Wikipedia is a classic example of how crowdsourcing can go wrong. The obvious problem is anonymity and the lack of accountability that goes with it.
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From James Zou and Londa Ziebinger at Nature: When Google Translate converts news articles written in Spanish into English, phrases referring to women often become ‘he said’ or ‘he wrote’. Software designed to warn people using Nikon cameras when the person they are photographing seems to be blinking tends to interpret Asians as always blinking. Word embedding, a popular algorithm used to process and analyse large amounts of natural-language data, characterizes European American names as pleasant and African American ones as unpleasant. Now where, we wonder, would a mathematical formula have learned that? Maybe it was listening to the wrong instructions back when it was just a tiny bit? Seriously, machine learning, we are told, depends on absorbing datasets of Read More ›