. And I did this last one, I did this talk last year, and I did this test today again. And these were my results.
07:43
Last year, I were more inclined to the 6% of the population that did this test. I had more, I associated more women to science than female, than male. There is some explanation for that.
08:01
In my case, for instance, I studied some since I was 12 in a school where STEM area were more focused, so we had a lot of women there. So for me, it's more natural to have more women, but for the majority of people, it is how this is what you can see to the 26 and 28% of the majority
08:22
that associates men with science than women. And today, I did the test again, and I was like, yay, I got the neutral position. That's what usually should be, everyone should be that one. You shouldn't have any kind of association between gender or in academic domains.
08:41
But I think that's more because I am more involved in community now, more aware of people's needs. So you kind of get sensitive to what people can say, and you change that. I think if you care, you start to change.
09:00
So why like a girl? This has something to do with a story that happened to me two years ago. I was working in a company. That's why I bought so many Legos. They made me work like 16 hours a day, and when I get home, I didn't want even to look at a computer. I just wanted to do something that had enough to do a computer, so Legos.
09:24
And we were having this problem. It affects about 60% of our customer base, and the problem involved money. So every time that a problem involves money, a lot of people get running after you for you to solve.
09:42
And my colleague was working, and he was responsible for fixing, because this was a part of the project that only he had work. I didn't have any knowledge of it. So every five minutes someone would go through the door and ask, did you solve it yet?
10:01
And every time, every five minutes, people from financial, from HR, from every single part of the company. So we closed the conference room, turned on the big TV, and we started debugging the code. After eight hours debugging together, we fixed the problem,
10:22
tested, patched, and deployed to the production servers. Everything was working, good as new. I was tired, I couldn't see more code in front of me for like two days, it wouldn't be enough if I hadn't seen it again.
10:43
But he stops, looks at me seriously and says, you're pretty intelligent for a girl. And I was like, I beg your pardon?
11:01
And he was serious, he wasn't joking, he really thought it was a compliment. Because he's my friend, I had some liberties with him. I could say some stuff. But I can't tell now because of the time.
11:20
But I wasn't mad at him because I knew he meant well. I knew what his intentions were. And I liked him very much. In many cases, he stood up for me, helped me. So I didn't take offense, but it really stunned me. Nobody had, it was the first time that anybody had said that to me.
11:43
People had called me stupid before, but it's like they weren't trying to compliment me, they were just trying to offend me. This was just the first time that someone tried to compliment me and they offended me. So, and that got me thinking, as women, we can't fail.
12:03
We don't have the luxury of fail. If we do fail, everybody notices. Because you made that mistake because you're a woman. That's why you made that mistake. And how many times have you got so
12:23
worried about doing something so wrong? And after just paranoid, you notice they were just paranoid. And how many times have you heard women can't drive? Like, I'm Brazilian, people that just scream on the street all the time.
12:41
Women can drive like horn. They're pretty vocal about that. And they're pretty vocal about this too in the IT industry there. So if you're a woman, you can't fail, so you get paranoid.
13:03
Because if you can't fail, you work harder. And other times, you hear, you're a woman and you work with IT, that's cool, what do you do, testing or customer support? Okay, there's a lot of quality assurance people that I know.
13:24
They're really, really good on what they do. I can't do what they do. I'm not discriminating them, but you have more ratio of women working there. Same goes to front end. A guy once, when I told him I was a developer, the first thing he asked me, are you a front end developer?
13:40
Like, the fastest response I've ever seen. I was, no, I'm a back end developer, but why did you think I'm a front end developer? Oh, because you know, design and stuff. Oh, see, I think that he doesn't know Angular or ReactJS. Because I don't know that stuff.
14:00
I wish I knew, but I don't. So we have these associations, just because you're a woman, you have all these expectations because you're a woman. And that really can have a weight on your shoulders for working in this field.
14:21
And I think that for the past three years, you see more companies worried about that. And they started to release these diversity reports. I'm going to talk next. And I think this culture is more common here in America. Everything's like a girl. You punch like a girl, drive like a girl.
