Oral-History:Cecilia Aragon

From ETHW

About Cecilia R. Aragon[edit | edit source]

Cecilia Aragon Feb 2020 headshot by Kathleen Atkins.jpg

Cecilia Aragon is Professor in the Department of Human Centered Design & Engineering, Director of the Human Centered Data Science Lab, Founding Co-Director of the Data Science Master's Program, and Senior Data Science Fellow in the eScience Institute at the University of Washington (UW) in Seattle. In 2016, Aragon became the first Latina to be named to the rank of Full Professor in the College of Engineering at UW in its hundred-year history. She earned her Ph.D. in Computer Science from UC Berkeley in 2004, and her B.S. in Mathematics from the California Institute of Technology.

Her research focuses on human-centered data science, an emerging field at the intersection of human-computer interaction (HCI), computer-supported cooperative work (CSCW), and the statistical and computational techniques of data science. She has authored or co-authored over 130 peer-reviewed articles and over 140 other publications in the areas of HCI, CSCW, data science, visual analytics, machine learning, and astrophysics.

She's authored 3 books:

  • Writers in the Secret Garden (with Katie Davis, MIT Press, 2019)
  • Flying Free: My Victory over Fear to Become the First Latina Pilot on the US Aerobatic Team (memoir, Blackstone Publishing, 2020).
  • Human Centered Data Science: An Introduction (MIT Press, 2021).

Aragon's early research in the 1980s laid the groundwork for her later contributions to human-centered data science; she focused on analysis of algorithms for processing large datasets. She is the co-inventor (with Raimund Seidel) of a randomized data structure, the treap, which has been commended for its elegance and efficiency, and is now widely used in production applications ranging from wireless networking to memory allocation to fast parallel aggregate set operations. She co-authored the first systematic evaluation of the simulated annealing algorithm on large datasets.

Her work on data-intensive science, particularly the Sunfall data visualization and workflow management system for the Nearby Supernova Factory, helped advance the study of supernovae in order to reduce the statistical uncertainties on key cosmological parameters that categorize dark energy, one of the grand challenges in physics today.

In 2008, she received the Presidential Early Career Award for Scientists and Engineers (PECASE), the highest honor bestowed by the US government on outstanding scientists in the early stages of their careers.

Aragon's research has been recognized with over $28M in grants from federal agencies, private foundations, and industry, and has garnered six Best Paper awards since 2004. She is a 2017-18 Fulbright Scholar. In 2015, she received the HCDE Faculty Innovator in Research Award from the University of Washington. She won the Distinguished Alumni Award in Computer Science from UC Berkeley in 2013, the Faculty Innovator in Teaching Award from her department at UW that same year, and was named one of the Top 25 Women of 2009 by Hispanic Business Magazine.

She has an interdisciplinary background, including over 15 years of software development experience in industry and NASA, and a three-year stint as the founder and CEO of a small company.

Aragon is also active in program service and supporting diversity in computing. She is a founding member of Latinas in Computing, was a board member of the Computing Research Association's Committee on the Status of Women in Computing Research (CRA-W), a founding member of Berkeley Lab's Computing Sciences Diversity Working Group and Women in Science Council, chair of the IEEE Computer Society's Entrepreneur and Pioneer Awards committee, and has served as a reviewer and program committee member for numerous computer science conferences.

Copyright Statement[edit | edit source]

This manuscript is being made available for research purposes only. All literary rights in the manuscript, including the right to publish, are reserved to the IEEE Computer Society. No part of the manuscript may be quoted for publication without the written permission of the IEEE Computer Society.

It is recommended that this oral history be cited as follows:

Cecilia R. Aragon, an oral history conducted in 2021 by Roli Varma, IEEE Computer Society

Interview[edit | edit source]

Interviewee: Cecilia R. Aragon

Interviewer: Roli Varma, University of New Mexico, Albuquerque

Date: 24 March 2021

Platform: Via Zoom

Varma:

My first question is to tell me the story of how you became interested in computers.

