SF Ruby/Women Who Code/PyLadies - Programming Diversity

@ashedryden Programming Diversity

@ashedryden Ashe Dryden @ashedryden ashedryden.com

@ashedryden What is Diversity?

@ashedryden more than gender

@ashedryden various backgrounds, experiences, and lifestyles

@ashedryden not always visible

@ashedryden race gender sexuality ability language appearance physical & mental
health age socioeconomic class and more!

@ashedryden Intersectionality the interactions of biological, social, and cultural traits
contributing to systemic inequality

@ashedryden race gender ability physical & mental health socioeconomic class

@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

@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

@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

@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

@ashedryden Privilege unearned advantages a person gets for a perceived
trait they possess, putting them in the “normal” group

@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

@ashedryden Stereotype Threat anxiety or concern where a person has
the potential to conﬁrm a negative stereotype about their social group

@ashedryden Source: xkcd, How it Works: http:/ /xkcd.com/385/

@ashedryden Impostor Syndrome a psychological phenomenon in which people are
unable to internalize their accomplishments

@ashedryden this is especially pronounced when negative stereotypes exist about
a group a person is in

@ashedryden less likely to apply for certain jobs

@ashedryden less likely to submit a talk to a conference

@ashedryden less likely to attend to a conference

@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.

@ashedryden society teaches us to do this to everyone within
marginalized groups

@ashedryden “I’m different. I’m logical and rational; I don’t see
gender or race.”

@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

@ashedryden even marginalized people do it to people within their
same social groups

@ashedryden How diverse is the tech industry?

@ashedryden Women make up 24% of the industry Source: FLOSSPOLS
- Gender Integrated Report Findings

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

@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

@ashedryden Lack of Diversity is a Global Problem

@ashedryden India 8% of CS students Source: Anita Borg Institute,
State of Women in Technology Fields Around the World

@ashedryden US 17% of CS students Source: Anita Borg Institute,

@ashedryden UK 18.2% of CS students Source: Anita Borg Institute,

@ashedryden France 20% of CS students Source: Anita Borg Institute,

@ashedryden Brazil 20% of CS students Source: Anita Borg Institute,

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

@ashedryden “Maybe women just aren’t interested in programming.”

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

@ashedryden there exists no physical or biological difference that impacts
a person’s ability to be a programmer

@ashedryden the differences that exists are purely social and cultural
constructs, and are therefore able to be overcome

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

@ashedryden Diversity Matters

@ashedryden Diversity Matters to businesses

@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)

@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

@ashedryden more creative & stimulated through persistent exposure to minority
perspectives Source: Charlan Jeanne Nemeth, Differential Contributions of Majority and Minority Inﬂuence.

@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)

@ashedryden the ﬁnancial success and viability of a company are
directly related to the makeup of its teams

@ashedryden Diversity Matters to society

@ashedryden heal the issue of unequal pay and opportunity

@ashedryden create class mobility

@ashedryden the wage gap is smaller in STEM ﬁelds

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

@ashedryden Why the lack of diversity?

@ashedryden Pipeline

@ashedryden Cultural Cues

@ashedryden difference in toys and games for boys and girls

@ashedryden no famous role models that represent them

@ashedryden Access to Technology

@ashedryden on average, men get access to their ﬁrst computer
at 11

@ashedryden women get access to their ﬁrst computer at 14

@ashedryden African American and Hispanic households have lower computer ownership
rates and broadband adoption

@ashedryden African American and Hispanic are adopting smart phones at
a much higher rate than their white counterparts

@ashedryden Access to Quality Education

@ashedryden quality high school education is one of the greatest
indicators of earning potential

@ashedryden schools in poor neighborhoods have lower quality math and
science programs

@ashedryden Access to healthcare

@ashedryden women are more likely to be caregivers

@ashedryden people of color, people with disabilities, and LGBTQ people
have less access to quality healthcare

@ashedryden Attraction

@ashedryden Lack of Role Models

@ashedryden less likely to see people like them represented in
companies and conferences

@ashedryden Geek Stereotype

@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

@ashedryden Attrition

@ashedryden 56% of women leave tech within 10 years Source:
NCWIT, 2012

@ashedryden that’s twice the attrition rate of men

@ashedryden harassment

@ashedryden people in a marginalized group are twice as likely
to report being harassed or mistreated

@ashedryden “I’ve never seen someone get harassed.”

@ashedryden discrimination

@ashedryden pay, advancement, job offers

@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

@ashedryden Myriad Solutions

@ashedryden Change Starts with Us

@ashedryden Education is the Trojan Horse to Empathy

@ashedryden Get to know people different than us

@ashedryden Understand that bias and discrimination are often subtle

@ashedryden Learn to Apologize

@ashedryden Advocate for Change

@ashedryden Talk about these issues openly

@ashedryden “That’s not cool :(”

@ashedryden Inﬂuence change in our communities and workplaces

@ashedryden Have the hard conversations

@ashedryden Increase Education and Access

@ashedryden help facilitate events for marginalized people in tech

@ashedryden volunteer at local schools and groups

@ashedryden commit ﬁnancial resources

@ashedryden work with colleges and universities

@ashedryden “What are you doing to help students who’ve had
less exposure to technology?”

@ashedryden remove bias from our schools and universities

@ashedryden “Have you programmed before?”

@ashedryden Change Our Workplaces

@ashedryden what does the ‘about’ page of your website look
like?

@ashedryden vocal support

@ashedryden job listing language and requirements

@ashedryden beneﬁts

@ashedryden interviewing

@ashedryden equal pay

@ashedryden culture

@ashedryden mentoring and career goal attainment

@ashedryden Improve Inclusion at Conferences

@ashedryden diversity in the organizing team

@ashedryden work with the community

@ashedryden codes of conduct

@ashedryden scholarships

@ashedryden anonymized proposal processing

@ashedryden outreach

@ashedryden there is no silver bullet

@ashedryden multi-faceted problems require multi-faceted solutions

@ashedryden requires participation from everyone

@ashedryden Questions?

@ashedryden Thank You! @ashedryden

SF Ruby/Women Who Code/PyLadies - Programming Diversity

SF Ruby/Women Who Code/PyLadies - Programming Diversity

More Decks by Ashe Dryden

Other Decks in Technology

Featured

Transcript