Season 2 Episode 3: Cultural Competence in Computer Science

Summary

In this episode, we talk with Nicki Washington, a full Professor of the Practice at Duke University, about cultural competence. We discuss the definition of cultural competence. Its history, why we should care, and what it means in the context of computer science. We also talked about Nicki’s new class on this topic and her 3C Fellows program. Finally, we close with a call to action. Many people and organizations have started learning, reading, and making commitments. What needs to happen next is to start executing plans and iterating on them quickly (agile method style). We need to hold people accountable because reading and planning aren’t enough. Our discussion did not close with a too long; didn’t listen segment, except simply “get uncomfortable and listen to the whole episode.”

Nicki mentioned many resources during our discussion. We have done our best to link to them in the transcript.

You can find this episode’s transcription down below!

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Transcript

Kristin [00:00] Hello and welcome to the CS-Ed Podcast, a podcast where we talk about teaching computer science with computer science educators. For context, we’re recording this episode on October 8th, 2020. So, potentially, some of the things we talk about may be out of date by the time you listen to this. However, hopefully, the world will be better when this podcast is released than when it is recorded. With the disruption of Covid-19 and the latest call for changes in education due to racial inequality, this season’s theme is, “Where should we go from here?” in hopes we can all take a pause and ask ourselves, “If I had time to reflect rather than react, what should I be doing?” I am your host, Kristin Stephens-Martinez, an Assistant Professor of the Practice at Duke University. And joining me today is the awesome and amazing Nicki Washington, a full Professor of the Practice at Duke University. And so, Nicki, tell us about yourself. How are things going with you and your transition to Duke University? 

Nicki [00:57] Thanks, Kristin. My transition is interesting, given this is October 8th and we’re knee deep into Covid and the semester. But it’s been good. So it’s been easier for me than if it were somewhere else because I’m from Durham, North Carolina, born and raised. So, thankfully, I’m able to come home and stay with my mom while I get situated and just throw things in storage. But overall, I think, in terms of transitioning in a time like Covid, a time like 2020, with so many things that are going on in this country around issues of racism, I think it’s wearing and taxing. And so it’s also trying to find a way to turn some of that anger and frustration into something productive, while still protecting some part of my peace. And I don’t know if I’m doing that as well as I should be, but by November, when the end of the semester hits, I definitely will be. 

Kristin [01:56] That’s good. So our main conversation today is cultural competency. And you are making quite a name for yourself with cultural competency right now. So how do we start with the basics, though? What is cultural competency and why should we care? 

Nicki [02:11] So cultural competence was created in social work in the late 80s. It’s a term that discusses, “You need to be able to work with people from—as the way it was defined originally—different cultures.” But cultures really apply to different identities. So race, gender, class, ability, sexuality, any type of background that constitutes identity. You should be able to engage in them in conversations and in discussions in ways that value their identities, but allow you to glean whatever information you need to gather as well as provide any relevant information or service that you need. It was born in social work because, of course, those professionals have to engage with people from a diverse range of backgrounds.

And so in the 90’s, it started to spread into education as well as health care. Why? Because these are also fields where graduates end up working with people from diverse backgrounds. More important, they work with people from vulnerable populations. So that extends across all of the ones that we’ve discussed. But it includes the elderly, people based on racial or ethnic backgrounds, people in socio economic backgrounds, prisoners, children. And so being able to ensure that graduates have this level of cultural competence where if I am now a social worker or an educator and I’m in a classroom with students who identify, for example, as Black or indigenous, am I engaging them in ways that respects their identity but also allows me to effectively impact them in ways that are beneficial and not harmful?

So my goal was to look at how and why is cultural competence not being used in the same way and taught in the same way in computing? Selfishly, there were a number of reasons that I was doing that, which was mainly because I was fighting my own battles of racism and bias at my prior institution. So for me, it was finding a way to resist. And, as I tell people, it was my form of protest. So I pivoted my research around this because I kept saying a lot of these issues I’m facing are because there are people in this field, students as well as colleagues, who don’t understand my experience as a Black woman. They don’t understand that the field is not level for me and that the goal posts often moves for people who look like me in ways that I can’t control. And until we start to get more people to understand that, specifically people who don’t share my identity, who operate in spaces where they are overwhelmingly represented in computing, then we’re not going to change the narrative and move the needle any. And a lot of the work that everyone claims to be committed to in terms of diversity, equity, and inclusion. 

