“I want every US presidential candidate…to give me a list of what they are going to in order to address institutionalized racism. I want to know what regulations, I want to know the policies, I want to know the data. And I want to be able to review your plan. Give me a plan for that. How are we going to address inequity in education? How are we going to address the fact that we have books written for and by white men? How are we going to start putting things in that highlight more than slavery when it comes to Black people?”
Dr. Brandeis Marshall is a computer science scholar, educator and founder of DataedX. Her work focuses on the racial, gendered and socioeconomic impact of data in technology, including designing data science pedagogy for marginalized communities and assessing the socio-technical implications of BlackTwitter. Dr. Marshall participates in increasing data literacy and understanding, sharing best data practices and broadening participation in computer + data science through speaker and workshop leader engagements. For more info visit www.brandeismarshall.com.
Kim Crayton: Woo! Hello, everyone, and welcome to today’s episode of the #causeascene podcast. I’m already giggling. So this will be a very interesting episode. I’m not gonna hesitate. I have Dr. Brandeis Marshall on the show today. And if you could introduce yourself to the audience, please.
Dr. Brandeis Marshall: Oh, sure. I am a computer scientist by training. I am an instructor/educator like yourself by occupation. I teach at the college level and above, and I am running a startup. So I just started a startup about a couple months ago, so we could talk about that too. I’m working day and night, traveling, speaking, resting, dealing with a lot of wellness. So it was very nice to get a little rest and relaxation over the past few days, and now we’re gonna get back to the grind. So that is me in a nutshell.
KC: All right, so I start the show as always, as you know: Why is it important to cause a scene? And how are you causing a scene?
DBM: All right. Oh, here we go.
KC: Here we go. Let’s dive into this. And also, just to let you know, this is an uncensored show, so you can use whatever words, whatever phrasing you feel like, go ahead.
DBM: OK, the United States, and in fact, I think the world, is becoming more Black and Brown. Yet our educational system does not reflect its constituents in the books that we learn from, in the instruction that we have. In particular, since I’m in this data science space, I work a lot with trying to broaden participation, access, inclusion and representation in computing and in data science. We don’t have any people of color, just period. So, as someone that has been teaching for a long time, I’m just now moving into trying to find nuggets and examples and showcase all of that. It could be at the collegiate level, it could be at the professional level, but I’m trying to build in race, gender, class to whomever I’m instructing.
KC: Yeah, yeah, yeah, yeah. So, when Dr. Brandeis logged in, I had to pause her for a second cause I had to complete a tweet. And I sent her the tweet, and we just started laughing because this tweet by an individual—and I’m gonna share it in the links—but it says,
“Sorry, Beale Street was too much for me. Though beautifully acted, written, and shot, I’m exhausted by examples of Black love engulfed in trauma and horrible endings.”
I had to tweet this because I said, “This is why I won’t view any more video of Black bodies being beaten by police or terrorized by whiteness going about our daily lives. Yes, Blacks have had to endure the horrors of white supremacy. YET I REFUSE to allow this to be the only NEGATIVE NARRATIVE that’s told.”
I just, I get it, this is the thing for me here on this. And then I want to talk about—cause I wrote some notes—I want to talk about your learning the language of Black Twitter. I think that’s interesting. And then we’re gonna talk about your startup. We can go anywhere with this in this hour, but I want to start here because it seems to me, and I said this several months ago, and people who know me… this started, and I didn’t have the language then, after watching “Boys in the Hood”. Let me look up when the hell that movie was, I want to let y’all know… 1991!
DBM: Yeah. So we’re dating ourselves?
KC: Yes. Yeah.
DBM: There was a whole genre of them, right? “Boys in the Hood”, “New Jack City”, you know. What was the one Eddie Murphy was in?
KC: “Harlem Nights”? Yeah, it was all of that, it was “Set it Off”. All of that stuff was out. At that point, I had been out of been out of high school a few years, at that point. I knew in my early twenties I couldn’t watch this stuff, and I didn’t have the language for it. I just knew that I just could not continue to watch this stuff. And now what I understand is I’m sick of you white people being voyeurs to our pain. This is so insidious. It is so disgusting to me that it takes you watching a video of us being brutalized by the police or some white woman calling the cops, whatever, for you to believe our lived experience that we have been trying to communicate to you for from day one. I will not participate in that. My friends know, if it ain’t funny, or a superhero movie, don’t ask me to go see it. I’m not, I can’t. I’m not doing it.
DBM: I mean, I get to the point where I can’t even see certain shows.
KC: Oh, exactly!
DBM: I can’t… what was the most recent one?
KC: That “Watchmen” that’s on HBO everybody talking about. I don’t want to see that.
DBM: I don’t wanna see that, but Ava Duvernay?
KC: Oh, about the Central Park Five?
DBM: I saw the first one and I was like, I can’t.
KC: Uh-uh, I don’t want to watch that. I’m not watching the “Handmaid’s Tale”. I’m not watching any of that stuff.
KC: I have to protect my mental health. I do not… and I get it. I get it. The stories need to be told, because they haven’t been told. It seems like there’s so many, because we haven’t been allowed to tell these stories. But as a Black person, I get to choose which stories I wanna watch, and I’m not watching. Because those things traumatize us, we act like… I’m not desensitized to that, and I shouldn’t be desensitized to that. And I don’t want whiteness to get desensitized to that because that’s what I’m seeing. When you can have a conversation about “Harriet” and not talk about the pain, but you want to talk about the actors or the fact that they added a Black character so that the white character could be the hero. I got a problem with that.
DBM: Mmm. I haven’t even seen “Harriet”.
KC: No, I’m not going to see it. I just heard they added a Black overseer who is an abuser so that the white—who is not even in the historical story, they added it to the story—so that the white slave owner saves her from the Black person. I’m not interested in that narrative.
DBM: Yeah, they have a buffer, got it.
