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

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

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Jez Humble

May 03, 2018
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  1. WHERE DO MANSPLAINERS GET THEIR WATER? 1

  2. WHERE DO MANSPLAINERS GET THEIR WATER? FROM A WELL, ACTUALLY

    2 @keegzzz / @ElBueno
  3. “WELL, ACTUALLY…” ANSWERS TO DIVERSITY AND INCLUSION FAQ BASED ON

    DATA AND RESEARCH 3 Jez Humble, CTO, DevOps Research and Assessment LLC | @jezhumble
  4. None
  5. FIRST, LET’S ACKNOWLEDGE WE HAVE A PROBLEM: REPRESENTATION AND PAY

    5
  6. @jezhumble high tech: demographics https://www.eeoc.gov/eeoc/statistics/reports/hightech/ May 2016

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

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

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

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

  12. None
  13. @jezhumble no difference in ability Terri Oda, http://bit.ly/2vLkYKt also http://www.pnas.org/content/109/41/16474.abstract

  14. None
  15. @jezhumble “preference” isn’t determined by gender NPR Planet Money, Episode

    576: When Women Stopped Coding. https://n.pr/2QToyNf
  16. U.S. Army Photo Betty Jennings and Frances Bilas programming the

    ENIAC
  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
  18. NASA Dorothy Vaughan, Katherine Johnson, Mary Jackson

  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
  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
  21. bias “Science faculty’s subtle gender biases favor male students”, Moss-Racusin

    et al| http://bit.ly/2wrzVza
  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”
  23. None
  24. None
  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
  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
  27. None
  28. INCREASING REPRESENTATION DOESN’T MEAN LOWERING THE BAR. IT MEANS PUTTING

    MORE WORK INTO FINDING SUITABLY QUALIFIED CANDIDATES 28
  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
  30. None
  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/
  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
  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?
  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 34 @jezhumble
  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
  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 • 50% off my CD video training, interviews with Eric Ries, and more • 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