The Rise and Fall (and Rise) of Datasets

The fast pace of development in machine learning research in the past two decades has been, in large part, fuelled by the availability of large benchmark datasets of images, videos, text and more. These make it possible to compare and evaluate algorithms, and help to define research goals. However, in recent years, the machine learning community has identified an alarming number of potential legal and ethical problems with many of the most popular image datasets, such as representational harms, effects of bias, privacy infringement and unclear or dubious downstream use.

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