Abstract. Automation of surveillance is a growing trend. In domains analogous to public health surveillance, automation has led to several well-documented problems, including decision biases, neglect, and errors of commission and omission. We review results from these domains, and propose means to mitigate these potential problems in the context of automated public health surveillance systems.