What does data science (and analytics, and artificial intelligence) have to do with Black History Month?
If one takes a wider view of history, the answer is “A lot!” and after reading this article I hope you’ll agree. One caution — I realize my point of view is informed by my own privilege, and the stories and links I note below are not from my own lived experience. But the topic, and the lived experience of Black data analytics, data science, and artificial intelligence (AI) professionals, are all too important not to share. With that in mind, I think there are important connections to make — and not obvious ones — with Black History Month.
The Oxford English Dictionary defines history as “The branch of knowledge that deals with past events.” But what does one do, when the dominant culture provides an imperfect record of past events, as is the case for Black history? A good starting point is to follow the scholars and thinkers featured in Black Perspectives, the award-winning blog of the African American Intellectual History Society (AAIHS). And of course, keep learning more from and about Black historians like Dorothy Porter Wesley, John Hope Franklin, and John W. Blassingame, and their essential work.
But let’s go further. Let’s include Black practitioners in the field of data science, analytics, and AI who are innovating and making history.
The work done by Black practitioners and researchers is vital; AI and machine learning (ML) have the potential to transform the world in positive, sustainable ways. AI’s positive impact is and will continue to be undermined, however, unless these known issues are addressed:
- Bias in artificial intelligence is a major issue, one driving new regulation
- Data sets for training and testing AI and ML systems often have bias that originates from structural racism
- There’s a history of disproportionate negative impact on Black communities from these issues.
Ensuring data science and analytics projects are driven by diverse teams, teams that are led by and include Black practitioners and researchers, can help mitigate the historic and present harms from biased AI and ML.
Beyond that, the work’s technical aspects can be considered a form of history — after all, even the fastest “real-time” data stream is a snapshot-in-time record of past events. In this framing, the data used in AI and ML workflows is historic. By using (and critiquing) these bits and bytes, Black AI and ML practitioners and researchers are transforming history to create the future NOW.
This Black History Month, take time to learn more about the work done by Black practitioners in data science, analytics, and AI
In this connected context, below are a dozen Black data analytics, data science, and AI leaders whose perspectives are shaping the future, even as they make history through their contributions. I acknowledge that this is an arbitrary and very incomplete list; to offset its shortcomings, I encourage you to discover more “Black in Data,” “Black in AI,” and “Black in Data Science” researchers and practitioners, and feel free to share them in comments.
Rediet Abebe. Dr. Abebe is Assistant Professor of Computer Science at the University of California, Berkeley and a Junior Fellow at the Harvard Society of Fellows. Her research is broadly in the fields of algorithms and artificial intelligence, with a focus on inequality and distributive justice concerns. Twitter: https://twitter.com/red_abebe
Ruth Agbakoba. Dr. Agbakoba has an extensive background in health informatics, digital health and eHealth from working on the UK’s largest innovation program in healthcare to date and leading on the evaluation of Scotland’s First National Digital Health and Wellbeing Service. Twitter: https://twitter.com/RuthAgbakoba
Teneika Askew. Teneika Askew is an Analytics Leader with more than 9 years of experience providing analytics, business process improvement and consulting services. She specializes in data analyses around financial, talent and operational data and driving workforce strategies for Fortune 500 companies. Twitter: https://twitter.com/teneikaask_you
Ruha Benjamin. Dr. Benjamin is a professor in the Department of African American studies at Princeton University where she studies the social dimensions of science, technology, and medicine. She is also the founding director of the IDA B. WELLS Just Data Lab, and a well-known author. Twitter: https://twitter.com/ruha9
Abeba Birhane. Abeba Birhane is a cognitive science Ph.D. researcher at the Complex Software Lab in the school of computer science at University College Dublin, Ireland. Her interdisciplinary research sits at the intersection of complex adaptive systems, machine learning, and critical race studies. Twitter: https://twitter.com/Abebab