KC: Yes, exactly. You know, I’m not interested in that narrative, and so it’s just so incumbent, I need you to… cause I had a conversation—and this episode will air in January—but I had a conversation recently because I’ve been talking about capitalism. I’ve been talking about… we’ve been reading as a group on Sunday. We have a #causeascene book club, and we’ve been reading “How to be an Antiracist”. And I’ve been pushing back on a lot of Dr Kendi’s assertions that he’s made. And one of them in particular, is about capitalism. Because he says he wants an antiracist anticapitalism, and I am of the opinion that we can have an antiracist capitalist system. And that’s where I want my research to go. Because capitalism, like Marxism, like communism, like socialism, is only a theory. It’s that all of them have been active and moved forward with white supremacy at its root.
I’m saying, can we, let’s see if we can do this capitalism thing without white supremacy as the root, as the thing. And until you, until someone can say that doesn’t happen, then I can… But I don’t have a problem with capitalism. It is how we’ve used it to justify the horrors around the world.
KC: And so, I was having a conversation with one gentleman in the community, because he’s really been trying to understand this and because he was like, he thought I was anti-capitalist. I’m like, no, no, no, I believe in business. No, uh-uh. It’s just that y’all white folks are the ones who’ve been able to run this stuff and make the rules. So he said—it was a conversation about Kamala Harris. And and he was saying, “Hey, I see you follow this other black woman who’s really talking about this. I would love for you to have her on the show so you can talk about this.” And I said, “One: She and I DM each other often to unpack what’s is going on in the world; and two: I’m not here, we’re, Black women are not here as a circus act for you, for you to learn from or for you to gaze at us. Why would I bring her on so that you can have entertainment?”
I mean, I get it. I get it, and this is the thing. I understand it’s an innocent request or thought, but it’s not innocent because it goes back to when we’re talking about just, you know, the whole you have to see me in pain for you to understand and believe that I’m in pain. Why should Black women have to openly have conversations about how Kamala Harris is being treated like shit in the media, being treated like shit among everybody else for you to believe? Why I got to have a conversation for you not to be able to see it for yourself?
DBM: Because the most dangerous thing is a bunch of Black women together. That’s the most dangerous thing. That is what my current pilot is looking at, it’s looking at building Black excellence in data science. So these women have joined this journey with me and several of my collaborators in order to form this community of just, a safe space to talk about data. And I talk about race and data, right? I talk about how systems have been constructed. You know, I talk about tech and talk about what is really data science. What is the workflow? How data is people. So if data is people then they’re talking about you, they’re talking about me, they’re talking about your life. They’re talking about your kids. They’re talking about your relatives.
KC: And I love how they always want to make data seem so unbiased. Data, and it is just like, you know, we’re gonna take the human… how the hell do you take… where did the data come from if not from humans?
DBM: Exactly! That’s what I talk about. I spend a weekend with at most 20 women. I’ve done two so far, one in Atlanta and one in Houston. We’re funded…
KC: Damn, I hate that I missed that! OK, go ahead.
DBM: We’re, this pilot is being funded through the Kapor Center, in collaboration with blackcomputeHER (https://blackcomputeher.org/). I’m not sure if you’ve heard of blackcomputeHER. We can talk about that in a minute. We were funded. So there’s gonna, there’s already two. So yeah, that one in Atlanta, one in Houston. And we put these women in a room and they come, some of them fly in. And we have two days, a Saturday and a Sunday, and we talk about it. And then every month we talk about other things. I put up little assignments. I share videos. I give them the opportunity to self-guide their learning and also ask questions of the community, of me, of each other. They post about different activities that are happening within their own spaces, what they might want to do in their career. I mean, this is a little alcove, right? This is a small alcove for you to actually come in, be present. Not have to worry about anything else, and just release.
KC: It’s so funny because this is something that my friends and I are putting together just because we’ve seen the power of Black women and the ability to get a group of Black women together to align and commit to helping each other rise. It is the fear of white supremacy. It’s the biggest fear of white supremacy.
DBM: It is the biggest fear! So I do everything I can in order to protect the community.
KC: Yes, and that’s that’s vital. That’s vital.
DBM: That is the work, labor that I do is to protect the community. I tell the women, look, we’re asking for you to sign off on any media releases and voter releases. And some are just like, “What are you talking about?” I was like, “Because I’m giving you a choice. How often are you given a choice? Do you want this out there?” So, on my LinkedIn, I finally posted the two pictures, one from the first group, one from the second group. It’s gotten all these likes and everything like that. But it took me a while to feel comfortable to even release those photos because I did not want to tag anybody. And I had to have that conversation, go, “Look, I don’t want to tag because I want to make sure that you have anonymity if you want it.”
KC: OK, now this is… you just spoke to it.
DBM: That’s why I’m starting… that’s why I have my startup, DataedX (https://www.dataedxgroup.co/), because its data education plus X, whatever the X may be.
KC: OK, so now let’s break this down. This is how this comes out. Just like you and I sitting over coffee. I go all over the place!
DBM: So right, right, we’re going all over the place. But this is… but that tweet hit on the reason why I do what I’m doing in this startup.
KC: Exactly! And this is where you just hit on something. And I’ve had several white people to come on and understand this: whiteness is all about their individual… it is about them as an individual. I can’t speak for any other people of color. I’m gonna talk about Black folx; it’s about community. And so you just spoke on, you highlight how I run and manage #causeascene as a community. My job is to ensure that people are safe. It’s not about the individual, or the person with privilege. So, I’ve made missteps when it comes to trans individuals, and when they call me out, I publicly make that a teachable moment. I changed my vocabulary and we move forward because I want to make sure that the most vulnerable are taken care of. Because when the most vulnerable are safe, everybody else is safe. Whiteness is not used to that. Whiteness is all about the individual. And so this is where I see the head butting happening in tech right now. You have these white tech guys who’re used to just doing what the hell they want to, whatever makes them comfortable and never having to not only not deal with the consequences of behaviors, but not even having consequences to behaviors.
DBM: There is that point, right, if there’s also other people of color, Asian, South Asian, Indian, as well as Asian as far as Chinese, Japanese, Taiwanese, and I’m missing a couple of other groups there. Sorry about that. That are also in the tech space and have blocked out…
KC: You coming! Keep going!
