Antipatterns for Diversity
This is a modal window.
The media could not be loaded, either because the server or network failed or because the format is not supported.
Formal Metadata
| Title |
| |
| Title of Series | ||
| Part Number | 134 | |
| Number of Parts | 173 | |
| Author | ||
| License | CC Attribution - NonCommercial - ShareAlike 3.0 Unported: You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this | |
| Identifiers | 10.5446/20171 (DOI) | |
| Publisher | ||
| Release Date | ||
| Language | ||
| Production Place | Bilbao, Euskadi, Spain |
Content Metadata
| Subject Area | ||
| Genre | ||
| Abstract |
| |
| Keywords |
00:00
Metropolitan area networkDifferent (Kate Ryan album)KnotChemical equationBitEndliche ModelltheorieTwitterMoment (mathematics)Observational studyLattice (order)Annihilator (ring theory)WhiteboardMultiplication signMedical imagingElement (mathematics)Right angleResultantGoodness of fitComputer programmingRule of inferenceGroup actionSoftwareImage resolutionLecture/ConferenceComputer animation
04:12
Bit rateNP-hardMathematicsKnotService (economics)Physical systemIcosahedronWeb pagePower (physics)Rule of inferenceNumberType theoryView (database)Event horizonQuicksortMultiplication signWordStaff (military)Physical systemPhysical law1 (number)Group actionSoftware testingData managementMereologyGenderPattern recognitionComputer scienceRight angleWhiteboardLevel (video gaming)TheoryDifferent (Kate Ryan album)Variable (mathematics)Cellular automatonTerm (mathematics)Sound effectComputer fileProcess (computing)NP-hardReal numberBitMessage passingUniverse (mathematics)CircleInclusion mapObservational studyFreewarePoint (geometry)Computer programmingDescriptive statisticsGoodness of fitNeuroinformatikComputer animation
13:48
Game theoryPort scannerSound effectNP-hardTouch typingMereologySpeech synthesisNP-hardLinear regressionStandard deviationTerm (mathematics)MereologyGroup actionException handlingVideo gameGame theoryPhysical systemBlind spot (vehicle)Self-organizationGoodness of fitMixed realityQuicksortElectronic mailing listGraph coloringOpen sourceLatent heatOffice suiteSocial class1 (number)Message passingPosition operatorAnnihilator (ring theory)Information securitySelectivity (electronic)Execution unitProcess (computing)Projective planeRight angleTouch typingMarginal distributionMultiplication signDot productPersonal digital assistantDependent and independent variablesMathematicsTwitterInclusion mapStatement (computer science)Medical imagingStudent's t-testGoogolBookmark (World Wide Web)Software developerKeyboard shortcutDecision theoryDoubling the cubeSound effectComputer animation
23:24
Metropolitan area networkLevel (video gaming)WordFood energyBoss CorporationPosition operatorMultiplication signLine (geometry)VideoconferencingGroup actionGoodness of fitDirection (geometry)SoftwareLattice (order)Computer animation
Transcript: English(auto-generated)
00:08
As he said, my name is Naomi Cedar. I've been in the Python community for longer, maybe, than I would care to admit. I am at the moment serving as one of the board of directors for the Python Software Foundation.
00:28
I am refusing to be rattled by flashing lights in my face. I encourage you to do the same. And among other things, I did found the first trans-themed hack day in Europe, Transcode.
00:46
So my, I guess what I would say, my somewhat unusual, although not completely unique experience, as I talked about a little bit here at EuroPython last year. And my experiences have led me to think a bit about diversity and advocacy and things like that.
01:06
Before I go any further though, I need to give you a commercial. In a very short time, right after lightning talks today, in the Baria room, one room, we will be having a meeting of the Python Software Foundation.
01:23
And everyone is invited to attend. For a while I, you know, foolishly put members meeting on it, but it's really for everyone. We want to update you on the new membership model that we have been putting in place for the Python Software Foundation over the past two years. A short story is that anyone can be a member,
01:46
and more of you, I think, than you would expect are actually qualified to be voting members. So we would like to tell you about that. Workgroups, which are a way that we hope will allow more people to be involved. And, as we always close such things, more. So I will see you there, I hope.
