Kim Ng Is Not Mediocre

Two years ago, Kim Ng became the first female General Manager of any sports league and the first Asian-American General Manager of Major League Baseball. I used that moment to write about my fandom of Ng, but also about the dangers of exceptionalism:

Progress has to start somewhere, and this is definitely something to celebrate. However, all too often, people point to barriers like these being broken and think that the work is done. The work is not done. If we live in a world where only exceptional folks like Ng get opportunities, then we will have failed.

A truly equitable world would be one where all professional sports leagues were full of mediocre GMs of all genders and races.

I ended my piece by saying:

I hope Ng succeeds, but in a weird way, I’ll be just as happy if she’s mediocre.

Well, Ng has once again proven that she is not mediocre. Three years after assuming her post, she has led the Miami Marlins to the playoffs for the first time in a full-length season since 2003. Good for you, Kim!

A World Where Mediocre People of All Races and Genders Have Opportunities

Today, the Miami Marlins named Kim Ng their new General Manager. She is the first female GM of any of the major professional sports leagues in the U.S. (baseball, basketball, football, and hockey), and she is the first Asian-American GM of Major League Baseball.

I’ve been a fan of hers since she joined my Dodgers as an assistant GM in 2001. It’s a historic moment for sure, and it’s also shameful that it took this long for her to get a GM job. Her credentials are impeccable. She’s been in baseball for 30 years, and she has three championship rings. By all accounts, she’s an incredible negotiator, talent evaluator, and manager, and she is highly respected by some of the biggest names in baseball. It seemed like a sure thing for her to get a GM job in the first decade of this century, and she got plenty of interviews. But it never happened, and in 2011, she took a job with Major League Baseball.

Progress has to start somewhere, and this is definitely something to celebrate. However, all too often, people point to barriers like these being broken and think that the work is done. The work is not done. If we live in a world where only exceptional folks like Ng get opportunities, then we will have failed.

A truly equitable world would be one where all professional sports leagues were full of mediocre GMs of all genders and races.

I didn’t fully understand this until I learned about Janice Madden’s groundbreaking study of Black coaches in the NFL. She found that, from 1990-2002, Black coaches far outperformed white coaches. Her research led to the Rooney Rule in 2003, which required that teams interview at least one minority candidate for coaching positions.

Here’s the kicker. Success isn’t just more Black coaches in the NFL. Success is more mediocre Black coaches in the NFL. As Madden explained:

If African-American coaches don’t fail, it means that those with equal talents to the failing white coaches are not even getting the chance to be a coach. Seeing African-American coaches fail means that they, like white coaches, no longer have to be superstars to get coaching jobs.

We should absolutely celebrate when we see superstars in any field who are women, Black, transgender, etc. Representation matters. But we should be even happier when we see fields full of mediocre women and other underrepresented folks, because that is a true indicator of equal opportunity.

I hope Ng succeeds, but in a weird way, I’ll be just as happy if she’s mediocre.

Misogyny and the Curious Case of Ada Lovelace

In honor of International Women’s Day, I’d like to honor two women, and I’d like to share a strange story about misogyny. The first is Ada Lovelace, the remarkable daughter of Lord Byron, who published the very first computer program in 1843. Because I have many friends and colleagues in technology, I often see Ada’s name crop up in various social media channels on this day. I also occasionally get surprised emails from friends, who start reading about her work, see references to some guy named, “Eugene Eric Kim,” and wonder if that person could possibly be me.

Yup, it’s me. In 1999, I co-authored a piece about Ada in Scientific American with the brilliant Betty Alexandra Toole, who is the second person I’d like to honor. I am exceptionally proud of the piece, because Betty and I cleared up several myths about Ada there. I also found a bug in Ada’s program, and am the first person to have identified and published it, 156 years after the fact!

I studied history of science in college, and while I was primarily interested in understanding scientific revolutions, I was irresistably drawn to the history of computers and computer science. Shortly after graduating, I came across Betty’s extensive and definitive scholarship on Ada and emailed her about it. Betty was warm and delightful, and it turned out she was friends with my colleague, the inimitable Michael Swaine, and his partner, Nancy Groth, and that she lived in the Bay Area. We became friends, and we talked often about her work.

One of the curious things I learned about Betty was how many people seemed to want to discredit Ada’s contributions to computer science. I found it interesting and weird, but I didn’t delve too much into it myself. I more or less trusted Betty’s scholarship, but I still reserved the right to be skeptical myself. If other historians were discounting Ada’s contributions, there was probably a reason for it, right?

Then, in 1998, Betty forced me to confront my skepticism. She wanted to write a popular article about Ada’s work, and she asked me if I would co-author it with her. I said I would, but that I needed to look at the data myself before I could do it with her. Betty not only agreed, this was her plan all along. She had copies of Ada’s original notes, and she knew that I could understand the technical parts.

So I spent a few months carefully reading through Ada’s notes, double-checking her math, and also reading the scholarly work that disputed her contributions. I concluded that those claims were baseless.

Ada first met Charles Babbage (the inventor of the first computer) when she was 17. She published the first computer program when she was 27. I was 23 when I first read her notes, so I tried to remember what I was like when I first started learning algebra, then I tried to adjust my expectations based on the state of education at the time. All of that was largely unnecessary. Ada was a competent mathematician and a skillful learner. At minimum, she would have been in the same advanced classes as me in high school, and she likely would have been ahead of me. Moreover, she would have argued with me often and put me in my place. She was clearly proud, independent, and stubborn.

