Abeba Birhane

Podcast Description

Within these social spheres, when you try, when you create algorithmic systems to predict social outcomes are you not only making a scientifically dubious claim because that’s impossible? But also you are doing something that’s ethically a red flag that harms people that harms minoritized communities.

Abeba Birhane is currently a Ph.D. candidate in cognitive science at University College Dublin in the School of Computer Science. She studies the dynamic and reciprocal relationships between emerging technologies, personhood, and society. Specifically, she explores how ubiquitous technologies which are interwoven into our personal, social, political, and economical sphere are shaping what it means to be a person. In doing so, she leans on theoretical frameworks from traditions such as embodied cognitive science, dialogism, complexity science, critical data studies, and philosophy of technology.

Additional Resources



Kim Crayton: Hello everyone, and welcome to today’s episode of the #CauseAScene podcast. I am happy to have my guest with me Abeni—no, see, I do not… my audience knows I try. I’m trying. I’ma get this right. Abeba Birhane.

Abeba Birhane: Yes.

Kim: Yay! [Laughs] Pronouns are she/her. Welcome Abeba.

Abeba: Thank you.

Kim: Could you introduce yourself to the audience—and the reason I do this… and let me stop, because I don’t want people to think I’m making fun of people’s names. The reason I do this is because my brain—how my brain functions with names, it just goes haywire. But I also want to model for people an inclusive environment that we mess up and it’s OK to mess up, if you just apologize and you keep moving forward. So that said, Ababa, would you please…

Abeba: Yes!

Kim: Yes! I said it! [Both laugh] Could you please introduce yourself to the audience?


Abeba: I will. Thank you. Thanks so much, Kim, for inviting me. Yeah, so I am a final year PhD student at University College Dublin, in Ireland. I come from Ethiopia. I grew up there. I’m here to study. And my subject is—so technically, I am a cognitive science PhD candidate and my background is in an area of cognitive science called embodied cognitive science—but as my PhD progresses, I am kind of almost leaving the cognitive side of things, and I’m more into the AI ethics—at the AI ethics end of cognitive science.

So my work is my work sits at the intersection of—as I said—embodied cognitive science, general systems thinking, and machine learning, and most importantly, I lean a lot on Black feminist epistemology, Black women’s work, to approach ethics, to think about, you know, what’s fairness? What’s justice? What would machine ethics, AI ethics, look like; one that is informed by Black women’s scholarship? So I try to bring so many elements into one, trying to kind of narrate one story through my thesis.

Kim: Great. So we start this show the same way every time: I ask my guest two questions. Why is it important to cause a scene? And how are you causing a scene?


Abeba: [Laughs] I try not to think of myself as not causing a scene, because as it is, I try so hard to just, like, keep my head down and and complete the PhD and just, you know, just have it done. But of course, you know, being a Black woman in a predominantly white academic environment, you cannot help but get frustrated constantly. So without my will—with or without my will—I end up causing a scene because I cannot help say nothing. So I end up saying things, and I do cause a scene every now and then. [Kim laughs] And [laughs] even though I do try to constrain myself, but sometimes it’s just like you cannot hold it inside. You have to say something.

So I guess how I’m causing a scene is again, when I see bad scholarship or a really naive or uninformed perspective into the ethics of machine learning, one that fails to recognize that when machine learning systems go wrong or when it’s a downstream negative effect from machine learning systems that are deployed into into the world, communities and individuals that are most impacted are usually vulnerable communities, people at the margins, Black women. But often that is not recognized. And when I see scholarship that completely erases that or that fails to recognize that, I say things I guess that causes a scene.

Also, I kind of see the usual general scholarship that has absolute blind faith in technology, and in which technology’s portrayed as a kind of savior or a magic that will… [Kim laughs] that will save, say, you know, Africa. So one of my articles on the algorithmic organization of Africa that came about from a frustration of people naively thinking that here we have a state of the art machine learning model; let’s bring it over to Africa and solve poverty or starvation and diseases. So that article actually came from, started as me causing a scene at a conference and then it became a blog post, and then it became a peer reviewed paper. Yeah, so when I see lack of critical reflection or when I see failure to acknowledge that when harms are caused by technology and the communities that are most impacted are those at the margin, when I see failure to acknowledge that I do say things and I cause a scene that way, I think.


