48. Jamika Burge of Capital One

In this episode of Dollars to Donuts I speak with Jamika Burge, the head of research for Data and AI at Capital One. We talk about her journey through academia, discovering user research, and intersectionality.

Doing good – for me, as a researcher, and as someone who wants to do good in the world, it means understanding people’s needs in context and providing opportunities for them to succeed. That’s what that means for me. Success can mean different things to different people. I can guess what success means from a business perspective. I can even guess what success means from a researcher perspective, but ultimately it’s that end user who tells us whether or not we got it right. I want that person to feel as an end user, free to share with us when we got it wrong, but also when we got it right. – Jamika Burge

Show Notes

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Transcript

Steve Portigal: Welcome to Dollars to Donuts, the podcast where I talk with the people who lead user research in their organization. I’m Steve Portigal.

I was recently a guest on the aptly named UX Podcast, where in reflecting on the 10 years since the first edition of Interviewing Users and the new second edition, we chatted about the changes in the user research field I’ll link to the whole episode, but here’s a clip.

Per Axbom: As you were describing this shift to in-house teams, I almost felt this sense of jealousy, in that in-house teams then get to work with research over time in a way that I as a consultant cannot. And they have a shared experience. And they can even reflect back on research they did two years ago, based around the same product or service. So that has to be a lot different, I guess, when you when you talk to people about research and how you’re doing the same type of research around the same type of product service for a long time.

Steve: Right. And, I’m a consultant myself. I see this with my clients, that they live with some space, they live with some product topics, set of stakeholders, set of users. Some have talked to researchers that meet with the same set of users over years, and they they build these kind of longitudinal relationships. And I’m jealous of them, too. I’m also personally happier where I am, I think I bring value not being in that…there’s a rut, I think that is easy to fall into. And the rut has all these wonderful attributes, like knowing that people and their limitations, like if you have their limitations, their strengths, their preferences, if you’re working with a bunch of different stakeholders, and they have different communication styles, or they have different ways that they engage or different availability, you the in-house person do not have to figure that out every time.

I mean, yes, as the team changes, you’re going to be constantly adapting your styles. And there’s even like a mention of this in the book, I think, because one of the people I quoted describes how they try to have a communication approach that is inclusive, but spread enough to deal with the different needs and expectations of everybody. And so yeah, right, as consultants, we come in, and we don’t have the lay of the land. And I think sometimes that’s an advantage. This may be arrogant sounding, but I think we have the responsibility to speak truth to power, we also have the opportunity, we’re a little less constrained by risk as consultants.

Per: And not as biased maybe.

Steve: Yeah. You know my compensation isn’t tied to the success of the product. Those models create all sorts of interesting incentives. You’re part of an organization, you’re part of a corporation, if that’s the domain that you work in. And your success is tied to success. And as a consultant, it’s not. Yes, the company does well, they hire us back, we want things to do well, but I don’t think we have the same kind of incentive model. So I’m glad there still are consultants, because I think there’s a nice triangulation, or a nice partnership that can happen. I love working with somebody that has the long view inside and they give me the highlights of who and what and I don’t have to do everything my way, but we can negotiate the kinds of approaches and practices. And I can be that unbiased voice just by the fact that I’m not part of it.

James Royal-Lawson: Yeah, exactly. You’ve got that, you know, the fresh eyed approach that you can offer as a consultant coming in. But then we’ve got the opposite edge of that. And you mentioned this in, in chapter 10, Making an Impact, that internal research organizations, they need to keep track of what they know, and what they don’t know. And, what have we already researched? And and that opens up a whole different aspect of historical record keeping, I guess, you could say, which as a consultant, maybe we didn’t have to deal with that. It wasn’t an assignment you were given. And then you delivered.

Steve: I will say and I’ve gotta imagine this has happened to both of you, though, where as the consultant you serve as the offshored institutional memory, where somebody writes you and you haven’t worked with them for a really long time, and they’ll say, Hey, didn’t we do a project about this or that? Do you know what it was? Do you still have the thing that happened to me like, I don’t know, six weeks ago, someone had an anecdotal memory of something and they weren’t involved. And no one was left working there. So, that organization wasn’t doing a great job of documenting whatever different initiatives and so on, and that they were…I could put my finger on it, like I actually had the document quickly. So, yeah, I think there’s an ideal of whatever knowledge management, institutional memory, what have we researched? What are we learned from it? Yeah, I think it’s a hot topic that people are working to try to define.

What I get nervous about is where that problem, which is an organizational one, and an institutional learning one is hoped to be addressed with a software solution. Without asking some larger questions like, what information do we need to save? Like, is it the existence of that report? Is it the report? Is it the person who you know, could talk you through it? Is it the raw data? Is it the decisions that we make? Is it the recommendations? That’s just me riffing on like, what do we want to track? And who’s going to query that information? Is it somebody that is quote a researcher? Or is it someone that wants to ‘hey, do we know anything about x?’ and discover it themselves? So I think there’s just a huge amount of challenges there, like, are you creating different things to archive? Are you archiving them in a way that they’re retrievable by who at what point?

A number of years ago, people in research organizations that were growing, were talking about bringing in somebody who’s a reference librarian, whose job it is, in other contexts, is to be a human being that interfaces between people who need information and storage of information? Yeah. And that’s very different than self-service. So this is like a huge kind of culturally based –any two organizations are going to deal with this differently – what they expect people to be able to do and who there is to do it. There’s a technical need here. But there’s also just a process and understanding of what information, why do we want to look back to what end and building those use cases in? And I think it’s turning out to be trickier, maybe than software vendors had promised us.

Again, that was from the UX podcast. Now onto our episode. I had the pleasure of speaking with Jamika Burge, the head of research for data and AI at Capital One. Jamika, thank you so much for coming on Dollars to Donuts. It’s just so lovely to get to speak with you today.

Jamika Burge: And so good to be here with you, Steve. Thanks for the invitation. I’ve been looking forward to this. Happy to be here.

Steve: I want to start off by asking you how you found user research.