14:43
And in Brazil, you just call someone a fag, even though they are female, you just call them a fag. And it's the same thing as calling someone like a girl here. That's the same effect here. And as a matter of fact, I do everything like a girl, because I am a girl.
15:03
I eat like a girl, I work like a girl, I code like a girl. Because I am a girl. I mean, I'm 28, I'm not a girl, but you get the gist. But another impact here is where the male lead developer in our industry can be demanding or perfectionist.
15:21
We women, if we are demanding or perfectionist, we are bossy. And to put it mildly, I heard other stuff, but usually bossy, they tell. And I was working at this company. I was the only female in 30 developers. And she said, I had a coach, and she said to me, you know,
15:43
you have a great responsibility here. I always said, how so? As the only female on the team, you need to become part of it without losing your identity, so they can learn how to work with women without treating you like a man.
16:02
And how many times have you heard a sexist joke and just ignored it? Because if you bring that to attention for your boss or someone else, he will say to you, ah, quit complaining and just suck it up.
16:20
Or you don't want to be that girl, the girl that complains, the girl that makes everything for a case, but this isn't healthy. So what she was saying to me is, I need to make my colleagues respect me because I'm a woman and treat me like a woman. And I said to her, this is a lot of responsibility.
16:41
I can't do that. It's more easy for me to just let it go. And you have to do that. And I mean, I like to think that I succeeded. They treat me very well. Sometimes they do a joke or another that's out of place, but I don't know. They're actually young. I think that's more because of their age, but because of their gender.
17:03
Yeah, like 20, 21, they don't know. And most of the diversity reports I'm going to show here are from Google, Apple, Google Apple, Facebook, and Twitter.
17:30
I forgot it. I had Yahoo, but they didn't release their 2015 diversity reports. Funny thing about Yahoo, they count transgender people separately
17:44
because that's not just binary. I find that cool because you have a different statistic there. You can see that nothing changed, really. But the good news is nothing got worse, so that's OK.
18:01
Yeah, it's no worse, so that's improvement. You see that Twitter has four points more. And percentage is such relative measurement because if you have one person and you get two person,
18:21
you get 10% improvement. So it's hard to tell how much relevant this is. But let's say it is, just for the sake of argument. And so in our areas, most companies have the same. You can grab these reports directly from the company's web pages.
18:41
It will have not only gender reports, but race and ethnicity, too. So it's nice to see. In fact, things got worse. It's worse. Twitter had 10% before, and they got 13%.
19:03
Now, I just read an article today from Intel. They doubled the number of minority hires there. But they got a program where if you hit for someone that is from a minority and that person gets hired, you get $4,000.
19:21
So money is a good incentive. But, OK, they had results. And I think that these companies in general have really hard process of admission. I mean, I tried Amazon a few times, and every time I failed. So that's OK.
19:45
From the Apple perspective, the number is curious because Apple counts a little differently. Every female saleswoman, every saleswoman on the Apple store is counted as a tech hire. I'm not going to discuss if it is or is not a tech hire
20:04
because I try to see here as a software engineers, database, a specialist, stuff like that, not like a salesperson. But their rights should count as that, I think. But that's why their number is higher than the others.
20:23
No tech, it's more balanced, except for Apple. You see Facebook got 5% more hires from last year for this year. And to be honest, I don't think the 50% it's tangible.
20:40
I think you should aim at that. But you won't be able to get that. And if you do, it's like more of a casualty than like a result of your efforts because it's just such a magical number. And I think if you aim at between 45 to 55 ratio, I think it's a good thing because 10% is not
21:04
that high of a difference from one another. And about high level, high levels, they call senior hires are people, managers, CEOs, CTOs, people like that.
21:22
I studied for Anita Borg shows that companies that have more women on top positions, they have better working environment for women on entry levels. Because women that are managers know
21:40
how hard it is to be new at a company or be inexperienced. So they try to create a better path for women to follow. Not as a mentor, but just in general because they went through that. They know how that works.