Kim: OK, so let me just… you said so much, but I just want to say this. I’m looking at your face—and no one can see this—and I’m just… I love to see the beauty in your face. And it reminds me of something I often say, that Black women are the moral compass of this country, but I also—that’s when I’m speaking specifically about the US—but Black women are the moral compass of this globe. Period. Period. And even… and you’re not alone. I had no intention of causing a scene. I entered tech, I was just gonna do a job and keep moving. And it’s like I look up and I’m like, “I did not ask to be in the civil rights movement. What the hell is going on? I didn’t sign up for this.” But since everybody else wants to act like it does not exist, and the outcomes actually impact people who look like me, I can’t morally sit around and say nothing.

Abeba: Exactly.

Kim: People act like we signed up for this, like this is fun. Like this is… no! Black women are goin’ up, tryna to go about our lives, mindin’ our own damn business, and we just can’t. [Laughs]

Abeba: Yeah, I was just thinking, you know, I also get a lot of push back for my work, and recently, one of the pushbacks was that—it was a criticism, I suppose they meant it as a criticism—is that my work is reactionary. And I was thinking maybe if there isn’t so much bullshit, I wouldn’t be forced to react.


Kim: [Laughs] To react, exactly. And that’s the narrative: whiteness gets always to be the hero or victim and never the villain. And so anybody who challenges it, we’re the bad guys. So before you get—I’ve never had a embodied cognitive scientist; I don’t even know what the hell that is. So if you could just explain what that is first and then we’ll get into some other things. [Laughs]

Abeba: Yeah, sure. I have a short article that was published in 2017 that really encapsulates the idea of embodied cognitive science, so I can give you a link if you wanna…

Kim: Yes, please, and we’ll add that to your episode.

Abeba: So, the idea behind embodied cognition is, so traditionally, or the canonical way of thinking about cognitive is you want to understand how your cognitive faculties, your cognitive abilities—say for example, how your memory functions—the normal, the traditional way people would go about it is, take the person, take them out of their living environment, put them in a lab, maybe I will give you a list of words or numbers or whatever to memorize, and you would regurgitate, and maybe then I would ask you to recall.

So, that kind of strategy is very common, and from the outside, it has helped us understand a lot about the nature of cognition, the nature of human beings, but when you scratch under, it rests on so many misconceptions and faulty assumptions. So one of them is the assumption that you can isolate the person from their environment, from their physical environment, but also from their social environment, and you can understand cognition as something that can easily be separated. So, if you follow that line of thinking, cognition ends at the skull—the brain ends at the skull and the self ends at the skin. But embodied cognition pushes against all that. It’s a relatively new field that emerged over the last 20, 30 years—maybe 40 years now. The idea is that it’s all much more blurry than you think; cognition does not end at the skin, and the idea of the person does not… the person doesn’t end at the skin and cognition doesn’t end at the skull.


The famous example is the extended mind thesis that came out in 1998. And in that paper, Clark and Chalmers argue that an iPhone, for example, is an extension of your mind, because it helps you keep track of your meetings, you can take notes on it, whatever. So anything you can aid yourself in improving or in aiding your cognitive capabilities is part of your cognition, but instead of thinking of cognition as something that’s just located in your brain. So then if you want to then understand—so that’s just one tiny element of the embodied cognitive science movement—but my background, or my embodied cogsci goes even further, and in that article that I will link you, the claim I make is that the person is never isolated, no person is an island. We are inherently interlinked, we exist in a wave of relations, so if you want to understand my cognitive abilities or who I am, you have to inherently understand me as something located with an embodied…

Kim: Yeah! Yes!

