Data 4 Black Lives
By Carrie Diaz Eaton, Associate Professor of Digital and Computational Studies, Bates College
Last year, I was checking what’s trending on Twitter (@mathprofcarrie) and started seeing a lot of really cool posts from individuals I respect, such as Dr. Piper Harron (@pwr2dppl) and Dr. Cathy O’Neil (@mathbabedotorg), being retweeted by my community. They all had the same hashtag: #data4blacklives.
Let me back-up: Twitter and other social media platforms have the power to amplify conversations (in good ways or bad). I use it as a personal learning network (PLN) to become aware of opportunities, to keep connected in two-way conversations with people from afar, and to spread the news about what I find in my circles. Learning about this conference from my network is exactly the reason why I use Twitter as my PLN. What was this conference, and what was going on?
Data 4 Black Lives is a social movement, the product of MIT’s Yeshimabeit Milner’s grand vision for interrupting the impact that data and algorithms are having on systematically marginalized people. Cases were investigated by Dr. Safiya Noble’s book, Algorithms of Oppression, which documents the ways in which Google’s search, ranking, and monetization algorithms shape narratives about black girls. Consequences were also well explored by Dr. Cathy O’Neil’s book, Weapons of Math Destruction, in which algorithms designed to determine credit rates have used zipcodes of applicants as part of a riskiness algorithm - a system in which the most impoverished are hit with the highest loan rates and fees. It was established by MIT’s Joy Buolamwini, who found that the facial recognition system of top companies, a technology now employed by US police departments, worked extremely well at identifying and distinguishing white men, but systematically misclassified people of color and women, and particularly women of color.
So I signed up for the mailing list and registered as soon as registration was open for this year’s conference, and went with my new Digital Humanities colleague, Dr. Anelise Hanson Shrout, to MIT. Why? Well the first reason is that I am co-organizing an NSF INCLUDES-funded conference this April called “Bringing the Conversation of Inclusion and Data Science to the Ecology and Environmental Science Community,” so I felt like I needed to be learning from the leaders in the field. Second, I am a new faculty at Bates College this year. I was previously a mathematics professor at an environmental college and was recruited as an expert in interdisciplinary curriculum design to help build a new program in Digital and Computational Studies, in a way that embraces community and inclusivity as a cornerstone (just like the MAA Math Values!). Third, I suffer from a serious case of #FOMO (fear of missing out), and let me tell you - seeing all of the really cool Twitter #data4blacklives chatter made me what to be there to experience it for myself.
It would take me a hundred posts to tell you everything about this experience, so somehow I’ll try to hold myself back, and instead share with you the highlights from my Twitter feed. Disclaimer - Tweets sometimes reflect my own thoughts, often in response to the amazing speakers I was hearing, so I want to give credit also to everyone I heard from even if it was not an explicit quote.
In addition to being inspired and tweeting out what I was learning, I want to share one of the most significant realizations for me. This conference was not just academics coming together and trying to figure out how to improve some “othered” community. This conference invited community organizers alongside the data scientists - and not just to be data scientists or be more literate, but to collaborate with them, doing the community organizing that was also equally important.
As a network scientist and community organizer myself (of professional academic communities), I admit this was a major blindspot, even though this is not the first time I’ve heard this message. I have just never experienced how that could change everything, and ashamedly needed to have that experience to really understand. We often invite academicians with “lots of important papers” into our conversations. When was the last time we invited half our audience or more to just be the people in our local community to do the community organizing work for advocacy that they are best at? To ask them what they need to know from the data so that they can take action. To let them tell us where we are failing in terms of policy? And to trust them to take that information and create change.
As I write that out, I am reminded of the same tension that has occurred between mathematics and biologists - with mathematicians using unmeasurable parameters or making unrealistic assumptions that could lead to misleading outcomes. On the heels of trying to figure out what it looked like to be a boundary researcher - a true interdisciplinary mathematician, we were introduced to the idea of “team science” and “sustainability science” which suggested that complex problems need to involve all stakeholders and the lenses of multiple disciplines. That is a philosophy that seems to embrace the MAA Math Values: Community, Inclusion, Teaching and Learning, and Communication. To what extent do we practice these values and to what extent do we all have blind spots?