But she wasn’t a mathematical prodigy, either, or a technical genius like Babbage. Her genius was in recognizing the brilliance and potential of Babbage’s invention, not just from a pie-in-the-sky perspective (Babbage himself was skilled in spinning yarns), but from a down-and-dirty, here’s-how-it-actually-works perspective. She was both a visionary and a hacker, a century ahead of her time.

Here’s what Betty and I wrote in our article:

We cannot know for certain the extent to which Babbage helped Ada on the Bernoulli numbers program. She was certainly capable of writing the program herself given the proper formula; this is clear from her depth of understanding regarding the process of programming and from her improvements on Babbage’s programming notation. Additionally, letters between Babbage and Ada at the time seem to indicate that Babbage’s contributions were limited to the mathematical formula and that Ada created the program herself. While she was working on the program, Ada wrote to Babbage, “I have worked incessantly, & most successfully, all day. You will admire the Table & Diagram extremely. They have been made out with extreme care, & all the indices most minutely & scrupulously attended to.”

The importance of Ada’s choosing to write this program cannot be overstated. Babbage had written several small programs for the Analytical Engine in his notebook in 1836 and 1837, but none of them approached the complexity of the Bernoulli numbers program. Because of her earlier tutelage, Ada was at least familiar with the numbers’ properties. It is possible that Ada recognized that a Bernoulli numbers program would nicely demonstrate some of the Analytical Engine’s key features, such as conditional branching. Also, because Menabrea had alluded to the Bernoulli numbers in his article, Ada’s program tied in nicely with her translation of Menabrea.

What strikes me, almost 20 years after I wrote that article with Betty, is how often people continue to question Ada’s contributions. Why would they do so? The scholarship is actually not extensive. Only a few historians have actually looked at the source material, and the same ones (including Betty and me) are cited over and over again. There is no smoking gun suggesting she is not responsible for her own work, and the evidence in her favor is considerable. Why is there any doubt? More importantly, why is the doubt so often propagated?

I have two hypotheses. The first is that people are lazy. Most people never bother looking at the historical pieces, such as the one I cowrote with Betty, much less the source material.

Second, most people are biased (consciously or not) against women. If Ada had been a man, and if the historical record were exactly the same, I have no doubt that far fewer people would be questioning Ada’s contributions. Remember, I fell into this category too. When Betty first told me about the controversy, even though I trusted her, I assumed the source data would be far less conclusive than it was. Truthfully, if I weren’t already friends with Betty, I probably would have just assumed that the skeptics were correct.

Betty, of course, understood all of this far more viscerally than I did. We talked about this extensively back then, and while I thought I understood, my understanding is far more deep and nuanced today. I know that my mere presence on the byline of the article we co-wrote (and that Betty deserves far more credit for) automatically boosted the credibility of our work, and that this had nothing to do with my reputation in the field (which was and deservedly continues to be non-existent).

It’s sobering, but I think there’s something heartening about these current times, despite all of the very real challenges we continue to face. People are far more conscious about unconscious bias — whether it’s about gender, race, sexuality, height, weight, age, fashion, whatever — than ever before. If we can acknowledge it, we can also do something about it.

So here’s to Ada Lovelace, badass and worthy hero to women and men everywhere! And here’s to my friend, Betty Alexandra Toole! Happy International Women’s Day!

Gender Breakdown of my Twitter Stats

I just read Anil Dash’s excellent, thought-provoking piece, “The Year I Didn’t Retweet Men,” and it made me curious about my own Twitter behavior.

I used the tool that Anil mentioned, Twee-Q, and it reported that 83% of my retweets are of men. I was stunned to see that number, so I decided to investigate further.

First, I checked the gender breakdowns of whom I follow. Followerwonk reported 22% female, but also 33% undetermined. I only follow 191 people on Twitter, so I decided to do my own count. I first eliminated group accounts and bots, unless I knew there was a single person behind the group account, as with @WiserEarth (female) or @wikistrategies (male). That brought my following number down to 172.

Of the individual accounts I follow, 62% are male, 38% are female. This is better than what Followerwonk reported, but still not 50-50.

Also, based on this breakdown, I was still disproportionately amplifying the voices of men. However, I didn’t trust the 83% number. First, I didn’t trust that Twee-Q was accurately determining which voices were of which gender, especially given the discrepancy I saw with my Followerwonk numbers. Second, I didn’t think retweets alone were an accurate representation. I sometimes added my own commentary and used a citation rather than a retweet.

I decided to manually count all of my retweets and citations (not counting conversation, only amplification) in 2014. I’m not a prolific tweeter, so this was easily doable.

In 2014 so far, 74% of my retweets and 60% of my citations have been of men. In other words, 66% (two-thirds) of my retweets and citations are of men. The gender breakdown of whom I cite roughly maps to the breakdown of whom I follow, but I definitely retweet more men.

My initial reaction to these numbers was surprise, then rationalization. I won’t bother going into either — I don’t think they’re particularly important. The reality is that there are some well-documented implicit biases in society, and I’m statistically likely to suffer from all of them, no matter how enlightened I think I am.

The true measure of enlightenment is what you do with that self-awareness. I thought Anil’s metrics were interesting, but his followup experiment was inspiring. I’d like to try a similar experiment as a followup; I’m just not sure what that experiment should be. Any ideas?