Uché Blackstock. Dr. Blackstock is a Harvard-educated physician and thought leader on bias and racism in health care, a former Associate Professor in the Department of Emergency Medicine and the former Faculty Director for Recruitment, Retention and Inclusion in the Office of Diversity Affairs at NYU School of Medicine. Twitter: https://twitter.com/uche_blackstock
Joy Buolamwini. Dr. Buolamwini’s research has a global audience, and she has championed the need for algorithmic justice at the WEF and the UN. She serves on the Global Tech Panel convened by the European Commission to advise world leaders and technology executives on ways to reduce the harms of A.I. Twitter: https://twitter.com/jovialjoy
Timnit Gebru. Dr. Gebru is the founder and executive director of the Distributed Artificial Intelligence Research Institute (DAIR). Prior to that, she notes that she was fired by Google in December 2020 for raising issues of discrimination in the workplace, where she was serving as co-lead of the Ethical AI research team. Twitter: https://twitter.com/timnitGebru
Jordan Harrod. Jordan Harrod is an American research scientist and YouTuber who works on neuroengineering, brain-machine interfaces, and machine learning for medicine. She writes, “I’ve always been interested in the ways that we increasingly interact with AI and algorithms, from social media, to education, to the military, and much more!” Twitter: https://twitter.com/JordanBHarrod
Yeshimabeit Milner. Founder of and Executive Director of Data For Black Lives, Yeshimabeit Milner has worked as a movement builder, technologist, and data scientist. She is an Echoing Green Black Male Achievement Fellow, an Ashoka Fellow, and was recently honored as a Forbes “30 Under 30” social entrepreneur. LinkedIn: https://www.linkedin.com/in/yeshimabeit-milner-a7788944/
Deborah Raji. A Mozilla Fellow, Deborah Raji is researching algorithmic auditing and evaluation, has worked closely with the Algorithmic Justice League on several award-winning projects concerning bias in computer vision, and has been a research fellow at the Partnership on AI and AI Now Institute at New York University. Twitter: https://twitter.com/rajiinio
Simone Webb. Dr. Webb is a Research Associate in Bioinformatics at Newcastle University (UK) and Visiting Scientist at Wellcome Sanger Institute (UK). Specializing in the fields of single-cell RNA sequencing analysis, immunology, and hematopoiesis, she also has been involved in higher ed equity, community building, and voluntary scientific outreach work. Twitter: https://twitter.com/SimSci9
There are many others whose work matters — follow #BlackInData, #BlackInDataScience, and #BlackInAI hashtags on Twitter to learn more from their work, their experiences, and their perspectives.
It’s not enough to recognize these leaders; those with privilege must support their work
In the case of data science and AI, there’s much future Black history being made this Black History Month. It’s vital to not only recognize and celebrate, but also work with and for those most impacted to change structures and institutions.
Some resources that can help readers learn more and take the next step:
The Algorithmic Justice League. “Through a combination of art, research, policy guidance and media advocacy, the Algorithmic Justice League is leading a cultural movement towards equitable and accountable AI. This requires us to look at how AI systems are developed and to actively prevent the harmful use of AI systems. We aim to empower communities and galvanize decision makers to take action that mitigates the harms and biases of AI.”
Data For Black Lives. “Data for Black Lives is a movement of activists, organizers, and mathematicians committed to the mission of using data science to create concrete and measurable change in the lives of Black people.” From Forbes: “…before we change the algorithms, before we change where the data is coming from, we have to change the people who are in charge of all this. That’s where the idea for Data 4 Black Lives came from.”
Distributed Artificial Intelligence Research Institute (DAIR). “We are an interdisciplinary and globally distributed AI research institute rooted in the belief that AI is not inevitable, its harms are preventable, and when its production and deployment include diverse perspectives and deliberate processes it can be beneficial. Our research reflects our lived experiences and centers our communities. … Instead of constantly working to mitigate the harms of AI research performed by dominant groups without an analysis of potential risks and harms, we encourage a research process that analyzes its end goal and potential risks and harms from the start.”
I hope you’ll take the time to follow and support the people and organizations mentioned above.
