Yeshimabeit Milner is addressing systemic racism with algorithms and big data.
Data 4 Black Lives
Algorithms may be hidden from most of us but they’re shaping many aspects of our lives. Who’s creating them, and what background and biases do they bring? Entrepreneur and data scientist Yeshimabeit Milner is sparking a movement of technologists, mathematicians, and community changemakers who want to use data to create a more equitable world. Ashoka’s Lorena García Durán spoke with her about why she started Data 4 Black Lives and what the big opportunities are.
Yeshimabeit, let’s start with you – you love data. How did your passion start?
Growing up, I was always curious and constantly looking for ways we can look at problems absolutely differently. That’s what brought me to data – getting to change things happening in my community, and see the results. At twenty-two, right after college, I went home to Miami to look into why Black infant mortality rates are disproportionately so high. With data from 300 moms we were able to change policies at the country’s largest public hospital. Data is a powerful tool for social change.
Fast forward to 2016 when you started Data 4 Black Lives – what were you seeing?
That technology was influencing our lives in ways we had no control over, no accountability. This is a process that we now call datafication – whether it’s Equifax and FICO credit scores that determine whether or not you qualify for housing, or risk assessments and facial recognition, or Facebook newsfeeds that continue to threaten our democracy. I was seeing the threats and also the opportunity to use technology to understand deep structural issues like systemic racism. The issues already existed of course – but technology was making them more obvious, scary, and urgent. I knew that 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. We launched the organization with a conference that sold out within a few days. That’s when I knew that we were tapping into something powerful and we should keep going.
Where was interest coming from – people in technology jobs?
For the most part, yes. Data science friends from school were working in places like Facebook, Instagram, Tumblr. They were really concerned about the direction the country was headed, and really concerned that their literal everyday jobs were being weaponized against vulnerable communities, in-particular Black and brown communities. They wanted to find a way to plug in, but they didn’t know how, besides maybe showing up to a protest. At that first conference, I was also surprised by how many Black and Latinx data scientists and software engineers showed up. These folks, even though they had the experience of being a person of color, were in spaces where they were told, “In order to be objective, you can’t bring in that experience. You can’t talk about racism, you can’t talk about discrimination.” That left them feeling so alone.
An example of a problem you’d want to work on?
Sure. Systemic racism shows up in many places, including housing and finance – so developing mortgage underwriting algorithms that are less racist than individuals is something we’re interested in. Our teams would want to look at how do we create machine learning systems that aren’t recreating history, but making it so that folks who qualify will be able to get a mortgage – and from there own a home and build wealth.
And today – what does the network look like?
We’re 4,000 software engineers, technologists, computer scientists, mathematicians, and community changemakers. We are building up support at many universities and are chartering D4BL Hubs in cities all across the country now. Why are people choosing to be part of Data 4 Black Lives? Because there has been no other place for them. Some other groups do data analysis really well, but we bring people into a movement that works on actual solutions informed by people on the ground, people in academia, people at tech companies, and leaders in data science and technology – elected officials, industry leaders, and so on. Movement and community building may be non-technical strategies, but they work.
What traction are you seeing from business?
People in business are starting to see the ways data is absolutely transforming their work and future. They’re seeing that it’s not good for the bottom line when you have an algorithm that discriminates against people – you might be sued for it, or it just erodes business integrity. They are also hearing from consumers about many issues that have to do with data who are saying, “This is what needs to change. We want to be able to take pictures and post them online. We want our packages to be delivered quickly, but not at the expense of our privacy or the planet.” Many business schools are totally changing their curriculum and bringing folks like me to speak, not because I’m going to say, “Hey, this is the threat,” but, “Here are all these examples that we’re seeing in our movement of how folks are using data positively.”
How do you navigate partnerships with big tech companies?
For example, in the case of Google, we were able to find a way by saying, “Hey, maybe Google, as a very massive company, has its issues, but who are the individuals within this company who really want to see change happen? How do we connect with them?” We went from Google sponsoring our conference one year, to their engineers partnering with community changemakers to lead workshops on how to use distance thinking and all these very technical tools. The Google employees who participated said, “This is one of the first conversations that I’ve had around politics, democracy, and racial justice that actually makes sense to me.” These kinds of partnerships have big ripple effects.
What’s ahead for Data 4 Black Lives and the data for good movement?
One of the most beautiful things about technology is that it’s accessible to everyone. You can go online and you can learn, whether it’s as complicated as building a machine learning model, or as simple as, “How do I survey people at our school to figure out how people really feel about climate change?” You just need to have imagination and believe in yourself. So this movement is for everybody and there are many ways to connect – come to our conference, sign up on our website. And yes, we especially want to reach and include younger people and build up their leadership. It’s a good strategy. And I have to also think – someone saw something in me when I was young, and they nurtured that.
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