22:01
And you can see that from Google and Twitter have 1% more and the others have the same amount. Bottom line is it's more of the same from one company to another. It doesn't change much. You don't have a company with 50% women and another with 10%.
22:20
So you could say this is a problem in your company. But what company usually do is to blame on the pipeline because you don't have enough women doing STEM courses at college. I mean, it may be true, but you can only blame on that.
22:43
There are women that are available for hire to be promoted and you're not promoting them and you're not hiring them. You can't maybe achieve 50% from one year to another, but you can achieve 55 to 30. It's not impossible. But I only see company complaining about that.
23:02
I don't see company doing anything to further that, to make it better. But why women aren't as much promoted as men are?
23:21
You see, men have 2.7 more chances to be promoted to a high level position than women. Because of that, I can see that I am one of these persons. I don't see IT as a meritocracy. Women usually don't, according to the study.
23:42
That's not me that I'm saying that's the study. But I agree with that because I don't see it as a meritocracy either. I see much about nepotism and favoritism. I saw someone before being offered a lead position
24:02
because he plays soccer with the boss. And I'm a girl. I don't play soccer. I don't like it. And so since it was an all boys activity on the company and I don't like soccer, and they said to me, oh, you can go to the soccer game. You can make a barbecue just because I'm the woman again.
24:24
Yeah. But he was hired. And I got mad and just left the company because it wouldn't make it better. He wouldn't change his mind. And I would be so frustrated to continue to work there. It's just better to leave.
24:44
Companies that already have women benefit from the fact that more women want to come to work for them. Because when I see a company that has someone that I respect from the community working there, I see they are friendly.
25:02
I want to work there also. Are you hiring? It's the first thing I ask. And so they have this advantage from other companies because of that. And the lack of role models that was found on the study, it's not like we don't have female developers that
25:22
aren't whole models. We do. I can't say about the Python jungle community, but I know a lot of good female developers in the PHP community. And they are my role models. But what the study means, it's inside the company. You don't have a role model inside your company. So if you don't have a role model inside your company,
25:41
you don't know how far you can get, if it is possible for you to get there, and to improve your path and improve your technical education. Because as IT, we never stop studying. We are always learning something. And in this case, the study shows
26:02
that the lack of role models are seen as a problem for men and women also agrees that is a problem. But companies itself don't see that as a problem. Also, they don't see the lack of mentoring as a problem. But both male and female people see.
26:22
Women values more flexibility than men. That has an explanation pretty obvious. This may fall under that category that women have two jobs. You work at a regular job and you work at home. And I heard that it's a third job
26:40
that is where you make yourself pretty because you need to be pretty. So you have three jobs. There is a book on that. I don't remember the name. A friend of mine said. But this report shows the majority of women that works in tech have a partner that also works in tech.
27:02
And I think that it's like when you see a doctor dating another doctor. It's because the other doctor knows how crazy their hours are, how you have to pick up the phone and run away to attend a patient. And I think as we are developers are also like doctors.
27:21
If something fails, you will need to stop what you're doing and go there and fix it because it's not people's lives but it's people's monies and capitalism. But the same men that work in IT
27:42
have four times more chances of having women having their partner being responsible for the primary responsibility for childcare. So the male here, they're here, have four times more chances to have their female or male partners, I don't know.
28:03
Taking care of their child. So if the majority of females have a male partner in IT, so yes, you have two jobs there. So that's why women value more flexibility than men and men value more money than women. And this leads to a factor
28:20
that women live in the workforce because of that. Not just because of that, but this is a contributing factor. You don't have flexibility. You have a job that's hard to be successful because you have less chance than a man to get a better position.
28:42
And you also have the responsibility of taking care of your family at the same time. Another article I read today, it was about Apple and Facebook. They were offering to freeze women's eggs.