DBM: People of color who are in this…
KC: That’s that model minority myth. That’s that model… they have come to protect their proximity to whiteness, and they will do anything to stay anywhere… to distance themselves from Blackness at all costs. I have found that the biggest, when I call something out, that the most rabid, the most vitriol, the people calling me a bitch the most, all of that on Twitter. Now they’ll send me emails cause they’re anonymous. But the ones on Twitter, are South Asian men. I actually had to go to one of my South Asian Twitter folx and say, “Hey, what the fuck is going on here?” Yeah, why? Because I understand the model minority myth. But why are they coming to the rescue or the protection or defense of whiteness in a space that is so, so hateful of me, when whiteness would throw them under the bus, and he was saying, and he really helped me understand. He’s like, “You know how you how you have learned to engage when mediocre white men attack? I need you to engage with these dudes the same way, because that’s how they are. They are insecure. They are trying to protect, because, let’s be honest, the only reason they’re in this country or doing this work, let’s be honest, because white supremacy has given them permission to do it. It’s not something that they have the agency to do on their own.”
DBM: So that’s I run up against more than anything. And I’ve been in computer science since ’96, when I started college, right? So it’s been a battle.
KC: Yes, and this is why I’m very clear when I say, don’t say “people of color” when you mean Black people, and don’t say “women of color” when you mean Black women. Say it, name it, because it’s not the same. So that has been your biggest, those have been your biggest obstacles?
DBM: Yeah, because I I taught in an R1 institution. So that means that there’s PhD programs, fully vested, as well as there’s a lot of federal and corporate money that professors are getting in order to pursue their research. And, yeah. I had grad students and some of those grad students, they did not like me as their advisor. Their research advisor. So I had it, I had a time. I had a quite challenging time to get students through the program, with the graduate work, for the master’s program.
KC: And think about that related to data. If you don’t… how do you? How do you say that data is is unbiased when you have individuals who don’t respect the individual who’s been placed to guide their learning.
DBM: In academia, you have certain bars, right? You have about six years as an assistant professor, before you go up for what’s called promotion and tenure. That’s promotion to associate professor, and tenure, which you come in untenured, or with non-tenure. So about halfway through you receive an evaluation, a formal, more formal evaluation. But that evaluation includes a little bit of your teaching, a little bit of your service. The lock share is going to be about your research production, which you are dependent upon graduate students, and of course, collaborators in your industry, in order to help you produce that work and gain those grants. You are having challenges in obtaining and maintaining good graduate students who are going to listen to you. Navigate through the process of getting through their degree program. You’re constantly recycling the work. You’re like a rabbit, just on this bad treadmill.
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DBM: You’re like a rabbit just on this bad treadmill. And then things happen to me.
KC: And you’re just hitting it because people want to act like these are innocent things, but you just hit it. You need grant money, and you need these things to keep your job. These are financial impacts.
DBM: Oh right, this is financial all day long. It’s finances in order to pay for a graduate student out of your grant, it’s finances to pay for yourself over the summer when you’re a faculty member at the collegiate level. It’s all about how the money runs. And if you don’t have a suitable cadre of workers, collaborators who are your colleagues and peers as well as undergraduates and graduate students, it’s very difficult to make it all work. It is very difficult to make it all work.
KC: This is so, this is new to me. See again, that’s why I love this show, because I learn so much because there’s so much that people want to make it seem like that white supremacy is KKK and swastikas, and I’m gonna add MAGA hats in there, because to me, I’m gonna tell you, a MAGA hat ain’t no different from a swastika to me. I’m not going… you might think, you might be wearing it because that’s what, you know, you want to fit in with your community, and you don’t really espouse… but whatever. I’m not gonna go around and figure out who really espouses, who really believes in this MAGA hat crap, and who don’t. I’m just gonna remove you from my circle of influence. So that said, and I’m saying this because I need folks to understand, cause I have to, as an educator, this is classroom management. I draw very clear boundaries. So you can try to argue that shit if you want to, but it ain’t happening here. So this is what I want to point, because everyone wants to act like this is innocent. Oh, it’s just this, it’s just a symbol, it’s just… No, this shit is fundamentally impacting how Black women advance professionally and economically. Now y’all want to talk about the, you know, the wealth gap, and we can’t get a leg up.
DBM: Right! I mean, if you look at the work of Fay Cobb Payton (https://cobbpayton.com/), put that name in your, just read her work. Because she talks about Black academics, she talks about Black women academics, she talks specifically about how we’re pushed out. We’re given the advisory mentoring role, officially and unofficially, especially at institutions that have very little diversity, people of color. And I do mean people of color, not just Black people, but just people of color. And then, we aren’t given the opportunities in order to move up. Or we’re getting so much slack and flack, that we just leave. She talks a lot about that, that’s the body of her work. So, as I said, I’m always trying to cite Black women and always trying to make sure that when I talk about data, about computer science, I am trying to highlight and amplify the work of others who have done some phenomenal things, that people are not paying attention to.
KC: I’m about to send her a tweet right now.
DBM: Good, thank you. I mean, I could just list women. I mean yes, cofounders of blackcomputeHER, Jamika Burge and Quincy Brown. There is another sister that I know, right? She is Dr. Nicki Washington (https://nickiwashington.com/). She’s just started Represent 365, where she is highlighting Black scholars instead. Now, these are all women in computing, because I’m in computer science. So these are women in computing. They’ve all got PhDs, you know what I mean? So as Black women being so highly educated, we’re doing this work.
KC: And getting no credit for it, because I would not think, based on what I see in the media, based on what I see in most social media, is that there are any Black women doing this work. You wouldn’t think that, because no one’s talking about talking about, talking to you, or talking about this.
DBM: Right, because they want my face on the website, but they don’t want my voice.
KC: And they want your data and your expertise, but they don’t want your voice.
DBM: And they don’t want to pay me.
KC: Woo! Girl! Gods almighty, damn, no, you just hit it. I got eight…
DBM: I talk about this all the time, I talk about money!
KC: Girl, I…
DBM: And they’re not gonna pay me. Pay me!
KC: Girl, somebody said…
DBM: If I have to ask… I’m sorry, right here.
KC: Go ahead.
DBM: I gotta go off on this point.
KC: And I’m right behind you.
DBM: If I have to ask you, how much is my honorarium? I’m already annoyed.
KC: Yeah. Exactly! Exactly!