Jamika: That’s a really good question, and I find myself asking myself the same thing, because I don’t think I came into it knowing that it was user research. And as I look back on my experience, you know, I started off as a computer scientist. In fact, even before that, I started as a business major in college. I want to study this area called business communication. I didn’t know what it was, but I knew that I really liked English, and I liked my AP classes, English and biology, in high school. And so it gave me an idea of how I approached learning and problem solving and presentation of what I knew in the world. And so I thought business and communications, okay, I’ll give it a shot. But then I got to college and had a work study assignment my first year there, and it was in the computer science department. So work study is for those of us who needed a little extra money paid to us for working on campus to supplement our education.

And for me, it was in the computer science department. And because I showed up to work every day or every other day, whatever my schedule was, I learned a lot about what technology was. I had never taken a tech course. I’d never programmed. But it for me was an opportunity to learn something new. And so I spent my first year developing my university’s first website. This was like in the mid 90s. And I’m learning about the internet, and I’m learning about what to do to create experiences on the internet, which at the time was web pages, or maybe some Flash, right? Adding a photo or an image online, which were all new things for me and even for us in the field. And so that was my entry into understanding the tech space more broadly, but only in the context of the internet. And after my first year, I changed my major from business communications, which at my college was really business, to computer science. Again, not really knowing more about the field than having spent my first year as a work study student in the computer science lab.

But at the end of my first year, I also had my first internship and was able to come back my second year in college as a full on computer science major. And I spent the rest of my college career as a computer science student, struggling, enjoying, celebrating, rethinking my role in the world, because computer science is not the easiest topic at all, but understood that there was so much to do in the space and so much more that I wanted to do. And even by the time I graduated, I had not learned about human centered experiences or human centered design, or even human computer interaction, which in computer science is the closest thing to user experience and user research. I had, however, learned a little bit more about AI and artificial intelligence.

And so I knew that was interesting and thought maybe I wanted to do more and decided to get my master’s degree and focused on agent based planning and understanding how to create and model agents and experiences using deontic logic, which was, I’m remembering now, the logic of prohibitions and epistemic knowledge, logic, the logic of knowledge. How do we know what we know and what does that mean? So I’m building these models and understanding model based design. And then I learned through an article that I read about human computer interaction, which is not just how to create artificially intelligent systems, but how to ensure that whatever systems we create, intelligent or not, are actually usable. And I was fascinated.

And one of the classes that I took that introduced me to that was called usability engineering, where we could actually test any technology that we created from a user point of view. It wasn’t from a tech point of view. It wasn’t from a performance point of view, but it was from a user point of view. And that excited me. And so that’s how I learned. This is my first year in a master’s program in computer science, where I’m learning about human computer interaction through usability engineering. And that was what started me on my way. I was already on my way towards digging into research more broadly in the computing space.

But here is when I realized, you know what, I could better understand how to create, build, sustain technologies in the context of those who are using them. And those who are using them don’t have to know how to develop them. And so that was my first time learning more about user research from the lens of a computer scientist. And I think I was certainly in graduate school, maybe three years later, when I decided, you know what, I’m going to focus on this thing called human computer interaction. And for a researcher in that space, that absolutely meant that it was user research as an opportunity to really broaden my perspectives about what it means to create experiences for users, technical, non-technical, whoever they were. And that was my first introduction into user research as a graduate student, technically.

Steve: Was there a point at which some of the work you were doing in grad school looked more like user research, like from a 2024 lens?

Jamika: I think so, because in my program, and I went to Virginia Tech, which had, and still has, a strong program in human computer interaction in different areas of the practice, like visualization and human computer interaction models and frameworks. But I think for me, in the truest sense of user research, I learned not just what it was, but how to practice it through my first project in a course that I took, where we were supposed to gather user feedback for a solution that we thought needed to be explored. And I think for this project, I was partnering with one of my colleagues in the program, and we were in a virtual reality class, and we were studying the impact of depth perception using in a cave environment. And a cave environment is, for virtual reality, is sort of this pseudo real experience that feels real because you’re putting on the headgear and you’re in a space that’s projected in front of you, and it’s immersive.

And it was also new for me, but it was an opportunity to investigate, okay, how are people really engaging in this space? And that, for me, was not just an opportunity to understand and see user research, but to embody it. Like, wow, this really is an opportunity to get real feedback from another person in a way that’s meaningful and in a way that helps me and my partner and the whole field understand more or understand something we don’t already know.

And that, for me, was fascinating because what I didn’t realize is that I’ve always been a researcher. Ask my mom. I’ve always asked questions and always asked why. And so, for me, it was a really nice way to see, oh, I know what this is, and I can apply it to something that I am right now in the moment getting trained to do. And it was the first time I think I’d ever really understood the value of loving what you are trained to do. Like, what is a career? Oh, it can be things that are fun and that are really interesting and that are also challenging in ways that I didn’t expect. But yeah, I think that was my first real introduction to user research in a hands-on way through a course that I took.

Steve: And describing it as a lightbulb moment or maybe a series of lightbulb moments sounds very powerful in the way you’re describing it.

Jamika: For sure. And we think about a graduate program and even a PhD as being research. User research is different, and it is much more applied and provides a lot more of what I call real-world perspective in a way that is truly unmatched. And so, for me, that was the appeal. And it led to even my research being a little unorthodox, but it was all about, for my dissertation work, but it was all about, okay, what are real people experiencing and how do we better understand that for the greater good? So yeah, that series of lightbulb moments, I think, really started me on the path that I find myself on even today.

Steve: What was unorthodox about your dissertation work?

Jamika: Well, I struggled. I’ll tell you this first. I struggled with my topic because I was in a computer science department, but my advisor was and still is a psychologist. And I was doing work that was highly integrated with bits of psychology, sociology, and anthropology. And so I struggled with, well, can I do this kind of work in a computer science department? And I was quickly assuaged. My fears were assuaged when my committee said, well, as long as we agree, of course, you can do whatever you need, you know, whatever. And that was all I needed to hear.