29:05
Yeah, so they can work now and get worried to be pregnant later. I was like, okay, I don't know what to think about it. But I think this is more a reflection of American culture
29:20
because you have, Lacy was talking to me, you have 12 weeks of unpaid maternity leave. In Brazil, you can have four to six months of paid maternity leave. And you can be fired if you're pregnant, if you are, company has to hire you or to institute you with money
29:40
for all the months you're losing from jobs. And when you come back, you have five months of stability. They can't fire you. So I think that's why they offer this kind of things because you don't have a good working law for mothers to take care of their child.
30:03
So the more time you put off to have a child, the more successful you will be in the company and more undispensable you will be so you can have a child later and don't have your career, don't have your career,
30:20
I forgot the name. Not have your career sustained from that. But I think it's one of those ideas that are a good idea in the surface, but usually it's not. In the inside, it's like someone's trying
30:42
to make you a compliment and in actuality, they're offending you. I think it follows the same category because this is my choice, right? I mean, okay, it's a benefit. You do if you want, but it's like if everyone is doing it, why you get pregnant now?
31:01
Some expectations come. If all your female colleagues do it and you decide to get pregnant, they will judge you. You will judge you because you're going to demand yourself to be better.
31:20
That's why. And I don't think that it's a good idea on the long run because of that. The same study shows that you have twice as many men proportionally, of course, in the high level positions than women.
31:42
Just because of this family and because of work frustration, women tend to leave when they're at the mid level and you have more women on the entry level than men. Women leave mid level positions as twice as much as the men.
32:02
What does this mean? If you have five men leaving the company every month, you will have 10 women leaving the company every month. Because another symptom of that can be the tokenism. That means, I don't know if you heard that word,
32:23
it means to have every women stereotype embedded into you and have people expecting you to behave like that. For instance, at that workplace where I said about the guy playing soccer,
32:43
they had, we were doing e-commerce, Magento, and every time the phone was ringing, I had to be the one to pick it up because I was the female. And my boss told me once,
33:00
because the customers like talking to you, I was like, okay, but I don't like talking to them. I don't wanna talk to them. I work in IT, I don't like to talk to people. I don't like people. So that wasn't the only time, but it was only one of the contributing factors
33:21
for me to leave the company, tokenism. And if that happens to me, it probably happens to any other women there. Since I have a low patience, so it doesn't need much for me to just leave it at it and go do anything that I want.
33:41
I just don't get confrontational. It isn't worth it usually. So why diversity matters? I said before about DNA diversity and some studies shows that women that have,
34:01
the companies that have women in the board of directors get the return of equity or return of investment as high as 35%. Yeah, it's a lot, 35%, it's a lot. Again, depends how much we're investing, but it's a huge number, 35%.
34:23
This study was made at Carnegie Mellon University. And another study was made to see how groups reacted when solving puzzles and doing collaborative tasks.
34:40
They created groups from three to five people. Often they are all males or all females, and they put only one male or one female in each group to see how people would respond. And every time a test was done, they would measure their IQs separately and sum it up
35:00
to see how much the collective IQ from the group was. They discovered that diversity increases group performance. How? The collective intelligence is increased because of that. And when they increase,
35:20
you have a team that are more effective. They come with better problem solving and find better innovative solutions. How they did that? So groups were supposed to talk about a problem or interact during the puzzle solving.
35:40
And they saw that group where one person dominated, that group was less intelligent than the group where people were more collaborative to solve the problem. So groups with a better conversation turn taking performed better than groups where individuals were the majority of the problem.
36:05
This is why that they got. They're not saying that because there are women there, they're dumber. That's not what this is. Please don't interpret that way. What this means is it's the following. They got a group with all males
36:21
and they measure their collective intelligence and they sum it up for 415. And another group with only one women and they sum it up to 405. If you're like, oh okay, they're dumber than the other.
36:40
But the group of the only one women performed better than the group of all males there. That's because women have something called socio-sensitivity, it's higher demands. So the better, if you get the group that had the better score from all males
37:02
and the group that had at least one women with the worst score, that group was even better than the one with the best score of all males. So you only need one woman to make things change there. This socio-sensitivity is a trigger for the number of speaking members.
