Fluent - Programming Diversity

Fluent - 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.

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Ashe Dryden

March 13, 2014
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  1. @ashedryden programming diversity

  2. @ashedryden

  3. @ashedryden ashe dryden @ashedryden ashedryden.com

  4. @ashedryden what is diversity?

  5. @ashedryden more than gender

  6. @ashedryden various backgrounds, experiences, and lifestyles

  7. @ashedryden not always visible

  8. @ashedryden race gender sexuality ability language immigration status physical &

    mental health age socioeconomic class
  9. @ashedryden in·ter·sec·tion·al·i·ty the interactions of biological, social, and cultural traits

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

  11. @ashedryden in the US, women 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
  12. @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
  13. @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
  14. @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
  15. @ashedryden priv·i·lege unearned advantages for a perceived trait, putting them

    in the “normal” or “default” group
  16. @ashedryden Better Education Access to Technology at an Earlier Age

    Higher Pay Assumed Competency Seen as Skill Set Instead of Traits
  17. @ashedryden ster·e·o·type threat concern where a person has the potential

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

  19. @ashedryden im·pos·tor syn·drome a psychological phenomenon in which people are

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

    a group a person belongs to
  21. @ashedryden less likely to apply for certain jobs

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

  23. @ashedryden less likely to attend a conference

  24. @ashedryden mar·gin·al·ized a minority or sub-group being excluded, their needs

    or desires ignored
  25. @ashedryden society teaches us to do this to everyone within

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

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

    favor male students, 2012 scientists & STEM professors do this to each other
  28. @ashedryden even marginalized people do this to each other

  29. @ashedryden how diverse is the tech industry?

  30. @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
  31. @ashedryden women make up 24% of the industry Source: FLOSSPOLS

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

    Gender Integrated Report Findings
  33. @ashedryden lack of diversity is a global problem

  34. @ashedryden India 8% Source: Anita Borg Institute, State of Women

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

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

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

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

    Women in Technology Fields Around the World
  39. @ashedryden “I guess women just aren’t interested in programming.”

  40. @ashedryden first compiler & programming language

  41. @ashedryden “Women aren’t biologically predisposed to programming.”

  42. @ashedryden no physical or biological difference

  43. @ashedryden purely social and cultural constructs

  44. @ashedryden Bulgaria 73% Source: Anita Borg Institute, State of Women

    in Technology Fields Around the World
  45. @ashedryden diversity matters

  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 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 & viability

  51. @ashedryden why the lack of diversity?

  52. @ashedryden pipeline

  53. @ashedryden access to technology

  54. @ashedryden boys get access to their first computer at 11

  55. @ashedryden girls get access to their first computer at 14

  56. @ashedryden lower computer ownership rates & broadband adoption

  57. @ashedryden adopt smart phones at a much higher rate

  58. @ashedryden access to quality education

  59. @ashedryden quality high school education is one of the greatest

    indicators of earning potential
  60. @ashedryden schools in poor neighborhoods have lower quality math and

    science programs
  61. @ashedryden access to healthcare

  62. @ashedryden people of color, people with disabilities, & LGBTQ people

    have less access to quality healthcare
  63. @ashedryden women are more likely to be caregivers

  64. @ashedryden attraction

  65. @ashedryden geek stereotype

  66. @ashedryden the geek stereotype is hindering us Source: Enduring Influence

    of Stereotypical Computer Science Role Models on Women’s Academic Aspirations, Cheryan 2012
  67. @ashedryden attrition

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

    Athena Factor, Center for Work-Life Policy, 2008
  69. @ashedryden that’s twice the attrition rate of men

  70. @ashedryden harassment

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

    to be harassed or mistreated
  72. @ashedryden “but I’ve never seen someone get harassed.”

  73. @ashedryden discrimination

  74. @ashedryden pay, advancement, job offers

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

    be promoted to a high-ranking job Source: Mercury News 2010, http:/ /www.mercurynews.com/ci_14382477
  76. @ashedryden yeah, but what can i do about this stuff?

  77. @ashedryden change starts with us

  78. @ashedryden education is the trojan horse to empathy

  79. @ashedryden get to know people different than us

  80. @ashedryden bias & discrimination are often subtle

  81. @ashedryden learn to apologize

  82. @ashedryden talk about these issues openly

  83. @ashedryden “that’s not cool :(”

  84. @ashedryden have the hard conversations

  85. @ashedryden change our workplaces

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

    like?
  87. @ashedryden culture

  88. @ashedryden job listing language and requirements

  89. @ashedryden equal pay

  90. @ashedryden mentoring & career goal attainment

  91. @ashedryden requires participation from everyone

  92. @ashedryden what can we accomplish together?

  93. @ashedryden thanks! @ashedryden ashedryden.com