Aragon:

I was in college at Caltech, and in those days, Caltech didn’t even have a computer science major. A friend of mine taught me LISP, so that was my first programming language. I thought it was so much fun, and I started programming for fun. The university did have a computer that they allowed students to use, but we just taught ourselves. I was a math major and I thought it was really cool how computing could supercharge math. There were problems and theorems I was working on, particularly in combinatorics and discrete mathematics, and I found I could write programs to solve many of the problems that took me a long time to do without these tools. I thought, "Wow. This is so cool. This is something I want to keep doing." I took some programming classes at another school during the summers, and I spent more time learning computer science on my own. When I graduated, I decided I wanted to apply to graduate school in computer science.

Varma:

Some family background questions. When and where you were born? Did you have siblings?

Aragon:

I was born in Illinois, and I have one sister who lives in Boston.

Varma:

What did your parents do for a living?

Aragon:

My father was an immigrant from Chile. He earned a PhD in the US and became a professor of physics. My mother was an immigrant from the Philippines. She was a social worker. Later on, she became an academic counselor. They both arrived in the US as adults, and met at the International House in Berkeley, California.

Varma:

I visited Chile a long time ago, in the early 90s. How would you characterize your family's socioeconomic background? Would you say upper class, middle class, working class?

Aragon:

My mother’s family started out working class in the Philippines. She told me stories about growing up with open sores on her legs, being so hungry she ate cooking fuel, and how their outhouse didn’t even have a roof. My father was a bit better off; his family was lower middle class in Chile. But his family’s standard of living was less than it would have been in the US. My father’s parents couldn’t afford to send him to any university that had a physics program. He’d wanted to be a physicist since he was a boy, but in those days, it wasn’t possible to study physics at the university level in Chile. His parents didn’t have enough money to send him to the US until an anonymous donor sent a check because he said my dad was the best student in the entire country. In those days, the University of California Berkeley didn’t have any tuition, so that was the least expensive possibility for higher education. And that’s how he ended up at Berkeley. He won an award for best PhD dissertation his year, and he became a professor of physics. So that meant I was fortunate to grow up middle class in the US. We were never poor. Although, my parents were always very frugal because of their backgrounds.

Varma:

When you were in elementary and middle schools, what did you want to be? If you can recall.

Aragon:

Well, I always loved math. I wanted to be a mathematician. But I also wanted to be an astronaut. Whenever I said, "I’d like to be an astronaut," I was told, "Girls can't be astronauts." In my middle school, I wanted to take shop but girls could only take home economics and only boys could take shop. Being a mathematician was kind of a little on the edge, but it was not as bad as being an astronaut, which was not considered appropriate for a girl.

Varma:

Which was not acceptable to you

Aragon:

Today, I don’t think it was acceptable. But as a child, your life is defined and shaped by teachers and adults around you. So I ended up never trying out to be an astronaut. I should also say that my elementary school teachers put me in the slow reading and math groups at the beginning of every year because my parents were both immigrants and spoke with thick accents. The teachers often assumed that I would have trouble in school, that I would not speak English very well. I loved writing but one time when I wrote an essay that was especially articulate, my teacher accused me of plagiarism. She said, "Someone like you could not possibly know those advanced vocabulary words." What I loved about math is when you got the answers right, no one could mark you down. That’s the beauty of math, especially for people who may have been faced with low expectations from teachers as a child.

Varma:

When you were in high school, you still wanted to be a mathematician?

Aragon:

In high school, I couldn’t decide whether I wanted to be a mathematician or a writer. I had always loved writing stories and I actually wrote my first story when I was four years old. In elementary and middle school I continued writing but I never showed it to anyone because I remembered the negative comments I’d gotten from some teachers when I was younger. However, in high school, that started to change. A couple of my teachers in high school saw my writing and told me it was very good and that made me happy. I considered becoming a professional writer, but for various reasons, decided to choose math and science as my career.

Varma:

You ended up writing a book about your life, including that you became a pilot.

Aragon:

Yes, after I’d established my career in computer science, one of my passions was mentoring young people in underrepresented groups in STEM fields. I returned to my first dream of writing because I remembered how much books had inspired me as a child, and I wanted to pay that forward. It turned out that I’d developed terrible fears in childhood that were hindering me in my career in STEM. Actually, I was more afraid of getting a PhD in math or computer science than I was of getting in a small airplane and facing death. How could that be? To understand why, I wrote a memoir called Flying Free: My Victory over Fear to Become the First Latina Pilot on the US Aerobatic Team. This book is about more than flying. It’s about overcoming internalized racism and about overcoming terrifying and severe fears of pretty much everything, like a fear of heights, a fear of flying, a fear of speaking in public and so much more. What I learned, which was really interesting, is that many of those fears came from my childhood background and the expectations of teachers. The book details this. Why for a young Latina is it more terrifying to be good at math and science than it is to face death in a small plane?

