"Well Actually..." Answers to Diversity and Inclusion FAQ Based on Data and Research

Transcript

1. WHERE DO MANSPLAINERS GET THEIR WATER?
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2. WHERE DO MANSPLAINERS GET THEIR WATER?
   FROM A WELL, ACTUALLY
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   @keegzzz / @ElBueno
   

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3. “WELL, ACTUALLY…”
   ANSWERS TO DIVERSITY AND INCLUSION FAQ
   BASED ON DATA AND RESEARCH
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   Jez Humble, CTO, DevOps Research and Assessment LLC | @jezhumble
   

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5. FIRST, LET’S ACKNOWLEDGE WE HAVE A
   PROBLEM: REPRESENTATION AND PAY
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6. @jezhumble
   high tech: demographics
   https://www.eeoc.gov/eeoc/statistics/reports/hightech/ May 2016
   

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7. @jezhumble
   high tech: demographics
   https://www.eeoc.gov/eeoc/statistics/reports/hightech/ May 2016
   

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8. @jezhumble
   software engineering: SV demographics
   https://www.eeoc.gov/eeoc/statistics/reports/hightech/ May 2016
   Professional /
   technical
   Sales Technicians
   Execs &
   Managers
   NON-TECH
   FIRMS: tech
   NON-TECH FIRMS:
   exec/mgmt
   Women 30% 25% 23% 28% 49% 43%
   Men 70% 75% 77% 72% 51% 57%
   Asian American 50% 11% 23% 36% 35% 20%
   Black 2% 3% 11% <1% 8% 5%
   Hispanic 4% 6% 12% 1.6% 15% 10%
   White 41% 77% 50% 57% 37% 62%
   

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9. https://hired.com/wage-inequality-report
   

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10. https://hired.com/wage-inequality-report
    

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11. https://hired.com/wage-inequality-report
    

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13. @jezhumble
    no difference in ability
    Terri Oda, http://bit.ly/2vLkYKt also http://www.pnas.org/content/109/41/16474.abstract
    

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15. @jezhumble
    “preference” isn’t determined by gender
    NPR Planet Money, Episode 576: When Women Stopped Coding. https://n.pr/2QToyNf
    

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16. U.S. Army Photo
    Betty Jennings and Frances Bilas programming the ENIAC
    

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17. “If it's a good idea,
    go ahead and do it.
    It is much easier to
    apologize than it is
    to get permission.”
    —Rear Admiral Grace Hopper,
    USN, 1906-1992
    

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18. NASA
    Dorothy Vaughan, Katherine Johnson, Mary Jackson
    

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19. Margaret Hamilton (Director, Software
    Engineering Division, MIT Instrumentation
    Laboratory) in 1969 with the source code
    for the Apollo 11 Guidance Computer
    http://bit.ly/2ciNWcY
    

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20. @jezhumble
    it’s bias
    “Without provision of information about candidates other than
    their appearance, men are twice more likely to be hired for a
    mathematical task than women. If ability is self-reported, women
    still are discriminated against, because employers do not fully
    account for men’s tendency to boast about performance.”
    “How stereotypes impair women’s careers in science”
    Ernesto Reuben et al, | http://www.pnas.org/content/111/12/4403
    

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21. bias
    “Science faculty’s subtle gender biases favor male students”, Moss-Racusin et al| http://bit.ly/2wrzVza
    

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22. which hypothesis correlates with % women?
    https://bit.ly/2XZmcOB | Sarah-Jane Leslie et al. Science 347, 262 (2015),
    “Expectations of brilliance underlie gender distributions across academic disciplines”
    

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25. @jezhumble
    how stereotypes developed
    “According to Ensmenger, a second type of test, the personality
    profile, was even more slanted to male applicants. Based on a
    series of preference questions, these tests sought to indentify
    job applicants who were the ideal programming ‘type.’ According
    to test developers, successful programmers … displayed
    ‘disinterest in people’ and that they disliked ‘activities involving
    close personal interaction.’
    https://stanford.io/2OMXPPL
    