Kristin [05:22] Alright. I love the nuance that you added that I actually hadn’t thought of about culture is not just what you standardly think about, which is race and gender identity and all of that, but also age. Like that hadn’t occurred to me. But that makes complete sense of how an elderly person’s culture basically is different from, like, my culture versus a small child’s culture. It’s very much broadening my understanding of the meaning of culture. So I love how you defined it and also wrapped in the “why we should care,” because clearly, you do not understand another person’s culture, almost period. Like every person is their own unique snowflake in a sense. 

Nicki [06:00] Right. And when we look at it in terms of a medical doctor. So when a medical doctor engages with someone who’s elderly, let’s say an elderly Black person. There are certain things that they think about and they’re concerned about in their communications with a doctor because of various historical reasons, right? Henrietta Lacks. Something that maybe a fifteen or sixteen year old who shows up with the same identity to the doctor is not necessarily thinking about in the front of their mind. And these are the ways that we also have to think about it in terms of computing. We do a lot of work on developing these cool technologies and making life easier. But who are we making it easier for? And at what cost? So when we have technologies that are biased. They’re great in certain aspects for some people. But at the expense of who. Right? And that tends to be people who are already systemically-marginalized and or vulnerable populations in some way. 

Kristin [07:16] I like your example of the doctor, but I’m struggling a little bit in imagining it more from the computer science side. And that’s mainly because, like a computer scientist or someone in computing is not in a position the way a doctor is in a position to a single other person. Like in computer science, it’s more, “You are a tech technical person in some way with a larger team and you’re interacting with a very large pool of faceless users in a sense.” So it’s not quite the same as a doctor patient kind of relationship. So what does it look like to have a greater cultural competency in that setting? 

Nicki [07:57] So if we look specifically at computing, I’d say take the examples of facial recognition software, because this is what women like Timnit, Joy talk about all the time, as well as Ruha Benjamin and others. When I sit in front of a camera… perfect example that I gave to class recently is an article that came out about students who are taking the bar right now. Well, because of Covid, everyone’s having to take the bar at home. Because they’re having to take the bar at home, there are certain states that are including specific software where you can sit in front of the computer, there’s facial recognition technology that will monitor you taking the bar to ensure that you’re not cheating or doing anything else. Well, the issue has come out that students with darker skin colors have issues with the technology recognizing their face. The same things that Joy, Timnit, and the Algorithmic Justice League talk about at length.

What they’re having to do is turn on, of course, all of these white lights to make sure that they illuminate their face as bright as possible so that the camera can recognize them. What is the impact of that while you’re taking the bar, though, which is already a lengthy process? So now I have this white light sitting on my face. I’m getting a headache. I’m frustrated because I’m having to do all of these extra things just to be seen by the software so that I can take a test which will basically determine if I’m able to build my career in the state that I want to.

How does that impact, especially when it’s only happening to people with darker skin tones? So there’s an entire demographic of people who don’t have to worry about this. This would have been circumvented if there were people who, when developing the technology, not only if there were people at the table who looked like the people impacted by it, but more important, if the people who were there just simply considered the case of have we thought about every skin color? Have we thought about the fact that everyone may not look like us, who will be taking this test? And how would that impact them? We need to make sure that when we test this, that we have found a diverse range of test cases. Which is flooring to me because one of the things we always talk about in early computing courses is ensuring that you do exhaustive testing. You test for the best case scenario, the worst case, and at least somewhere in the middle. So how did you not consider a worst case scenario as developers in this field? 

Kristin [10:34] And, plus, the skin color issue for cameras has been around I feel like at least for a decade.

Nicki [10:41] And historically, it goes back into the 70’s. Right. So look at the first portable cameras and any type of photography period. The first, right, you have that Shirley card that was used to adjust lighting for when film was developed. And when that was done, the Shirley card was a picture of a woman and everyone who developed film would use this Shirley card to make sure that their settings were correct when they developed the film so that the color came out. Well, Shirley was a white woman. A blond white woman at that. And so what you found was that people with darker skin colors were always underexposed in pictures because of that. But that’s something that started in the late 70’s. And we’re still seeing it in the technology that’s developed just in the last 10 years, which is problematic in itself because why didn’t we learn the lessons from what was happening in photography for decades? 

