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When it comes to the popular naming of infectious diseases, xenophobia has long played a prominent role. Susan Sontag, in her 1988 work, AIDS and Its Metaphors (a follow-up to her extended essay from a decade earlier, Illness as Metaphor), observed that "there is a link between imagining disease and imagining foreignness. It lies perhaps in the very concept of wrong, which is archaically identical with the non-us, the alien." Cognizant of how geographic labels have been unfairly used in the past, the WHO (World Health Organization) introduced a new set of best practices for naming infectious diseases, in 2015. Geographic names are to be avoided in order to "avoid causing offense," though the WHO did not insist that already established names like Middle East Respiratory Syndrome, or MERS, should be retroactively changed.

Bradley Hayes, a post-doc student at the Massachusetts Institute of Technology, has invented @DeepDrumpf, an amusing bit of artificial intelligence. DeepDrumpf is a bot trained on the publicly available speech transcripts, tweets, and debate remarks of Donald Trump. Using a machine learning model known as a Recurrent Neural Network, the bot generates sequences of words based on priming text and the statistical structure found within its training data. Created to highlight the absurdity of this election cycle, it has amassed over 20,000 followers and has been viewed over 12 million times -- showcasing the consequences of training a machine learning model on a dataset that embodies fearmongering, bigotry, xenophobia, and hypernationalism. Here's a sample tweet: "We have to end education. What they do is unbelievable, how bad. Nobody can do that like me. Believe me."