Abeba: Yeah, as something that’s historical, as something that is impacted by the norm, the culture, my background, and the social infrastructure…

Kim: Yeah, lived experience.

Abeba: Yes, lived experience.

Kim: So you’re speaking—’cause I’m hitting so often—so cognitive… so maybe this is a simplified from what I understand of what you just said—because I wanna draw parallels to some things I talk about—is that in tech—and it goes to where a lot of the things that you’re sayin’ about machine learning and all these faults—we rely so heavily on quantitative data, which is a moment in time, and we refuse to deal with qualitative data, which is what you’re talkin’ about. So my cognition is situated in my lived experience, is situated in what’s happenin’ to me right now, because you could give me that same list and if I’ve had a great meal, I’ve slept well, all of these things, I will perform differently then if I just had an argument with somebody, I haven’t eaten, I’m homeless, all those things matter to how we… and this is why intelligence, these tests are bullshit because… [laughs]


Abeba: Yes. Yes. [Laughs] So it all it all links to, I mean, it’s really difficult to say this is embodied cognition, embodied cognitive science thinking, and this is the other thinking—which is often called Cartesian thinking or individualist thinking—so you can’t really can’t make a clear cut, but if you look at the overall train, what you find is all this obsession with measurement, trying to capture intelligence, and trying to datafy or quantify things all goes back to this Cartesian individualist thinking with the assumption, with the background that any higher level thinking such as pure form of logic or abstraction or analyzing things are superior to understanding something, compared to context or background or things that…

Kim: Context matters. [Laughs]

Abeba: Yes, so the whole idea behind all this embodied cogsci movement is things are much more ambiguous, sometimes are unquantifiable, and…

Kim: And that is the problem with tech, because we want to be binary, and I’m like, “No, we have to live in the gray.” We have to live in the gray! Everything is nuanced. There is no binary, there’s no neutral, there’s no apolitical; there is messy. Humans are messy.

Abeba: Exactly. Exactly. So you can either live under the illusion that you can be objective, you can neatly quantify things, so you can adhere to that illusion of objectivity, or you can come to terms with the fact that reality’s messy, people are inherently indeterminable, unpredictable, and work with that…



Kim: That doesn’t work in tech, because how do you code that? See, that’s the… you know, it is like, when whiteness is the default and I come to them and say what you just said, how do you… they don’t have a codebase for that. They don’t have an algorithm for that. It’s so easy in tech for us to try to extrapolate out, or automate the human as quickly as possible. And it’s like, “Nooooo.” [Both laugh] So tell me, how did you make the jump from… ’cause you said… OK, I wrote “embodied cognitive science, generalized systems thinking, and AI ethics.” How did that… I love this thing that you’re bringin’ together. How did that triangle come together?

Abeba: So embodied cogsci has been my background, and it remains also central, but general systems thinking also—you know, it’s very broad, general systems thinking, most of it within mathematics and physics—so…

Kim: Because my background, my research is in learning organizations, which is systems thinking. So I’m just like… I’m just… OK, let me stop right here, because people don’t understand how big a smile I have on my face listening to you, because this is like, this is my jam. I’m just loving this conversation. [Laughs]


Abeba: Yay! Yeah, yeah, yeah, yeah. So there are—philosophically speaking—embodied cogsci and systems thinking share so much commonality, so much metaphysical assumptions, so they’re really very closely knit together. And because in my thesis, at least in in the first chapter, what I’m trying to do, what I’ve been trying to do is to lay out the foundations of how people and social systems, as complex adaptive systems, are inherently unpredictable, inherently indeterminable, because of the nature of the phenomena. So that’s why I go beyond embodied cogsci I and lean into systems thinking because there’s so much solid groundwork done in clearly identifying and clearly laying out, here is why you cannot predict with precision how people will behave, how people will act, you know, how…

Kim: People get so frustrated with me when they want to… when they think they want to hire me to come in and they want the snap answers. I was like, “I can’t give you… there is no formula for this.” I’m like, “It depends on…” I need to interview, I need to go in, I need to look at so much stuff before I can even come up with an opinion because it’s not a silo, it’s a system. Any decision we make in one area is gonna impact other areas.