And so it took me on a path of really understanding how people share high-stakes emotions across tech media and tech media and channels like email and phone and the internet, IM, for example, and even face-to-face. That’s a medium. And so I brought couples in relationships into the lab and effectively had them argue. That was my culminating academic user research project, if you will. And the context around that was at the time, this was the early to mid-aughts, and there was an influx of technology options to support remote interaction. So we were seeing a lot more IMs pop up. We were seeing instant messaging systems pop up. We were seeing a lot of people engaging in social media before we called it social media, right? There were lots of those activities and even people who were engaging in relationships and even maintaining relationships via email, right? We didn’t really have video at the time the way we do now. And so people had to stay connected, especially people who were away from their loved ones. It was important to do that.

And so I found myself trying to understand, well, even for me in graduate school, I was away from my family and benefiting from understanding ways to get through some pretty heavy experiences and maybe even to resolve high stakes interactions like arguments and even extreme excitement were important. And so it led to my thinking about, well, what are the opportunities for using communications media effectively to support communications for people in relationships? And the value there in relationships is that if people are vested with each other, then we can stress test the tech medium a bit to get at things like, well, how were they able to resolve the conversation or what were the extremes of the conversations that emoted the most or what were some barriers in the conversation that kept them from meeting a resolution or what were some interesting indicators, depending on the medium, for example, where they couldn’t see each other, where one person in the couple behaved a certain way and the other person didn’t get the benefit of seeing that.

Those are some all interesting questions. And while broadly the opportunity of understanding how we use media, tech media to connect was interesting, but the underlying real question was, can we actually get them to argue in a lab? And we were able to do that, but it unlocked a lot of learnings about people, about how we communicate, about what we think about what we communicate to others and the ability to resolve any kind of conflict, especially when it’s not face to face using technology.

Steve: So when couples came into this lab, were they having these interactions mediated through some tech platform?

Jamika: Yeah. So they come in to the lab not knowing at all what they were going to do, which is by design of course, and they’re told what they’re going to do, how they’re going to be spending their time, and they are put into one of three groups. They’re told that they’re either going to be in a face to face condition, an IM, an instant messaging condition, or the phone condition. And if they are in the instant messaging or the phone condition, one person will be moved to another room where they could actually engage with each other separate from each other. And in the face to face condition, they were both in the same room.

Now there’s some pre and post things that are happening. Like before we actually get started, there are course signing informed consent forms that we can talk later about how I learned the value of communicating consent, but also doing no harm, because this work is really important to understanding that when you’re having people come into the lab and argue, we’re sort of creating a level of stress. And I’ll note here, probably appropriately, that we partnered with the University Counseling Center and we gave our participants pointers and paraphernalia that if they needed support as a result of this conversation, or any time in their conversation, the Counseling Center was available for them. So that’s important. But that said, part of the preconditioning and pre activities were I wanted to understand what their current state of mood was.

So I used a PANAS inventory, which is a, wow, I’m really digging back here. It was an inventory that measured people’s mood, their level of happiness. And there were some 50 to 100 questions I had to answer, just so we can get a baseline of how their moods were. So we did that before and after the experiment. And we also did a depression inventory to understand, you know, how are people feeling just in general? Again, what are their baselines? And how might our understanding of their mental state, at least at rest, if you will, change in the course of these conversations, which also helped us to determine, you know, whether or not they were actually arguing and able to get to some level of resolution. So we did that at the beginning, and we did not take depression inventory at the end.

And before we started, we also had people talk about, you know, what are things that you generally argue about? You know, and there’s some common things, we can get into that in a minute. I think you asked me, you know, what was the process of determining what tech media, but all this is before they’re actually separated or assigned to their condition. But once we’ve taken care of all that, they were ready to go. And we’re then separated into the different, according to the tech media that they would be using.

Steve: So you did this research, and then this is for your dissertation. What is your, I mean, it’s a terrible question to ask someone, but like, what is your dissertation conclude? You know, I think I’m sure you’re talking about weekly nowadays.

Jamika: Well, I’ll tell you, I actually talked about this with a colleague a couple of days ago. So it’s not as unusual to talk about it as we might think. And I have some conjectures about why that is. And I’ll come back to that. But there were a lot of things, actually, that were the results of this research. And for those who are a bit more versed and probably closer to this than I am now, know that this research is an area of even media uses and gratifications theory, which means that the technology that we use can help us to deliver news with different kinds of results. And an example is maybe if you’re feeling uncomfortable about having a conversation with somebody, a friend or otherwise, but mostly a friend, you might, depending on how uncomfortable you are with the conversation, choose the communication media based on that feeling. So if I’m telling someone that I, you know, I’m sorry, I’m not going to make the party tonight and I know it’s a big deal for you, but I just I can’t make it tonight, then to keep from being overly uncomfortable, you might not call, but you might text. It’s not the good thing to do, right? It’s just it’s not good, at least socially.

But personally, the pressure of having to tell somebody that you can’t do something that you said you were going to do or that is personally uncomfortable means that folks will likely choose the technology based on what goal they’re trying to accomplish and how it makes them feel in doing that. And so for me, it helped me to see that as one of the results that we found was that people are able to argue, first of all. So they do argue.

But it also because we also let me back up and say this, we recorded them as well in the context of these arguments and that they were able to argue in front of a camera was also very fascinating. And it’s because of the camera in the room that enabled us to learn some other things. And one of the things that we learned is that, you know, people will self-soothe in arguments even when their partners can’t see. And it’s that self-soothing that can aid in the conversation or might give them cause to check out. And as an example, there were a few times where the men in the conversation, particularly in the phone condition, would touch their heads with their foreheads and sort of shake, you know, massage their temples as though they were in pain and trying to massage themselves because they were distressed in the moment. Obviously they’re arguing. But they really weren’t communicating that distress. But they were showing it on video knowingly to some extent because there was one person even in an IM condition when he wrote something back to his wife, he said, she’s not going to like that. And he looked right at the camera. Right? Like those kinds of things were really fascinating. Not that they necessarily needed to be witnessed by the partner, but that they were part of self-soothing for those who were experiencing or emoting in that way. So that was one of the major things.

