#DataScienceWhileBlack


Here we are again, at the inception of a new field -- this time, formalizing data science. New tools, technologies and platforms are being created, tested and discussed everyday.

I am a Black woman who works and engages in spaces where the folks look like me.

I notice that these spaces are just starting to realize the depth, breadth and magnitude of data science for, to and about the Black community.

I notice that many of these spaces are lacking direction in what to do about data science.

I care about these spaces being welcomed and included in the development of data science.

The history and future of data science is being written right now. The contributions of those in America’s past, such as Ida B Wells (data journalist) and W.E.B. DuBois (data visualizer), and present, such as Stacey Abrams and Dr. Vetria Byrd, are quietly shared. Anecdotally. Interjecting purposeful content as part of the data science culture could help incentivize this group to increase their computational and data skills.


However, the trajectory is looking somber. The future will mimic the past if no course change happens. As every org is seeking to increase its “diversity numbers” and claim “they can’t find suitable Black candidates” to fill computing and engineering positions, the same fate I predict for data science. Nearly 50% of all S&E Black Bachelor degrees recipients earned their degree at a Historically Black College and University (HBCU). HBCUs currently don’t have data science degree programs. There is *maybe* 1 course). Many HBCUs are under resourced in a lot of aspects. They are not in a position to build capacity in data science. For instance, I can’t think of HBCUs that has a statistics department. Statistics is disbursed across mathematics, economics, psychology, political science, etc.

So I pose questions for your consideration —

  • How can data science be more socially responsible and culturally relevant?

  • What steps can we do to create an accessible learning platform for Black kids, students and professionals?

And a final note about this one slide: I intentionally gave the faces with no names of those in the inner circle and the names with no faces of those Black folks working in data-inspired and data-driven spaces. Learn about them, include them in your technical work and, by no means, is this slide sharing a comprehensive list of Blacks in data science.

Thank your time and attention.

~ Brandeis Marshall


#FooCamp #DataScienceWhileBlack

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