At Q42 I initiated Project <div>, a series of open letters about and internal push to improve diversity & inclusion at the company. While doing so I began to gather anything I read online that could help. The below list includes articles I read, videos I watched and data I found that I could use to explain why transitioning from a homogeneous culture to one with more diversity and a focus on inclusivity over being an exclusive club would be rewarding. I also included my notes and excerpts where relevant.
Disclaimer: this list is by no means exhaustive and quite ad hoc, as I was just jotting things down as I came across them. However, feel free to reuse anything and let me know if you find something wrong or have any recommendations.
What large tech companies are doing
Some of the major tech companies have started publishing transparency reports about the diversity of their employees, which in turn may inspire others to make diversity & inclusion a priority. At Google, Apple, Facebook, etc. the number of women in technical roles is quite low, around 20%, so they face a similar challenge.
Both Google and Facebook are addressing the problem in multiple areas. One area they’ve both decided is a good starting point is in combating unconscious bias. Here are sites they’ve created that discuss their approach:
They also publish figures:
Spotify tried hosting a hackathon with 50/50 female and male participants: “We wanted to expand outside our Facebook hacker groups. So we talked to university teachers, local communities, brothers, sisters, cousins and friends from other cities to push the event outside the usual “tech bubble”.”
One useful metaphor to use when talking to engineers about this is to think about it as “diversity debt” as described by 500 Startups’ partner, Andrea Barrica. Like dealing with technical debt, it’s a matter of deciding to pay attention to it and then refactoring, in this case, the company culture and attitudes towards the issue. It also becomes harder to fix the longer you wait: as the company grows, and if you don’t address this, you’ll end up hiring the default applicant (white male). Once you have over 100 employees it will become increasingly improbable that you’ll be able to rebalance without a Herculean effort.
- Unlocking the Clubhouse
- Lean In
- Everyday Sexism
- The Confidence Code
- Gender Codes
- We Should All Be Feminists
- Recoding Gender
- Quiet: The power of introverts in a world that can’t stop talking
- Model View Culture Quarterly
- Mentoring and Diversity: an international perspective
- Programmed Inequality
- Being a Man in the Workplace (BuzzFeed)
- OPPRESSED MAJORITY
- Tim Cook on why he came out
- Unconscious bias at work (Google)
- Louis CK: Explaining the Meaning of Being White
- Making the unconscious conscious (Google)
- Doll Test
- We should all be feminists
- Everyday Sexism
- The danger of a single story
- Inclusion, Exclusion, Illusion and Collusion
- Cultural Differences in Business
- The Paradox of Diversity
- Why do ambitious women have flat heads?
- Did you hear the one about the Iranian-American?
- Model View Culture’s Resources
- Geek Feminism Wiki
- Map of Women in Tech communities around the world
- 50 Best Workplaces for Diversity 2016
- Gendered Language in Teacher Reviews
- Science faculty’s subtle gender biases favor male students (PDF)
- Project Implicit
- Implicit Association Test (Gender)
- Bias Cleanse
- How unconscious bias affects everything you do
- 4 Ways to Recruit Girls to Try Computer Science
- You’re more biased than you think
- Exposing hidden bias at Google
- Unconscious Bias at Work
- Google ReWork Unbiasing
- The Tech Diversity Blind Spot
Events & conferences
Organisations working on diversity & inclusion
- Hire More Women In Tech — long list of resources, best practices, exec summaries, facts
- Social rules at Recurse (formerly Hacker School)
- Forms of Gender
Reports & papers
- Debunking Handbook
- Women in the Workplace 2015
- Images of Computer Science Report
- The Big Lie: Tech Companies and Diversity Hiring
- Feminist Frequency Feminism in the Workplace 101
- Some garbage I used to believe about equality
- How our engineering environments are killing diversity
- Diversity Debt
- Look for the best person for the job (creator of Gone Home)
- How to Develop a Diverse Workforce
- Lieke’s Girls in Tech talk on Unconscious Bias at Girl Code
- Gender stereotypes persist across the world
- How elementary school teachers’ biases can discourage girls from math and science
- Gender and tenure diversity in GitHub teams
- Hermione Granger and the Goddamn Patriarchy
- On nerd entitlement
- How to Start a Women’s Group When Nobody Cares
- I am Alex St. John’s Daughter, and He is Wrong About Women in Tech
- What Do Women Want At Hackathons? NASA Has A List
- Film Dialogue from 2,000 screenplays, Broken Down by Gender and Age
- Uncanny Valley
- Introducing Project Include
- For Female Astronomers, Sexual Harassment Is a Constant Nightmare
- Is everybody a racist?