Kristin [11:40] So digging deeper. Why are we struggling with this?

Nicki [11:45] So I think there are people who genuinely don’t care. And I think we see that, I’ve seen it personally in some of the communications on different computer science educator listservs. Right? There are people who explicitly go out of their way to say that, “This is computer science. We should just be teaching theoretical computer science. Why are you making this about race?” Which becomes its own form of gaslighting that we see in this country in general where people, who tend to be in the majority demographic, don’t want to talk about things regarding these issues of race and identity because discussing it means that I have to acknowledge that I’ve either been complicit in it or that I have been an active participant in discriminating against people of certain identities.

There’s also the other subset of people who and maybe there’s a third set, but there’s a subset of people who really want to do the work but don’t know where and don’t know how, which is to no fault of their own. As computer scientists, we are not trained in anything relating to behavioral and social sciences unless you go out and actively seek that as an elective course. And so because of that, we understand very clearly X plus Y equals Z and all about an algorithm being a step-by-step solution to a problem. But if we start to get into issues of bias and how those algorithms are skewed, then it really doesn’t register when we’re taught things like “fail fast, fail often”—get things out there quickly and iterate on it. But when you get it out there quickly, you are not doing your due diligence and thinking about other people who may not share your identity.

But then there’s this third pocket of people, I think who, who are kind of just OK with it. They kind of recognize that there’s a problem. But it works for me, so I’m pretty much okay. I’m not going to ruffle any feathers because of that. And I think that those people, the first and third groups of people are the people we really need to focus in on. That first group, sometimes, I don’t even know if you can, you can help that group because they’re kind of set in stone. So you’ve really got to target that second and third. The people who want to help but don’t know how. And the people who are just pretty much complacent, but if nudged enough by everyone in that second group, they’d move into action. And specifically noting that this has to be work that’s done by people who do not identify as systemically-marginalized.

Part of the problem that I see has been that a lot of the work that’s been done in computing has been focused on the students. So, specifically, systemically-marginalized students and even systemically-marginalized faculty. So we’re going to provide mentorship and access to resources and things. That’s fine. But that’s not the biggest problem. Because if you give a student access to courses early enough, I’m living proof that a student will develop the skills. The issues become… when you place them into environments where no one else has been taught that the way it is, is not OK. And the way it is, is not the way it should be or is supposed to be. And so they have to deal with issues of bias and marginalization and struggle with a sense of belonging. Not because they’re only getting it from their peers, but they’re also getting it from the faculty and administrators.

So until we focus in on decentering the systemically-marginalized students and making sure that we focus in on teaching and training everyone else, who does not identify as systemically-marginalized, we’re gonna continue to see these issues because there’s a lot of projects. If you think about all of the efforts, even from K–12 to higher-ed, that are designed to push for more diversity, equity and inclusion. How successful are they right now? There’s a lot of work in the K–12 space that’s focusing on making sure that every student has access to computer science courses. Well, what happens when that student shows up and that’s a Black student—a Black girl—who shows up at a predominantly white university and she’s the only person who looks like her in her classes. There are no faculty who look like her. And oh, by the way, there are peers as well as faculty members who are insinuating either explicitly or implicitly that she’s only there because of affirmative action. 

Kristin [16:16] So what can we do, it feels early in the conversation to ask this by feel like we probably will spend a lot of more time on this. So I’m asking all of my guests. What do you think we should do right now? What do you think we can try and accomplish in a year? What can we work towards to achieve in five years? 

Nicki [16:34] So the first thing we have to do right now is admit there is a problem, collectively. One of the best TED talks I’ve seen is by Kimberly Crenshaw, who coined the term intersectionality. And she discusses explicitly that in order to solve a problem, you have to acknowledge that the problem exists. And we’re still struggling in computing with people at all phases, K–12 through industry, acknowledging that there is a problem and that they in some way have helped to create that problem. And that’s hard because that means that people have to acknowledge, one, their complacency or their ability to just not care. And that—and again—that’s hard. 

