People Assumed I Was A Tech Whiz Because I'm Asian

Philip Guo was on the fast track with his computer programming career. But he says that's because he's Asian and people assumed he was a whiz. He talks to guest host Celeste Headlee about benefiting from racial profiling.

CELESTE HEADLEE, HOST:

Racial profiling has been blamed for everything from unnecessary police stops to perhaps a lack of job opportunities. But our next guest says racial profiling helped build his career. Computer programmer Philip Guo says he was given more credit and better jobs in his field than his skills merited, all because he's an Asian-American man. And people assumed he was a hotshot programmer, even though he was just so-so at the time. He wrote about that experience for his blog, and the essay was later picked up by Slate. Philip Guo joins us now. Welcome to the program.

PHILIP GUO: Hello.

HEADLEE: So you your piece begins with, I guess, what would be a stereotypical bio for a programming prodigy, right? You start working on the computer at age 5. You're creating your own programs in high school and then spending weekends at the keyboard. But that's not your story. So how did you get into this field?

GUO: So I actually - I was always sort of interested in computers like a lot of kids were growing up in the '90s. But I never had any programming experience beyond just one small class in high school. And I was fortunate enough with my academic background to have gotten in at MIT, which is very well-known for training programmers. And it was really during my freshman year at MIT as a computer science major that I really started getting deeper into the field - so really starting in the beginning of college.

HEADLEE: Do you think that you got special preference getting your very first job out of college because of your race?

GUO: I think that - see, my very first job was my first summer internship. This was after my freshman year. It was my first programming job. And I don't know if, you know - I don't know if race was the only thing, but I think definitely I sent out a bunch of resumes to various companies. And I had very little experience at the time, but definitely as an, you know, Asian-looking name from MIT that - I'm sure that gave people the benefit of the doubt. And I was offered an internship back in California where my family was really without much actual programming experience.

HEADLEE: And yet, as you say, I mean, MIT has its own recommendations as well. When did you first start to suspect that maybe you'd gotten preference or gotten a leg up because you're Asian-American?

GUO: I think that, you know, there was two factors, right? There was being Asian-American and also being male because computer science and, you know, computing in general is very a male-dominated field. I think the first time I really started to notice was in various summer internships and research jobs I had in school. It always seemed like during meetings, for example, even though I was just an undergrad. it seemed like people assumed that I knew what I was doing. You know, during meetings, people would talk to me in a very positive and respectful way as though I had a lot of experience. And I have peers who did not fit my demographic as much, and they were, you know, I would say implicitly looked down upon without, you know, much prior evidence.

HEADLEE: Well, let's be more specific about that because in your essay you say you saw other young programmers, and especially women, who were actually discouraged by either their professors or by their bosses, even though they were fully qualified. Can you, like, relay without using names? Tell us about one of those incidents.

GUO: Sure. So in my article, I described a friend of mine who, after her freshman year, she was looking for research opportunities on campus. And she got a research job that - where she would be building graphical applications. And at the same time, a male student, also with the same experience level - they both had the same resume because they had both just taken the introductory class. As far as I knew, he did not have a ton prior experience. But the manager - the research manager gave him the job that was the actual programming job, and he kind of put her on the more mundane sort of menial task of transcribing notes and other sorts of non-programming tasks. And as a result of that, she got fairly discouraged because she saw throughout summer that her male counterpart was actually learning a lot and improving and feeling very satisfied with his job and she was not. She was really doing something that she didn't sign up for.

HEADLEE: Did you ever talk to people about - your fellow students or colleagues - about these things?

GUO: I have. And, you know, throughout both my undergrad and grad school, this topic kept on coming up again and again. And as this article has come out, lately, I've been discussing it lot because after this piece came out, my blog got kind of spread virally on Twitter and also then Slate picked it up, and it got even wider exposure. I've gotten - my inbox is filled with over a hundred e-mails from people all around the U.S. and even around the world who've talked about their personal stories of implicit discouragement and discrimination in both school and the workplace. And a lot of those e-mails, you know, make me very frustrated and sad. And so I've been e-mailing people, and I'm hoping to write a follow-up piece about that.

HEADLEE: But, I mean, I imagine the immediate response might be, look, it's worked great for you. Why complain?

GUO: Yeah, so, I mean, my - I'm of two minds in this, right? Of course, I've been a beneficiary of this sort of - these sorts of implicit stereotypes, so I feel lucky in one regard. But on the other hand, there's sort of a bit of guilt as well, right? That I feel like I've gotten a lot of opportunities that others have not as much. You know, other people of my similar sort of technical skill level just did not get the encouragement that I did. And I wish that we lived in a world where these sorts of inequalities just didn't exist.

HEADLEE: You know, I wonder if you really should be feeling any guilt, or maybe you can describe to me how that guilt works for you inside your head. I mean, you're not responsible for someone else not getting an opportunity. You're not responsible for someone giving you a job, and maybe they just felt honestly, without regards to race, that you might be better qualified. So why would you feel guilty?

GUO: That's a great question. Yeah, so maybe guilt was a bit strong of a word. I think maybe part of it is that, you know, I think as people - especially, I've been trained as a computer scientist and as a scientist - kind of coming from a science background, you're always kind of trained to question yourself and question your beliefs and your technical abilities and the merits of your work. And so maybe a part that stemmed from the fact that I questioned, oh, wow, if I had, you know, looked different, if the color of my skin had been different, if I had been of a different gender, I might have not gotten as far as I have in my career so far.

So, you know, part of that is good and part of it is just feeling fortunate as well. And I feel like the thing I would say to younger people kind of who are looking up to me as role models who are in my demographic is that you should feel very fortunate and make the most of the opportunities you've been given. And also, at the same time, kind of pay it forward and not - and try your best not to, you know, show these sorts of biases against younger people.

HEADLEE: And you're going to be an assistant professor of computer science at the University of Rochester in New York, right?

GUO: Yes.

HEADLEE: So what will you tell your students? If you have African-American students or Latino students or especially women students, how will you prepare them to deal with this if racial profiling is going to be part of their work life?

GUO: That's a great question. And it's something that I've read - I've started reading a bit about. And it's a delicate issue to deal with, especially because I am not of the demographic, right? So I don't feel like I have a true understanding of what they might've gone through and what they may be going through. So it may be presumptuous of me to try to, you know - it may be kind of a paternalistic tone if I make statements that are too broad.

So I think what I would say is - I would really be encouraging in class for people to come talk to me, for students to talk to me at office hours. And then privately, if they have concerns, I'll be very candid about it. Another thing I might do is share stories or refer them to role models that I know who are, say, African-American or women in computer science. So I feel like a big part of my contribution is actually connecting students to my colleagues and friends who have been successful in overcoming these challenges and hoping that they can kind of talk to them as role models.

HEADLEE: Well, I applaud you for being so open and honest about a topic that remains unspoken so often. Philip Guo, computer programmer. He joined us from the studios at MIT. Thank you so much.

GUO: Thank you so much.

Copyright © 2014 NPR. All rights reserved. Visit our website terms of use and permissions pages at www.npr.org for further information.

NPR transcripts are created on a rush deadline by Verb8tm, Inc., an NPR contractor, and produced using a proprietary transcription process developed with NPR. This text may not be in its final form and may be updated or revised in the future. Accuracy and availability may vary. The authoritative record of NPR’s programming is the audio record.