I love writing code. I love problem solving and the shape of ideas. I love it when the pieces fall into place in my head with an almost physical gratification. I believe I am good at programming because I am good at language… when I write code, I just define something, and name it, which creates it. Code is art, or simply craft.

I don’t believe I am good at coding because I am a woman, or in spite of it. I refuse learn how to be a woman programmer.

Every unique part of me influences the code that I write. I bring all of my experience and none of it. Sometimes the code I write benefits from my experience and sometimes I need to open my mind to the discovery of the unknown.

I am a programmer. I am a woman. These are two independent facts.

On April 9, 2013, we celebrated the Equal Pay Act of 1963.
This day marks how far in 2013 women must work to earn what men earned in 2012.
That is APRIL 9th, over three months into the year.
Women in the United States are paid on average 77 cents for every dollar paid to men [1].
Women currently hold 4 percent of Fortune 500 CEO positions and in the Fortune 1000, a whopping 4.5 percent of CEO positions are held by women [2].

Boys in elementary and middle school call out answers eight times more often than girls. When boys call out, teachers listen. But when girls call out, they are told to “raise your hand if you want to speak.” [3]

In the supposed meritocracy of open source, where volunteer work determines the future of critical infrastructure software only 3% of contributors are women. [4]
But if we look at the PTA and not-for-profit volunteers, that work is dominated by women, these do-gooders who hold no real power.

Nearly 60% of all young women have experienced abuse [5] and 30% of adult women report having been in an abusive relationship [6].
Girls are called sluts and boys are just having fun [7].

They say women are disempowered in our society, and yet…

Women are responsible for 85 cents of every dollar spent in the United States [8].
Comscore, Nielsen, MediaMetrix and Quantcast studies all show women are the driving force of the most important net trend of the decade, the social web.
You know more women use Facebook, but did you know that more women use Twitter, tweet more and have more followers than men? [9]

Senior women age 50 and older control net worth of $19 trillion and own more than three-fourths of the nation’s financial wealth [10].
Women have been starting businesses at a higher rate than men for the last 20 years [11].
Nearly 104 million businesses are majority owned by women. They provide 12 million jobs and generate more than a trillion dollars in sales. [12].

Women make 80 percent of health care decisions for their families. [13]

They say women are disempowered in our society.

Are we?

Certainly, if a company interviews only men for a specific position, then there is no possibility that they will hire a woman for that spot. I spoke about this in an NPR interview and was delighted to read a tweet that led me to learn about the Rooney Rule (via @randomsumu).

The Rooney Rule requires National Football League teams to interview minority candidates for head coaching and senior football operation jobs. During the league’s early years in the 1920s, Fritz Pollard coached several NFL teams. But after that there were no minority coaches until 1979!

The rule ensures that minority coaches, especially African Americans, are considered for high-level coaching positions. The rule is named for Dan Rooney, the owner of the Pittsburgh Steelers and the chairman of the league’s diversity committee, and indirectly the Rooney family in general, due to the Steelers’ long history of giving African Americans opportunities to serve in team leadership roles. In 2006, the percentage of African American coaches was 22%, up from 6% prior to the Rooney Rule. (via Wikipedia)

In 2010, there were 913,100 software developers. If 20% are women, that means there are over 180,000 women in the country who might fill your next position. Ok, maybe you are in a niche market, but there are thousands or tens of thousands of qualified candidates who happen to be women. Find one of them to interview.

And while you are at it, think about your hiring criteria — what is really important for success? are you filtering for that? Go find at least one person to interview who is qualified, but is also different from you. You might actually find a better candidate than those who you are currently talking to.

Background: Minecraft is a very popular world-building game. They announced last November that they will release an API, but they have a friendly attitude toward users who have reverse-engineered how to create “mods” (extensions to the game and changes to the behavior of objects in the world). Minecraft Forge is the de-facto standard API toolkit for making mods.

We found that the easiest way to run a server is to run it locally on an old MacBook, allowing external connections to connect to a noip domain and tunnel into our home network.

Prerequisites:We’re running Mac OSX SnowLeopard. We need Java and the JDK, 1.6 or better.

Check that java is installed

$ java -version
java version "1.6.0_37"

Check that the JDK is installed

$ javac -version
javac 1.6.0_37

We installed 64-bit version of Eclipse.

Other than those platform-specific details that I had to look up, we had no problem following the basic modding tutorial. The mod doesn’t do anything yet, but we can run minecraft and see it load:

Along with games from Disney Interactive, DoubleFine and ZeptoLab, Leap Motion has announced that Corel’s Painter apps and 3D software from Autodesk will support the device.  In the interview, I talk about an application for this device that would have broad consumer appeal.  Combined with a 3D printer, either in the home or as a service, we can imagine preparing for a celebration by sitting down at a “virtual potting wheel” and creating a vase for your parents’ anniversary party or teacups for your kid’s birthday, then you could choose a photo or drawing to decorate the object.  You can already upload these virtual 3D objects to printing services which will ship them to you — you may even spend less than you would on other party favors and entertainments.