Varma:

It is mind-boggling.

Aragon:

Exactly. It explains, to some extent, why there are so few Latinas in STEM fields and, particularly, in academia, why are there so few US-born Latinas. I think part of it can be explained by what it is like growing up in an environment where it’s considered an accomplishment if you’re merely average. There wasn’t any encouragement for me as a Latina to be excellent. Let me explain that a bit. My parents, obviously, experienced racism in the United States. When you speak with an accent, when you come from another country, you’ll often experience racism here, even if it’s unconscious. I’m not saying the people in the US are all racists in a negative way but the system in the United States has all these unconscious expectations that are drilled into everybody from an early age. If you experience that as a child, you internalize it and actually turn it against yourself and start to doubt your own abilities. This is the big difference between growing up Latina in the US versus growing up in a South American country. When my father experienced discrimination, he’d just shrug it off and say, "Those people are racists," or "They are wrong," whereas I would think, "Maybe I’m not good enough." That is an important difference between how he experienced it and how I did. This is why it is critical to reach out to young people and to make sure that they do not experience these unrelenting negative and low expectations from childhood on. This is why I became a professor, because I want to inspire young people to go into STEM fields. I want to be a voice of support for them, the way I did not get from my teachers when I was younger.

It only takes one voice. For me, what enabled me to succeed was my father’s belief in me. When none of my teachers believed in me, my father told me I was brilliant. He would say, "My buttons are popping," when he was proud of me. That gave me the confidence to fight through these low expectations. It is incredibly important. Now as a teacher and a professor, I try to reach out to young people today and tell them when you have trouble in a math class, it’s not you. It’s not your inability. It’s that the teaching may not be at the level that you need it to be. Perhaps you haven’t gotten sufficient training to be able to understand that level. Don’t blame yourself. Maybe the teacher is aiming the class differently than you need, and find another teacher who can help you because math is wonderful and beautiful and we need more young people to go into math and science. We need more math and science in this world. We particularly need people of color, we need women in these fields. Women are absolutely as capable at math and science as men are. Math has nothing to do with your race or gender or anything like that and you can do it. That is what I tell my students.

Varma:

In your own words, what experience was most responsible for your decision to go to college?

Aragon:

I have to give credit to my parents, who wanted me to go to college. My high school guidance counselor did not expect that I would go. I wasn’t even notified of the existence of the PSAT until a week before the exam. Since my parents were immigrants, even though they went to college themselves, they didn’t know the rules for how to send their child to college in the US. My father found out about the PSAT by chance a week before the exam, told my guidance counselor to sign me up for it, and the guidance counselor grudgingly gave me this little thin booklet about it. So, I didn’t have any prep for the test. Oh, there were no AP classes in my high school either. I showed up for the PSAT pretty unprepared, but I did well enough to become a National Merit semi-finalist. Then when I took the SAT the next year, I won a National Merit Scholarship, which helped me go to college. Caltech is expensive! Having someone in your life who encourages you to aim high is really, really important. I was lucky that I had a dad who did this for me. I know many kids do not have a dad or do not have a family member who encourages them. Then I think it falls to the schools to do it, but there are gaps. My goal is to reach out to as many young people as possible to encourage them to aim high.

Varma:

How were your parents supportive of you going to college?

Aragon:

I was very lucky, very privileged to have wonderful parents who always supported me in whatever I wanted to do. They encouraged me to go to college. When the scholarships I won didn’t quite cover the cost, they scraped together enough to pay the difference. They encouraged me to live a life of high achievement. They were loving and supportive all my life really. Even when I did things they disagreed with.

Varma:

Did you have a role model for your study in college? You mentioned your parents.

Aragon:

It was my parents. They both overcame significant obstacles to attend and succeed in college, and they both valued learning tremendously.

Varma:

Did you want to add anything? You gave a wonderful example of rushing you through PSAT.