Abeba: Exactly. Exactly. Yeah, see everything is connected. And and do exist, as I said earlier, in a web of relations. So if you want to understand something, you really have to try to understand it in its web, in its relation, rather than just taking…

Kim: Yeah, takin’ it out and to put it in a sterile laboratory because you’re not gonna get the real… you’re not going to see that when John passes by, Mary tenses up and you’re like, “Why’s Mary tensing up every time John passes by?” Which leads to another question, “What’s going on between John and Mary?” [Laughs]


Abeba: Yeah. Anyway, because the general argument, the general point I’m trying to make in my thesis is that people—and social systems as complex adaptive systems—are unpredictable and here is how and why. And then I move on to looking at canonical machine learning systems, and again, the idea there is to look, to say, look, machine learning systems, especially deployed within the social sphere, are inherently trying—their central objective is making predictions. So when they’re making predictions, especially like for making predictions of who is a good hire, who should go to jail, who should be out on bail, who is deserving of a social welfare, who should get what kind of grades—they had algorithms over in the UK in the summer—within these social spheres, when you try when you create algorithmic systems to predict social outcomes, are you not only making a scientifically dubious claim, because that’s impossible, but also you are doing something that’s ethically a red flag that harms people, that harms minoritized communities.

So with that background, then the third theme, the final area of my thesis—you can’t only talk about problems as you know, [laughs] you also have to propose solutions; that’s the nature of academia, I guess. In the last part, I focus mainly on not solutions, per se, but ways forward, ways of thinking about how we can avoid harming minoritized communities, how we can avoid deploying machine learning systems that make fallacious, scientifically fallacious and ethically problematic predictions, especially when it comes to predicting social outcomes. And that’s when I bring in a lot of the scholarship from Black women scholars because they really have nailed, you know, not only…

Kim: We’ve been there. And that’s what I tell people, I say the collective liberation is through Black women.

Abeba: Yes, yes, yes.


Kim: People think I’m sayin’ it because I’m a Black woman, and that is partly because, but it’s because I know the things that I am able to think about, the things that I’m able to do; if it were a white dude, I would be so much further, I would have so much more impact, I would be believed, we wouldn’t have these conver—you know, it’ll be so different. But because Black women are in the positions that they are, that they come with this knowledge, that they come with this ability, and yet no one listens; we have to—we work even harder. [Laughs] And there’s this level of… and as we were saying before, you can put up roadblocks, but morally, I can’t walk away from this. So I’m gonna stay here, and you’re gonna still have to deal with me.

Abeba: So one of my my heroines, Patricia Hill Collins, has written this in her Black feminist epistemology, where she identifies two different kinds of knowing…

Kim: What’s her name again?

Abeba: Patricia Hill Collins.

Kim: OK, all right.

Abeba: She’s one of the most brilliant, Black feminist epistemologists. So, she distinguishes knowledge as having two forms: the first one is book learning, and that is what academia teaches you, or that’s what you learn when you go to school; but the second one she calls wisdom, and that is something you get through lived experience. And she goes on to say book learning might suffice for the survival of the white man, but wisdom is essential for the survival of the Black woman. [Laughs]


Kim: Woo! That has been my whole thing with this pandemic and… or—’cause you’re in Ireland; so we’re talking about that to a Black person in Ireland, a Black immigrant in Ireland—but one of the things that I talk about is when, in the US, the Black community, particularly Black women, decided that Biden was going to be the presidential nominee and they took over, and people kept saying “low information Black folx.” No, no, no, no, no, baby. It is from their wisdom that they made this decision. It’s from lived experience that they knew he was the only candidate—at that point because you got rid of all the people of color—they knew that he was the only candidate that was gonna be able to succeed against what is already here in the United States.

