Madhumita Murgia has written a book Code Independent exploring the grey and murkier areas of AI. She tells the story of data labelers of Kenya who contribute their labour to train the algorithms of self -driving cars. There is a story of a mother whose child is added to the list of potential criminals. The addition is not by a human agency but a machine that uses facial recognition technology with all its racial bias. The book goes beyond Silicon Valley. The book points out the global north-south divide.
Big Tech elite in Silicon Valley are paid hefty sums of money while the mundane monotonous repetitive task is outsourced to the poor populace of the developing world. It is referred to as data colonialism. This term was first used by academics Nick Couldry and Ulises A. Mejas.
AI jobs in Kenya and Philippines are handled by data labelers who could afford school education for their children out of their earnings for the first time or could avail of healthcare for their parents. They are doing digital jobs (maybe better than physical jobs in not so conducive conditions). The governments see these as employment generation. AI should bring prosperity to everyone, but there is no such thing happening in global south. AI still is a minimum-wage job. The workers sign an NDA : no-disclosure agreement. They cannot talk about all this to anyone, cannot unionize, and at times do not know who their employer is.
There is hype around AI as companies feel FOMO — fear of missing out.
People should understand the implications of this technology. They should understand the dynamics of change in the tech industry. Third, people should understand how AI affects other industries.
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