37:24
What this means is not because women talk more, that's not what they are meaning. They're saying that women are more engaged to have other people participating in this problem solving. So as women, we tend to have more, if we see six people and only one is talking,
37:41
we go there, say something. We usually are more preoccupied with that where men are not that preoccupied usually. That's what they are saying on their study. So my ideas were exchanges, so they got a better problem solve skills.
38:02
They also discovered that diversity powers innovation. In our field, innovation is like key for success. You see a lot of IT companies, when they don't innovate, they get like behind. You see, for instance, Blackberry.
38:25
But many people think there is a link between women and innovation. I think they don't know the cause yet, but they think there is a link. There is the Center of Talent for Innovation.
38:42
They found this correlation, but some things that can be said are, competitive advantage, because diversity trumps individual ability. Companies that are more diverse, they are ahead of other companies. Diverse groups have outstanding performance,
39:02
and for instance, in the academic field, since this is an university, patents and other studies that have mixed gender on it are cited 30 to 40% more often than only all males or all females studies.
39:24
And a sketch page from the University of Michigan said, if people think alike, they no matter how smart they are, they are most likely will get stuck at the same locally optimal solutions. Innovating requires thinking differently. That's why diversity powers innovation.
39:41
And makes sense. If you're all women, you're going to think that way. If you're all black males, you're going to think away. If you're all white males, you're going to think away. So the more diverse group of people you have, the more out of the box ideas you have. It makes sense, but people usually choose to ignore it.
40:01
Another study from London Business School concluded that the optional representation is 50-50, but it depends on the task you are doing. For knowledge transfer, experimentation, and task performance, it's 50-50%. But for self confidence, it's 60%.
40:23
That I think, and this is me thinking, that's not on the study, just me conjecturing something. When you're on a crowd, and there are more women there, you feel more safe. Because as, I don't know where I saw this,
40:43
but men are the first cause of women's death. If you count domestic violence and stuff like that. I think it's more about our limbic system that is made to protect us. And our limbic system is more like you run,
41:00
or you attack. It only has two responses. And if you have more females, the limbic system responds you don't need to attack. You can't be there, cool. It's more like a primitive response than a conscious response. That's what I think, but you can't spook that. That's okay.
41:23
And I wanna talk about this guy. Black-sized dude, or the guy who does Cosmos, the web series. He has 17 honorary doctorates. That means he's know his shit.
41:45
And there's a conference in New York where people were talking, I don't know about what, but someone asks, what about chicks and science? And the mediator said, oh, someone here wants to talk about the genetic difference between women and men.
42:02
And he was like, hi, I wanna talk. I never been female, but I have been black all my life, he starts. And he starts to saying that working as an astrophysicist was the path of most resistance to him. And I can relate to that
42:20
because when I told my mom, I would like to do electrical engineering, I did two years of electrical engineering, and my family were all like, don't you wanna do business administration or nursing school? I was like, no, I don't. And he was told the same. So every time people would take you down,
42:45
they were trying to minimize your dream to say it's not possible. And this is so true for him as a black male, and as for us as women in science. And there is a link I'm going to have there.
43:02
You're going to see. And he ends with that. Before we start talking about generic differences, you got to come up with a system that seek opportunity. Then we can have that conversation. So it doesn't matter we are generically different.
43:20
We have different opportunities. A guy has 2.7 more chances to be promoted, and we don't have the same chance. So we can't talk about generic differences if you don't offer me the same chance as you do the other guy. So how can we as a community help to improve diversity?
43:42
I wanna talk about this. This is a project from a female co-developer at the PHP community, Kayla Daniels. But it's pretty generic. It's not just for women. It's for everything. I think it's a ecosystem to empower developers.
44:01
And you have discrimination. You shouldn't discriminate someone because of what they believe or what they are. Boundaries, it's like your comfort levels are different than mine. So you need to learn to respect that. We are our biggest assets.
44:23
None of us learn when we were born knowing everything. We all learn from doing our lives. So because of that, we are our biggest assets. So return the favor, teach someone,
44:45
respect the finance, treat others like you wish to be treated. That's like everyone should think like that. I don't want to be mistreated, so I want to mistreat others. Just simple as that.