And the other thing was not only were people able to argue, they were able to resolve their conversation, resolve those arguments irrespective of the medium. The difference was the speed, obviously. People in face-to-face conditions were able to resolve their arguments or even the time they spent in the argument was shorter than those who use different media. And that is not surprising. Obviously it takes more time to type. And certainly the less rich the medium, the more time it takes to communicate certain feelings that may be more obvious by looking at people, obviously. So that was interesting that the medium didn’t really have an outsize effect on people’s ability to resolve the conflict. But seeing how people managed in the moment was really fascinating, especially when they weren’t face-to-face. And I think that for me was really interesting, particularly given the range of participants, the range of experiences they had in their relationships, and that they didn’t know what they would be doing when they came into this experiment.

Steve: So where did you take things after this program?

Jamika: Yeah. And I wondered what was next for me. During my graduate school career, I interned at IBM Research and got a fellowship through IBM and knew, “Okay, I’m going to go to IBM Research and be there.” But it didn’t quite work out, I think in part because while I knew I didn’t really want to take the tenure track, I think I knew I didn’t really want to go into the research industry either. And part of it was I felt that there was so much more for me to learn. I’ve always felt, and I think in many ways that’s why I continued my education, there’s so much more to learn, there’s so much I don’t know. How can I grow my thinking and my skills in ways that make me worthy to do more of this work without realizing that I actually had a good handle on things and was pretty good all along, but what did I know?

And so it was thinking about, “Well, if I’m not going to be a faculty member someplace and if I’m not going to go into a research scientist role, what else is there? I didn’t know.” So I actually decided to do a postdoc and I worked with Jack Carroll at Penn State. At the time, he and Mary Beth Rosson, actually, who was my initial advisor, Mary Beth Rosson and Jack went to Penn State. So I ended up going to Penn State. Again, it was not planned, but I worked with Jack. And in that space, I was working on understanding, now that I knew that computer science could be a part of the human experience in ways that I didn’t realize before I started my graduate program, I thought, “Well, what else can I do?”

And so with Jack, I worked on understanding how nonprofits might leverage wireless technology. And this was in the time where free Wi-Fi or walled gardens in cities was taking off. How might we get access to free Wi-Fi so that people could be connected to the internet and it helps to increase access to technology? And so I spent a year and a half, a couple of years, connecting with nonprofits locally and understanding what their technology needs were in the context of internet and access. And it was a really interesting and even fulfilling body of work because it helped me to understand that while I understand and am trained in technology and all the opportunities that there are, there are so many that don’t have that access. And forget understanding, it’s access. And that for me reminded me, okay, what else might I do in this world that helps us knowers of the technology and of its capacity and its capabilities? How do we bridge the gap between those who know and who have access and those who don’t or who rely on technology in ways that maybe don’t have a choice or for whom we can make those experiences easier? And so for me, it was an opportunity to learn, well, what does giving back look like? And what does doing good look like? And that was my next journey after finishing my PhD.

Steve: I want to pick that up. I also want to go back first though, if I could. It seems like a large contrast to me as you’re describing it between people in labs, one on one, very experimental communication. It seems very like, oh, this is academic research. And to go from that to, I don’t know, social problems and entities and institutions and large social forces. And I don’t know if service design is part of the vocabulary there, but something that seems ethnography-y, the aesthetics, if you will, from the two different major studies that you’ve described, it seems like a really significant transition to hear you describe it. And with that, was it even a transition for you? How did you go from that dissertation world to the postdoc approach?

Jamika: Yeah, that’s a really good question because to me, it felt natural. It felt like an obvious point of transition in my story where I could go from learning about how to do the work to actually doing the work in the field, in practice. And I think that’s what shifted my thinking about the kind of work that was possible for me. And it absolutely is a shift, right, from being highly academic, very much theory-based and driven, and showing our proof of concept, for example, in experiments and questions that we might ask ourselves that help us to get closer to answering our question, the big questions posed in our dissertation, to, okay, now how do we make this real? How do I make this real? And what am I bringing to bear in this work in the community? They don’t care about my dissertation. They don’t care that I did this other work. They don’t even care about the underlying theories. They’re just trying to feed the homeless, or they’re trying to support youth in the community. So for me, it was, okay, now I can go from understanding the academics to applying those learnings in a practical way.

And I think that’s when I realized, you know what, I am much more interested in applied research. How do I practice what I know in real-world experiences? Because that’s, I think, how I can do the most good. Not that I can’t do good in the academic space, or writing a paper, or doing research that changes hearts and minds, right? Whatever that means. I think it was, for me, an opportunity to, if not forsake one, then embrace them both. And that, I think, has been my purview since as well. I’ve never abandoned my academic roots, but I also recognize that practicing the work of research, or even user research, is best when we understand the underlying frameworks and methodologies that help us to get the most, the best, the most useful results, right? So I think they go hand in hand, for sure. So it is a jump, but I try to do both. And it isn’t always easy, but I think it’s important.

Steve: You were starting to bring up that this idea of giving back and doing good came out of the things you learned about access, and that that led you towards the next stages. What was that?

Jamika: Yeah. Well, I love the way you’re setting up the story, Steve, because I’m going back down my own memory lane. And I am appreciating that, at the time, I didn’t like my journey. I thought, I mean, I got my PhD in, I think, ’07, ’08, and it was right around the housing crash. And so many of us who were finishing our programs were looking for work and couldn’t find them, because it was also, in many ways, the crash of the dot-coms. And so all of us were sort of competing for smallish roles, or at least small numbers of roles, not smallish roles, but maybe there were small roles. But there wasn’t a lot of work to go around, at least for those of us who were looking for very specific kinds of research roles. And so in my postdoc, not only was it an opportunity for me to figure out what I wanted to do when I grow up, it also helped me to find another area of research, and even applied research, which wasn’t obvious for me. And that was government research. And so that was what was next for me. I went from my postdoc to doing government contracting work, where I worked at the Office of Naval Intelligence and at DARPA, the research arm for the Pentagon, and did some fascinating research that, in my mind, was the next level, or maybe another opportunity to apply my learnings in some real-world situations to hopefully do some good.