Aragon:

My mother modeled unconditional love. She was very bright and encouraged me to excel, but never made me feel bad for falling short. My father was extremely proud of me, and he encouraged me to be a little bit defiant in some ways. When my teachers told me that someone like me was not good enough, he would say, "Those teachers are wrong." I think that independent spirit of sometimes defying conventional wisdom gave me a lot of inner strength. When a professor at Berkeley once told me, "Women don’t have the intellectual capacity for computer science," I heard my father's voice: “That teacher is wrong.”

Varma:

I am amazed that this perception has still continued when women have done so many things. Were you a full-time or a part-time student when you went for your undergrad?

Aragon:

When I went to Caltech, I was full-time. Again, I was very fortunate. I received scholarships and my parents sacrificed financially to make up the difference. I did work about 10 hours a week throughout my time at Caltech, at a work study job. I always worked, but I was able to spend most of my time on my studies.

Varma:

Did you go to graduate school right after your undergraduate degree?

Aragon:

Not exactly. I graduated from Caltech and started looking for a job. There was a recession going on at that time. I think there was also some element of discrimination. I remember I applied for one job and the hiring manager, a white man, told me, point-blank, "Well, we were actually looking for a young man." It was surprising that he actually said it out loud, but I suspect that many more thought it to themselves. Out of the 100 resumes I sent out, almost nobody replied. So I took a job as a secretary, because that was the only job that I could get, despite the fact that I had a bachelor's degree in math from Caltech. After about a year of working, I decided to go to graduate school because I could not get a full-time job in a technical field. I applied to UC Berkeley and was accepted into their Ph.D. program in computer science. I stayed in that program for several years and got a master's degree. Then I ended up dropping out because I lost my confidence in my ability to complete a Ph.D. I became convinced I wasn’t smart enough to complete a dissertation, and so I left.

Varma:

Even though your inner voice, your father's voice is telling, "They are wrong."

Aragon:

The problem is even though that one voice can be strong, sometimes it can get drowned out by those hundreds of voices, of classmates, teachers, the world around me. The American culture was telling me that I was not good enough, and, temporarily at least, those fears won out and I dropped out. But fortunately for me, in 1987 it turned out that companies were so desperate for programmers they would even hire a Hispanic woman. Then, once I was working, they discovered I was surprisingly good and I started getting glowing letters of recommendation, and then it became easier for me to find new jobs because of the recommendations that I brought with me.

Varma:

So what happened then?

It was during this time that a colleague at work said, "How would you like to go for a ride in a small airplane?" My first thought was, "Oh no. I am not the sort of person who does something so risky." I was still very timid and fearful at the time. All of these voices in my childhood had combined to fill me with self-doubt. But in that moment, I remember hearing my father's voice in my head, saying, "I’m proud of you. You can do anything you want." And I realized if I always listened to the fear in my life, I would never accomplish what I really wanted to do. So I told my colleague, “Yes.”

That Saturday, I went up with him and even though I was terrified, it was one of the most incredible experiences of my life. I loved flying so much. It was spectacularly beautiful to soar above the earth, to see the sunlight glittering over the water of San Francisco Bay. When we got back down on the ground, I signed up for flying lessons.

And although I was a terrible student, very fearful, I kept at it because the joy of flying was greater than the fear. As I continued with my flight lessons, I slowly started to overcome my fear. This is the story I tell in Flying Free, that I could use mathematical techniques to face my fear and as I did that, step by step, the fear started to recede and I became more confident, not just in my flying, but in the rest of my life. So, long story short, it eventually gave me the confidence to try out and make the United States Aerobatic Team. I was the first Latina pilot to do so. That made my family incredibly proud. After that, I realized that I wanted to go back and finish my Ph.D. and that now I had the confidence to do it because I could face my fears.

Today, I have confidence that in any difficult task I take on, I can apply the same techniques I used to learn to fly. In 2003, I went back to the Ph.D. program in computer science at UC Berkeley. This time, I had a job and two small children. But I went back, finished my dissertation, and graduated, and it was fun. I really enjoyed it. As soon as I had overcome my fear, I realized how much fun I had doing math and computer science. This was what I wanted to do. I wanted to do research in computer science. I wanted to be a teacher and encourage other people to go into this amazing field. I’m now a professor at the University of Washington. In 2016, I became the first Latina full professor in the College of Engineering at the University of Washington in its 100-year history. All because I used math to overcome my fears and learn to fly.

