Photo Courtesy of Color Code
On Thursday, the ColorCode committee learned that Columbia University Computer Science professor Satyen Kale assigned to his Machine Language (COMS 4117) class a competition “to produce the eponymous cyborg law enforcer.” Drawing on data from the NYPD’s “Stop, Question and Frisk” records, students have been asked to create a machine learning algorithm to “decide when a suspect it has stopped should be arrested” based on characteristics ranging from “sex” and “race” to “suspect was wearing unseasonable attire”, “suspicious bulge”, and “change direction at sight of officer”. Stop and Frisk is a violently racist program that allows police to stop, question, and frisk any pedestrian who arouses “reasonable suspicion.” Numerous studies and investigations of the NYPD’s own data have shown that Stop and Frisk disproportionately targets Black people. It has torn apart Black communities in the city and contributes to a system of mass incarceration and policing that brutalizes, incarcerates, and kills Black people across the nation. The program has even been deemed unconstitutional by federal courts.
That a Columbia professor would ask students to implement a program that reproduces and aids Stop and Frisk policing with zero acknowledgement of the violence and harm inflicted by the actual program–and in fact suggest that machine learning algorithms like this constitute “the future” of machine learning applications— is an egregious example of racist, ahistorical, and irresponsible pedagogy. Data are not apolitical. Algorithms are not objective. To teach technical skills without also teaching antiracist, antioppression developing principles is unforgivable, despicable, and dangerous. For us, as students of color who also are coders, entrepreneurs, and engineers, assignments like this confirm feelings of exclusion and isolation accumulated over many semesters here–being one in a only handful of Black students in a lecture hall, for example, or graduating from SEAS not having had even a single Black professor. It confirms the department and university’s disregard for our wellbeing as students of color, which always is intertwined with the wellbeing of our communities.
Moving forward, ColorCode demands that this Machine Learning assignment be revoked, and that the professor issue an apology addressing the concerns above. We demand that students in the class be provided with alternate ways to receive credit. We demand that the professor and the department acknowledge these concerns, apologize, and make significant, structural changes to ensure this does not happen again. Finally, we support the demands of Mobilized African Diaspora/BCSN and in particular add our voices to demand that the School of Engineering commit to hiring more Black professors and underrepresented professors of color.
ColorCode is a group focused on getting people of color into the technology sector. To respond to this op-ed or submit one of your own, email firstname.lastname@example.org