But once upon a time, I was like most folk. I thought that computer programmers had boring jobs where they typed in numbers into dead machines. So, anytime someone asks… I mean, when they really want to know… I take time to tell them what it is really like, at least what it is like for me. Because there’s no way you can really know till you do it, if you are one of those people who would want to sink into this alternate reality and make magic happen.

I just got this letter in the mail yesterday. I have no words to express how much this means to me…

The letter actually came in a package. I have 9 more letters to deliver to my former colleagues. I’m going to enjoy hunting them down — I think I am only in touch with two of them. If you know them, if you are them, let me know:

• Bruce Hunt – got address
• Andy Rose – sent
• Tim Wilson – got address
• David Spells – sent
• Steve Pasos – connected!
• Matt Bendiksen – got address
• David Gangwish
• Loius LaSalle – connected!
• Heather Rose

I must have been working on Shockwave at the time, Bruce Hunt was Director of Engineering and Heather Rose was the Product Manager, but I must have sent the email to a wider list. There was some list, I can’t remember the name of, where we could send random, company-wide emails, or maybe it was just the Director team and friends. Who remembers?

He references a historical visualization that was new to me. In 1858, Florence Nightengale’s visualization of cause of death in the Crimean War told a compelling story of the how the real enemies were cholera, typhus, and dysentery:

Edward Tufte highlights a similar story about Napoleon’s disastrous invasion of Russia in 1812, which maps the size of his army over space, time, and temperature:

I agree that visualization today is more an art than a science, but I believe it will always be so. Visualization is editorial. What we choose to highlight with shape, color and annotation tells the story. Our ability to collect data has far outpaced our ability to process and analyze that data. I believe there are many answers to urgent questions that lie dormant on personal hard drives and cloud storage.

I’ve been spending time with d3js, which is a fabulous, modern visualization framework. For now, it provides flexibility for rather sophisticated programmers; however, it is my hope that the tools will emerge that will allow any person with critical thinking skills to ask questions and tell stories by pouring data into images.

Here are some modern examples (with code!):

Small Multiples: stock prices over time, nested by symbol

Multiple Area Charts: an infographic with multiple area charts along with a context tool to zoom and pan the data.

Lots more examples in the d3js gallery.

Relative to the population, the number of tech creators is small. We could solve the gender imbalance by finding more of the women who can fit into the specific tech culture that emerged in the last century or we can welcome all types of individuals allowing for a diversity of approach, personality, culture, and background, and then we can filter only for ability to effectively do the work. From reading popular media, one would think that the latter approach is rare or non-existent, but my experience proves otherwise. At the recent Lean Startup Conference, I saw this approach in action, and I was inspired to share this pattern that is also having a deep effect at RailsBridge, and at my own company, Blazing Cloud.

Lean Startup Conference

I went to the first lean startup conference, “Startup Lessons Learned,” in 2010. I was impressed at how Eric Ries had transformed a loose collection of ideas into a movement. I was starting to think about how I could spread the word about the good work that was happening at RailsBridge, so I approached Eric at the end of the event to ask his advice. He was open and gave me some practical tips and encouragement for hard work involved behind the scenes, and then he asked “Are you the Sarah who gave that talk?” He was asking about Sarah Mei’s talk Moving the Needle: How SFRuby got to 18%. He shared with me about he struggled with this issue in his own community — women were as poorly represented in tech startup founder groups as in open source software. He said that used our example to challenge his colleagues: “if something as geeky as the San Francisco Ruby Meetup can get to 18%, why can’t we?”

At this year’s Lean Startup conference,about one third of the speakers were women and there were a few people of color, but that superficial diversity was less significant than the range of experience represented. Over the past year, I saw Eric go through a few iterations of CFPs seeking talk proposals from a diverse audience. I was impressed by how he defined diversity. They were not simply seeking people who looked different from each other to decorate the stage, but sought to surface all of the ways that Lean Startup methodologies were being applied in diverse organizations to diverse challenges.

The day provided an existence proof: you can do lean startup anywhere. We heard from Todd Park, the CTO of the United States, talk about how he successfully applies lean startup techniques to get parts of the US government to act like a startup, and from Beth Comstock, SVP at GE, who works to give small groups the opportunity to experiment and fail, in order to innovate. There were stories from small and large companies, from consulting to product, and from hardware and mobile, from design and code. For every situation where it was hard to imagine that Lean Startup techniques could possibly work, there was a speaker who talked about how they made it happen, often sharing their painful failures along the way. If they can do it, why can’t we?

RailsBridge and SFRuby Meetup

At RailsBridge workshops, most events are targeted at women, but we welcome men to help as volunteers or join as the +1 of another woman student. We’ve define a safe space for learning. Of necessity, we teach communication skills and conflict resolution along with the code. We have created a culture where people respect each other, people teach what they know, and every failure is simply one of the many things we haven’t gotten right yet. RailsBridge has many projects, but the workshops have been most successful, spreading to at least 14 cities all over the world, with hundreds of volunteers and thousands of participants. I often see its effects first-hand, here in San Francisco, where we started.

