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Enter the data labelling professional

Thursday, 16 November, 2017

You hear the words “artificial intelligence” and what do you think of? Dystopia vs. Utopia. Stephen Hawking warning us to leave Earth and Elon Musk sounding the alarm about a Third World War. On the other hand, we have Bill Gates saying there’s no need to panic about machine learning and Mark Zuckerberg urging us to cool the fear-mongering. AI and apprehension and confusion go hand-in-hand today. The fear of a future unknown is combined a present dread that AI will take our jobs away, but every disruptive technology has seen the replacement of human workers. At the same time, we’ve been ingenious enough to develop new jobs and AI could be every bit as much a job generator as a job destroyer.

A recent report by Gartner predicts that while AI will eliminate 1.8 million jobs in the US, it will create 2.3 million jobs. The question is: Which kind of jobs will these be? Data scientists, with qualifications in mathematics and computer science, will be eagerly sought and highly paid, but what about the masses? Three words: Data Labelling Professional.

Imagine you want to get a machine to recognize expensive watches, and you have millions of images, some of which have expensive watches, some of which have cheap watches. You might need someone to train the machine to recognize images with expensive watches and ignore images without them. In other words, data labelling will be the curation of data, where people will take raw data, tidy it up and organize it for machines to process. In this way, data labelling could become an entry-level job or even a blue-collar job in the AI era. When data collection becomes pervasive in every industry, the market for data labelling professionals will boom. Take that, Stephen Hawking.

watches


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