Abeba: Yes.

Kim: And that’s unquantifiable. That is qualitative data.

Abeba: Exactly, exactly.

Kim: That is what Black folx sit around a table and talk about, that you cannot put a number or metric or rating on.

Abeba: Yeah, yeah, yeah, yeah. So I’m just going to quote Patricia Hill Collins now; this is from her “The Social Construction of Black Feminist Thought.” So she says, quote, “Knowledge without wisdom is adequate for the powerful, but wisdom is essential for the survival of the subordinate.” End quote.

Kim: Mmm, mmm mmm. And I just pulled that up as you were… Patricia Hill Collins.

Abeba: Yes.

Kim: Yes, “The Social Construction of Black Feminist Thought.” See, I love when I talk to brilliant people like you cause I learn new people. I get so much smarter. [Laughs]

Abeba: Same, same here, I’m also learning.


Kim: Yeah, I get so much smarter. I really want to dig, first of all, I want to talk about what is it like being Black in Ireland? Because Ireland swears to god that they have no racism. [Both laugh] And I wanna talk about your algorithmic colonization of Africa, ’cause you hit on something right there. This is why missionary work is rooted in white supremacy, all of that stuff is rooted… you want to save those that you think are beneath you. And so now we’ve taken tech as a replacement for missionary work and we’re goin’ out to save the savages.

Abeba: Yes. Yes.

Kim: And so if we could talk about what it’s like being Ethiopian in a white country that swears there’s no race issues and then—or you could talk about your paper first, either one—but just those are the things I really wanna make sure we address.

Abeba: Yes, so I’ll start with being Black in Ireland because I’m going to be very brief, [Kim laughs] because it’s really really difficult to even just bring up that, you know, to even say, to even drop the word racism. People are just like, “Oh my god!” So it’s really anything you say, you get so much backlash. So I don’t talk about… this is why I try to keep my head down and just do my work and survive, because the exhaustion that follows from causing a scene is so much, so tasking, so emotionally big, it’s really difficult to come back from it. So you end up feeling you are better off just not having any discussion, because the backlash, the follow up is just most of the time more than I can handle. So I just…


Kim: And because there’s so few of you there, you become the burden. You’re the only target… there’re not many Black… see, in the US there’re so many of us, it’s like, “Yeah, whatever.” And that’s why I think everybody wants to make racism a US issue. And I’m like, “No, no, no, no, no, no, no, no.”

Abeba: No. No.

Kim: So we can move on, ’cause I don’t wanna cause any anybody who hears this episode, I don’t wanna make you a target, so let’s talk about the “we wanna save Africa.” [Laughs]

Abeba: Yeah.

Kim: Hold on, but before we go there, before we go there, I really want—’cause my audience is white, my target audience is white—and I wanna make this point before we move on, everybody. I want you to understand that this brilliant Black woman in a white country cannot talk about the thing that impacts her life, that impacts her embodied cognitive science, because white folx don’t wanna hear it. That’s all I’m gonna say and we can move on. But go ‘head.

Abeba: [Laughs] Yeah. Yeah, thank you for that. Yeah, we’ll move on to my article on algorithmic colonization of Africa. Yeah, I mean, it’s really… I don’t even know where to begin with my frustration with the whole mentality of… first the mentality that we, if we have enough data, if we have enough technology, we can solve all problems. Sometimes people even make you believe that the only thing that the continent is lacking is data and technology. If you have those, all problems will disappear all of a sudden.


Kim: OK, I’m gonna stop you there because I want to draw a parallel. Because in the United States, right after World War One, there was this “we need to save everybody,” and that’s why we got Prohibition, which was a shit show—and Prohibition, for those who don’t know, is when the country banned the sale, importation, and manufacturing of alcohol—that turned out to be the one of the worst things. They put it as a part of the Constitution, and they had to repeal—that was the first and only amendment to the Constitution that was repealed because it was a not only a failure, abject failure, because you cannot legislate morals, but it was the lead to the rise of criminal enterprises, because they were selling illegal liquor. [Both laugh]

Abeba: Oh, my god.

