New approach can help organizations scale their data science efforts with artificial data and crowdsourcing.
Although data scientists can gain great insights from large data sets — and can ultimately use these insights to tackle major challenges — accomplishing this is much easier said than done. Many such efforts are stymied from the outset, as privacy concerns make it difficult for scientists to access the data they would like to work with.
IN 1907 John D. Hertz, the owner of a taxi firm in Chicago, asked some academics at the University of Chicago to do a piece of research for him. He wanted to know what colour he should paint his cabs in order to make them stand out among the sea of black vehicles that then inhabited American city streets. The researchers’ conclusion was: yellow. Now, more than a century later, a group of researchers at a different university have concluded that yellow was a wise choice for other reasons, too. In a study just published in the Proceedings of the National Academy of Sciences, Ho Teck Hua of the National University of Singapore and his colleagues show that yellow taxis are less likely to be involved in accidents.