- I Am A Transwoman. I Am In The Closet. I Am Not Coming Out.
- Diversity in Tech FAQ v0.1 (by Github’s Nicole Sanchez)
- Women, leadership and the myth of merit
- Ageism in Tech: The Industry’s Biggest Secret
- Computers are for Girls, too (Melinda Gates)
- Harvey Mudd College took on gender bias and now more than half its computer-science majors are women
- A new study shows how Star Trek jokes and geek culture make women feel unwelcome in computer science
- Diversity in tech too often means ‘hiring white women.’ We need to move beyond that. (Atlassian/Aubrey Blanche)
- Some garbage I used to believe about equality
- Why Are There More Women in CS in Other Cultures?
- How Lever Got To 50–50 Women and Men
- The Loneliness of the Female Coder
- Study on quotas: Gender quotas and the crisis of the mediocre man
- A Woman’s Day
- Meet the Badass Women of Google’s Security Team
- Google Proves That TV Teaches Girls to Not Like Computer Science
- Grace Hopper Academy
- Women write better code, study suggests
- Diversity Policies Rarely Make Companies Fairer, and They Feel Threatening to White Men
- If you think women in tech is just a pipeline problem, you haven’t been paying attention
- Reading the Mind in the Eyes Test
- The Athena Factor: Reversing the Brain Drain in Science, Engineering, and Technology
- Women in the Workplace
- Diversity in Tech Companies WSJ graphic
- Women in the Workplace WSJ interactive presentation
- “Facebook Inc. and Pinterest Inc. have tried out an approach known as the Rooney Rule, which requires that at least one woman or underrepresented minority be interviewed for open jobs.“ https://en.wikipedia.org/wiki/Rooney_Rule
- What’s Holding Back Women in Tech
- Dispelling some myths about the autistic wunderkind programmer
“Cisco is ensuring that job candidates encounter at least one interviewer of their same gender or ethnicity, a practice that has resulted in a roughly 50% increase in the odds a woman will be hired for a given position” —What’s Holding Back Women in Tech?
“You certainly need some senior people and to be fair, most of the senior people on our team are male. But here’s the thing about positive feedback loops, they create self-perpetuating cycles. The men on the team have the experience and track record to be the best person for the job, because we’ve been given the chance to prove ourselves.” — Don’t Look for the Best Person for the Job
“For all the talk about how important diversity is within organizations, white and male executives aren’t rewarded, career-wise, for engaging in diversity-valuing behavior, and nonwhite and female executives actually get punished for it.” — Study Shows Women and Minorities are Punished for Speaking Up
“Research shows that individuals and organizations that believe they are meritocratic often have the poorest outcomes. That’s because when biases aren’t acknowledged, we can’t deal with them.” — Managing Bias
When Women Stopped Coding
(Similar graphs are featured in the book Unlocking the Clubhouse)
100 Women 2015: How can we stop unconscious bias?
This is useful for starting an informal unconscious bias chat with coworkers.
When sorted by explicit bias, Netherlands ranks worst (and % of majors & researchers is relatively low):
UNESCO Distribution of tertiary graduates by field of study
UNESCO source as referenced by noceilings.org
CBS: Just 30% of technically trained women in NL still working in tech
CBS source (Dutch)
Ministry of Economic Affairs: Diversity in NL IT market
From ICT, Kennis en economie 2016, bijlage 2.2.1a, “werkzame ICT’ers naar achtergrondkenmerken” (Dutch)
McKinsey report on Why Diversity Matters
From the article:
Women in selected STEM occupations, 1990–2013
Diversity Programs That Get Results
Do Europeans Fear Diversity?
From a report by Pew Research on how European countries feel about whether diversity would make the country a better place to live or not.
Girls and women under-represented in ICT
From a study by eurostat with Netherlands coming in last among students (and Belgium second), though the difference is smaller when measured among those employed in IT jobs:
- Occupational Feminization and Pay: Assessing Causal Dynamics Using 1950–2000 U.S. Census Data
- UNESCO Distribution of tertiary graduates by field of study
- Global Gender-Science Stereotypes
- Does diversity-valuing behavior result in diminished performance ratings for nonwhite and female leaders?