And that was my next journey, going into government research, which completely eluded me my entire educational career. I did not realize, “Wow, I could do this research? I could do this kind of work?” It didn’t occur to me. And so I think for those couple of years that I was at Penn State, it helped me to get in touch with what I really enjoyed, and not be so constricted by what I was expected to do in my career. As a newly-minted PhD, we’re told, “Oh, you should go pursue academic posts and be a faculty member.” But I knew that that really wasn’t what I wanted to do.

And so giving myself the opportunity to explore really helped me to think more about what can I do and what makes sense for me. And so that led me to DARPA, where I did some pretty cool stuff in two different domains. The first was supporting military service personnel who were suffering from traumatic brain injuries or PTSD and developing technologies that could help support them, to developing game-based learning experiences for K through third graders to teach things like calculus and Newtonian physics, but through games.

And for me, that was a nice connection between the human-centered design tech world of supporting the development of technologies that could support our military personnel to the outreach piece, the doing good, to helping our young people see math and science as a career option. And to use games through that was exciting. So that was my next chapter, if you will, of applied research.

Steve: You said that at the time, you didn’t like your journey. It’s hard to reconcile because you’re telling it as a retrospective, but in the way that you’re telling it now, I can’t see what it is that you didn’t like about it at the time.

Jamika: You’re right. There is the benefit of hindsight. At the time, I felt like my path should have been straighter because I’m already jumping at this point. To back up a bit, I got my BS in computer science, went straight to a master’s program. The summer after I graduated from my master’s program, I actually interned at IBM Watson, which is in Westchester County, New York, an IBM lab, and again, studying HCI, whatever that means, right? I don’t even remember the project. But I enjoyed it so much that I considered staying. But I also knew that there would likely be more opportunities for me if I pursued a PhD.

And so instead of staying at IBM Research, I was at Yorktown Heights, for those who might know the area. I decided to actually teach. I taught for two years at Spelman College, an HBCU, an historically Black college or university in Atlanta, Georgia, for women. And so I was there for two years. And the reason I took that stint was I figured, well, if I’m teaching and if I’m close to a university experience, I’m probably going to be more likely to go back to school for myself. And I’m not sure why I thought that, but two years later, that’s exactly where I found myself. I found myself enrolling at Virginia Tech and was there for the next five years. So already my path is a little crooked.

And in many ways, I was behind my peers who decided to keep going to grad school. And so for me, again, in my mind, my experience, we’re always told, go straight through. And there’s a process here. So I’m already breaking the mold. I’m not doing the things that made sense. Finished my PhD for being there five years. And then I’m not getting a job, as many of my friends would say. You don’t have a real job being in grad school, but I beg to differ. But then finished that and then went on to a postdoc, which was in many ways additional education for me.

And so again, a little crooked path, not quite straight. But for me, even looking back, it helped me to really figure out what made sense for me and to be okay that the path was a little broken. Or in my mind, it seemed broken. So I finished my postdoc and then go into government research and thought, okay, well, I could get used to this, but there’s got to be more. And even there, I thought, well, okay, it’s a little crooked still, because I didn’t directly move into working at DARPA when I finished my PhD or my postdoc. I did a little bit of extra contracting work where I was at the Office of Intelligence and some other places. And so that felt a little crooked too.

And again, I didn’t know the industry. I didn’t know that that was what research looked like outside of the academy and outside of the research industry. It just was. And so I had to get my head around understanding that, first of all, it’s my journey and it’s totally fine that it’s not all the way straight. That’s just life and that’s okay. But then also, I’m doing things, a lot of my peers and a lot of the folks whom I called mentors who came before me didn’t do. So I’m kind of creating my own path. And at the time, it doesn’t feel that way. It just feels different. And that’s what I remember. I remember that as part of my journey, but I also look back and appreciate that my role was different because it meant that I was meant to do different things. And that’s what you’re hearing. I’m even reconciling those differences.

And the cool stuff that I can look back on having done, but in the moment I thought, “Okay, well, this is great for now, but what’s going to be next?” I never knew what was going to be next for me from graduates, from being an undergrad. Every point next happened because the stars aligned, not because I planned it. And I think that was part of what I was also feeling in the moment, not really knowing what was next, but not really appreciating what was now.

Steve: It seems like that’s part of how we grow up is there, I think many of us go on these crooked paths and many of us are not told that that’s how it’s supposed to be. And so I totally relate to you feeling like, “Well, I must be doing something wrong because it’s something wrong. What I have exposure to says this is not what to do.” And you can see other people “succeeding.” And at some point, hopefully for all of us, at some point we realize, “Oh, this is actually the way it goes.”

Jamika: That’s right. That’s right. And looking back, I’d have it no other way. But yeah, we’re not told in the moment. Steady as you go, it’ll work out. And this is exactly the way it needs to be. Completely agree.

Steve: So what happened after DARPA?

Jamika: What was great about that work is that not only did I get to participate in some really great work and interesting work and learn more about what DARPA is, high risk, high reward projects that shape our world. Like Siri started off as a DARPA project. The internet started off as a DARPA project. And so these opportunities to impact at a different level were new to me. I knew what the academic route was for even understanding research and experimentation and user experience. And the frameworks that govern those experiences and the knowledge of those experiences. I even knew what the applied world looks like, particularly in the context of social good and community service.

But now I was starting to learn you could actually drive research and research programs in a way that can actually change lives at scale. That’s what I learned in the government work. And that set me on a couple of different trajectories actually, which I think are the same, but it got me to thinking in my mind about dual track opportunities for myself. It was when I decided, you know what? I’m going to keep doing this user research thing. I’m going to keep building and growing my skills and learning more, learning more about the community and all these things, especially through my work, my day job.

