Algorithms are hidden from most of us, yet they are shaping many aspects of our lives — and they perpetuate systemic racism.
To understand how this happens, and how we can correct it, we turn to Yeshimabeit Milner, a data scientist, social entrepreneur, and Ashoka Fellow. In 2016, Yeshi started Data 4 Black Lives, a community of mathematicians, tech experts, and changemakers who are using data and movement-building as tools for a more equitable world. Ashoka’s Konstanze Frischen spoke with Yeshi this week. Here are our highlights:
An early spark to find solutions
Yeshi grew up in Miami, the daughter of a single immigrant mother. School was a refuge for her, but in high school, fellow students witnessed a vice principal put a student, a 14-year-old, in a chokehold. In response, students organized protests, and Yeshi joined in. She shares what happened next, when they asked themselves: “Beyond protests, what can we do?”
A case study in encoded bias: credit scores
Like algorithms, systemic racism is hidden yet affects so many aspects of our lives. Yeshi drills down on one place it surfaces, with far-ranging consequences for Black communities: FICO and credit scores. These are the three-digit numbers that signal credit-worthiness to conventional lenders, determining whether you can buy a house, start a business, or finance an education. Here’s Yeshi on the creation of credit scores and why assumptions about tech must be challenged, even if intentions seem on the mark:
Data, health equity, and Covid-19
Yeshimabeit has worked on data and health outcomes since right after college. At age 22, she gathered data from 300 moms at the country’s biggest public hospital (in Miami) in order to understand why Black infant mortality rates are disproportionately so high. Fast forward to today: when Covid surfaced in the U.S. in March, she and Data 4 Black Lives went immediately to the data:
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