Data-driven decisionmaking in city government has expanded rapidly in recent years, driven by advances in technology and the digitization of many city services. The Urban Institute applauds the growth of data-driven decisionmaking, but they also recognize there are real concerns about the potential for bias in data used to guide public decisions. Left unchecked, unrepresentative data can directly lead to inequitable policy outcomes that harm vulnerable groups.
For example, many public works departments have started using citizen complaint data, like 311 requests, to allocate scarce city resources to perform sidewalk repairs and fix potholes. On the surface, this may seem like a way to make governments more responsive to citizen needs. The problem is that citizen complaint systems are more likely to be used by certain demographic groups, namely white residents, highly educated residents, and high-income residents. Follow this link to learn more.
Sourced from: Data@Urban