Then I also thought, you know what? I think I want to be an entrepreneur too. I want to start my own business. I want to do more of this social good in the context of tech in a way that allows me to grow in different ways. And so that was when I continued to do research. I continued to be part of organizations that enabled me to use those skills. And I also started my own tech nonprofit where I was able to apply my academic research background in doing research, but also developing programs and experiences to develop capacity for tech capacity in particular for black women and girls through my organization called blackcomputeHER. And so there’s blackcomputeHER. That’s a part of my world now, or at least after government work. And then I’m also doing research as part of my day job and negotiating the two because there’s a day job and then there’s the after job work, which is a part of the work of an entrepreneur anyway. And so that was next for me. How might I take my learnings and go to yet another level that enables me to use my skills meaningfully and to explore what else was out there, perhaps in ways that others of my peers or even others who’d gone before me hadn’t done. So again, I’m thinking, okay, I’m going to give it a shot. I don’t know what it’s going to look like, but I’m going to go for it. And that was what was next for me, being an entrepreneurial minded researcher who even now is learning to blend the two in everything that I do. So that was what started for me as, okay, let me figure out what this entrepreneurship thing is and what’s possible.

Steve: I’m struck by the fact that, you know, in describing your choice and your motivation to launch something like blackcomputeHER, and you’ve mentioned a few times being interested in giving back and doing good for the world, but you identified one or one and a half other motivations for you, which I hadn’t really thought about. Like why do people do things that are good for the world? And you said this is also a way to develop your own skills, is to learn and keep growing as a person and as a professional and as a researcher. And then even the entrepreneur aspect of it, which I think maybe straddles between the two. It’s interesting. And maybe it’s, I guess it wasn’t obvious until you said it, and maybe it should be obvious that motivations that we have for phrases like giving back are so loaded in motherhood apple pie type terms, but it’s not incompatible to our own selfish pursuits that we can do things that are good for the world, but also we’re hungry for because of what we’re interested in, in our own development.

Jamika: That’s right. Both things can be true, right? And this was also at the time, and I think it’s less amplified these days, but, you know, it was a big deal eight, 10 years ago to have as a skillset for a major tech company, entrepreneurial thinking, right? What does that mean? How do you bring big ideas to bear for the organizations in which you work? And so that was also on my mind at the time as I’m thinking back and reflecting on what you’re saying here, because I thought, well, I think that way, I’m sure, because you have to think that way from an academic perspective. That’s what professors do. They are entrepreneurs of their own labs, of their own research groups. And it was just a different way of thinking about it.

And while I did an adjunct role for a few years and I was able to write grants and secure funding for some of my nonprofit work, the nonprofit became the vehicle for more, right? More learning, more capacity building for others, more expansion of who I am as an individual, how I think and what I wanted to do and contribute in the world. And that doesn’t have to just be about where I work, right? I’m all the things. And I think that’s exactly a good way of thinking about it, Steve. You know, both things can be true, starting your own business or learning can merge in ways that you didn’t expect. But for me, I’ve learned, I think we’re quite necessary for me to get to wherever I’m going next. And I’m not sure where that is yet, but, you know, it’s all a journey.

Steve: When you started blackcomputeHER, what were some of the things that you were doing?

Jamika: Well, when we started, our mission was to, and still is, to provide professional development and capacity building in tech for Black women and girls. And the reason that matters is because Black women in tech are one of the least represented or Black women are one among the least represented in tech careers. And design isn’t so different if we think about, you know, where user research often falls in our career spaces. So as a person who identifies as a Black woman and having experienced differentiated experiences as a Black woman in tech, I thought, well, what else can we do? And I have two cofounders who are also Black women, and we thought, well, what can we do to, if not change the conversation, we can at least create community?

And we’ve been able to do both. So we’ve created community by starting out with a conference for Black women and girls and allies. I mean, everyone is invited. But we’re very clear that if we want to provide parity in the field, in the professional workforce, then we have to ensure that there’s parity of people who are in the workforce for the skills that they bring to bear. And so how do we start? Well, let’s figure out who the community is. So we started by having yearly conferences where we grew from about 12 as our first initial planning experience to over 200. We’ve had over 200 in our meetings.

And the value of the community is that we get to know each other. We can point to others who are also in the field. And it ensures and reminds us that we’re not alone, you know, in our growth and in our advancement, and in our pursuits of our careers in tech and design. And the other thing that it’s done is helped to change the conversation and change what we know about women, women of color in tech, and Black women in particular.

And my work with blackcomputeHER also led to my being part of the National Academies Committee where we actually focused on that very thing. How do we change the trajectories of women of color in tech, knowing that there isn’t equity, there isn’t parity, but there’s more that we can do to change the conversation. And so that, I think, has been a really great opportunity for me to keep learning, keep pushing, keep changing the conversation, especially through things like intersectionality. How do we acknowledge that there are different experiences for different people, particularly given the different kinds of discriminations that they feel, but also the way that they identify? And how do we bring that level of awareness to the work that we do, to work that I do?

And I can say that now that I’m at Capital One, if I go along that journey of, you know, after DARPA, I came to Capital One and have since, if I can pull the blackcomputeHER face to the Capital One work, I started our intersectional symposium, the first that we’ve ever had, where we talked about our experiences as people coming from different identities and from different dimensions of experience. It all matters. And that actually is a really great way not to separate us, but to actually connect us, because I can have more in common, you know, with a white guy, with you, Steve, than I do with other Black women, because of my experiences, because of my journey, because of my growth opportunities that I’ve had. And that doesn’t make me better, it just makes my experiences different.

Steve: What have you seen people who have participated in the blackcomputeHER events go off and do?

Jamika: One of our staple programs that we have through blackcomputeHER is our Fellows Program. And our Fellows Program is different from a traditional fellowship. We don’t provide funding, but we do provide an experience. We provide with a cohort of those who apply. This is an application experience, so folks have to apply. We invite a cohort to participate over the course of the year, where they participate in webinars that feature subject matter experts across a range of tech areas, even executive coaching expertise and executives in the field. So we provide access to experts in a way that our fellows who are early to mid-career professionals don’t usually get. So we provide that level of exposure.