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26. @jezhumble
    stereotypes act as a gatekeeper…
    “Computer science and engineering are stereotyped in modern
    American culture as male-oriented fields that involve social
    isolation, an intense focus on machinery, and inborn brilliance.”
    Sapna Cheryan et al, “Cultural stereotypes as gatekeepers: increasing girls’ interest in computer
    science and engineering by diversifying stereotypes”
    https://www.frontiersin.org/articles/10.3389/fpsyg.2015.00049/full
    

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28. INCREASING REPRESENTATION DOESN’T MEAN
    LOWERING THE BAR. IT MEANS PUTTING
    MORE WORK INTO FINDING SUITABLY
    QUALIFIED CANDIDATES
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29. Setting targets for the number of candidates from
    underrepresented / marginalized groups in your hiring pool
    (including leadership and management positions) is necessary to
    counteract bias.
    https://martinfowler.com/bliki/DiversityMediocrityIllusion.html
    https://hbr.org/2016/04/if-theres-only-one-woman-in-your-
    candidate-pool-theres-statistically-no-chance-shell-be-hired
    

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31. @jezhumble
    over 50% of qualified women drop out of STEM
    “Over time, over half of highly qualified women working in science,
    engineering and technology companies quit their jobs... In 2013, just 26
    percent of computing jobs in the U.S. were held by women, down from 35
    percent in 1990… Although 80 percent of U.S. women working in STEM
    fields say they love their work, 32 percent also say they feel stalled and
    are likely to quit within a year.”
    https://www.eeoc.gov/eeoc/statistics/reports/hightech/
    

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32. @jezhumble
    50% of women drop out of tech
    Joan C. Williams, “The 5 Biases Pushing Women Out of Stem”
    https://hbr.org/2015/03/the-5-biases-pushing-women-out-of-stem
    

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33. promote more women and people of color
    stop perpetuating the innate ability / 10x developer myth
    create an inclusive environment and don’t tolerate intolerance
    check salaries, recruiting, and reviews for bias and correct imbalances
    monitor tenure, progression and job satisfaction by gender and race
    what can i do?
    

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34. WE WILL KNOW WHEN EQUALITY (AND
    MERITOCRACY) HAS BEEN ACHIEVED WHEN
    THERE IS AN EQUAL DISTRIBUTION OF POWER
    AND WEALTH ACROSS GENDERS, RACES,
    ABILITIES, AND SEXUAL ORIENTATION
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    @jezhumble
    

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35. @jezhumble
    thanks
    Rani Sanghera @ranisanghera | Bridget Kromhout
    @bridgetkromhout | Nicole Forsgren @nicolefv | Erica Baker
    @EricaJoy | Leigh Honeywell @hypatiadotca | Sue Gardner
    @SuePGardner | Randi Lee Harper @randileeharper | Shanley Kane
    @shanley | Marco Rogers @Polotek | Faruk Ateş @kurafire | Marie
    Hicks @histoftech | Cat Swetel @catswetel | Soo Choi @soosiechoi |
    Ashe Dryden @ashedryden | Cate Huston @catehstn | Alice
    Goldfuss @alicegoldfuss | AnnaLee Flower Horne @leeflower |
    Nicole Sanchez @nmsanchez | Yonatan Zunger @yonatanzunger
    

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36. thank you!
    © 2018 Jez Humble & Associates LLC
    https://continuousdelivery.com/ | https://devops-research.com/
    To receive the following:
    • 30% off my new video course: creating high performance organizations
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    • A copy of this presentation
    • A 100 page excerpt from Lean Enterprise
    • An excerpt from The DevOps Handbook
    • A 20m preview of my Continuous Delivery video workshop
    Just pick up your phone and send an email
    To: jezhumble@sendyourslides.com
    Subject: devops
    

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