Kristin [17:22] What is a way to get to that place? Because I think people individually, especially probably quite a few people listening to this podcast would agree with you that there is a problem. But how do they help their colleagues also get to that place? 

Nicki [17:39] I think you have to provide research and evidence that supports it. Because a lot of times when you debate certain topics, it comes across, or people choose to argue, that it’s being debated based on emotions and not facts. And especially in engineering fields, everyone is hard on facts and we don’t really get into feelings that much. So if you come with hard facts, then you can start to demonstrate that, which is why it’s important for people to immediately, even if you think you’re part of the choir that I’m preaching to, that you make sure you’re well versed in the facts so that you can start to present those as evidence to people who are nonbelievers.

For example, the work of the Algorithmic Justice League, the work of Ruha Benjamin and Safiya Noble. Coded Bias as a documentary is a great film to start looking at the ways in which, for example, facial recognition technology is impacting people of different identities. And then you use that as your basis to infuse some of the social science research that we talk about, right?

So, for example, we see a lot of times right now that especially in 2020, there are a lot of universities and a lot of organizations who are making these commitments to racial justice and social justice. Well, by doing that, you’ve got to start also holding people accountable. What are you willing to do? What are you willing to sacrifice and give up in order to make space for this type of work, this type of initiative? And the people who are doing that work? 

It does not always mean that people in computer science or engineering, for example, are the experts. That means you have to go to the spaces where these are, the social sciences, which for a lot of us is hard to acknowledge as valuable. I’m sitting on review boards and things for different papers where a paper that comes in that is based on qualitative data is kind of frowned upon. And “Well, I’m not really sure because their N is small in terms of sample size.” And I have to say, “You know, I need you to really understand that there’s a difference between quantitative analysis and qualitative.” This is perfectly fine in a qualitative space, but we need to make sure that we are presenting evidence of that to others in our field.

We also need to make sure that we are well versed. Like I said, reading, researching, reviewing this information. As computing faculty, it’s always interesting to me when people say, “Well, where do I start and what do I do?” When, if your student asked you that, a lot of you would say, “Google is a thing. You can start there.” So having said that, it’s exactly the same, right? If you’re interested in certain things, you will take the time to invest in learning and researching valuable information. It’s a ton of it out there. Like I said, the Algorithmic Justice League has a ton of resources on their website. Books like Race After Technology, Algorithms of Oppression that specifically talk about these issues in the context of race and computing. Automating Inequality. Invisible Women. All of these are specifically talking about the problems that we create as computer scientists, but from the experts who have the ability to map it to issues in society. So I’d say starting there.

But you can’t just read books. And that’s my biggest thing. And that’s a lot of things that we’re seeing right now. Everybody has a book club. Everybody’s reading. But then you’ve got to move from reading to processing and acting on that. And that’s probably, over the next year, what I need to see and I would like to see is people who are taking the time to collectively say, “We’re going to be intentional about inclusion. It’s not an afterthought, but this is something that we are planning for in every part of our curriculum. It’s also something that throughout our department, it is a mandate. It’s a priority and it is a focus. And we’re not going to wait for organizations to require it to happen.” By organizations, I’m talking about ABET or CSAB, for example. We’re going to do this ourselves because this is the expectation that we have of every student coming out of this department. And because of an expectation of every student, it also should be an expectation of every single faculty member, which means that somehow performance reviews, tenure and promotion, any post-tenure reviews, all of these things should be tied into, “How are you creating equitable and inclusive environments for diverse faculty as well as students?” Because the faculty are having the exact same problems that the students from marginalized groups are. 

Kristin [22:37] Wow, that feels like, it’s this combination of, “that feels like a tall order,” but like I completely agree with you at the same time. And so I’m having a moment of, like, that, that’s heavy. That’s a big lift. 

Nicki [22:50] It’s a big lift. And, and honestly, I tell people all the time, because I created the 3C Fellows program, which works with faculty on this, and Shani Daily, who’s an Associate Professor of the Practice in Electrical and Computer Engineering, as well as Cecilé Sadler, who’s a graduate student in Electrical and Computer Engineering. They’re working with me on developing that. So, as a team, we put together a strong program to work with faculty in doing this.