Kim: Exactly. So when you think you have the one solution that’s going to solve all the ills of the world, you’re already on the wrong path. [Laughs]

Abeba: Yes. Yes, yes. Thank you. Exactly. Yeah, yeah. And also, not only that, the thing that many people fail to question—even we Africans ourselves—fail to see is the narrative that’s, you know, this whole “we’re gonna come and save you,” you know, this white savior mentality, but disguised in tech now. What’s underneath that is this insidious perpetuation of a very tired cliched image of the continent. You look at research, it’s like, “Here, we have a machine learning system,” or “We have collected data on hunger or starvation or diseases,” or, you know…

Kim: And your biggest white savior is Microsoft… what’s his name?

Abeba: Bill Gates. [Laughs]

Kim: Yes. He’s the biggest white savior. He’s gonna save Africa from itself. He’s gonna use his billions. And he gets so much credit for malaria and da-da-da, as if Africa cannot solve their own problems if white folx will stop dipping in. [Laughs]


Abeba: Yeah, and the insidious problem is how the fact that through this narrative of “we’re getting rid of malaria,” or whatever disease, folx like Bill Gates are really perpetuating a negative image of Africa where people see us as driven by, riddled with hunger or diseases or drought; whereas the positive things—philosophy, for example; I love philosophy—the first conception, anything that can be called philosophy…

Kim: …came from Ethiopia! That’s what gets me. And the only image I knew of Ethiopia growing up was these big bellied babies with flies all over their faces. That’s the only image I knew of Ethiopia until I became an adult and started doin’ my own research, and realised that Ethiopia is the seat of culture, is the seat of society. The first university, the first church, all of it is in Ethiopia. [Laughs]

Abeba: And so much of what the continent has contributed throughout history and continues to contribute, you know…

Kim: I was gonna say, let’s not even talk about history; Africa is kickin’ ass with this doggone coronavirus. If white folx refused to listen to how… Africa doesn’t have the numbers that the US has when it comes to the coronavirus.

Abeba: Yeah, yeah, yeah. That’s what you hear is like people writing, you know, especially Westerners writing, “Why isn’t Africa suffering? Why isn’t there so much?” It’s like they’re surprised, almost.


Kim: Well, not even that they’re surprised, it’s the fact of, “We’re suffering, why the fuck aren’t they?” [Both laugh] So it’s not even surprised that you’re not; it is the fact that you should be. It is very… and that’s what I say: anti-Blackness is the most successful global export of white supremacy. It is everywhere. Anti-Blackness is everywhere. And then Westerners wanna bring their religious or their moral values to people who culturally understand community. Whiteness does not understand community; it’s all about the individual. How does Africa solve the coronavirus? Because it’s a community. They know they have to work together to do this. This ideology, people going to the capitols with guns because they don’t wanna wear a fuckin’ mask? That’s why we’re in the situation we’re in. [Laughs]

Abeba: Yup, unfortunately. Unfortunately exactly. Exactly.

Kim: I had these ideas before, but what really brought it home, I watched a movie called “Poverty Inc.” and it talks about NGOs and how they’ve destabilized, ’cause one of the things they talk about, Kenya had the most luscious, very diverse cotton in the world. They had the varieties of cotton. But when NGOs came in and started giving people free shit, it decimated Kenya’s cotton producing ability. So then you have a country that now needs loans to take care of itself, and then there’s interest on that, and now everything they get… now Kenya has to import cotton. And then you want to say it’s something wrong with them.


Abeba: Yes. Yes, yes, yeah. And whiteness has so much to answer. And just because Europeans left Africa doesn’t mean colonization stopped. How many nations still have to pay colonial taxation fee—I don’t know the exact terminology—where they have to pay government…

Kim: People payin’ back France, people payin’ back all these countries. Yes.