- http://noceilings.org/ & http://noceilings.org/stem/
- Github repo full of data: Where are the numbers?
- Massive Google doc full of data: Why women leave tech: what the research says
- Gender differences and bias in open source: Pull request acceptance of women versus men
- Athena’s Angels
- Percentage of women educated at a technical institute in the Netherlands employed in a technical position is under 30% — CBS
- Sexy, Strong, and Secondary: A Content Analysis of Female Characters in Video Games across 31 Years (not really relevant, but awesome research)
- Elephant in the Valley — “We focused on five main areas including: Feedback & Promotion, Inclusion, Unconscious biases, Motherhood, and Harassment & Safety. We asked 200+ women focusing on women with at least 10 years of experience.”
- Solving the Equation: The Variables for Women’s Success in Engineering and Computing — Research paper with tons of data and significant conclusions. See page 104 for how organisations can act.
- How stereotypes impair women’s careers in science: “We show that implicit stereotypes (as measured by the Implicit Association Test) predict not only the initial bias in beliefs but also the suboptimal updating of gender-related expectations when performance-related information comes from the subjects themselves.”
- Taulbee Survey — Chart based on data about gender
From Solving the Equation: The Variables for Women’s Success in Engineering and Computing (page 104):
Maintain good management practices that are fair and consistent and that support a healthy work environment
- Communicate clear responsibilities, goals, and paths toward advancement.
- Assign employees challenging projects that help them develop and strengthen new skills.
- Provide training and development opportunities for employees.
- Acknowledge and reward employees’ contributions.
- Ensure that employees have manageable workloads and are not expected to routinely work excessive hours.
- Provide and encourage the use of work-life balance support such as on-site daycare, flexible work schedules, paid parental leave, and telecommuting.
- Provide opportunities for senior technical workers to mentor students or junior-level technical workers.
- Put in place anti-harassment policies such as that instituted by the Ada Initiative, adainitiative.org/what-we-do/conference-policies.
- Work to establish welcoming environments through inclusive workplace policies.
Manage and promote diversity and affirmative action policies
- Ensure that job advertisements, mission statements, and internal communications explicitly convey that your organization values diversity and gender inclusiveness.
- Assign responsibility for diversity to a diversity committee or full-time diversity staff.
- Involve men, especially white men, in gender diversity efforts.
- Conduct effective diversity training for employees.
- Monitor your progress in increasing women’s representation in technical roles.
Reduce the negative effects of gender bias
- Make job qualifications clear and apply them evenly to all candidates.
- Base hiring decisions on objective past performance information when possible.
- Purposely remove gender information from evaluation scenarios when possible.
- Allow sufficient time to make in-depth and individualized evaluations of applicants.
- Ensure that hiring managers and other employees are aware of their own potential gender biases, such as by taking the gender-science Implicit Association Test at implicit.harvard.edu.
- Survey employees to assess the level of gender bias within your organization.
- Hold managers and recruiters accountable for their hiring and promotion decisions.
Encourage a sense of belonging
- Create a welcoming environment for all employees.
- Encourage a supportive, friendly, and respectful environment.
- Root out uncivil and undermining behaviors.
- Increase the number of women at all levels of management.
- Provide opportunities for women to develop a support network of other technical women.
- Formally recognize necessary nontechnical work such as working well with others and mentoring — work that is not male-stereotyped — along with technical work.
- Be proactive and vocal about management’s commitment to increasing the representation of technical women in your organization.
Facilitate opportunities for employees to work on projects or issues that are socially relevant
- Pursue projects with clear social impacts whenever possible.
- Showcase how professionals’ everyday work aligns with the societally beneficial outcomes that are the ultimate goals of engineering and technology.
- Establish social service days where employees volunteer in their communities.
Harvard Business Review on diversity
“Firms have long relied on diversity training to reduce bias on the job, hiring tests and performance ratings to limit it in recruitment and promotions […] Yet laboratory studies show that this kind of force-feeding can activate bias rather than stamp it out. As social scientists have found, people often rebel against rules to assert their autonomy. Try to coerce me to do X, Y, or Z, and I’ll do the opposite just to prove that I’m my own person.” […] It’s more effective to engage managers in solving the problem, increase their on-the-job contact with female and minority workers, and promote social accountability — the desire to look fair-minded. That’s why interventions such as targeted college recruitment, mentoring programs, self-managed teams, and task forces have boosted diversity in businesses. Some of the most effective solutions aren’t even designed with diversity in mind.