Diversity in data science: 40 resources to promote equity and representation for people of color

We live in a data-driven world, where important decisions are made based on information collected through platforms designed by big tech companies. Over time, as more people have come to interact with technology daily, enormous amounts of data have been compiled for analysis and conversion into insights and intelligence. 

The rise of big data and analytics has opened the door for data scientists to decipher meaning from these stockpiles of raw data. But while increased data creates opportunities for innovation, its interpretation leaves room for bias, which can amplify social and political issues and create new challenges for underrepresented groups.

In an article for Built In, Olusayo Adeleye Funke Aderonmu, policy analyst and Fellow at the Ph.D. Excellence Initiative at NYU writes, “in the wake of a global reckoning with the effects of systemic racism, economic and social injustice, the field of data science offers a valuable opportunity to meaningfully advance equity and inclusion. Doing so is critical to ensuring that the future benefits of a data-driven world are shared and leveraged equitably to solve societal problems rather than exacerbate them.”

Barriers to entry and opportunities for social justice in data science

Data science can be a huge asset in solving some of the problems facing society today. However, STEM fields tend to lack diversity, creating a need for people of color within those industries. This not only helps in terms of representation, but it can also lead to a range of insights and points of view that may have previously been overlooked. Those perspectives are especially useful in organizational decision-making. 

“Recent estimates show that Black people make up just three percent of data and analytics professionals, and women overall make up only 15% of data scientists. Such paucity of diversity likely means Black women are largely missing from data science. A number of barriers, including inadequate STEM education and mentorship opportunities, as well as bias in recruitment and exclusionary work cultures, serve to keep Black women and other underrepresented groups from entering data science careers,” Olusayo Adeleye Funke Aderonmu notes.

Research by Zippia indicated that “the most common ethnicity among data scientists is white, which makes up 66.1% of all data scientists. Comparatively, there are 25% of the Asian ethnicity and 5.2% of the Hispanic or Latino ethnicity.” Only 1% of data scientists are Black or African American, and only 0.9% are American Indian and Alaska Native, according to their statistics.

Another important finding from the research is the lack of female data scientists: only 20.4% of data scientists identify as women. To ensure their representation in tech moving forward, more young women of color are needed in STEM education programs as well as in the data science field.

41 resources to promote equity and representation for people of color in data science

There are a variety of resources to help BIPOC overcome barriers to entry in data science and STEM education. Below, we have compiled a list of organizations working toward social justice in data science, books about diversity in data science, as well as video content by creators of color to help learn more about data science from people currently working in the industry. 

12 resources to promote equity and representation in STEM education

Since women are already underrepresented in STEM, many groups and organizations focus on helping create opportunities for women of color. The resources below can help bridge the gap for women and other underrepresented groups in STEM.

1. Equity Resources for STEM: Grand Valley State University offers resources to increase equity in STEM through featured profiles of women and BIPOC in STEM. 
2. Education Week Resources for Getting Students of Color into STEM: This Education Week special report features an interview with John Urschel. The former NFL player and advocate for Black students in STEM offers advice for educators. 
3. 11 Professional Organizations That Support People of Color in STEM: Ripple Match lists 11 professional organizations that support people of color in STEM education to help close the racial divide.
4. 55+ Free STEM Educational Resources & Opportunities for Women and Minority Groups: Knoji compiled a list of over 55 STEM resources specifically for Black, Hispanic, and Indigenous American students that also includes resources for LGBTQIA+ individuals and people with disabilities. 
5. Black in Stem Resources: This resource created by Cold Spring Harbor Laboratory includes a variety of resources in different formats, including articles, journals, books, podcasts, and interviews. 
6. Women and Minorities in STEM: These resources from STEM Study shares professional networking groups, as well as advocacy and mentorship programs for women and minorities in STEM. 
7. STEM Education Equity & Anti-Racism Resources: The Texas Alliance for Minorities in Engineering put together a list of resources specific to anti-racism in STEM. It includes resources for pronouncing students’ names correctly, which can have an impact on their sense of belonging in STEM classrooms. 
8. Inclusive Teaching Resources for STEM Courses: The University of Michigan offers practical resources for teachers to make their STEM classrooms more inclusive, covering topics like implicit bias, inclusive syllabus language, and conversation prompts about race and racism. 
9. Resources on equity and inclusion for STEM and higher education: The Accelerating Systematic Change Network put together a list of articles and resources on equity and inclusion in STEM for use in the classroom, on campus, and within specific disciplines.
10. 10 Books to Help Children Celebrate Diversity in STEM: The National Inventors Hall of Fame put together a list of 10 books that can help children learn about inventors and other STEM leaders to promote diversity in the field. 
11. 10 Networking Communities for Underrepresented Data Scientists: In this article, Built In lists 10 established communities to help data scientists from underrepresented groups find and advocate for each other.
12. 9 Black Women in Data Science You Should Know: In this article, Olusayo Adeleye Funke Aderonmu identifies nine Black female leaders who are promoting equity in the field of data science.