And some of the responses that we get is that what we’re asking is a lot in the preparation material for it. My response is, “Yes, it is.” But imagine how much more it is for your marginalized students and colleagues to continue to have to endure the racism and the bias that they have been dealing with, not just since they’ve been at your institution, but their entire lives. So if you can’t be inconvenienced enough and uncomfortable enough to do the work, then why should any of us ever believe that you’re really committed to change?

And at the end of the day, also, you have to think about it in the context of what we’re seeing in this country and what we’ve seen historically, which I tell people all the time. Look at every major movement in this country. No social justice movement has ever been successful by keeping white folks especially comfortable. They have to be uncomfortable. They have to be moved to make hard decisions and do things that require a ton of heavy lifting on their side. The civil rights movement. The abolitionist movement. Everything else we’re seeing even in, in these split versions that we see of the feminist movement. 

Kristin [24:26] Wow, OK. So what I’m, I’m definitely hearing, like there’s step one, acknowledge this problem. In the next year, it sounds like, yes, it’s OK to have a book club. But definitely plan to do more than just your book club over the next year. Like more than read, also, start planning. In the next five years, kind of execute on a plan. Does that sound like a reasonable summary? 

Nicki [24:49] Somewhat. But I’d say five years, waiting five years for you to execute is five years that we’re going to lose more Breonna Taylor’s, George Floyd’s, and Ahmaud Arbery’s. And just this week, Jonathan Price. So we don’t have five years to wait. We have, like, we were just talking about at the beginning of this podcast, right? Reading does not require a year. So with the onset of audio books that you can process information a lot better and in formats that are more conducive to your current work environment and your current learning environment. It’s important that constantly reading and prepping is something that we tell students that they should do because you should always be in a state of learning.

So that should not be a, “Complete this step and then increment to the next one.” It should kind of be, this is where you kind of can pull in some of that agility of the software engineering models or software lifecycle models, right? You need to do some reading, implement, plan, strategize, roll out. Implement some more. Read some more. And keep doing that because it’s a learning process. Myself as a computer scientist and as a Black woman, I’m still finding books, like I said, to read and learn about because I know I don’t know everything. But I can’t keep waiting to read. And I think that’s what, what even moved me to push to get a lot of the work that I was doing done this semester. Instead of waiting, for example, to the spring because I kept saying, spring can’t wait.

You know, specifically, I remember the point in time in May when Christian Cooper ended up almost having the cops called on him by Amy Cooper. And I specifically noted and tweeted that day, thank God we know Amy Cooper’s name and not that man’s name, because at that point he was still alive. So he wasn’t a hashtag. Little did I know until I woke up the very next morning. George Floyd had been murdered that exact same day I was tweeting that out. And that was a turning point for me that was like some of these things that I’m talking about. I can’t wait anymore because this is just too much. And to the credit of my outgoing and incoming chairs at Duke, both Pankaj Agarwal and Jun Yang, as well as Owen Astrachan and Susan Roger. They all gently nudged me like, “Hey, I know that you were thinking about rolling this out in the spring so that you could advertise it better to students. But I think this is something that would be really important to get on the books in the fall. If you can, we will do everything we can if you’re ready to push this forward.” And I said I really don’t have a choice. Some things just can’t wait.

And that’s how I think about the question about five years to implement. I think reading now is great. Starting to have those conversations now is great because, again, it’s going to take people who don’t look like me to impact and change the people who are the nonbeliever’s right now. So if we’re talking about a field that’s predominately white and Asian men, it’s gonna take other white and Asian men to influence and impact them. 

And the same goes for women, because I think a lot of times we assume that women all get it because we’re all marginalized based on gender. But there’s a ton, a ton of literature and research back from the suffrage movement, where they talk about the fact that Black women are always marginalized in any push for women’s rights. We saw it with Ida B. Wells and the Black women and other women of color who were marginalized in the suffrage movement. All the way up to the feminist movement and what we see now.

