In Code Dependent: Living in the Shadow of AI, award-winning Indian-British journalist Madhumita Murgia, artificial intelligence (AI) editor at the Financial Times in London, recounts meeting a woman who set up a company that watched the data-labelling industry grow from its early years.

Data-labelling is the process of identifying raw data including images, text files, videos, etc, categorising the data, and adding informative labels to each in order to provide context that enables a machine learning model to learn from it. The woman’s company operated in Kenya, Uganda and India, where thousands of workers were engaged in this laborious and repetitive labelling work, a kind of back-end spine for AI models.

Such low-paying employment has lifted 50,000 people in East Africa out of poverty by offering digital work, including for dependents of workers, the company said in 2022.

“The great false hope of Silicon Valley is automation,” the founder told Murgia. “But we’re only pretending—it’s actually humans behind it.”

It is one of scores of examples from across the world through which Murgia tells the story of how AI is impacting ordinary people, exploiting cheap labour markets, exacerbating structural social inequities and more.

The book describes the impact of technology that marks children as future criminals, an app that brings medical diagnoses to a remote tribal community, deepfake sexual imagery that devastates women, among other tales, many of them cautionary stories on what could go wrong.

India, a major market and a labour market for AI developers, has been bullish about the sector, with government data stating that there was a 109.6% rise in private and public expenditure on AI during 2018, to reach US$ 665 million. By 2035, AI has the potential to add $ 1 trillion to India’s economy, according to the NITI Aayog, the government think tank.




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