02:05
Okay, so to begin, we know that diversity is a good thing. I'm going to take that as an article of faith. If you strongly disagree, then maybe you better go find another talk, because this is the assumption. In fact, studies have shown diverse teams solve complicated problems better, diverse teams
02:23
are more adaptable, diverse teams are more creative, and these studies have been around literally for as long as I have been alive. And that is longer than almost all of you have been alive, okay, a long time. We also know that in our particular sector we have a shortage
02:43
of talent. We need more people. Recruiting, whether it's in my experience in Chicago or in London, is kind of a nightmare to find people, and it's only going to get worse. We need more people, not fewer people. And finally, this probably should not need to be said, but I feel an obligation
03:06
to say it in any case. We have, I would submit to you in the tech world, a good thing. We have interesting work to do that allows us to make a good living. Not sharing this, it strikes me, is just wrong. Yet, I went looking, this is on Google UK, under image search for a programmer.
03:31
I'll give you a second to appreciate that as they did a little comment here. We've got 15 images, got one duplicate, we've got one rather abstract, although still kind of much looking character
03:42
there. We've got a cartoon or two. And out of those 15 images, you'll notice that we have one that appears to be a woman, and we can't see her face. Okay, we have one person who is black, and if you look closely, he looks both puzzled and angry. The rest of them, I don't
04:09
need to say anything about. To put this another way, Twitter in the US, after a campaign to improve
04:21
diversity, announced not long ago that they have now 49 black engineers out of their engineering staff. That's less than 2%. As Lynn mentioned in her talk earlier today, women are leaving, the tech world in mid-career, and this comes from, I think, the same article that Lynn had
04:45
referenced, they are leaving in droves. They are leaving more than they leave other things, they're leaving far more than men do. So, in other words, we don't just have a pipeline problem. In fact, if you look at the numbers of graduates in computer science, and the data
05:02
that I could find was US specific, but I have a feeling it's pretty general, the percentages of minorities, women, et cetera, graduating from computer science programs are not matched by the percentages being hired. So, again, it's not just a pipeline problem.
05:22
On Tuesday, how many of you saw this hashtag trend? Oh, that's a thing. In my circles, it was a big deal. It started trending late on Tuesday. I strongly encourage you to look it up. Real diversity numbers started trending late Tuesday and on through Wednesday. And, basically,
05:42
this was started asking the tech world for, let's have some real diversity numbers. Let's find out how many people who are, you know, depending upon gender, age, race, economic status, et cetera. There were things posted like, yes, companies, please tell us how many autistic people
06:03
had to quit your wonderfully open planned company because they couldn't stand the sensory overload and do their work. Please tell us how much more work a black female needs to do in your company just to get the same amount of recognition as a white male. Things like this,
06:22
it's a provocative thing to read. Again, I strongly encourage that you do that. And I need to stop here and say that I wouldn't go along with what Lynn said earlier. The Python community has done a lot. There's very, very much that I'm proud of. Honestly, in many ways,
06:40
the fact that I'm standing here is a testimony to that. The fact that I am on the board, all of those things. But I do also have to say that when I'm at a conference like this, not just this one, but like on US, other ones, I tend to ask myself, who am I not seeing here?
07:02
And I'm not going to tell you who I'm not seeing here. I'm instead going to invite you, maybe not now, maybe later, whenever, to think a little bit about who it is you don't see at these things. And then maybe the next thought would be, what do we need to do so that we do start seeing this? So diversity, that is getting lots of different people involved,
07:28
is a hard problem. Inclusion, that is making them feel like they really belong so that they stay involved, is a harder problem. But it is everybody's problem. And I don't have clear
07:52
answer to that. I'm not talking in this talk about them. And I'm not talking really about you. I'm talking about me as well here. These are things that I particularly also think about
08:05
because I think we need to be really clear here that being part of a marginalized group, being in some way, quote, oppressed, does not excuse you. It does not give you a free pass for everybody else. Okay, the fact that in the tech world, I am an old trans woman,
08:23
that's three strikes already, does not excuse me from worrying about questions of race, economic status, disability, any of those other things. So I'm really, these are things that I have been thinking about as well. These are things that I try to watch myself about here.
