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Well-designed technologies that offer high levels of human control and high levels of computer automation can increase human performance, leading to wider adoption. The Human-Centered Artificial Intelligence (HCAI) framework clarifies how to (1) design for high levels of human control and high levels of computer automation so as to increase human performance, (2) understand the situations in which full human control or full computer control are necessary, and (3) avoid the dangers of excessive human control or excessive computer control. The methods of HCAI are more likely to produce designs that are Reliable, Safe & Trustworthy (RST). Achieving these goals will dramatically increase human performance, while supporting human self-efficacy, mastery, creativity, and responsibility., Comment: 15 pages, followed by 4 pages of references, 6 figures

The monthly Bureau of Labor Statistics Employment Situation Report is widely anticipated by economists, journalists, and politicians as it is used to forecast the economic condition of the United States. The report has broad impact on public and corporate economic confidence; however, the online access to this data employs outdated techniques, using a PDF format containing solely text and fixed tabular information. Creating an interactive interface for dynamic discovery on the BLS website could elicit more dialogue between the public and government spheres, drawing more traffic to government websites and triggering greater civic engagement. Our work suggests that the implementation of interactive visual analysis techniques to enable dynamic discovery leads to rapid interpretation of data as well as provides the means to explore the data for further insights. This paper presents two inspirational prototypes: a dashboard of interactive visualizations and an interactive time series explorer, allowing for temporal and spatial analyses and enabling users to combine data sets to create their own customized visualization.