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​COMPAS: A Machine Learning Algorithm beyond the code

This is a presentation of my research on the COMPAS algorithm, a tool for predicting recidivism, that was​ exposed as biased against Black and Latinx people by ProPublica, an independent news agency in 2016.

In this presentation I begin by describing who creates this technology and the Business to Business model attached to it. I dig into the assumptions that the algorithm is based upon and continue by explaining different avenues to explore the bias in the algorithm and a number of factors that contribute to its failure.

I include reflections on the impact of this tool for the crisis of mass incarceration, and highlight the need for an ecosystem that enables communities to deal with harm. I conclude with a commentary on the social effects of this technology, especially as it contributes to the construction of imaginaries about Latinx and Black people, often reinforcing stereotypes, and directly damaging these communities.
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The narrative attached to this presentation is located within the context of Design education. I invite students and facilitators to question assumptions that are built within the technologies we develop and the larger socio-political effects of our practice.