Abeba: So people talk about how white folk—like all the likes of Bill Gates—are, through their philanthropy are helping Africans. But if you really want to make a change, think about the structure. Change the structure. Dump, get rid of all these colonial era taxations where African governments are still paying.



Abeba: …these colonial era taxations where African governments are still paying.

Kim: What he could do is pay the damn debt. Just pay the damn debt.

Abeba: Yes!

Kim: Just pay it! You have it. [Laughs] Pay the debt. He has more than some of these countries have in debt. Pay this debt, so they are free—just like student loans—so you’re free not to have to think about that anymore. And then you can put that energy into your own… so whiteness… so I say this: there is nothing original about whiteness except for theft and appropriation. That’s all it knows how to do, is steal, appropriate, and then blame.

Abeba: Yeah, yeah, exactly. I mean at the end of the day it’s all about these folx that call themselves philanthropists; if they stop what they’re doing, then they would not be the center of attention and they would also stop benefiting from it. As it is, the only benefit that… the only body that’s gaining is them themselves. And it’s a perpetual state where they have to keep going, where they give the illusion of they’re making change by making people dependent on them, but also in the process gaining profits for themselves, but also making themselves the saviors and the centers of attention.

Kim: It’s centering whiteness, as in whiteness is the… you know, just like there’s a white Jesus. You know what? As I said, Ethiopia had the first church and there was no white man in it.

Abeba: Yes, exactly. Exactly. Yeah.


Kim: Tell me if you’re… I really wanna know about Ethiopia. I’ve always wanted to go. My mom did a DNA test years ago, and I’ll go into a Ethiopian restaurant right now and people’ll call me, “Are you family?” I’m like, “I…” ‘Cause we do have some Ethiopian and I didn’t even know it. And I’ve always wanted to go and see, because… the shape of my head? People’re like, “Yes.”

Abeba: Yes, yes. Yeah, you do have an Ethiopean look, yeah.

Kim: If I take off my glasses…

Abeba: Oh yeah, even more.

Kim: A little bitty nose with the little round head, and I have the same curls you have. [Laughs] I’ve never done this, but I want you to tell me if I ever—when, not if—when I go to Ethiopia, what would I see as a person who’s from there but did not know they were from there because we were kidnapped, we were taken. What would I… what would the experience be like? What would you tell me?

Abeba: You know, I talked a little bit about embodied cogsci at the beginning and in the article, it’s not just embodied cogsci that advocates for embracing ambiguity or embracing codependence and interrelations; I also go into an African philosophy—almost a way of life—called Ubuntu, mostly Southern African philosophy. And so, at the core of Ubuntu is a person is a person through other persons. So you become who you are through your relation, through your interactions with others, with your community. So Ethiopia is very much… a lot of the culture is really grounded in that communal, caring living. So take eating, for example. So eating is a very communal thing, where you would—you go to Ethiopian restaurants, right?—so you would have a big plate and… [unintelligible] Yeah, and I mean it’s… people don’t eat by themselves, and even if you are in a restaurant, it’s custom, it’s tradition to ask, even if it’s a stranger, you ask them to join you, to eat with you.

Kim: Oh, that speaks to my soul. That speaks to my soul. That’s community!


Abeba: And you see such a spark, a really clear difference between the US tradition and Ethiopia, for example. So things like even raising children is, in the US, also in the Western world, is considered as your responsibility; people put so much emphasis on privacy. But whereas where I grew up, raising children, making sure they’re going to school is everybody’s responsibility. If you see a kid skipping school, whether you know them or not, you will feel obliged to make sure…

Kim: That’s how it was in Black communities in… Yes, particularly in the 70s and 80s and before, where it was a community thing. People would say, “You get a whippin’ from Miss Auntie down the street and she gonna take you to your mama.” [Laughs]

Abeba: Yes. Yes, yes, yes, yeah. So it’s people live with that spirit very much with… you always, the older you are, the more you are the moral compass of the community. So you don’t live for yourself. You make sure everybody’s looked after; you make sure that the youngsters are going in the right direction.

