Philip Guo (Phil Guo, Philip J. Guo, Philip Jia Guo, pgbovine)

NPR Interview on Silent Technical Privilege

Earlier this month, I wrote Silent Technical Privilege. It attracted a fair amount of attention online, with ~76,000 unique page views so far. One week after release, an editor at Slate republished it and pitched it on the home page as I Got Away With Being a Bad Programmer for Years Because of How I Look.

Even though I was a bit embarrassed by that headline, it definitely attracted eyeballs, with ~297,000 unique page views in its first week alone. (Being featured next to a giant baby probably helped.) One Internet forum commenter didn't even click on the article and just ranted: “I refuse to give Slate the hits. Am I to assume from the title that he got jobs in the technology sector using his good looks instead of his brain?” (Definitely.)

My inbox quickly flooded with hundreds of emails and a few interview requests. The one from NPR stood out since I've been a long-time listener, so I decided to take it. I had never been interviewed in a studio before, so I was curious to try.

(If you're impatient, listen to the full interview here.)

The studio

The program that wanted to interview me was called Tell Me More, but I had no idea about the context of the episode before I entered the studio. And I had no media training whatsoever.

The show's staff booked me a 30-minute slot in a recording studio on the MIT campus, where I currently work. It was a small soundproof room with a chair, desk, microphone, and headphones. Once I closed the door and put on my headphones, it was almost dead silent. I could hear my heartbeat.

I put my laptop on the desk so that I could refer to my article if needed. The microphone was placed off to the side, and the audio engineer in the next room ran some sound tests before connecting me via the Internet to the NPR studios in Washington DC. When I first got connected, I talked with the audio engineer on the other end to run through their sound test. He wanted me to back off a bit from the mic, which meant that I had to sit far back in the seat.

Then the host, Celeste Headlee, came on the line and introduced herself. Her voice sounded crystal-clear just like the people I heard on NPR shows! I was just like, “Uhhh, good afternoon.”

She made some small-talk with staff over in her DC studio. And then she mentioned, “ahh good, the editor is here ... he makes sure we don't say anything inappropriate and can bleep us out if we do.” And I was like, “k, I'll try my best” ... “uhh, not to say anything inappropriate.”

When she was ready to record, she told me, “Remember, don't say 'good morning' or 'good afternoon' or reference the time of day, since we don't know when this segment will air. Got it?” Then she counted down, “three ... two ... one ...” and the interview began.

The interview

Celeste introduced the segment in the most NPR-like voice ever:

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.

At this point, I'm squirming a bit since I never used the term “racial profiling” in my article. When she said it, I felt like it sounded too strong and politically-charged for the kinds of implicit privilege and bias that I've witnessed in technical fields. But without any time for this to sink in, I heard in my headphones ...

Philip Guo joins us now. Welcome to the program.

I tried really hard not to say “good afternoon,” so I just uttered “HELLO!” like a 12-year-old.

Aside from that awkward start, the interview went well. Celeste's questions were on point and gave me a chance to describe my article. But it became clear that the theme of the episode revolved around race and racial profiling, which wasn't something that I had any expertise in.

Still, I tried my best to come up with coherent answers and to phrase everything tactfully. In doing so, I ended up saying lots of filler words such as “you know” and “right?” and repeating phrases while working through my thought process. It also felt unnatural to remain still in my seat because the audio engineer didn't want me to lean forward into the mic too much.

The interview lasted about ten minutes, which flew by super fast. I thought the engineers would later edit my audio stream to clean up stutters, but they left it mostly unedited. So I ended up sounding, well, like I do in real life ... like I'm thinking out loud.

In contrast, Celeste was able to adapt to what I said and come up with new questions on-the-fly without a single stutter. She was able to construct self-contained, punchy sentences in her head moments before uttering them so that it seemed like her thoughts were wholly formed before coming out of her mouth.

On the whole, this was a fun experience that also inspired me to try to improve my public speaking voice while still sounding like myself.

Listen to the interview here:

or on NPR's website.

Read the transcript, which I edited to eliminate stutters and redundancies ...

Edited transcript

Question (from Celeste): 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?

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

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

My very first job was a summer internship after my freshman year of college. I don't know if race was the only factor, but I think it helped. I sent out a bunch of resumes to various companies. And I had very little experience at the time, but definitely as someone with an Asian-looking name from MIT – I'm sure that gave people the benefit of the doubt. I was offered an internship back in California where my family was, without having much actual programming experience.

Q: And yet, as you say, 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?

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

Q: Let's be more specific about that, because in your essay, you say you saw other young programmers, especially women, who were actually discouraged by either their professors or by their bosses, even though they were fully qualified. Can you tell us about one of those incidents?

In my article, I described a friend of mine who, after her freshman year, was looking for research opportunities on campus. She got a research job where she would be building graphical applications [GUIs]. At the same time, a male student with the same experience level was also hired.

They had the same resume because they had both just taken the introductory programming class. As far as I knew, he did not have a ton of prior experience. But the research manager gave the male student the job that was the actual programming, and he put her on the more mundane and menial task of transcribing notes and other sorts of non-programming tasks. As a result of that, she got fairly discouraged because she saw throughout the 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 doing something that she didn't sign up for.

Q: Did you ever talk to your fellow students or colleagues about these things?

I have. Throughout both undergrad and grad school, this topic kept on coming up again and again. And I've been discussing it a lot lately because after this article came out on my blog, it spread virally on Twitter; and when Slate picked it up, it got even wider exposure. My inbox is filled with over a hundred emails 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. A lot of those emails make me very frustrated and sad. So I've been emailing people, and I'm hoping to write a follow-up piece about these responses.

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

Yeah, so I'm of two minds on this issue: I've been a beneficiary 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. I feel like I've gotten a lot of opportunities that others have not as much. Other people of my similar technical skill level just did not get the encouragement that I did [because of how they looked]. I wish that we lived in a world where these sorts of inequalities just didn't exist.

Q: 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?

That's a great question. Maybe guilt was a bit strong of a word. I think part of it is that I've been trained as a computer scientist, and coming from a science background, you're always trained to question yourself, your beliefs, your technical abilities, and the merits of your work.

So maybe a part of that feeling stemmed from the fact that I questioned myself like, “Wow, if I had looked different – if the color of my skin had been different, if I had been of a different gender – I might not have gotten as far as I have in my career so far.”

Another part is just feeling fortunate. The thing I would say to younger people 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, pay it forward and try your best not to show these sorts of biases against younger people.

Q: You're going to be an assistant professor of computer science at the University of Rochester in New York, right? So what will you tell your students? If you have African-American, Latino, 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?

That's a great question. And it's something that I've started reading a bit about. It's a delicate issue to deal with, especially because I am not of their demographic. So I don't feel like I have a true understanding of what they might have gone through and what they may be going through. It may be presumptuous of me to try to make statements that are too broad, which may come off with a paternalistic tone.

I would really be encouraging in class and ask students to talk to me at office hours. And then privately, if they have concerns, I'll be very candid. Another thing I might do is share stories or refer them to role models I know who are, say, African-American or women in computer science. 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 talk to my students as role models.

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.

This transcript is Copyright © 2014 NPR. For personal, noncommercial use only. I have lightly edited it to re-post here.

Created: 2014-01-22
Last modified: 2014-01-24