8 organizations creating equity for people of color in data science

Many organizations are helping to lead the creation of equity for people of color in data science. Some of them are targeted toward women of color, a highly underrepresented group in tech. 

1. Ida B. Wells Just Data Lab: The Ida B. Wells Just Data Lab brings students, educators, activists, and artists together to develop a critical and creative approach to data conception, production, and circulation.
2. Data for Black Lives: Data for Black Lives is a movement of activists, organizers, and scientists committed to using data to create concrete and measurable change in the lives of Black people.
3. Algorithmic Justice League: ​​The Algorithmic Justice League combines art and research to illuminate the social implications and harms of AI.
4. Mechanism Design for Social Good: Mechanism Design for Social Good (MD4SG) is a multi-institutional initiative to improve access to opportunity for historically underserved and disadvantaged communities. They do this with the help of algorithms, optimization, and mechanism design, along with insights from other disciplines.
5. AI4ALL: AI4ALL opens doors to artificial intelligence for historically excluded talent through education and mentorship.
6. Advancing Indigenous People in STEM: The American Indian Science and Engineering Society (AISES) is a national nonprofit organization focused on substantially increasing the representation of indigenous peoples of North America and the Pacific Islands in STEM studies and careers.
7. Girls Who Code: Girls Who Code’s mission is to close the gender gap in technology, and to change the image of what a programmer does and looks like.
8. Black Girls Do STEM: Black Girls Do STEM works toward equitable representation of Black women across all STEM fields to increase their curiosity. They do this through deliberate education, access, and opportunities for STEM learning for Black girls in every community they work with.

12 books about data science and diversity

For a deeper dive into these issues, we have put together a reading list with recommendations for all age and education levels. This diversity in data science reading list covers a range of issues at the intersection of data science, race, and representation.