45:02
Respect the reactions require grace. As I heard my male colleagues saying that I was pretty intelligent for a girl, I wanted to punch him. But it will not service anything. It wasn't worth it. So to think better how to respond to stuff like that.
45:24
And opinions are just that, opinions. If you respect your own opinions, you should respect the opinion of others. So even though you don't agree, you should respect their opinion. And sure, it's human. So you need to tolerate honest mistakes.
45:41
Sometimes people will say something they don't mean, and you should learn to not take offense on it because you're probably going to do it sometime at some point. So that's my description there on the website, and you can help. Last year we only had seven items.
46:01
The tour is human, it's new. So you can always contribute not only for PHP developers, for the whole developer community. The other one is this one. I saw people talk about mentoring. This is the example we have in the PHP community. So people who have time available are listed there
46:24
to help someone that doesn't know much. And this is not only for minorities, it is for everyone, so everyone can help someone. And there is a IRC channel on Freenode. At the case for PHP mentoring, it's the same name.
46:43
So I think you can take this as an example and took what is best and fit it only in our community. It's just for that. It works, I have a mentor, and he helped me a lot to improve my performance, to improve my code,
47:02
and I think people should, and I am mentoring someone else so it's like you learn when you teach, so you should give back to others. And other programs that's more focusing on women, I can talk about the other ones only from PHP women,
47:22
but we don't only have women there, we have a lot of men there too. It's all inclusive, everyone can participate. We don't discriminate anyone. There's a lot of white males there too, and they help us, and we accept any help. Any help is welcome. And I think, I don't know about the others,
47:41
but I think the idea is the same. It's to be inclusive, not exclusive. Questions?
48:03
Can the women who have had that question that she brought up a couple of times, or this compliment? You are very talented for a woman. Can you raise your hands?
48:28
To summarize, I think that was every woman in the room. I would, I could encourage that discussion, and we could just keep going with our experiences
48:41
as women, but I would love to hear more about positive, forward, specific steps that you've experienced. You said that you left a company. Have you had to confront anyone,
49:01
and what was that like for you? Or something along those lines. I actually have a very confrontational spirit, but I learned that work doesn't bode well to do that.
49:20
But at the beginning of my career, I would say that for people's face, and it would mean usually me getting fired, or people not talking to me for a while, because I had a lot of anger, because I didn't understand why people were that way. And after a while, I learned why people are that way,
49:44
and how can I, and I learned that being confrontational, it doesn't help. You need to be more, I don't mean for you to run away from it, but you need to show some thought about it.
50:01
You need to show some data, because all of the stuff I told you here are from studies. Some stuff, in other words, my opinions, but because usually from people from our industry, people rely on data and much less on the opinion. So if you confront people with facts
50:22
and not just opinions, it may be a little, go better than just, why did you tell that to me? Maybe that, I think it works better. But usually, me getting away from a company it was me running away from it, from the problem,
50:42
because I couldn't deal with it. And now I know a little more how to deal with that. But it's still hard, because it's easier to run away and get another job. I live in Sao Paulo, it's the biggest city in Brazil, so there's a lot of jobs there. So, okay, are you going to treat me that way?
51:02
There's another company I can go. And that was more that way. This is hard, because when you go to job interviews, why did you change jobs? Yeah, you know, I wasn't feeling like, it's hard to explain, because usually the people from EGR doesn't know how it is to be a woman in the industry,
51:21
and they just have to say, oh, they were downsizing, and you have to lie, because if you tell the truth that you left there because you were treated badly, they didn't treat you with respect, they are going to say, this girl is problematic. People don't get that. Usually, unfortunately, I mean,
51:42
there in Brazil, it's like that. So I had to say, yeah, the crisis, I don't know, the economy. It's something like that. Unfortunately, you have to go with that, because everybody goes with that, so they won't dispute that, but that's okay.
52:00
Well, Red Hat has an office in Sao Paulo, and we would love to have you. I just got a job, now I can change it. Well, thank you again.