DBM: If I have to ask you, “Are you covering my travel?” I’m already… I’m just thinking about how to roll this back, because I can’t deal with this no more. That I will get, I will sit in a room, and there will be someone, non-Black, come in for just that hour and a half that they’re scheduled to, to talk at me and the group of people that I’m with, who happen to be of color, and get paid who knows how much…
KC: Ooh, girl!
DBM: And then they walk out, and I’m just in here like so, you willing to pay that to come and tell me this that I already know? But you’re not willing to…
KC: OK, so let me read you this message I got from LinkedIn:
“Hi Kim, my name is BLEEP, and I’m from BLEEP here in Atlanta. I was talking to a coworker of mine, and we got on the topic of people she would like to meet or spend more time with, and she mentioned you as someone she would like to meet. This coworker’s name is BLEEP, and she runs recruiting for our Atlanta offices and is a leader in building out our Diversity and Inclusion hiring strategies.”
She’s a young white woman, so I don’t know why she’s doing that. But that’s another story.
“I know this is a strange request, but I thought it would be cool if I could arrange for the two of you to grab lunch sometime. Please let me know if you’re open and I will facilitate the introduction. Thank you Kim, and if you have any questions etc. please let me know, and you can reach out to me directly.”
My response to this, hold on because I just want to…
DBM: Oh, you responded?
KC: Oh, yes. Baby, baby, baby, baby. My response was, “Thanks for reaching out. And I’d be happy to meet with her at my consulting rate of $500 an hour.”
Have I heard from him? No.
DBM: You responded, that’s good.
KC: No, I do that because, I do that because I need, my job, my work is to highlight this bullshit. I don’t want any opportunity, I don’t want him to walk away thinking I didn’t see it. I don’t want him to walk away with, I didn’t understand the request. I don’t want him to walk away with nothing, but your ass should have thought about paying me. I can buy my own damn lunch. My fee is $500 an hour for that bullshit. Why? How does that equate to a lunch? To give a white girl information on how to do her job? Because she obviously don’t know what she doing.
DBM: This is something that I battle as well, because you have a luxury because you’re outside the academic state right now. But inside the academic space, it is like, it is part of the other duties as assigned. You’re supposed to be able to just give out, like 20, 30 minutes to people like it’s candy. And I was in here like, “Wait a second, what do you want to talk to me about?” And all of this data garbage that I get, which is flyers to forward to individuals. Stop. I am not working for company X. You’re not gonna use my credibility and then push it out, and transfer that credibility to whomever you want to engage with. Like, that is…
KC: I get the same thing, where people DM about, “Can you retweet this job?” Who the hell are you? Do you have anything in place since you’re trying to recruit these underrepresented, marginalized individuals, what is your plan to ensure that, not only that you recruit, which is diversity, but you retain, which is inclusion. If you don’t have that conversation, if you’re not ready to have that conversation with me, don’t tag me, Don’t DM me, don’t do nothing. And moving into 2020, it will be a fee because we’re launching #causeascene Jobs. Oh, I’m not doing this shit for free. Oh, no. And this is one reason I am, I have my own business because I knew I wouldn’t last in corporate America anymore. And I’m actually finishing up my doctorate. I just decided to finish up my doctorate, and I don’t see myself going into academia. Not like that. I could be a visiting somebody, but I couldn’t do you, because, no, no, sir. I need to be able to say no.
DBM: Right, I need to be able to say no. So that is, I still come back, is this notion that, you know, you send an email with the flyer, that that email is somehow gonna be parlayed and distributed out on an expectation that it is… no. Wait a second. And then I also have to school individuals about this as well, because what some of these recruiters will do, will try to hook into one of the learners, and “Hey, can you help me get in with whatever organization or institution and set up a meeting?” Or whatever. I’m just looking at this… I was like, “Um, baby. What? Are you getting money for this?”
KC: Oh baby, exposure pays mortgages.
DBM: Maybe I’ll get an internship, maybe. No. Maybe. No, no, no no no no no! I’m not gonna pimp out anyone that I’m instructing.
KC: But that goes back to what you said, what we talked about before about us protecting us, being that safeguard around, helping them make informed decisions.
DBM: But not all skin-focused.
KC: That’s why again, I’d tell people in the heartbeat, “Don’t ever think that I’m going to throw a Black woman under the bus”. I don’t care about Candace Owens, I don’t care about them Diamond and Pearl folks, I don’t care about that, what’s her name? Omarosa, except for the fact that she was able to infiltrate the highest levels of government, cause y’all underestimate her ass. I love her for that. How the hell did she get recording devices into the Situation Room? But ok, because…
DBM: I was like, oh, receipts?
KC: Exactly! Exactly! But you know what? I tell you this, and I say this, Black folks have to deal with our own internalized white supremacy and anti-Blackness. Those people deal with, I don’t have to be in a room with them, but what I’m not gonna do is throw them under the bus, because that’s what you expect me to do. I’m never, and I’ve learned, I’m never going to go to the rescue of anybody. If I’m challenging somebody, if I’m going toe-to-toe, it’s because a Black woman has been, y’all done did something to one of us, because I have not seen that reciprocated on my end. And so, no, I might say, you know, I might comment, retweet, and say, you know this is some bullshit right here, but I’m never gonna come to your defense, and they, and the ones who get it, understand it. I’m not gonna do that. You don’t need my defense. You have white supremacy on your side. You don’t need my defense. But yeah, and so yeah, when you say “I’ll skimp from…” No, I learned the hard way. No, I will not. I’ll just let you, yeah baby, you can sink or swim.
DBM: I’m just gonna sit back and get my little folding chair out and just eat my popcorn. I’ll just wait, when you come back around? I’ll be right there.
KC: Exactly, cause what you’re gonna do is, white supremacy gonna slap you in your face at some point. You gonna be like “Damn!” Well yeah, that’s how that thing… but you chose that path. So you know what? You need to get your face slapped on that one, we’re gonna let that one go.
DBM: Yeah, faceplant, faceplant.
KC: Exactly. So going back to the money thing, cause it’s so funny, because people think like, followers mean something. First of all, I have seen that, oh, my god, baby. Wells Fargo ain’t taking followers for mortgage. They just don’t translate into dollars. And it’s like, so I have a process where you could become a #causeascene Community supporter, because there are people in this damn community that have some money, and I have 8000 followers. 21 people are giving me $100 a month to do this work. I’m, I don’t care about y’all. What, 21 people, when my damn hosting just went up to $155 a month?