And I’ll say that as an example of a good news story, and there are a few of them, but a good news story that I have is that one of our first fellows from our first cohort — we’re moving into our seventh or eighth year now, so we’ve been doing this for a while. And one of our fellows who joined our program was in transition. She didn’t really have a role in tech, but was interested in starting, but had done very well in a STEM career. Maybe it was chemistry or something. I don’t remember what it was. But she was interested in moving into a tech career and knew that to do that, she believed that she needed to go back to graduate school. And so she participated in our program for a year, was exposed not just to our mentors, our experts, but also to other fellows in the program. But a couple years later, she sent me a note saying, hey, Jamika, I just wanted to share with you that I have applied to and been accepted into MIT’s program where I get to study more about tech and design experiences, which was really exciting to hear.

And that’s exactly what we want to be able to do, to provide a space for women to know that there are more opportunities out there. And if we can provide an extra rung in that ladder, another step up to help them see and find those opportunities, we want to do that. Now she got into MIT on her own. I’m not going to take credit for that. But I do think there’s value as she’s communicated to us and she’s come back and participated in other programs, is that there’s nothing like community and exposure and connection, especially when you’re one of a very small number of folks in a space. It can feel like you’re the only one ever. But that I think is a mistake for any of us because it can keep us from doing, being, offering more. And that for me is exciting.

We’ve got other experiences and stories like that, but I think that’s one of my favorite. It hearkens back to me, our discussion about being uncertain on our paths because we’ve only been told this is what a path should look like.

Steve: And that I can imagine for this woman that you validated a path or she took from that fellowship experience the confidence to do what she was already capable of.

Jamika: I hope so. You know, the research tells us, especially in broadening participation and in areas where we’re trying to get even more women in the field, role models and cohorts matter. So again, that’s part of that academic training of knowing that there are frameworks that I’ve applied before and other training programs that I’ve created for young people who participated in. This is what helps us to grow community and capacity. And so applying that in this context is again, a nice combination of what do I know in this space and then how can I apply it to create the change that I think we need in the world. And so it’s been a really great opportunity to grow, to fail, to have really great experiences, a celebration, which I think is what entrepreneurship is, right? Like, would you agree? Like that’s part of the gig. And so it’s been fun. It’s been a journey, but I hope to keep learning.

Steve: I hear both, you know, trying to support individuals, but also exploring how you can kind of change the systemic aspects. I have a naive view of that. So my questions are going to be naive, but it’s clear how you help these individuals and your example of the symposium at Capital One seems like that’s about the system. And I guess, is this true, the more Black women go into tech, the system does change based on who’s in it. And that I think naturally would change the opportunities for black women in the future. Is that how this works?

Jamika: Yeah, I think so. I mean, I’m one of those people who, I mean, systemic change is hard and it takes a long time. And so I don’t profess that any one thing I do or even any number of things that I do can change the system at Capital One or otherwise, actually. I actually appreciate that we were able to have a conversation around intersectionality at a tech company that happens to be a bank and is also very highly regulated. That hadn’t happened before. And so in my mind, yeah, it was a way to talk about some real experiences for people who needed to be heard. And it wasn’t just Black women, right? I mean, all of us have experiences and all of us have stories. All of us have identities that make us who we are. Race and gender are the obvious choices, but they don’t stop there. Where did we grow up? What’s our educational background? How many languages do we speak? Are we living in this country, but maybe coming from another country, right? How many degrees do our parents have, right? There are all these dimensions of who we are, including how freely and able we are able to move in the world. Like that’s a level of identity that we often don’t think about. But all of these dimensions and all of the dimensions are very rarely held by one person. There are so many parts of who we are that makes that conversation around intersectionality so meaningful for everybody. It is not an exclusive term. It’s actually an inclusive term.

And I appreciate that we’ve been able to have that conversation at Capital One, which I hope begins to empower others or help others feel empowered to have similar conversations. And I’d be very curious to know if any other organization is having that level of conversation because I haven’t heard it. I’ve been invited to lead those conversations in other organizations, in university as well, but it’s also not an easy conversation. So I think what my approach is in that recognizing that there is an opportunity for systemic change is to know that the system can be fixed, but that isn’t necessarily my job.

I want to make sure that for those of us who are in the system, that we feel supported, that we have what we need to succeed and persist. And that when I have an opportunity as Jamika to lend my own experiences and expertise in an effort like through the National Academies of Science and Engineering, which is a pretty big organization, then I can also share, well, here’s what else we can do. Here’s what we’ve learned from blackcomputeHER, for example, that really helps our community members persist. Or here’s what I’m learning that we’ve discussed in an organization that is not all Black women, but we see the value of hearing our voices. I think finding ways to, again, be myself in both worlds is what I strive to do because again, I’m more than the work that I do. I’m Jamika. I happen to be a lot of different things and do a lot of different things and have a lot of different hats that I wear.

So I would love to be able to, I would love to hear other people talk about themselves in that way too, which I think goes back to the user experience. Who are we? That’s really what I think my role as a user researcher is. How do we help people to not just tell us who they are, but to be comfortable being who they are wherever they are? That for me is pretty cool. There’s context in the middle of all that, but at the end of the day, I want to know the people that I’m serving. There are lots of different ways to support that and to support it meaningfully.

Steve: I guess to say yes and to that, yes, we can do a great job at helping people to tell us who they are, but also sharing that information in a way so that people who are otherwise reduced to artifacts on a wiki somewhere or marketing documents or whatever, trace logs through a tool are more fully presented or richly presented and in a way that looks more like how they’d want to be presented.

Jamika: That’s right. That’s right. More of that, please. Yeah. I think that’s always easy or obvious, right? Sometimes even in recruiting participants or thinking about who might give us the feedback. It’s as simple as ensuring that on the one hand, our participant pool is diverse, but how are we ensuring that even for those who might be considered the mainstream audience, that we’re not pigeonholing them in their experiences either? How are we soliciting the kind of feedback that truly is inclusive, not just through a diverse pool of participants? I think again, it’s a different way of thinking about experience and enabling that extra layer of support for the people that we serve.