Kim: And so that’s the whole “It takes a village.”

Abeba: Yeah, exactly, yeah. So when someone graduates, the whole village—literally, so when I graduated, my first degree was back home in Ethiopia—it’s something that the whole village celebrates. It’s like everybody’s proud of, it’s like as if everybody has contributed.

Kim: And they have. And they have.

Abeba: And they have. Yeah, exactly. Yeah, I constantly think it’s my folx, my community back home, but also here that really is central for me, that enables me to do what I do, to achieve what I have achieved. It really is. It really comes down to my community, to my circle of supports, and I’m grateful for that.


Kim: I’m about to cry. That feeling—I mean, just to hear about that, because that speaks to the Black experience in the US. And that is why we… whiteness has not destroyed us, but that’s what they keep trying to, they keep tryna… they don’t understand that the reason we aren’t goin’ anywhere is you can take—in slavery—you could take the woman’s husband, you can take her. You can sell him off. Wherever he’s going, they’re gonna welcome him there, and then her community’s gonna embrace her and her kids. You can sell her children off, but on that plantation, they were gonna make sure that woman, outside of Massa’s vision, was taken care of. That’s some powerful… that, oh my god, that’s like… chills. Because that’s some powerful shit.

Abeba: Yes, yes, yes, no words. Yeah. Yeah.

Kim: Wow, that’s some… woo! I’m just… And funny that—so I looked up Ubuntu—and this tells you what… what’s interesting is the first thing is about Linux. It’s not about the… when you…

Abeba: Aw, no! No!

Kim: Yeah, exactly. Exactly. I had to find “Ubuntu philosophy” for me to… yeah, exactly. So even tech has taken over that community thing.

Abeba: Yeah, that is not good. [Kim laughs] Yeah. Yeah, it’s definite—I wasn’t definitely talking about the operating system—it’s… yeah. [Both laugh]

Kim: Exactly. And what’s so funny is, and this is… so my assistant scheduled this. I didn’t even know who, I didn’t remember who you were until I looked at the tweet that—because I have it in the notes—but I didn’t know you were Ethiopian. And I can tell you, last night I was thinking, I need to find somebody from Ethiopia who’ll teach me how to make spicy red lentils.

Abeba: [Laughs] Yes! It’s the best. It’s the best.

Kim: Oh, it is amazing. [Laughs]


Abeba: Yeah, I hardly cook because it takes a lot to cook—Ethiopian food is a lot of… it takes a long time. But again, I have such amazing community here—the Ethiopian community’s so tightly knit—I was just reflecting the other day, I only have to drop—we have a phone call regularly—I only have to just say how I miss something, and the next day it appears on my door. That is like… [laughs] that is… yeah, I mean, I just… I mean, I cannot imagine myself existing without the community that I have.

Kim: And I’m now in tears, because that is how Black people have always survived. When somebody couldn’t pay the rent, people came together, cooked meals, did whatever they could, because we are about community. We could not survive without each other. We survive whiteness because we are community.

Abeba: Yes, yes, yes, yes.

Kim: Oh my god. What would you like to say in your final—this has been amazing. What would you like to say in your final moments on the show?

Abeba: I have enjoyed this so much. Yeah, I don’t know. I’m speechless. [Laughs]

Kim: We definitely have to stay in touch.

Abeba: Yes, definitely. And I have just dropped a link to my article.

Kim: Yeah, I just pulled it. I just got it. Thank you. And I’ll make sure it’s added to your episode. Oh, I am sitting here in tears, but they’re not tears of sadness. They are tears because on this day I feel so connected to you and my heart is wide open. Thank you.

Abeba: Thank you. Thank you. Thank you. I also feel very touched and I have no words. Thank you so much. Thank you.

Kim: Thank you, and have a wonderful day.

Abeba: You too.

Kim: Bye bye.

Abeba: Take care.

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Abeba Birhane

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