DBM: Oh, what?
KC: Because I’m getting, I’m getting popular, so I’m getting more, I’m getting more hits on the website, and it went from $67 so $155 a month. And that’s one thing that I’m paying for to support this community and you people, particularly you San Francisco, New York-ass people will spend $100 on some sushi and you can’t give me $100 a month? If you don’t get that, that this is where I don’t care. This is why I say what the hell I want.
DBM: That’s right.
KC: No, you ain’t about shit here. You have not put in, so all of you ain’t nothing but parasites and voyeurs. Because that’s what whiteness does. I mean, it does not, it sits back and sucks up all this great knowledge from Black women, oh follow Black women, vote like Black women. But yet Kamala Harris is getting torn to shreds because, yeah, it doesn’t translate. How do you follow and vote like Black women, but the Black woman is not getting treated equitably in any way, but Buttigieg, who reminds white folks that a kid, that little innocent little white boy is polling… Well, why? Who? Who the hell is this dude?
DBM: What has he done lately?
KC: Well he is just a white dude to me. He’s just a white dude. I run into them every damn day. They about as generic as I don’t know what.
DBM: I don’t even know. OK, politically, that’s a whole separate episode. Because I’m sitting back, still waiting for someone, like like I tweeted out, just yesterday, which I pre pre-tweeted out in July. I want every US presidential candidate, including the GOP nominee, to give me a list of what they’re gonna do in order to address the institutionalized racism.
KC: Oh, if you’re not antiracist, I don’t know what I can do with you.
DBM: That’s what I want to know. I want to know what regulations, I want to know what policies, I want to know the data, and I want to be able to review your plan. Give me a plan for that. How are we going to address inequity in education? How are we gonna address the fact that we have books written for and by white men? When are we gonna start putting in things that highlight more than slavery when it comes to Black people?
DBM: In history…
KC: And the civil rights movement. That’s the two things we get.
DBM: Yeah, the two things we get, and that one month. When are we going to start to learn what the Latinx community has done, especially in the Southwest? That has just completely been just co-opted.
KC: And ignored, yup.
DBM: And ignored. When are we gonna talk about the fact that most of the United States, the names of the United States, actually come from Native American language, when are we gonna start talking about all of that, when are we going to really deal with all of that?
KC: Oh, and being here in Georgia is interesting because the Cherokees were everywhere. And no, I mean, the Chattahoochee River. I mean that, that runs throughout the damn state, but you would think they’d never existed.
DBM: Right, and when are we gonna start talking about all the little communities that have been completely wiped out, because of power structures and domination?
KC: Girl, the West End about to go, they about to redo the West End Mall. God damn.
DBM: Everything. I mean, what? When are we gonna actually have a real conversation? When are we gonna change some things?
KC: When we gonna call a thing a thing?
DBM: What we’re actually gonna do is just do this. That’s what I do. I work to build and create curriculum in tech that considers race, gender, and class. And we actually going to do this. And I’m going slow, cause it’s me and my collaborator, and… But listen, we gotta to start someplace, because we can’t continue to do this. We can’t continue to have people of color walking around thinking that everything is in a white glaze. We have to start to educate ourselves about what is working and what’s not working. We also gotta start educating the next generation. But we also have to think about the mindset, because I’m a big mindset person. I’m a big growth mindset person. So I try to identify if someone’s a growth mindset or a fixed mindset person. Because I have to understand how…
KC: Yes! How I’m gonna engage.
DBM: Because if you fixed, I’m gonna be on my way. OK, fixed? I’m gonna move on. Because I can’t convince you, try to prove to you that lifelong learning is necessary. We’re in the…
KC: Information Age, yes!
DBM: The Knowledge Age.
KC: Knowledge! Yes!
DBM: You cannot be fixed. Anything, you’re gonna have to recycle, you’re gonna have to rebuild, you’re gonna have to up-skill, you’re gonna have to work, you’re gonna have to lifelong learn. That’s it!
Interlude: I can’t believe it, but we’re almost done with the #causeascene Book Club selection, “How to be an Antiracist”. Our next selection will be by Nell Irvin Painter, “The History of White People”.
Ever since the Enlightenment, race theory and its inevitable partner, racism, have followed a crooked road, constructed by dominant peoples to justify their domination of others. Filling a huge gap in historical literature that long focused on the non-white, eminent historian Nell Irvin Painter guides us through more than two thousand years of Western civilization, tracing not only the invention of the idea of race but also the frequent worship of “whiteness” for economic, social, scientific, and political ends. “The History of White People” is a mind-expanding and myth-destroying exploration of notions of the white race. Not merely a skin color, but also a signal of power, prestige, and beauty to be withheld and granted selectively.
DBM: You’re gonna have to work, you’re gonna have to lifelong learn. That’s it!
KC: Girl, you have hit on some stuff that, oh lord! You… OK, so, yes. So, let me tell you, first of all, what my pinned tweet—probably won’t be when this comes out—but this December 1st, my pinned tweet, and it’s talking about because this whole bullshit that happened with Kamala Harris this past week and I said, “Y’all gonna fuck around, and Black women, who are the moral compass of this country are finally gonna align across class, generations, color, etc, because we have no more fucks to give and no desire to elect another racist or assimilationist as president.”
DBM: That’s right.
