👉 Racial computing refers to the ways in which technology and algorithms can perpetuate, reinforce, or challenge racial biases and inequalities. It involves the analysis of how data, often collected and processed through digital systems, can reflect and exacerbate existing racial disparities in areas such as hiring, lending, criminal justice, and healthcare. For instance, facial recognition software may have higher error rates for people of color due to biased training data, or predictive policing algorithms might disproportionately target minority communities. Conversely, racial computing also offers opportunities to address these issues by developing more equitable algorithms and data practices that aim to mitigate bias and promote fairness.