So it’s important that everyone in every space who does not have, especially an intersectional identity that is marginalized, that you become the advocates and the activists and accomplices. Not just the allies. And you start to have these hard conversations. You start to push people and make them uncomfortable. And when you see something, like Congressman John Lewis said, you say something and you do something. So for me, it becomes over that next year, while you’re reading, you should be putting plans into action and implementing them. This is, what, October? So even for the spring semester, there are a ton of things that educators in the CS space can be doing then to enact change. It can be small pockets, but every little bit helps. 

Kristin [29:14] In some ways, it sounds like you’re advocating for, like, an agile development version of enacting change for this rather than the waterfall method, which is what I realized I was kind of proposing. 

Nicki [29:26] Exactly. Exactly. It’s that iteration, right? So we have to kind of, you have to spiral it and you have to make sure that you’re taking the lessons learned with each small version that you implement and building upon that, recognizing that there are probably going to be some mistakes along the way. But if you’re doing the work, which is why it’s important to really push yourself right now and get uncomfortable, you minimize those mistakes.

It’s also the exact same thing I tell my students. Right. Good programmers are good designers. If you design first, like we all teach in programming, then your errors will be as minimal, if any, as possible when you get to the point that you actually start implementing it on a computer. But nothing you do first and foremost should be sitting in front of a computer and typing away when you get a problem because you’re gonna make a ton of errors. And the same thing is happening right now. In this space, when we’re talking about race and other identities, you should not start going out gung-ho and saying, “I’m just going to do whatever. And I have this great idea. I have embedded it and let’s roll with it.” No, you need to make sure that you have taken the time to think it through, design it, run that design by a couple of people, if you’re unsure, iterate on that and then roll it out. And if it has a few glitches in it, then we can tweak those. But it’s a lot easier to explain those small glitches than those egregious ones. 

Kristin [30:55] How is your class going? Like, you had to rush it, it feels like. But otherwise, is it going well, though? 

Nicki [31:00] It’s going extremely well. So I wouldn’t say I had to rush it. I think the design part I always had. It was just putting all the pieces together that I hadn’t thought about and I plan to do probably over this August to December time frame. So the race, gender, class and computing classes, it’s really going well. I have about 18 students enrolled, which is a good number because the max we capped it out was 25. I was concerned if I would even get 5 or 10 because, again, I’m a new faculty member and nobody knows who I am. And so I’m just hoping that some people sign up.

So for me, the design part, I was very meticulous about. Part of it was that lived experience allowed me to pull together a number of things. I also tell people I’d been pushing for this course for about a year and a half. So three semesters I’d been fighting to get this course on the books at my prior institution. And so because of that, there were all of these things that, as I heard a podcast or I saw a TED talk or read an article, I kind of committed to memory and then would start dumping it into one document with a link to it. So, when the summer hit and Jun and Pankaj and Susan and Owen said, I really think that it would be great to go ahead and roll this out. I started going back to that document and saying, “OK, now how do I put all of these pieces together to make it make sense?” So I had this huge document with hundreds of articles, episodes, documentaries, and blogs. But how do I schedule this in a way that makes it make sense? And that was the part that I spent the summer doing. So I decided to take the first half of the course and really just focus in on understanding identity. So then we move in the second half of the class into technologies and how certain technologies impact all of those identities that we talked about in the first half.

So I’d say it’s going really well. It’s a great group of students. I tried to plan for—because I tend to be a half empty kind of person—I tended to plan for every worst case scenario possible. So I wanted to make sure that it was a safe space for every student, that there was no gaslighting, there were no issues of bigotry or racism in any comments from students. And I think, you know, to the students credit, they’re phenomenal. I haven’t had to worry once about that. And because the students reflect in journals, I’ve even read where they say, “I really appreciate the fact that we were able to set house rules to begin the first week of class,” where I created some and then I let them also input some house rules. Such that everybody was able, even when they’re asking questions, they don’t feel like they’re going to be attacked for asking a question because they really just want to understand, not try to gaslight anyone. And so it’s really refreshing to see students be able to appreciate the intention behind everything that was done. 

Kristin [33:59] Can you define gaslighting? Because I actually only recently really learned what this term meant. And I’m wondering potentially if some of our audience haven’t looked up what it means. 