KC: That’s just that thing right there. And then the work that I’ve been doing in tech, because people want to call me an Inclusion and Diversity expert, no I’m not. We just can’t get past this shit, so that’s why I have to keep focusing on it because I can’t get to the real work because there’s no diversity and inclusion, so I can’t move forward. So, my doctoral study that I’m finishing up, it’s basically about how do you scale organizational knowledge within an organization? How do you scale that? How do you get that tested knowledge out of somebody’s head to be able to scale it for competitive advantage, innovation, differentiation. And that that leads me into, again going back, because y’all know I can always bring it back to, you know, creating the safe spaces and ensuring that we are always prioritizing the most vulnerable. The book that I’m gonna be working on next year is called, “Redefining Capitalism without White Supremacy: the Economics of being Antiracist”. Because this is where… uh-uh. I’m not… I might not prove nothing. I may not get… but you’re not going to say when Kim left this earth that she did not try to do, put something of value in this. And this is where when I’m talking at conferences, when I’m speaking to these tech dudes, and I’m telling y’all, first of all, we need to change how we define the word “technical”. We’re using that wrong. We’re using “technical” wrong. I have more technical skills than if all you can do is compute. What you have are technical skills related to technology. I have technical skills related to how humans and cultures interact. And when you’re talking about automation, it’ll be a long time before they can automate what the hell I do as opposed to what you do. So we need to start using those terms correctly because in tech, when we say “technical” and then we call everything else “nontechnical”, that’s why you and I don’t get paid.
KC: Because we’re not valued, we’re nice to have, but then, the people who can put some code in there, with some curly brackets, they consider valuable, the ninjas or whatever, but they don’t do anything in an information economy, in a knowledge economy to help forward what’s going on in that university, in that organization, in that community, because they again, it’s that singular stuff.
DBM: Right But it’s singular for this reason though, it’s because they want people to code whatever someone else told them to code. Not for them to think about what they wrote and how to code.
KC: And that’s, you see that from Stack Overflow. You just go and copy and paste.
DBM: Copy and paste. So you know, this is what I talk about data science. That’s why I have not adopted the term AI to replace data science, because…
KC: Oh, I didn’t know that was a replacement. I didn’t know that people are using that as a replacement.
DBM: Oh yeah, as a replacement. People are replacing…
KC: How is that replacing? That’s two different things.
DBM: That’s it. People on this, it’s impossible to see my face right now. But yes, because…
KC: AI uses data, it’s not a replacement of data.
DBM: Correct. But, in order to make it more nationally, easier to digest, data science is too, is not quite understood, right? ‘Cause the definition of data science isn’t really understood. So they use AI because AI proceeded data science. AI has been around for about 60 years or so, right? So people completely understand, ok, AI is about rule-based systems. If/then. If you do X, then Y will happen. That’s easy for people to understand. So they just say AI. And then they say automation, because people understand automation, because of manufacturing, right?
KC: But that was Industrial Age.
DBM: That’s Industrial Age, exactly! But that’s where some people’s minds are.
KC: And I talk about that in my talks, I talk about that often. I was like, we’re no longer making widgets.
KC: We need to cultivate knowledge. And so y’all still acting like we’re making widgets.
DBM: Exactly. So that’s the reason why I think AI has replaced data science.
KC: I did not know that!
DBM: Right, because you don’t hear data science, you hear AI. And now you’re hearing algorithm.
KC: Yeah, I hear the terms, but I didn’t know they were trying to transplant that for data science, that doesn’t make sense.
DBM: That’s what I’ve seen. Because they don’t want to talk about the data because data is from the beginning to the end of the system, right? As soon as it comes in, all the way into it’s being used inside of not only digital systems, but also physical systems, and then what is the communication coming out of that system? That is what is the full ecosystem of data science. AI is just one part of it.
KC: And that doesn’t even incorporate the fact that once you put the data in and it comes out, now, we’ll never talk about—and this is why we have problems with Facebook and everything—we never talk about how that whole system impacts people in the real world.
DBM: Exactly. We don’t talk about the communication and the, what I call, what I like to call, data storytelling, right? So data storytelling is, I believe, a term that came out of the humanities and social science. I cannot remember who first gave that term, but I talk about data storytelling like, ok, once you have the data, that data plus credibility gives you information. OK, so data is different than information. We need to have credibility in the middle. So data plus credibility equals information. So that information therefore has to be communicated.
KC: And so you hitting on something, hitting on something right now, because people also could try to use information and knowledge. They’re not the same thing. Data, information, and then knowledge. Because knowledge comes from lived experience.
KC: Girl! You just… haha!
DBM: This is why you should be at my weekend! ‘Cause we talk…
KC: Well, exactly! And this is where I tell people, I’m a researcher at heart. So all this other stuff is just like, I knew I had to do it my way because I knew academia wasn’t gonna work for me. I just, I had to figure this out my way. But yes, you are talking my language here! Because I tell people, data is nothing.
DBM: It’s just raw.
KC: Exactly. Then people don’t get it… information. OK, information is, this is why I went to a doctoral program, to get a doctor’s in business administration focusing on technology entrepreneurship. Because there’s a whole bunch of information on the Internet. People say Google all the time, but that didn’t help me at all.
KC: I needed a way to take the information and put it through my own lived experience, and it come out as knowledge.
DBM: Knowledge, right. And that is what we have a deficit in, is data literacy.
KC: Girl, you just scratching my itch!
DBM: We have, so unless you understand how data works, there’s no understanding how money works,
DBM: The corollaries are all there.
KC: And that’s how capitalism works.
DBM: And that’s how capitalism works. So now you’re talking, we’re talking about Kamala Harris. But it all makes sense. OK, so she’s a Black woman who is a senator, who is a prosecutor by training, served in that capacity for the majority of her career. So she is factually based. And then you are going to try to find a pathway in order to discredit her.
KC: Yup, and it happened through Becky, who decided to, when that damn thing came out, and if you don’t remember, y’all need to go Google, when Becky’s decided to do her little, I think her name was Kelly, Kelly something… Becky decided to do her little… she couldn’t just resign from the campaign and just quietly, just, you know, go. No, she had to resign and make a whole kerfuffle about how incompetent and unorganized the campaign is. Hell, every campaign has that. But then, then started… OK, so then I had “OK boomer” moment with some folks, because they were like, “Yeah, neh neh neh neh neh”, and then I was like, “Ah, ah-ah, no, no, no, no, no”. Because this is it. I was like, “No, no, no. Let’s be honest. Not one of these candidates, nothing they saying right now is gonna mean shit if Mitch McConnell is still at the head of the Senate when they get in because there are over 200 damn pieces of legislation sitting there that he will not bring to the floor!” So I don’t even care about that at this point. Now I want to look again, the race, now I need to look at some other stuff, because that ain’t gonna happen. So I need to look at, and so now, I’m digging up underneath that y’all didn’t want, this is what happened, y’all didn’t want us to dig underneath, so y’all should have…
DBM: Right, because you’re going into the data.
