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I’m a former educator, gone data scientist/machine learning researcher. I originally planned to go into data science and machine learning to learn more about how data is appropriately utilized in the social sector. As an educator, I kept seeing irresponsible usage of data to judge students, teachers, and schools, instead of using data to help promote best practices. The punitive structure utilized, I learned, is a fairly normal practice in many social settings, and is what attracted me to learn more about data and machine learning ethics.
Through my work with DataKind, I developed my foundational knowledge around AI ethics, and helped develop a framework for how to execute data for good projects ethically. Soon after that work, I joined Gretel and then Arthur, as a researcher focusing on natural language processing, but more importantly fairness and transparency.
I now actively work on research projects related to fairness and transparency, where I open source code, write thought leadership posts, and generally try to align my work with product goals.