Steve: Since we’re talking about Capital One a little bit, could you just maybe give a little context to what you work on and say a little more about Capital One and your work there?

Jamika: Yeah. I am head of research for data and AI, and that really means that our researchers on my team and I are responsible for supporting data rich and data inspired products and experiences. And we’re supporting and beginning to support AI and machine learning based experiences as well for our customers.

Steve: And is that part of a business area or a product area at Capital One?

Jamika: Yeah. In particular, Capital One is a highly regulated banking tech company, has lines of business that it supports, card and bank and such, but it also has enterprise level supports and the enterprise supports really enables all functions of the company, including card and bank. And so my role is in the enterprise area of work where I in particular am really interested in ways to scale our efforts and to apply our learnings in ways that not only help our customers externally, but supports our customers internally, which can be associates, right? Or me or others in the organization. So that’s kind of where I’m situated in the kinds of problems that I’m solving.

Steve: When you think about not just Capital One, but the profession that we’re in writ large, and I know you have lots of exposure to researchers from all sorts of different organizations through your own career. In this world of, I’m going to call it like modern day corporate user research, what do you think doing good looks like in our field right now?

Jamika: Doing good. I acknowledge it probably means different things to different people. For me, as a researcher, and as someone who wants to do good in the world, like I just do, it means understanding people’s needs in context and providing opportunities for them to succeed. That’s what that means for me. Success can mean different things to different people. I can guess what success means from a business perspective. I can even guess what success means from a researcher perspective, but ultimately it’s that end user who tells us whether or not we got it right. I want that person to feel as a user, an end user, free to share with us when we got it wrong, but also when we got it right.

Building the right kinds of relationships and the right kinds of processes that support that are really important. Relationships between whom? Well, I think there are lots in the process, but certainly the relationships with our end user. Again, who is our customer? Who are we serving? That requires a level of engagement and relationship that I think allows us to really deeply understand their needs and to support their successes, whatever that looks like. What are they trying to do? What activities or tasks or jobs are they trying to get done? That’s the context that defines what success looks like. I’m very interested, and I think doing good means supporting those tasks in context in a way that helps them feel that they can determine what success is and attain that success in context.

Steve: This is going to be a slight non sequitur. I just want to go way back to something you said early on. You just were talking about yourself as a child. I think you said you were always a researcher and that you always ask questions, but I wonder is there more or do you have a childhood story about a canonical kind of Jamika thing that was like you as a researcher?

Jamika: I know I always ask why, which isn’t so unusual for kids. I remember being insatiable in my questioning. In a way where I remember, and maybe it’s just my mom getting exhausted, but I remember I’d asked a question. I took dance as a kid. Before you really learn proper form, you do a lot of kicks and twirls. I was a little girl. That’s what I did. I remember once I was asked to be part of a choreography for an organization or church or something. I don’t know what it was. I had asked my mom who was helping to choreograph. She wasn’t a dancer per se, but she supported me and my siblings and was always there. I remember thinking, “Mom, what if we do this and this and this? Can we do this and this? Can we kick like this? Can we kick like this?” I do remember her saying to me, “No, there’s too many kicks.” I remember being really pensive and thinking, “Oh.” Too many kicks is obviously a thing. I didn’t realize that as a seven-year-old. But in real world, as someone who’s much older now, and even after learning more about the craft of dance, you don’t want too many kicks unless you’re a Rockette. That’s context. It matters.

But in that moment, I think it was also my mom’s way of saying, “You know what? No more questions. It’s too many kicks.” But she said it so thoughtfully and so calmly that it’s just what I needed. It was the response that got me thinking more. Like, “Oh, that’s why. Too many. Okay.” I think that’s just how I see the world. I need to be able to grapple on my own terms. Even if the person or the people that I’m asking don’t know the answer, some kind of response to get me noodling and to get me on my own path is helpful. I think that’s what drives my thinking about user research too, and about understanding the big questions. That’s what drives me. I don’t know if that really answers your question, but that’s one of my memories. We gather data, and then we have to make sense of that data. Make sense of it.

Steve: There’s an element of that story too that’s about there are rules about the path that are given to us or not given to us. You’re describing a journey of learning what those rules are and then also choosing to interpret them to follow your own heart at different points along the way.

Jamika: That’s right. The guidance is fine and useful, and for me as a structured thinker too, sometimes necessary, but I also have learned and appreciate the grappling that I have to bring to bear. You’re right. Creating my own destination from what I’ve got and knowing that it’s okay, whatever that looks like, and to be okay with the grappling, especially, which can be hard, is also okay.

Steve: Are there ways that people who are listening can support blackcomputeHER?

Jamika: Oh, sure. We’re a non-profit, 501(c)(3), so donations are always welcome. I’d love for folks to just see what we’re doing and to see that we’re not creating a separate community that competes. We’re actually creating a community that can help inform and transform tech and design in ways that otherwise would be pretty empty and not reach what I think are areas of necessity given where tech is going now, given where we have the opportunity to make the greatest impact, areas like AI and areas like advanced learning through technology, whatever the opportunity is, I think it’s richer by the most diverse problem solvers on the job. I think that’s where the opportunity for understanding more about our organization and, frankly, the way we can all work together to do more good together lies.

Steve: I will put a link in the show notes to the organization so people can check that out. Jamika, I really enjoyed and learned a lot from talking with you today. As I always do, thanks for sharing your story and reflecting on it in such a nice way today.

Jamika: Thank you, Steve. It’s been so much fun. Thanks for having me.

Steve: There you go. What do you know? That’s the show. Find Dollars to Donuts wherever you get podcasts and at portigal.com/podcast for all of the episodes with show notes and transcripts. I would really, really, really, really, really be grateful if you would rate and review Dollars to Donuts on Apple Podcasts. Our theme music is by Bruce Todd.

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