Varma:

Some gender and ethnicity specific questions about your college journey. In your opinion, what was it like to be a Latina at Caltech & UC Berkley?

Aragon:

It was challenging in many ways. Most people were very kind and welcoming at both universities. The problem was because of the way I grew up not believing in myself, whenever somebody made an offhand comment like, "Oh, you are pretty good at math for a woman," those comments had an outsized negative impact on me. I would immediately plunge into despair, thinking, "Maybe I’m not good at math. Maybe I am just good for a woman." That is a really toxic view. Even if that person was trying to be positive, because they grew up steeped in a culture that believes that women have particular roles and men have particular roles, that view ended up infusing my life, despite their good intentions. We need to combat this system, this toxic system, by never telling girls and women, “You’re pretty good for a girl.” We have to say, you are great at math. Period.

Varma:

Do any other incidents come to mind, related to being a Latina in a scientific field?

Aragon:

I’m afraid there are many. After I became a professor, I was once talking to a white woman about my childhood and about some of the experiences that I had as a child where I was bullied by my classmates and called racial epithets and told I was disgusting for doing well in math and science. She actually said, "Maybe it’s all this adversity that’s made you so strong today." I was kind of taken aback. I was telling her a story about racism I experienced as a Latina and she was trying to tell me that racism made me strong. No. It was my father’s voice telling me to overcome racism that made me strong. I think that’s an example of how some people don’t really understand what it’s like to experience unconscious racism as a child.

Here’s another example. I had an acquaintance who had a Ph.D. in physics, and she worked at a national lab. At one point, I expressed an interest to her in applying to that national lab. At the time, she didn’t know my background. She just knew I was a Latina. Her face fell a little and she said, "Well, it’s really hard to get a job at this lab." So I said, "I have an undergraduate degree in math from Caltech and a Ph.D. in computer science from Berkeley." I’ll never forget how her face changed. I could see that she had a certain impression of me, and it completely changed when she heard about my degrees. This confirms research about what it means for people of color to have a pedigree, an academic pedigree. If you’re a white man, it doesn’t really matter what university you get your degree from but, for women or people of color, having degrees in science and math from highly ranked universities improves their career outcomes. It shouldn’t be this way, but for me personally, this pedigree was important because it acted as a counterpoint to people’s expectations. I’m small, 5 feet 2 inches, and I was often quiet in those days. So when I talked to hiring managers, I had to actively counteract the stereotype of being a small, quiet Latina in the US by saying things like, "I have a Ph.D. in computer science from UC Berkeley," which should not have to be necessary because it’s hard for me to say these things. I always felt like I was bragging, but if I don’t say them, if I don’t give this background, people tend to think I am less than I am. I’m caught in the horns of this terrible dilemma. I think this is something that affects many people, not just Latinas. It could happen to a young man who comes from a rural background, for example, or anyone who grew up poor. Any time you do something that goes against stereotypes, you need to fight.

It should not have to be this way. We need to change the stereotypes so that all young people can believe they have limitless potential. They have to believe they are not funneled into a particular occupation. Your socioeconomic class should not define who you are as an adult, your race or your gender or your background should not define who you are. You should be able to choose the life you want to have. You should choose it freely. You should not choose it based on unconscious stereotypes that you’ve internalized.

Varma:

What happened when you finished your doctorate? What did you do next?

Aragon:

I applied for research positions in industry and academia. I received multiple offers, and I chose a research position at Lawrence Berkeley National Lab, truly a wonderful opportunity. Also it happened to be where I was already living, so my family didn’t have to move.

Varma:

You have done all sorts of things. You have done software development in the industry. You are the founder of a startup. Now you are in academia. Could you talk about opportunities and challenges in these three different sectors?

Aragon:

Absolutely. I may very well be uniquely qualified to advise students trying to decide whether to go into academia, industry, or government labs or start their own business. Of course it depends on their individual goals. For people interested in research and who want the freedom to choose their own research topics, academia is the best of these various choices. I’m certainly happiest here. Now, that’s not to say academia is free from racism or sexism. On the contrary. On the other hand, I’ve experienced more racism and sexism in for-profit companies than in nonprofit organizations such as academia or government. I’m not really sure why, but it may be that if the organizational goal is focused on the good of society rather than shareholders’ bottom line, there is more room to question stereotypes or the status quo.

