This document discusses the benefits of diversity in teams and initiatives to promote diversity. It summarizes research showing that diverse teams outperform non-diverse teams due to increased innovation and collective intelligence. However, biases still exist as implicit association tests show most people more strongly associate men with science and women with liberal arts. Several companies are reported to have more gender diversity in non-tech roles than tech roles, and women are underrepresented in higher levels of tech companies. The document advocates for diversity programs and policies to address these issues.

1. C O D I N G L I K E A
G I R L
How teams with women gain with diversity
Gabriela D’Ávila
@gabidavila

2. A B O U T M E
• Major in Digital Game Development
• Senior Software Engineer with 8 years in the market
• Web Development
• Women in Technology Advocate
• Lego =)
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3. W H AT TO E X P E C T
• Diversity
• Bias
• Like A girl
• Diversity Reports
• How diversity is important
• Initiatives
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4. D I V E R S I T Y
4

5. D I V E R S I T Y
• Gender
• Racial
• Ethnic
• Sexual Orientation
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6. B I A S
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7. P R O J E C T
I M P L I C I T ®
7
http://implicit.harvard.edu/implicit

8. 8

9. P R O J E C T I M P L I C I T ®
9
0% 7.5% 15% 22.5% 30%
1%
3%
6%
18%
18%
28%
26%Strong automatic association of Male with
Science and Female with Liberal Arts
Moderate automatic association of Male with
Science and Female with Liberal Arts
Slight automatic association of Male with
Science and Female with Liberal Arts
Little to no association between
genders and academic domains
Slight automatic association of Male with
Liberal Arts and Female with Science
Moderate automatic association of Male with
Liberal Arts and Female with Science
Strong automatic association of Male with
Liberal Arts and Female with Science
Source: Project Implicit
2015
2014

10. L I K E A G I R L
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11. 11
"You know, you are pretty intelligent, for a girl. "
- Undisclosed friend

12. L I K E A G I R L
• You drive like a girl
• You punch like a girl
• You fight like a girl
• You [verb] like a girl
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13. D I V E R S I T Y
R E P O R T S
13

14. A L L A R E A S
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0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
34%30%32%31%
66%70%68%69%
Male Female
Source:CompaniesDiversityReports
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
30%30%31%30%
70%70%69%70%
Male Female
2015 2014

15. T E C H
15
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
13%18%16%21%
87%82%84%79%
Male Female
Source:CompaniesDiversityReports
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
10%17%15%20%
90%
83%85%80%
Male Female
2015 2014

16. N O N - T E C H
16
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
50%47%52%37%
50%53%48%
63%
Male Female
Source:CompaniesDiversityReports
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
50%48%47%35%
50%52%53%
65%
Male Female
2015 2014

17. H I G H L E V E L
17
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
22%22%23%28%
78%78%77%72%
Male Female
Source:CompaniesDiversityReports
0%
20%
40%
60%
80%
100%
Apple Facebook Google Twitter
21%21%23%28%
79%79%77%72%
Male Female
2015 2014

18. T E C H W O R K F O R C E F A C T S
• Men 2.7x more chance of leading positions
• Women gravitates towards other women
• Lack of role models
• Women values flexibility more than men
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Source: Anita Borg Institute, Climbing the technical ladder

19. R A N K L E V E L S
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Source: Anita Borg Institute, Climbing the technical ladder
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Women Men
20.2%
10.9%
55.2%
56%
24.6%
33.1%
Entry Mid High

20. W H Y D I V E R S I T Y
M AT T E R S ?
20

21. D I V E R S I T Y
I N C R E A S E S G R O U P
P E R F O R M A N C E
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22. G R O U P P E R F O R M A N C E
• Collective Intelligence is increased
• Diverse teams are more efficient
• Better problem solving
• More innovative solutions
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Source:Ernest&Young,Prof.AnitaWilliamsWoolley,AnitaBorgInstitute

23. G R O U P P E R F O R M A N C E
• Three factors:
Proportion of females on the group
Social sensitivity
Numbers of speaking members
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Source:Ernest&Young,Prof.AnitaWilliamsWoolley,AnitaBorgInstitute

24. D I V E R S I T Y P O W E R S
I N N O VAT I O N
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25. I N N O VAT I O N
• Competitive advantage
• Diverse groups outstanding performance
• Patents with mixed gender cited more often
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Source:Ernest&Young,Prof.AnitaWilliamsWoolley,AnitaBorgInstitute

26. 26
I N N O VAT I O N
26Source: London Business School, Anita Borg Institute
"If people think alike, then no matter how smart they are they most likely will
get stuck at the same locally optimal solutions. Innovating, requires thinking
differently.That's why diversity powers innovation."
–Scott Page, University of Michigan

27. I N N O VAT I O N
27Source: London Business School, Anita Borg Institute

28. N E I L D E G R A S S E
T Y S O N
28

29. N E I L D E G R A S S E T Y S O N
Astrophysicist
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30. 30
“Before we start talking about genetic differences, you got
to come up with a system that is equal opportunity.Then
we can have that conversation.”
– Neil deGrasse Tyson, at 2009 NewYork Conference - Link

31. H O W C A N I H E L P ?
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32. T H E C O D E M A N I F E S TO
• Discrimination limits us
• Boundaries honor us
• We are our biggest assets
• We are resources for the future
• Respect defines us
• Reactions require grace
• Opinions are just that: opinions
• To err is human
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http://www.codemanifesto.com

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34. P R O G R A M S
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35. Q U E S T I O N S ?
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36. T H A N K YO U
• Twitter: @gabidavila
• Web: http://gabriela.io
• Email: gabidavila@gmail.com
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37. R E F E R E N C E S
• ANITA BORG INSTITUTE - Climbing the Technical Ladder
• ANITA BORG INSTITUTE - The Case for Investing on Women
• ANITA BORG INSTITUTE - Women Technologists Count
• ANITA WOLLEY - Evidence for a Collective Intelligence Factor in the Performance of Human Groups
• CATALYST, Why Diversity Matters?
• ERNST & YOUNG - Groundbreakers
• ILLUMINATE VENTURES - High Performance Entrepreneurs
• CODE MANIFESTO - Website
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