08:42
So I'm not trying to externalize this as me lecturing you or as me pointing a finger at them. This is us that I am talking about. So if what we're doing isn't working, why do we keep doing it? This was what prompted this whole talk. And really, it sort of then led me to think about, as far as technical people,
09:07
we like to solve problems, we do things. And I think TDD is kind of an example of that. Everybody now says, yeah, this is kind of a good idea. Unless you actually change your behavior
09:21
and write the tests, it doesn't work, of course. If somebody says, oh, yeah, yeah, TDD is wonderful, but we just aren't having much success with it. Well, why is that? Well, we haven't actually written any tests yet. Nobody's going to buy that, okay? So this is what I'm thinking of. And then, honestly, just so that I could get a provocative
09:41
title, it occurred to me, anti-patterns is what we're talking about here. All of these things that seduce us down the wrong path when we're trying to do something, whether that's in coding, or perhaps it's in management styles, taking care of people. If you actually go look up anti-patterns on Wikipedia, they have pages upon pages upon pages of the ways that we can
10:01
mess ourselves up. So these are the things that I'm going to talk about. So the first thing I'd like to mention is, and by the way, this is just my sort of wash-the-cup grouping of these. If you want to debate the niceties of how these should be classified, then that's fine. I hope you find somebody who wants to debate that.
10:23
So the first one I said called denying the problem, or denying that there is a problem. And you do still see this here, and I mean this, I think, is the meritocracy thing. It's like, well, we would hire good people, there just are no good people of type x, whatever that might be.
10:42
And, in fact, it seems to me, and I know that for some people meritocracy is a very sacred idea, but it seems to me meritocracy is a way for the people who are successful and in power to make a story that justifies why they're successful and in power. Similarly, there are people that say, well, I don't see a problem with sexism. You will notice
11:03
that the people who never see sexism are all male. I'm just observing that. You can draw your own conclusion. Or, you know, similarly, there's the whole, well, but people of type x, whether it's women or minorities or whatever it is, they don't want to do this kind of work,
11:24
that's not, that's why it's there. So, all of these actually are sort of ways to kind of shoo the problem away and say that it doesn't even really exist. And, of course, then the last one is kind of a generic description of what a lot of the industry does, that is,
11:43
say, yes, yes, yes, we want it to be diverse, and then just hope nobody notices the actual numbers. So, again, refer back to the real diversity numbers hashtag. Similarly, you can deny, you can say, yes, yes, it's a horrible problem, but x, y, and z is not a fix. There is no fix, in fact. This is also quite common. So, the people who blame the pipeline
12:08
are, in fact, saying, well, there's nothing we can do. Somebody else is screwed up, and now it's just all, you know, we can't fix that. Or it's the education system. Or, you know, just for whatever reason, there's nobody here that even wants this job. It's a problem.
