There is a vast hidden workforce behind AI

Subscribe to enjoy similar stories. WHEN DEEPSEEK, a hotshot Chinese firm, released its cheap large language model late last year it overturned long-standing assumptions about what it will take to build the next generation of artificial intelligence (AI). This will matter to whoever comes out on top in the epic global battle for AI supremacy.

Developers are now reconsidering how much hardware, energy and data are needed. Yet another, less discussed, input in machine intelligence is in flux too: the workforce. To the layman, AI is all robots, machines and models.

It is a technology that kills jobs. In fact, there are millions of workers involved in producing AI models. Much of their work has involved tasks like tagging objects in images of roads in order to train self-driving cars and labelling words in the audio recordings used to train speech-recognition systems.

Technically, annotators give data the contextual information computers need to work out the statistical associations between components of a dataset and their meaning to human beings. In fact, anyone who has completed a CAPTCHA test, selecting photos containing zebra crossings, may have inadvertently helped train an AI. This is the “unsexy" part of the industry, as Alex Wang, the boss of Scale AI, a data firm, puts it.

Although Scale AI says most of its contributor work happens in America and Europe, across the industry much of the labour is outsourced to poor parts of the world, where lots of educated people are looking for work. The Chinese government has teamed up with tech companies, such as Alibaba and JD.com, to bring annotation jobs to far-flung parts of the country. In India the IT industry body, Nasscom, reckons annotation revenues could reach $7bn a