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But because a machine learning model learns the boundaries of its world from its input data, just three people informed how any model using that dataset would interpret if 'childbirth' was emotional. This led to a perspective that has informed all of my work since: a dataset is a worldview. It encompasses the worldview of the people who scrape and collect the data, whether they're researchers, artists, or companies. It encompasses the worldview of the labelers, whether they labeled the data manually, unknowingly, or through a third party service like Mechanical Turk, which comes with its own demographic biases. It encompasses the worldview of the inherent taxonomies created by the organizers, which in many cases are corporations whose motives are directly incompatible with a high quality of life.

Have you ever noticed that when you present people with facts that are contrary to their deepest held beliefs they always change their minds? Me neither. In fact, people seem to double down on their beliefs in the teeth of overwhelming evidence against them. The reason is related to the worldview perceived to be under threat by the conflicting data.