DBM: To understand the information to improve your knowledge.
KC: And then the next day, the story comes out that Becky quit the damn campaign to go work for Bloomberg. Uh-huh, so while all y’all was sitting up there talking about believing that bullshit, what was actually going on, it’s because whiteness is always cast as a hero or a victim, never the villain, Becky had to cast herself as a victim of this campaign so that she could feel that she had the right to justify her move over to this Bloomberg campaign. So this is how y’all get caught every single time, and I will dismantle your argument every single time, because you always looking at the surface. I’m looking, like you said, I’m looking at the data.
DBM: Yeah, look at the data. That’s why I always focus in on, what is the data?
KC: Yes! Girl, I feel like we done went to church!
DBM: What has… you’re welcome! Praise the lord where all things flow. Ok, so, you have to look at the data, and you have to question whether or not the data is accurate. And you have to be of a sound mind and of a knowledgeable mind and a critical thinking mind, in order to ask insightful questions about the data. Because you cannot, you cannot tell me that all of this stuff is happening by circumstance. So we talked about Mitch McConnell. For example, there is one legislation that I helped create, which is called the Deep Fakes Accountability Act, and that is looking specifically at deep fake technology. And how it has, is one form of tech harm, particularly to Black and Brown people. And also to women, right? Revenge porn is probably what it’s colloquially known as. But Deep Fakes is looking at regulating how deep fake videos, audio, and imagery is handled. There’s gonna be, well, if it gets passed anyway, it would actually look at providing some type of recourse for anyone that’s dealing. It means that you have to certify, if you’re creating a deep fake that it’s a deep fake. You have to say that it’s fake, and you gotta say where you got all the videos and all that audiovisual information from. And then if you don’t do it, there’s gonna be repercussions that could be very legally binding and include some prison time. But you see, we’re not talking about any of that.
KC: Oh that’s sitting on Mr. McConnell’s desk, in his inbox somewhere.
DBM: Sitting there. And there’s one that came before that as well, that’s just sitting there.
KC: But he is pumping, they pumping out them damn judges, those conservative judges, though, pumping them out!
DBM: Pumping them out without a problem. We’re talking about altered, doctored video.
DBM: That is impacting the presidential election in every election…
KC: Around the world.
DBM: Around the world. And we could possibly, looking at how could we regulate this? How could we have a conversation? Just have a conversation. Let’s have a conversation about this. Make it more national, so people will look at a video that they get on whatever social media is their favorite, and really start asking questions about it. But that means that you’re gonna want people to be informed.
KC: And that’s the thing. And that’s, I said this, I don’t know when I came up with this, I think it was when I started really… so I was in Catholic school most of my life, but my high school years, I had some real rebellious nuns. Oh, my lord, they were like an answer to a prayer for me because they had me just start questioning stuff like, I was reading comparative religions and all kinds of stuff. And it flows from again, when you talk about that fixed thinking, and I used to say all the time, “Facts change. Truth remains the same.” And people like, “What do you mean?” I’m like, “Look at our textbooks. Look at whoever is in power gets to change the facts.”
KC: But that doesn’t change the truth, right? And I’m a person, I want to know the truth. Whether that’s painful or not, I want to know the truth. I don’t care about… and so data helps me get to the truth.
KC: Before you start slapping on all these narratives that you want to tell about facts.
DBM: True. Right. But the data is hard to get at.
KC: Oh, yeah.
DBM: Because it’s being protected under intellectual property, data privacy…
KC: But they’re taking it from us, and then they’re protecting them for themselves. Exactly. Then they’re making it, then they own it, right? Yeah. Yeah.
DBM: So our data isn’t owned by us.
DBM: It is about us. So every… so I just, as I’m just waiting for people just to get a clue.
KC: Yes, baby. And that’s what all #causeascene is. And that’s why I go back again, why I respond to those kind of things. Because I need you to understand that I I see what you’re trying to do. You ain’t getting away with shit here. I see…
DBM: But you helped me, because now I know how to respond.
KC: Oh girl, yes, girl. Oh, yeah. Uh-huh. ‘Cause what they’re gonna do, as a Black woman, they’re gonna discount me. So no, no, no, no, you’re gonna do that anyway, but I’m what I’m gonna do, is I’m gonna put my voice out there. I’m putting my narrative out there. Now, you can, again, you can create whatever facts around my truth you want to. But at least I’ve communicated my truth.
KC: So, before we wrap up, because I really want to know, what is this learning the language of Black Twitter?
DBM: Yes, so this is a project that started probably about four years ago. And it was because I noticed that who I was teaching didn’t really know any people of color in computing. And they didn’t know Black people in computing. So I started this #blackcomputing series with the with the class. And then that kind of parlayed into, let me look at Twitter, and let me look at Black Twitter. And so two students at the time and I started to look at Black Twitter, look at the different categories of how Black people were communicating online. And then Oscars 2016 happened. And if you don’t remember Oscars 2016, there was no black people nominated. In fact, I don’t believe there was even any people of colour nominated. And so…
KC: That was #OscarsSoWhite right?
DBM: Right. So then #OscarsSoWhite hashtag was now elevated, right? So April, I believe April Reign, was the first one who used that, because of her hair, about two years before that. And so we started tracking #OscarsSoWhite. So, during the live broadcast, we were grabbing tweets. #OscarsSoWhite, #Oscars, and then anything that had to do with Black culture at the time. Grabbed that, in 2016. We did it again in 2017, 2018. And the students have since graduated, they’re off at grad school, and I just did 2019. And so I started, we started just collecting it, and then we… I have a paper out about it. About what we what we found in the very beginning, which was kind of interesting. You know, we saw #OscarsSoWhite actually not only account for maybe 5% of the tweets that we were able to to grab, out of the, you know, million or so that we were able to grab between the three of us, over the over the three years. Then we started to look at different types of categories inside of those tweets. We started looking at the tweets themselves. And I said, let’s do some natural language processing on these, just to see what we get. And of course, the results as per what you saw, the language of Black Twitter… Some of the positive tweets that we as Black people would say were positive, were inconclusive or negative. And a lot of the tweets that we found were negative. They were, you know, just tagged as negative. And I was like, well this isn’t negative. This is from 2016. We just used the 2016 tweets in order to do this. So, I’ve been now, you know, looking at the tweets themselves, and looking at these natural language processing algorithms that if their default is inconclusive, if they can’t tell positive or negative…
KC: Of the tweet? They default to negative?