12:26
And, again, this is a way of saying, well, I don't have to do anything about it. This one is perhaps a bit slippery, more slippery, but I think another thing that we all fall into is assuming that everyone is like ourselves, and if they aren't in that,
12:45
in some way that we think important, like ourselves, then they can't be good at what we do, right? I mean, we can't have coders who don't want to play ping pong or something like that. I mean, that just wouldn't be right, because all of us here in this group play ping pong. No offense, but I hate ping pong. So, you know, it's that sort of thing. So,
13:04
we start talking about, then, culture fit, or I was hired by doing this long, grueling, whiteboarding programming exercise. Therefore, anybody who is good at programming must be able to do the same thing. All of these sorts of things. This also actually ignores a couple
13:24
of things that I would like to revisit some time at another time, and that's the notions of imposter syndrome and stereotype threat. These terms are thrown around a lot, so I'm going to sort of assume that you've heard of them before. Imposter syndrome is, of course,
13:43
very prevalent amongst very, you know, highly skilled people who look around them, see everybody else, and decide that they themselves must be a fraud while everyone else must be doing wonderfully. And it tends to rob us of a lot of good efforts by people who say,
14:01
oh my god, I don't think I can even try to do this because I'm going to be caught out as a fake. It tends to cause a lot of anxiety. It's a problem, it's not a problem specific to women, but I think it is a problem endemic with women in tech. Stereotype threat, if you haven't heard
14:20
this one, this is the one where if you tell, say, a room full of people about to take a math class, maybe the, you know, mixed composition, you say, oh, by the way, black people will almost always do poorly at math. This very fact will make the black people start thinking, oh crap, nope, I'm not going to fall into that stereotype, I'm not going to do it, and their performance
14:42
goes down by the very fact that they're now worrying about that rather than what they were supposed to do. And this happens with almost any population. Again, women and minorities particularly get struck by that. If you have processes or ways of sort of bringing people in that don't take this into account, then you're not going to have very much success, would be my
15:05
thing. I call this one rigging the game because it is, basically these are things that will make it impossible for somebody who is not in the system to really succeed in the system.
15:21
And microaggressions, this is the first one, and how many of you have heard the term microaggression? Pretty much everybody, good. How many of you committed one? All lying, thank you. So, microaggressions are things that you, that are done, that are micro, they're not
15:43
necessarily big, but they sort of eat away at you. My particular personal favorite in my life is that I've had a couple of friends tell me, you know, you're really, you're really pretty impressive. You're not totally crazy like the other trans people I know. Okay, so if you're thinking about,
16:05
well, that's a compliment, right? I mean, if you call people and say, what, I was trying to be nice, in effect what you're saying is that I probably really am crazy, I'm just good at hiding it. Or the classic one that some women will have heard, sadly I have not, is you're too pretty to
16:24
be good at coding, right? This manages to kind of say, tie your appearance to your talent, kind of to the detriment of your talent and things like that. So there are a lot of these things out there, and in fact, they happen a lot, and they tend to wear people down.
16:43
My favorite metaphor for this kind of process is pecked to death by ducks. I mean, it's nothing, it's just endless, and this is a reason, honestly, that people will leave. If they have to put up with this day after day after day, hour after hour, minute after minute, and if you don't
17:00
believe this happens, then you should talk to somebody who is sort of in a minority position in an organization for just five minutes to hear their stories. Double standards, this one, again, and this one I think is one that women point out a lot, of course it applies to other
17:21
minorities as well, where you basically get caught in a double bind for things that don't really apply to everyone else. My favorite story, when I transitioned, I went from never having anybody having a problem with my wonderful and sweet personality to being told that I was unapproachable and too nice. Okay, you can't win against that. Women are quite often accused of
17:47
being shrill if they happen to get angry, even if they do happen to get angry, as a matter of fact, stating a fact can get you in trouble. Not having defined processes, this would particularly apply in a company or something like that, whereas, you know, so how do I get promoted? Oh, don't
18:02
worry, we'll take care of it. I suppose there's a complaint about harassment. Oh, we'll work it out at a time. All of those things tend to mean the people who are marginalized lose, okay? And there was, in fact, a good talk by Katie Heddleston at PyCon US about this,
18:22
and there is now a project called No Null Processes to work on, kind of coming up with open source statements of processes. And then finally, and this is the big one that a lot of women are leaving the industry in mid-career, is that they're not given a way that, well, they're underpaid, this is kind of a fact, and they're not given a path
18:42
to advancement. A junior female developer can say, well, okay, so I want to go to the next step. Well, you need to have worked on a good project for that. Okay, so I want to work on a good project. Oh, well, we don't think you're ready yet. Well, so how about I get a mentor so that I can get ready, and you're sort of shoved off one way or another or another.
