In “The Data Dilemma of Racial Profiling” episode of the MIT Institute for Data, Systems, and Society (IDSS) podcast Data Nation, S. Craig Watkins (MIT MLK 2021-22 Visiting Professor) discusses how data is used against marginalized communities and how it should be used to protect and serve them. Watkins is joined by Brandon Del Pozo, former police chief in New York City and Vermont.
When it comes to racial profiling, data both hurts and helps. Hosts Liberty Vittert and Scott Tranter investigate the damage policing data can do to communities and how data can also be used to solve the problem. A Native American man gets pulled over for driving a nice car, a black man is arrested in front of his family for a crime he didn’t commit – innocent people are at risk because of racial profiling. But to stop profiling, you have to first identify it, and that’s not as easy as it seems. Liberty and Scott are going deep into data in this episode, investigating how data is used against marginalized communities, and how it should be used to protect and serve them. They go to the experts to find out which methods are failing, what solutions can mitigate the dangers of facial recognition technology and smart policing, and how we know we’ve succeeded in ending profiling.