I recently attended a SFRuby Meetup, sponsored by Social Chorus. Sandi Metz spoke about object-oriented design. There were 10-20% women in the audience, but more importantly, there were men and women with deep experience in software patterns and people who had just started to learn, and all levels in between. This diversity of experience led to a wide range of engaging questions from the audience. You couldn’t tell someone’s background by looking at them. Most of the women and some of the men were there because they were first introduced to the Ruby programming language and to this community through RailsBridge. The RailsBridge outreach workshops in SF were designed to create gender diversity, but caused the happy side-effect of creating a group that is more welcoming of new people and includes people of different levels of experience and background.

Blazing Cloud

At Blazing Cloud, I sought to create the place I wanted to work, with people who care about making great software, people with good communication skills and a passion for learning. I wanted to work with interesting people who challenged me, who could also learn from. There are 50% women, but also diversity of age and interest and culture.

When looking for software developers, I didn’t try to hire Javascript developers or iOS developers, I looked for smart people where I had evidence that they could solve problems by writing code. I also hired people who solve problems by creating images or writing words or making spreadsheets. So we ended up with people from several agile (and non-agile) cultures, various educational backgrounds, and different levels of skills and experience. We had different practices, sometimes with similar names, and we found we needed to establish our own unique processes, create ways for them to evolve, and teach each other what we know. We struggle through our differences, but when we need apply new tech, chances are someone on the team already has knows how. More often new technologies burst forth as proposed solutions to new problems. I have discovered that our diversity doesn’t just make it a fun and engaging place to work, it actually increases our effectiveness, our creativity, and therefore our ability to deliver great software to our clients.

Diversity Paves the Way for Excellence

Diversity increases creativity and resilience of a team because it allows the team to draw from a wide range of experience and apply different kinds problem-solving skills and communication skills. If every individual on a team can work with people of different cultures and different skill sets, then the team will work together better and be able to adapt to more challenging situations.

If we can look at a team or a group and everyone looks alike, that is likely to be a symptom of a deeper problem. Homogeneous teams are often fragile. Our world is changing. We need to change to adapt. If we’re used to adapting to different kinds of people that we work with every day, it is much easier to adapt to change from any direction. Especially in tech, we need everyone to participate, so that we can come up with solutions that work for the very real and urgent problems in our world today.

R is a free implementation of a dialect of the S language, the statistics and graphics environment for which John Chambers won the ACM Software Systems award. S was consciously designed to blur the distinction between users and programmers. S is a high-level programming language, with similarities to Scheme and Python. It is a good system for rapid development of statistical applications.
— R fundamentals

R has amazing built-in primitives and libraries for what scientists like to do with data and incredible graphing options. I struggled to find good, simple resources to approach learning R as a programmer. I loved this tutorial. Here are my cliff notes:

The most fundamental objects are vectors — basically an array, where index starts at 1.
Names of objects are case sensitive
Comments starts with ‘#’

Examples:

n <- 25
v1 <- c(2,5,1,9)        # create a vector, combine a list of columns
v2 <- numeric(4)        # initialize a vector of specific length (with zeros)
v3 <- rep(3, 10)        # initialize a vector with number: repeat 3, 10x
v4 <- 1:4                  # specify a vector using the range 1-4
v4 <- 4:1                  # you can count down, 4,3,2,1
v4 <- 3:-1                 # even to negative numbers: 3,2,1,0,-1
v4 <- seq(1, 1.5, by=.1)   # easy to generate a sequence of equality spaced non-integers
v5 <- c(v3, v4, 7)        # c will combine or concatenate vectors

v2[1] <- 4         # use bracket notation to access (or set) an element
v2[1:3] <- 4:6     # you can even access (or set) a range

For those of us who already know it from Math class (or computer graphics), vector math in R works the way you would expect:

• when an operation involves a vector and a number, the number is used to modify each element of the vector as specified by the operation
• when arithmetic involves two vectors of the same length, then the operation applies to elements with the same index.

Adding vectors of different length doesn’t really make sense in real life (although maybe there’s an application for that I don’t know about), but R conveniently defines that the shorter vector is repeated as often a needed to match the length of the longer vector.

Like many languages, and more importantly, like Math, functions are a name with its arguments enclosed in parentheses.  Here are some common ones:

max(v1)
mean(v1)
sum(v1)
prod(v1)
length(v1)
unique(v1)

By using parentheses for grouping, one can combine several expressions that involve
functions.

(sum(v2^2) - (sum(v2)^2)/length(v2)) / (length(v2) - 1)

A simpler way to get the same result would be to use the var function.

var(v2)

The standard deviation is computed by using the expression sqrt(var(v2))

Comparisons are cool.

> 1 < 2
[1] TRUE
> 1:2 < 2:1
[1]  TRUE FALSE
> v6 <- c(4,5,2,1,9)
> v6[v6 < 3]    # find all elements in a vector which are < 3
[1] 2 1
> length(v6[v6 < 3])    # count how many are < 3
[1] 2