Open Source Bridge - Keynote - Programming Diversity

Open Source Bridge - Keynote - Programming Diversity

It's been scientifically proven that more diverse communities and workplaces create better products and the solutions to difficult problems are more complete and diverse themselves. Companies are struggling to find adequate talent. So why do we see so few women, people of color, and LGBTQ people at our events and on the about pages of our websites? Even more curiously, why do 60% of women leave the tech industry within 10 years? Why are fewer women choosing to pursue computer science and related degrees than ever before? Why have stories of active discouragement, dismissal, harassment, or worse become regular news?
In this talk we’ll examine the causes behind the lack of diversity in our communities, events, and workplaces. We’ll discuss what we can do as community members, event organizers, and co-workers to not only combat this problem, but to encourage positive change by contributing to an atmosphere of inclusivity.

Objectives:
Educate about the lack of diversity and why it is a problem
Examine what is contributing to both the pipeline issue as well as attrition
Isolate what is and isn't working
Inspire direct action by examining our own behavior and learning more about the people around us so we can empathize better

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Ashe Dryden

June 20, 2013
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Transcript

  1. @ashedryden Programming Diversity

  2. @ashedryden Ashe Dryden @ashedryden ashedryden.com

  3. @ashedryden What is Diversity?

  4. @ashedryden more than gender

  5. @ashedryden various backgrounds, experiences, and lifestyles

  6. @ashedryden not always visible

  7. @ashedryden race gender sexuality ability language appearance physical & mental

    health age socioeconomic class and more!
  8. @ashedryden Intersectionality the interactions of biological, social, and cultural traits

    contributing to systemic inequality
  9. @ashedryden race gender ability physical & mental health socioeconomic class

  10. @ashedryden in the US, women on average earn 80.9% of

    what men do Source: ABC: How to end the wage gap between men and women, http:/ /abcnews.go.com/ABC_Univision/News/women- make-men/story?id=18702478#.UZt3yitASqk
  11. @ashedryden but Latina women earn 59.3% of what white men

    do Source: ABC: How to end the wage gap between men and women, http:/ /abcnews.go.com/ABC_Univision/News/women- make-men/story?id=18702478#.UZt3yitASqk
  12. @ashedryden the unemployment rate in the US is ~7.5% Source:

    High Rate of Unemployment for the Blind, http:/ / work.chron.com/high-rate-unemployment-blind-14312.html
  13. @ashedryden the unemployment rate for the blind is 70-75% Source:

    High Rate of Unemployment for the Blind, http:/ / work.chron.com/high-rate-unemployment-blind-14312.html
  14. @ashedryden Privilege unearned advantages a person gets for a perceived

    trait they possess, putting them in the “normal” or “default” group
  15. @ashedryden Better Education Access to Technology at an Earlier Age

    Higher Pay Assumed Competency Quality of Social/Professional Network Seen as Skill Set Instead of Traits Easily Fit Into/Identify with Subculture
  16. @ashedryden Stereotype Threat anxiety or concern where a person has

    the potential to confirm a negative stereotype about their social group
  17. @ashedryden Source: xkcd, How it Works: http:/ /xkcd.com/385/

  18. @ashedryden Impostor Syndrome a psychological phenomenon in which people are

    unable to internalize their accomplishments
  19. @ashedryden this is especially pronounced when negative stereotypes exist about

    a group a person is in
  20. @ashedryden less likely to apply for certain jobs

  21. @ashedryden less likely to submit a talk to a conference

  22. @ashedryden less likely to attend to a conference

  23. @ashedryden Marginalized Someone pushed to the edge of a group

    and accorded lesser importance; a minority or sub- group being excluded, their needs or desires being ignored.
  24. @ashedryden society teaches us to do this to everyone within

    marginalized groups
  25. @ashedryden “I’m different. I’m logical and rational; I don’t see

    gender or race.”
  26. @ashedryden Source: Moss-Racusin, et al. Science faculty’s subtle gender biases

    favor male students, 2012 scientists & STEM professors do this to other scientists & STEM professors
  27. @ashedryden even marginalized people do it to people within their

    same social groups
  28. @ashedryden How diverse is the tech industry?

  29. @ashedryden Women make up 24% of the industry Source: FLOSSPOLS

    - Gender Integrated Report Findings
  30. @ashedryden ...but only 1.5-3% of OSS contributors Source: FLOSSPOLS -

    Gender Integrated Report Findings
  31. @ashedryden Source: Mercury News. Blacks, Latinos, and Women lose ground

    in tech companies, 2011 Women Hispanic Black Asian White 0% 25% 50% 75% 100% Tech Industry US Population Tech Industry vs US Population
  32. @ashedryden Lack of Diversity is a Global Problem

  33. @ashedryden India 8% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  34. @ashedryden US 17% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  35. @ashedryden UK 18.2% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  36. @ashedryden France 20% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  37. @ashedryden Brazil 20% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  38. @ashedryden South Africa 25% of CS students Source: Anita Borg

    Institute, State of Women in Technology Fields Around the World
  39. @ashedryden “Maybe women just aren’t interested in programming.”