Unfortunately, in many companies there’s a lot of lip service and programs that are supposed to improve inclusivity but are more focused on appearance and PR than on actual improvements. Let me give an example. I applied to one large tech company that claimed they had a program to hire more women. But I was only interviewed by young men, young white men, and they actually said, "We have a policy that you won’t be interviewed by the group who wants to hire you. We have people all across the company interview you because that is fairer. That is less biased." No, it’s not. It just means that unconscious bias gets to play a larger role in the hiring decision. None of these young men knew anything about my field in computer science. They asked me questions that were completely irrelevant. I was honest. I said, "I don’t know the answer to your question. It’s not in my field. Are you going to ask me questions about my area?" Only one out of the six men who interviewed me was honest enough to say, "I am not qualified to interview you." Right. But all the others were also not qualified. Of course, I didn’t get a job offer. I also noticed the only women I met were in HR or other non-technical fields. This was unconscious sexism. This particular company is still doing this. I will not say the name, but it’s a major company that’s still having problems with racism and sexism today. Again, I don’t think they’re truly aware of what they’re doing. I think many of them really believe they are working toward diversity in hiring. But racism and bias are not only, "I am going to call you a racial epithet" or "Women cannot do computer science." It’s also when high-ranking executives say, “The reason we don’t have as many women in programming positions at our company is that they choose not to come, we can’t find enough women, it’s a pipeline problem.” No. It’s a biased environment that drives women away. Because guess what? Everybody likes to work in a place where they are valued, where they feel like they belong. If the company makes you feel like you don’t belong, well, you’re not going to have as many women accept offers and remain in positions for the long term. Recruitment and retention need to be looked at in the right way.

Varma:

I noticed in your biography that you have an interdisciplinary focus. How does this work out in academia? Which tends to be a lot more disciplinary.

Aragon:

In my opinion, interdisciplinary work is the future, particularly in STEM fields. I work in data science. I’m the co-founder of our data science master’s program at the University of Washington. We’ve discovered the incredible value, over the years, of what we call pi-shaped people — the Greek letter pi. A pi-shaped person is someone who has depth of knowledge in more than one discipline. Most people graduate from their undergraduate or their Ph.D. program with depth in one area, like number theory, and then they have a broad background in related fields. That’s a T-shaped person. But a pi-shaped person may have depth in two fields, say, image processing and machine learning, for example. When I worked at my first job after my Ph.D., I joined an astrophysics collaboration and because of my interdisciplinary background, I was able to see issues that the physicists, who were all incredibly smart but simply did not have knowledge in these other areas, could not. Because I had multidisciplinary training, I was able to develop a new algorithm that brought machine learning and image processing to a physics problem, and I was able to dramatically improve their data pipeline. When I joined the project, they had six postdocs working four hours a day just on manual labor, not on science, and by the end, I had modified their data science pipeline so that it only took one postdoc one hour a day to do the tasks that needed a human in this data science pipeline. As a result, more people were able to do science and write papers and go on and get jobs after their postdocs. This is what an interdisciplinary background brings, particularly in data science — the insight to solve difficult problems that may involve more than one area of expertise.

I think it’s vital for students to get this extra training in a field outside a single discipline. Universities and companies are starting to recognize the value of interdisciplinary training. I joined the University of Washington over 10 years ago. At that time, there were no academic data science programs. As a matter of fact, when we started building the program, I heard comments like, "Well, isn't this just a fad?" A big part of the reason I chose the University of Washington back in 2009 was the eScience Institute, which was already doing interdisciplinary work by the time I joined them. I knew I wanted to be a part of this university because they were supporting this kind of education. And as I’ve been involved in the Institute, we’ve been the leader in a variety of data science programs, such as data science for social good summer schools, data science incubator programs, and human-centered data science courses and research. Another example involved six departments that got together to develop a multidisciplinary data science master’s program. We also have data science programs at the undergraduate and Ph.D. levels as well. We’re not the only ones now. There are well over 100 programs throughout the US and the world because today data science is seen as a useful and important field.