1. Algorithms of Oppression: How Search Engines Reinforce Racism by Safiya Umoja Noble: This book by Safiya Umoja Noble, associate professor in UCLA’s Departments of Gender Studies and African American Studies, reveals how negative biases against women of color are embedded in search engine results and algorithms. Through an analysis of textual and media searches and extensive research of paid online advertising, Noble exposes a culture of racism and sexism in the way discoverability is created online.
2. Black Software: The Internet & Racial Justice, from the AfroNet to Black Lives Matter by Charlton D. McIlwain: In his book, Charlton D. McIlwain, Vice Provost of Faculty Engagement and Development at New York University, includes never-published, firsthand accounts of African American pioneers in computer networking and the internet.
3. Abby Invents Unbreakable Crayons by Dr. Arlyne Simon: Written by Black biomedical engineer, patented inventor, and author Dr. Arlyne Simon, this picture book teaches children the importance of perseverance and follows the story of a young girl who creates her first invention and earns her first patent.
4. Gary and the Great Inventors: It’s Laundry Day! by Akura Marshall: This children’s book highlights Thomas Jennings, the first African American inventor to receive a patent in the U.S.
5. Hidden Figures: The American Dream and the Untold Story of the Black Women Mathematicians Who Helped Win the Space Race by Margot Lee Shetterly: This popular book tells the true story of the Black female mathematicians at NASA whose calculations helped fuel some of America’s greatest achievements in space.
6. Black Faces, White Spaces by Carolyn Finney: This book looks beyond the discourse of the environmental justice movement to examine how the natural environment has been understood, commodified, and represented by both white and Black Americans.
7. Weapons of Math Destruction by Cathy O’Neil: In this book, winner of the Euler Book Prize and longlisted for the National Book Award, author Cathy O’Neil reveals that the mathematical models being used today are unregulated and uncontestable, even when they’re wrong. She also notes that they reinforce discrimination.
8. Successful STEM Mentoring Initiatives for Underrepresented Students by Becky Wai-Ling Packard; Norman L. Fortenberry: Written by an acknowledged expert in the field of STEM mentoring, this book presents a step-by-step, research-based guide for higher education faculty and administrators who are charged with designing mentoring programs to recruit and retain students from underrepresented groups. 
9. Gender and Diversity in STEM: An Introduction to the Intersection of Gender, Race, and Sexuality Within Science, Technology, Engineering, and Math by Deena Murphy and Ashley Simons-Rudolph: In this book, researchers Deena Murphy and Ashley Simons-Rudolph offer an introduction to topics related to intersection of gender, race, and sexuality in STEM.
10. Invisible Women: Data Bias in a World Designed for Men by Caroline Criado Perez: Written by award-winning campaigner and writer Caroline Criado Perez, Invisible Women exposes how, in a world largely built for and by men, we are systematically ignoring half the population. The book exposes the gender data gap, which has created a pervasive bias that has a profound effect on women’s lives.
11. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by Seth Stephens-Davidowitz: Author Seth Stephens-Davidowitz, a Harvard-trained economist, former Google data scientist, and New York Times writer, reveals how new data from the internet reveals the truth about who people are based on their behavior online rather than how they present themselves in society.
12. Naked Statistics: Stripping the Dread from the Data by Charles Wheelan: In this bestseller, Dartmouth’s Charles Wheelan focuses on the underlying intuition that drives statistical analysis. The book demystifies key concepts like inference, correlation, and regression analysis and reveals how biased or careless parties can manipulate or misrepresent data.

8 videos about data science featuring Black and AAPI thought leaders

These videos created by people of color in data science provide a brief overview of data science diversity, including equitable initiatives to address these challenges. 

1. Creating diverse and equitable initiatives in data science | Tiffany Oliver | TEDxMorehouseCollege: In this video, geneticist and professor Tiffany Oliver provides steps on how to increase diversity, inclusion, and equity in the field of data science.
2. 7 Different Career Paths In Data Science | Data Science As A Career: This video offers seven different career paths for students or professionals considering a career in data science.
3. Why everyone should become a data scientist | Joseph Kachiliko | TEDxLusaka: In this talk, Joseph Kachiliko, a data expert IT auditor at one of the world’s leading audit firms, speaks about the benefits of increasing data literacy.
4. Demystifying Data Science | Asitang Mishra | TEDxOakLawn: In this talk, Asitang Mishra shares his experiences as a data scientist at the world-famous NASA Jet Propulsion Laboratory.
5. Real talk about my Data Scientist jobs + salary for entry-level data science: Content creator The Almost Astrophysicist talks about why she left astrophysics to become a data scientist straight out of college and shares five realizations about the industry.
6. Why being a data scientist is awesome!: In this video, content creator Tina Huang talks about exciting salary and career opportunities for data scientists. 
7. Work Week In My Life | Data Scientist at Spotify: In this video, content creator Julia Fei shares a week in her life working in tech as a data scientist at Spotify.
8. What is Data Science?: In this video, Luv Aggarwal, a data solution engineer at IBM, goes through the basics of data science and explains how the discipline deploys data mining, data cleaning, machine learning, and more.

What we do today to help promote STEM education to underrepresented youth will determine the future of representation and equity in the tech industry. The more information we share, the more we can help people overcome barriers and increase opportunities for people of color in data science.