DBM: It defaults to inconclusive or negative.
DBM: And so, I’m still working on it. I’m by myself doing this. But I’m still just kind of noodling around every so often, trying to just try different gates, right? Because that’s what you do; you’re trying to tweak an algorithm, right? What’s happening? So I’m just still trying to figure out how to tweak it. And the tweaking isn’t going well. It is interesting, because if there is any negative word, the negative sentiment factor is gonna go up for the tweet.
KC: Give me an example of a negative word?
DBM: So, a negative word could be “protest”.
DBM: Negative word could be cursing.
KC: Oh hell! Yeah, uh-huh. Yeah, that’s me all day long. And it could be… and that’s why I tell people I love the word “motherfucker”, ’cause you can say that so many different ways and means so many different things. Go ahead.
DBM: So, if you use blackface… there’s these words that are coded as negative. But the sentiment, which… natural language processing is supposed to be looking at sentiment…
KC: Definitely “nigga”, if you’re talking to your homegirl or whatever, that’s negative, but it’s you talking to your homegirl.
DBM: Right. And you might be saying something positive.
KC: Yeah, exactly!
DBM: But the positive connotation that you intend is not being coded…
KC: Into the damn algorithm.
DBM: Into this algorithm.
KC: Surprise, surprise. Yeah.
DBM: So I did a presentation back in May about language of Black Twitter, and I gave some examples of some of the quote, positive and quote, inconclusive and quote, negative ones, and people looked at it like, “Really? That’s not negative! That’s not positive!” And that’s why my slides are online, because I wanted people to see it. I want people to look and go, you know, this is encoded.
KC: Yes, yeah.
DBM: I mean, who decided that “protest” was a negative word? Who decided that cursing was negative?
KC: Oh girl, everybody.
DBM: Right, so we are looking at our language—and this is just English—I’m not even looking at other languages. Just English, right? That’s the only language I know, that I can think well in. So what are we doing as far as encoding these words to be prescribing them as positive and negative? We can’t really get the sentiment of a tweet, unless you look at the whole tweet. Because a tweet is engineered to need a human brain, but still we try to use an algorithm, replace what the human brain would see as, understand as positive or negative. But it also depends on the lived experience of the person.
KC: Thank you! And this is what gets on my damn nerves, is we always, we’re trying to automate out shit… people in tech as soon as we can. If I see one more thing talking about, oh, a COO position could be automated out… How is the one position that’s about putting in process, procedures, and policies about managing people, how can that be automated out? Can you please not do that?
DBM: So that is, then that is a tweet. And, just as a final note on this Black Twitter conversation, there is work out of the UK that dropped about a year and a half ago, that looked at American Twitter. And what were the trending words, and what was the new words putting into our vernacular, and guess where those words originated? Black Twitter.
KC: Oh, yeah, most definitely.
DBM: And the words that were originated were not very favorable to Black people. They were racialized and sexualized. I’ll send you the document and you can read it.
KC: Oh yeah, we’re gonna add this to your episode.
DBM: I’ll just send you to diagnose. I mean, I have a hard time reading the documents, but since you are a researcher at heart, you’ll appreciate… just look at the visualization, and you will see that the words, the origin of the words, come from places that are heavily populated with Black people. And of course, metropolitan areas, which tend to have more diversity, more people of color. You don’t see the words coming out of somewhere in Middle America. You see it coming out of the coasts and particularly in the Atlanta area.
KC: I’m gonna tell you, I already said that whiteness is not creative at all; all it does is steal and appropriate.
DBM: Co-opt. So it’s just like, to have someone out of the UK to now take tweets that were for Twitter in America, and then turn back and say, and get shine off of the fact that Black Twitter is changing the vernacular of American English…
KC: And has always.
DBM: And has always.
DBM: And there is a way…
KC: But we get no credit for that.
DBM: No credit at all. So what are we doing? I saw, I was just like, oh, so he was gonna talk about American… he was gonna talk about a whole different country’s Twitter.
KC: Yeah, that speaks English, but a different English.
DBM: Different English. And he talking about a marginalized group—’cause I don’t use [inaudible].
KC: You don’t use what?
DBM: I don’t use “underrepresented minorities”.
KC: Oh, no, no. It’s “marginalized”.
DBM: It’s “marginalized”. Or “highly disenfranchised”. So you’re just going to say how a marginalized community is basically changing the vernacular of some other country. And you think that’s ok to do. And then you get press about it, and then decided to go ahead and just roll with it.
KC: Woo… all right. This has been what I thought it was gonna be when we logged in and I saw you, and I was creating that damn tweet. I knew this was gonna be a hullabaloo! So what would you like to say in your last, in your final words?
DBM: Oh, my goodness. Final words?
KC: ‘Cause we have gone… you can say whatever, cause we have talked as if we done sat around the kitchen table.
DBM: We sure have. I think my final words is gonna be this: Take some time to learn about the history of another culture, and teach it to somebody else. So don’t just take it for yourself…
KC: We scaling this knowledge.
DBM: At scale. We need education at scale. That is inclusive. And that’s my final thought.
KC: Thank you so much. This has been a wonderful exchange.
DBM: This has been great, Kim. Thank you so much for having me on.
DBM: Especially when you’re in the middle of a tweet. Yes, next time you’re in the middle of a tweet, let’s talk memes.
KC: Oh yeah, exactly! Have a wonderful day.
DBM: All right, you do the same.
KC: Bye bye.
Closing: Thank you for listening to this week’s episode of the #causeascene Podcast. And I’d like to thank all our current sponsors of the podcast and the #causeascene movement. Of course, we strongly encourage everyone to become an individual sponsor of the #causeascene community. Just visit the website at hashtagcauseascene.com to sign up today. On behalf of everyone here at #causeascene, we’d like to thank you again for listening to today’s show and have a wonderful day.