Columbia University linguist John McWhorter opines on the impact AI translation might have on second language learning. We already know that Americans and UK folx are the most monolingual populations in the world; fewer than one in 100 American students currently become proficient in a language they learned in school. McWhorter argues that AI might offer utilitarian practicality for casual users, e.g. translating useful phrases on the fly while traveling: "With an iPhone handy and an appropriate app downloaded, foreign languages will no longer present most people with the barrier or challenge they once did." Yet McWhorter also says, "I don't think these tools will ever render learning foreign languages completely obsolete. Real conversation in the flowing nuances of casual speech cannot be rendered by a program, at least not in a way that would convey full humanity." He also suggests that genuinely acquiring a language will still beckon a few select people, e.g. those relocating to a new country, those who'd like to engage with literature or media in the original language, as well as those of us who find pleasure in mastering these new codes: that language learning will become "an artisanal pursuit" of sorts.
The U.S. National Library of Medicine launched the Unified Medical Language System (UMLS) in 1984 to help computers understand biomedical meaning as well as retrieve and integrate information from various electronic sources such as patient records and biomedical literature. From the set up of parameters for vocabulary sources, to the release of the UMLS "Metathesaurus," this article takes a look at how a vocabulary database tackled the most significant barrier to the application of computers in medicine, the lack of standard language in medicine.
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