Civic Analytics NSF Grant Profiled

....this project addressed bias in citizen reports data to improve the fairness of data-driven decision-making in the urban context by: (1) building statistical machine learning models to estimate reporting rate biases, (2) providing tools to city decisionmakers, policymakers and planners to understand and visualize the spatial and socioeconomic dependence of reporting behaviors, and (3) developing methods to account for observed biases in responding to resident reports. In other words, this project developed methods to compensate for bias in reporting data to improve allocation of city services.