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The global economic impact of AI is expected to reach $15.7 trillion by 2030, and we’re
already seeing AI incorporated into areas like medical diagnosis, self-driving cars, and
customer support. We decided to tackle two key challenges (Diversity and Tech Ethics)
Now is a critical time for AI. AI and other STEM fields do not currently reflect the diversity of
our country, since they continue to be dominated by white males, while women and other
racial and ethnic minorities continue to be underrepresented.
Artificial Intelligence remains a field with one of the greatest gender gaps and least racial
representation. The primary causes of this are the lack of early exposure to computers,
access to opportunities and resources, and encouragement to succeed.
• An AI Now study revealed that women comprise only 10%-15% of AI research staff at top
tech companies, and the numbers are even more dismal for people of color in advanced
• In the industry, women comprised only 24% of the field of computer and information
sciences in 2015, according to the National Science Board
• The STEM workforce is 89% white and 72% male, while the overall workforce is 78%
white and 53% male.
• By the time students reach college, women are significantly underrepresented in STEM
majors — for instance, only around 21% of engineering majors are women and only around
19% of computer and information science majors are women.
• African American and Hispanic workers continue to be underrepresented in the STEM
workforce. African American make up 11% of the U.S. workforce overall but represent 9% of
STEM workers, while Hispanics comprise 16% of the U.S. workforce but only 7% of all
• Low-income students in the U.S. account for only 14% of students in the nation’s top 200
postsecondary institutions. These students who attend low-income schools are more likely to
have very limited access to STEM resources, classes, and experiences. Poverty squanders
a wealth of STEM potential.
As a result, a homogenous group of technologists is building AI solutions for our diverse
population. This lack of diversity results in biased AI products that, at best, don’t serve
everyone and, at worst, actively harm underrepresented groups. There is evidence that
existing societal biases, including sexism, racism, and other forms of discrimination, are
being built into AI products. It is crucial to take action now to ensure that everyone has the
opportunity to guide the creation of AI as a tool for good.
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