19:05
This is my one image. I wanted to do more images, except that I did a Google search for them yesterday and got so depressed that I had to stop working on my talk for a while. So, but I figured XKG, so this is kind of the example of the double standard that you see. Digest that
19:24
on your own. Ignoring intersectionality, the problem with the way that marginalizations can work is that one of them's bad, two of them is more than twice as bad, three of them is more than three times as bad. They add up. If you're a woman, that's not great. If you're a woman of
19:43
color, that's even worse. If you're a trans woman of color, that's even even worse, and so on, and it builds. And unless you understand that in the people that you're dealing with, you know, you're not equipped to even talk to them intelligently. And then finally, and this one here honestly touches my experience perhaps more than any of the others even,
20:06
is not listening. And the first part of that is that if you're not actually involved, if you're not involved is wrong, if you don't actually experience those things, if you are not the target of those things, it's often quite hard to see this. So I'll go back to the thing
20:24
where I, again, I have heard from many men of absolutely good faith that they just don't see sexism in their industry. And that almost always means, yeah, that's because they're men, they don't see it, it's not there. You know, a white person, it's not likely to see racism.
20:44
I mean, and these things, and here again, I'm speaking from having spent a large part of my life, as one of my students put it, undercover as a cisgender white male. And when I was getting ready to transition, and I've mentioned this before, I was really worried
21:05
about some of these things, and I tried to watch for it. This was not a matter of me trying to brush something under the rug. I was actually trying to see what I would be up against. And honestly, even trying from that viewpoint, it was very hard for me to see things that
21:21
once I was in that position became totally, completely obvious. Okay? You need to, and we all need to be aware of those blind spots. That is, if it is not something that affects me, I may have a hard time seeing it. That means that when somebody who is affected by it
21:43
tells me something about it, I need to listen, not ignore it. Okay? If a person of color tells me about racism, my saying, I don't see any racism in this industry, does not mean a thing. They're the ones that are experiencing it. I know from experience that they are probably right.
22:03
This can be a little bit uncomfortable because quite often, listening in these situations can feel like you're being accused of something. If someone I know who is black tells me about racism in the U.S. and how I have gotten an advantage that they haven't had, it feels like
22:21
an accusation. In fact, it isn't. It is a problem. It is the truth, but we need to get past this whole, no, I didn't do it to you. Maybe I didn't, but I benefited from it, so it's my responsibility to help fix it. So again, as I was saying, diversity is a hard problem. Inclusion is even harder.
22:44
We don't have any easy answers. We don't have any overnight fixes, but this affects all of us. Again, just because we're part of one minority, just because we're part of one marginalized group, that doesn't give us a pass for everybody else. So we all need to be part of the solution,
23:02
and this will require having different people join us, will require doing different things. We need to come to terms with that. We need to write the tests if we're going to do TDD. We need to actually make the changes, and I believe that will make us all better. Thank you.
23:39
Thank you, Naomi. Does anybody have any questions?
23:50
Hire people, handle the situation, because I probably would like to increase the... Most of the people in my group, they are white men, but I cannot tell my boss,
24:04
I'm not going to hire a white man, and my company wouldn't accept that. So I don't know how to handle that. I don't want to start interviewing white men, because these are going to be the majority of the people applying, and rejecting them simply because of that.
24:20
So I don't know how to handle this. I promise, I'm going to stick to my promise, I don't have a good answer for that. I have been in those situations where we needed to make a hire, and these were the people that we had, and I did not have the time or energy to find anybody else as an alternative. So I can't say there's a good
24:43
answer. I try to think of ways that I can get the word out about positions to other communities. So I think making contact with other things, networking with other people is a way to start, but there isn't necessarily always an easy answer. We have to do what we can, where we can find
25:02
what things to do. Okay, that's unfortunately all the time we have, so if you have any more questions, talk to Naomi directly. We'll be around at the PSF meeting. Thank you.