  40. @ashedryden “Or maybe women aren’t biologically predisposed to programming.”

  41. @ashedryden no physical or biological difference

  42. @ashedryden purely social and cultural constructs

  43. @ashedryden Bulgaria 73% of CS students Source: Anita Borg Institute,

    State of Women in Technology Fields Around the World
  44. @ashedryden Diversity Matters

  45. @ashedryden Diversity Matters to businesses

  46. @ashedryden sales revenue, number of customers, market share, and profits

    relative to competitors increase Source: Does Diversity Pay?, Cedric Herring, AMERICAN SOCIOLOGICAL REVIEW, 2009, VOL. 74 (April:208–224)
  47. @ashedryden solve complex problems better and faster Source: Scott Page,

    The difference: How the power of diversity creates better groups, firms, schools, and societies. Princeton University Press, 2009
  48. @ashedryden more creative & stimulated through persistent exposure to minority

    perspectives Source: Charlan Jeanne Nemeth, Differential Contributions of Majority and Minority Influence.
  49. @ashedryden make better decisions, generate more innovation Source: Caroline Simard,

    Ph.D., Obstacles and Solutions for Underrepresented Minorities in Technology, at 8, Anita Borg Institute for Women and Technology (2009)
  50. @ashedryden financial success and viability of a company are directly

    related to the makeup of its teams
  51. @ashedryden Diversity Matters to society

  52. @ashedryden heal the issue of unequal pay and opportunity

  53. @ashedryden create class mobility

  54. @ashedryden the wage gap is smaller in STEM fields

  55. @ashedryden in tech women earn about 87% of what men

    do
  56. @ashedryden Why the lack of diversity?

  57. @ashedryden Pipeline

  58. @ashedryden Cultural Cues

  59. @ashedryden difference in toys and games for boys and girls

  60. @ashedryden no famous role models that represent them

  61. @ashedryden Access to Technology

  62. @ashedryden on average, men get access to their first computer

    at 11
  63. @ashedryden women get access to their first computer at 14

  64. @ashedryden lower computer ownership rates and broadband adoption

  65. @ashedryden adopting smart phones at a much higher rate

  66. @ashedryden Access to Quality Education

  67. @ashedryden what is the greatest indicator of earning potential?

  68. @ashedryden lower quality math and science programs

  69. @ashedryden Access to healthcare

  70. @ashedryden women are more likely to be caregivers

  71. @ashedryden less access to quality healthcare

  72. @ashedryden Attraction

  73. @ashedryden Lack of Role Models

  74. @ashedryden less likely to see people like them represented in

    companies and conferences
  75. @ashedryden Geek Stereotype

  76. @ashedryden people who don’t identify and aren’t represented by the

    geek stereotype are turned off by impression of someone who represents the stereotype Source: Enduring Influence of Stereotypical Computer Science Role Models on Women’s Academic Aspirations, Cheryan 2012
  77. @ashedryden Attrition

  78. @ashedryden 56% of women leave tech within 10 years Source:

    NCWIT, 2012
  79. @ashedryden that’s twice the attrition rate of men

  80. @ashedryden harassment

  81. @ashedryden people in a marginalized group are twice as likely

    to report being harassed or mistreated
  82. @ashedryden “I’ve never seen someone get harassed.”

  83. @ashedryden discrimination

  84. @ashedryden pay, advancement, job offers

  85. @ashedryden men are 2.7 times more likely than women to

    be promoted to a high-ranking job, such as vice president or senior manager Source: Mercury News 2010, http:/ /www.mercurynews.com/ ci_14382477
  86. @ashedryden Myriad Solutions

  87. @ashedryden Change Starts with Us

  88. @ashedryden Education is the Trojan Horse to Empathy

  89. @ashedryden Get to know people different than us

  90. @ashedryden Understand that bias and discrimination are often subtle

  91. @ashedryden Learn to Apologize

  92. @ashedryden Advocate for Change

  93. @ashedryden Talk about these issues openly

  94. @ashedryden “That’s not cool :(”

  95. @ashedryden Influence change in our communities

  96. @ashedryden Have the hard conversations

  97. @ashedryden Increase Education and Access

  98. @ashedryden help facilitate events for marginalized people in tech

  99. @ashedryden volunteer at local schools and groups

  100. @ashedryden commit financial resources

  101. @ashedryden work with colleges and universities

  102. @ashedryden “What are you doing to help students who’ve had

    less exposure to technology?”
  103. @ashedryden remove bias from our schools and universities

  104. @ashedryden “Have you programmed before?”

  105. @ashedryden Change Our Workplaces

  106. @ashedryden what does the ‘about’ page of your website look

    like?
  107. @ashedryden vocal support

  108. @ashedryden job listing language and requirements

  109. @ashedryden benefits

  110. @ashedryden interviewing

  111. @ashedryden equal pay

  112. @ashedryden culture

  113. @ashedryden mentoring and career goal attainment

  114. @ashedryden there is no silver bullet

  115. @ashedryden multi-faceted problems require multi-faceted solutions

  116. @ashedryden requires participation from everyone

  117. @ashedryden Questions?

  118. @ashedryden Thank You! @ashedryden ashedryden.com