Varma:

You are the first Latina to accomplish multiple honors such as full professor in the College of Engineering at the University of Washington and a pilot in the U.S. Aerobatic Team. To me, these appear two distinct paths: academic and action-adventure. Could you talk about each of them? How it has been especially for you as the first Latina?

Aragon:

First of all, I love flying and I still do it as a hobby, but I spent a number of years flying professionally, not for the airlines but as an air show pilot and as a competition aerobatic pilot. For me, this was my form of art. Aerobatics was dancing in the sky, it was the path that enabled me to overcome my fear and to overcome a lot of negative emotions and self-doubt. Doing something like flying was the scariest possible thing I could imagine doing. By taking on that incredibly scary task, it gave me the courage to have an intellectual life, which is something that I always wanted to have from childhood. I don’t think you have to do just one thing in your life! I never want to stop flying and I never want to stop doing math and computer science. I never want to stop teaching. I think that it is important that people realize that you do not have to just do one thing. You can do many things. Really, the biggest limits that we all face have to do with our own fears and our own self-doubts.

Varma:

Could you explain what is your current technical field and what made you choose that particular area of interest?

Aragon:

My current research field is called human-centered data science. This is an interdisciplinary field that combines human-computer interaction with data science. We develop statistical and machine learning algorithms and combine them with social science techniques from human-computer interaction and social computing. It’s important, particularly today, because data science and computation and artificial intelligence are having a huge impact on society and millions of people’s daily lives. Today, you can’t build a machine learning algorithm without thinking about the societal consequences. We see this, for example, now with facial recognition. If you treat facial recognition as only a statistical algorithm, and ignore the fact that there is bias in the training datasets, there is bias in the composition of the developer teams, there’s even bias in the categories humans choose to label their data, well, then there is the potential for impacting society in a negative way and for causing a tremendous amount of harm to individuals. You can’t develop artificial intelligence without taking into account the societal and human impacts and that is why human-centered data science is so important today.

Varma:

In your opinion, how are careers with a computing-related degree attractive to Latinas?

Aragon:

First of all, they are really great careers. A lot of fun. You can do important work that has an impact. It’s kind of like solving puzzles for a living. It’s great for Latinas, in particular, because as I think I have mentioned before, the advantage of a career that is technical, that has a mathematical or computational component, is that you’re not judged as much as in a more subjective field. A novel might get reviewed by someone with an unconscious bias against Latinas, whereas if I prove a theorem or write a technical paper, there’s more logic involved. That’s not to say there isn’t any bias in computing. Of course there is. But it’s a matter of degree, and it’s possible to fight back with logic.

It’s not that we don’t experience a hostile environment or negative views, but having a computing background gives you a leg up, it gives you a certain advantage to be able to prove a theorem and nobody can tell you it’s wrong. That is incredibly wonderful. It’s still hard. It’s hard to be a high-achieving Latina. I’m not going to sugarcoat it. It’s challenging. We are capable of it. Science and math are some of the wonderful tools that can help us achieve the life that we always wanted to achieve, take care of our families, and have a positive impact on the world.

Varma:

What would be your advice to a Latina woman high school senior thinking about computing?

Aragon:

What I do with my students is try to dive deeper into why are they are or are not interested in computing or math. I’ve had students say, "Well, my brain just doesn’t work well in math." I’ll say, "What made you think that?" Very often it will be, "I took a class and I didn’t do well in it." I say, "Maybe you need to try a different class with a different teacher," because I feel that if math is taught well, everybody can learn it and everybody can understand it. Your path toward learning may be different. It may be slower, it may be faster, it may wind back and forth like my own path. Never believe, “I don’t have a math brain,” or “I’m not a technical person.” That is just wrong. Everybody can be a technical person. If someone says they’re leaving the field, I try to find out what made that individual believe they could not do math or computer science. Then I pick it apart logically and say, "Why don't you try this? Go to this class, do it with this teacher. Learn it in a way that is comfortable for you." Because you can do it.

Varma:

I have just two questions. You have been very active in the larger computing community, especially about issues of diversity. Can you want to talk about some of the things that you have done and your general reflections on broadening participation issues?

