We have tried to predict the future since ancient times when shamans looked for patterns in smoking entrails. As this special package explores, prediction is now a developing science. Essays probe such questions as how to allocate limited resources, whether a country will descend into conflict, and who will likely win an election or publish a high-impact paper, as well as looking at how standards should develop in this emerging field. Social scientists and the machine learning community are acquiring new analytical tools to distinguish meaningful patterns from noise. New tools are exciting. But using software packages of the shelf, without understanding them fully, can lead to disaster. Several authors in this special section describe the importance of realistic goals that seek to balance machine learning approaches with the human element.
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