AI underpinned by developing world tech worker ‘slavery’

In dusty factories, cramped internet cafes and makeshift home offices around the world, millions of people sit at computers tediously labeling data.

These workers are the lifeblood of the burgeoning artificial intelligence (AI) industry. Without them, products such as ChatGPT simply would not exist. That’s because the data they label helps AI systems “learn.”

But despite the vital contribution this workforce makes to an industry that is expected to be worth US$407 billion by 2027, the people who comprise it are largely invisible and frequently exploited.

Earlier this year nearly 100 data labelers and AI workers from Kenya who do work for companies like Facebook, Scale AI and OpenAI published an open letter to United States President Joe Biden in which they said:

To ensure AI supply chains are ethical, industry and governments must urgently address this problem. But the key question is: how?

Data labeling is the process of annotating raw data — such as images, video or text — so that AI systems can recognize patterns and make predictions.

Self-driving cars, for example, rely on labeled video footage to distinguish pedestrians from road signs. Large language models such as ChatGPT rely on labeledtext to understand human language.

These labeled datasets are the lifeblood of AI models. Without them, AI systems would be unable to function effectively.

Tech giants like Meta, Google, OpenAI and Microsoft outsource much of this work to data labeling factories in countries such as the Philippines, Kenya, India, Pakistan, Venezuela and Colombia. China is also becoming another global hub for data labeling.

Outsourcing companies that facilitate this work include Scale AI, iMerit, and Samasource. These are very large companies in