Aragon:

I believe very strongly that it’s good for the field of computer science, this country, and the world, for there to be a more diverse group of people studying math and computer science, working in computing. There has been a tremendous amount of research showing this to be true. Companies that have a more diverse workforce, more diverse leadership, do better financially. They innovate better. This happens over and over again. Also, we need science in this world today. We are facing some intractable problems. We need as many smart people as we can get to work on these issues. If women, if people of color, if Latinos or Black or Indigenous folk are discouraged from applying their intelligence to these scientific problems, the pool of people who can solve these issues will become smaller and we may miss out on the next genius. The next genius may be a person whose parents never went to college, who’s working in the fields right now. They may be somebody who has always been discouraged or who’s been told they should just become a housewife. That genius needs to be nourished. It’s completely wrong that “genius will out.” People follow paths that are laid out for them; it’s very difficult to beat your own path. It often takes extraordinary encouragement from an adult starting from a very early age. As I said, it was my father's encouragement that allowed me to fight my way off the beaten path and achieve in a scientific field. What about all the people who don’t have that? Who is going to encourage them? My role is to reach out to those people who don’t have that kind of encouragement. That’s why I’ve volunteered so much of my time in diversity issues and broadening participation initiatives and why I will continue to do so, because it is so important, not just for people who look like me, but for everybody. Everybody in the world will end up benefiting if a larger and more diverse group of people goes into technical fields.

Varma:

What advice do you have for academia to make their departments diverse and inclusive?

Aragon:

Academia needs to be aware of their own unconscious bias and do their best to hire and retain faculty of color in fields where any group is underrepresented. They should try to make the professoriate look more like the country. There should be role models among the professors for the student body and the people who are applying, the people who are not there yet, and that is incredibly, incredibly important. I sometimes hear people saying, "Well, we don’t want to lower the bar." It’s a false belief.

Varma:

That is, again, the bias.

Aragon:

Yeah. I will give an example of the problem with this belief. Again, this has been backed up by a great deal of research, so it’s not just an anecdote. In my example, I had one teacher in high school who was biased against me, who gave me a B despite the fact that my assignments averaged to an A in his class. Because of that one B, I wasn’t the valedictorian in my high school graduating class. So if you compared me with a valedictorian, you might say my resume didn’t look quite as good. It might not even be a conscious appraisal. And maybe it’s not a big deal, but imagine that type of bias being multiplied over time. So if you imagine that, say, a Black kid or a poor kid or a girl in math is given just 1% lower grades and letters of recommendation over a lifetime, all those small differences add up to a significant disadvantage in a resume over a career. So that’s why it’s incorrect to be “race-blind” in the application process. It’ll end up being biased because of the sum total of all those small bits of racism that are encoded within the process itself.

The other thing that is very important is to realize that we all have unconscious biases. I’ve seen it in myself, and I have to fight it. Just because you have a diverse committee and letters of recommendation from a diverse group of people does not mean unconscious bias has been removed. Absolutely not. I’ve seen people say, “You were judged by a diverse committee,” as though that’s enough to ensure fairness. But no. A woman can be biased against women. A person of color can be biased against people of their own race. We all have to consider this in ourselves. When you’re looking at CVs or resumes or applications, ask yourself, "Am I allowing my own preconceived notions about this person’s race or religion or background to sway my judgment? Am I as impartial as I think I am? Has this applicant experienced a lifetime of unconscious bias? Did it lower their grades, change their letters of recommendation?” It’s not easy to question ourselves in this way. But we should never give up.

Varma:

This is the really final thing. Is there anything you would like to add, which I did not ask you?

Aragon:

If there are Latinas, in particular, reading or hearing this, I want to say that you are wonderful, you can do anything you want to do. Do not give up. I believe in you and many other people do as well and we need you. We need your insights, your creativity, and your intelligence.

Varma:

Thanks a lot for a wonderful interview.

Aragon:

I want to thank you, Roli, for having me on here. I appreciate the opportunity to let people know about the importance of going into math and science and also not allowing your fears or your unconscious beliefs to lead you into an easier path. Taking the challenging path is so much more fun and so much more rewarding in the long run. When I wrote my memoir, it was scary to reveal so many personal and intimate things that I’d never told anyone before. It was challenging to explain exactly why and how I had turned my life around that day I decided to fly. But it’s so important to do difficult things. Thank you for giving me this chance to talk about this work that means so much to me.