Nicki [34:08] I say gaslighting is a situation where someone is purposely minimizing the impact or ignoring the impact of certain actions or words and how they impact other people in ways that are done to intentionally marginalize them even further and intentionally ignore these concerns with the purpose of inducing some sort of emotion or making that person feel like they are crazy for thinking that what is happening is. That’s probably the biggest piece of gaslighting, is having someone or making someone believe that what they know to be true is not the case. And essentially making them feel bad for even thinking that in the first place.

For example, I talk about my experiences, but my experiences are common. Right? And I think that that’s something that it’s really important for the audience to remember, is that the things that I’ve discussed, the personal experiences that I’ve had—especially the bad ones—they are way more common than anyone probably thinks.

And that’s also something that I could go back to that people should do immediately, because one of the things I tell everyone in every talk that I give, if there’s any questions around these issues, go out to Twitter and take a look at #BlackInTheIvory. Go search that hashtag and see the experiences that Black faculty, students, and staff at predominantly white institutions across this country are sharing about the racism that they have been subjected to every single day. And how frustrating it is being gaslit, being denied, being rejected, marginalized, and constantly still having to show up and be twice as good to get half as much as someone else—who’s barely doing enough to get by—is getting easy access to with no questions asked and no vetting. And it’s flooring. It’s heartbreaking. It’s infuriating.

I remember when that hashtag was live and running and it was just going on Twitter. But you see so many common themes that relate exactly to what I’ve said. And I tell people the real kick is those are only the things that people were willing to share on social media because some people are still working in those environments. Some people are still trying to get a degree or tenure and promotion. So they’re still treading lightly with what they share. And if that’s what is the best of the worst, then you can only imagine what they’ve kept. 

Kristin [37:02] Aww, that makes me so sad. Just hearing about it. 

Nicki [37:07] It’s infuriating. And that’s why I said it’s not enough to wait. It’s not enough to just read, because as people are reading, there are still not only Black men and women and children being killed in the streets, but there are Black women, men, and children who are being impacted in classrooms and educational environments and work environments every single day. And they are being emotionally taxed, psychologically taxed. And given the impacts of stress and everything else that we’ve seen and the added pressures of Covid. How it disproportionately impacts Black people and indigenous people and other people of color. It’s really important that people just realize that you have to start doing something. 

Kristin [37:56] So we’re almost out of time. And I’m wondering if it’s worth… Is there a way to end this podcast on a positive note, or is it worth actually leaving it at this point? A more call to action. What are your thoughts? 

Nicki [38:11] Well, for me, I’d say there’s very little that’s positive about what’s going on right now, so asking me to do that would be faking. 

Kristin [38:18] Okay, we won’t do that then. 

Nicki [38:20] I say that, you know, it is a call to action. Right? We are—We are frustrated. We are tired. We are overwhelmed. We are exhausted. I say every other day, “my Black is tired.” And when I, and when people ask me, well, what does that mean? Because someone interviewed me and said that he was trying to Google what that meant. And he couldn’t find it anywhere, which I find hilarious. It means that I’m tired. I, you know, my blackness has been on full display for 42 years since I’ve been on this earth. And I’ve been trying to explain it, justify it, and push to be seen and valued. And we’re tired. 2020 is taking a toll on all of us. But if you look at communities of color, especially Black people, we are overwhelmed. And so it’s time that people put their money where their mouth is and start doing some walking and less talking. 

Kristin [39:14] Mm hmm. It feels almost like closing with a TL;DL, too long, didn’t listen, isn’t even worth it. Like, I feel that in this case, someone should just listen to the whole podcast. There is no way to summarize it. What do you think? 

Nicki [39:27] Yeah, absolutely. Get uncomfortable. 

Kristin [39:29] Yeah, get uncomfortable. Maybe that’s how we can end it. Like TL;DL: get uncomfortable. Alright. Well, thank you so much for joining us, Nicki. 

Nicki [39:37] Thank you for having me. 

Kristin [39:38] And this was the CS-Ed Podcast hosted by me, Kristin Stephens-Martinez at Duke University, and produced by Amarachi Anakaraonye. And, remember, teaching computer science is more than just knowing computer science. And I hope you found something useful for your teaching today.

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