7 posts
Myth of the impartial machine

In its inaugural issue, Parametric Press describes how bias can easily come about when working with data: Even big data are susceptible to non-sampling errors. A study by researchers at Google found that the United States (which accounts for 4% of the world population) contributed over 45% of the data for ImageNet, a database of more than 14 million labelled images. Meanwhile, China and India combined contribute just 3% of...

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Fake correlation

Gabriel Rossman, a sociology professor at UCLA, describes colliders — or when correlation does not equal causation and the former might not even exist either. Referring to the simulated plot above, Rossman uses Hollywood actor selection as an example: For instance, suppose that in a population of aspiring Hollywood actors there is no correlation between acting ability and physical attractiveness. However assume that we generally pay a lot more attention...

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