In 1989, American author Norman Cousins wrote that poetry was the key to preventing computers from dehumanising us: “The company of poets may enable the men who tend the machines to see a larger panorama of possibilities than technology alone may inspire. Poets remind men of their uniqueness.”
Twenty-six years later, researchers in the US are testing that idea, starting with search engines and image databases. Any nuance or metaphor gets lost on an engine such as Google: search “sorrow”, for example, and you’ll get pictures of people crying, whereas a human might associate a more varied range of images, such as a foggy seascape or an empty forest. This is because computers use metadata (the data search engines associate with the millions of digital objects out there, from YouTube videos to Instagram pictures) in a completely different way to the human brain. Our human “metadata” tends to be far more symbolic and less literal. But what if an image bank was populated by poems? Can robots learn from our view of the world?
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