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In this multi-part series, I'll be exploring different aspects of learning computer science and software development that negatively affect the diversity of the industry as a whole. First, I'll spend some time describing the issue, followed by a discussion of different views of how we might go about solving the problem, and finally I'll suggest practical ideas to start moving in the right direction.

The Problem

The demand for software developers is exploding, and it has been for some time. In the 2012 Occupational Outlook Handbook, the Bureau of Labor Statistics recorded over a million jobs in software development alone, with an expected growth of 22 percent by the year 2022—most occupations are expected to grow by only eight percent in this same period. It is a lucrative field, with a median salary just above $90,000 per year.

Research by the company CareerCast consistently ranks ‘software engineer’ among the top ten careers for job satisfaction in their annual Jobs Rated report, which takes environment, income, outlook and stress into consideration. Employers in the tech industry tend to be innovative, flexible, and generous (imagine Google's well manicured gardens, nap pods, and gourmet chefs). Many developers skip traditional employment altogether: plant yourself anywhere in the world and remotely serve a vast array of clients as a freelance developer. The best part is, in most cases, you do not necessarily need a tech degree. Generally, the industry places value on what you are able to do, not where or how you learned how to do it. It's a dream.

Learn just enough to get an entry-level job, and your career may forever be changed. Take as long as you need to learn the skills, keeping whatever pace suits you, and use whatever resources you like best (there are too many to count). Soon enough you will be living in that dream.

So what is stopping you? What is stopping so many people? This promising career forecast ought to attract a variety of people from every sort of background, and the demographics of the industry should reflect that. However, despite the promises of a lucrative career, there remains a big problem. Software engineers, whether aspiring or professional, all sort of look the same: mostly men, mostly white.

Nearly halfway through 2014, the leaders of the tech world began disclosing the diversity of their workforce. “We’re not where we want to be when it comes to diversity,” writes Google on their new Diversity webpage, “And it is hard to address these kinds of challenges if you’re not prepared to discuss them openly, and with the facts”. The fact is that their company is 70 percent male, globally, and 61 percent white within the United States. Asians make up another 30 percent with all other ethnicities comprising just nine percent. When you look at the people working strictly in technical divisions, the gender demographic shifts for the worse: 83 percent are men.

These statistics are nearly identical at places like Twitter, Facebook, Apple, and Microsoft and only look worse within the leadership at these companies. Where does this problem come from? What is keeping a diverse crowd from entering a booming industry?

The problem is complex to be sure, but a particular facet of it may be somewhat simple, though seemingly hidden in plain sight: learning. More particularly, the views each of us have about our ability to learn. In her research, Carol S. Dweck, a professor of psychology at Stanford University, has identified a particular mindset that greatly inhibits not only the person it clings to, but all those it interacts with as well.

This fixed-mindset, which regards ability and skill as inherent and unchangeable, hinders the progression and development of a diverse workforce in software development. It does so by convincing us that looking smart is more important than deep learning, which entices us to believe that we cannot learn, leading, finally, to stereotypes that keep people avoiding software development and tech entirely—despite the promising future therein.

In the next post, I'll look further into the fixed-mindset, and see just how it effects our individual abilities to learn as well as our collective understanding of what it means to be smart.

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Drew Price



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