World Bank: between 150 and 430 million people now do the hidden data work that keeps AI running

# TL;DR A new documentary reveals that AI systems rely on a hidden global workforce of between 150 and 430 million low-paid data workers—often refugees or people in countries with economic crises—who label, annotate, and moderate data under exploitative conditions, while NDAs and corporate secrecy keep their labor invisible. ## The Hidden Workforce Behind AI AI is often portrayed as autonomous, intelligent, and self-sufficient. But as sociologist and computer scientist Milos Micevic, who leads the Data, Algorithmic Systems and Ethics research group at the Vitam Institute, explains, "When we talk about AI and so-called intelligent autonomous systems, we are talking about human beings working behind the scenes. AI is just a bunch of labor, a bunch of resources, a bunch of labor coming together to produce an outcome. I think most people don't know this—probably intentionally. It's meant to create a narrative, to create a myth around these systems. The labor and the resources component are deliberately hidden from public view." ## The Scale of Data Labor A World Bank report published last year estimated that between 150 million and 430 million people worldwide are employed as data workers—people who generate, label, or process the data that AI systems need to learn. The number has grown exponentially over the past year. Othmane Rani, Senior Economist at the International Labour Organization (ILO), notes, "It is time to step back and understand to what extent these things are AI and to what extent they are human participation. There are many invisible human workers behind AI doing data work, feeding data into the system so algorithms can develop further and models work properly." ## What the Work Actually Entails Data work takes many forms. Anab Tas, a 29-year-old from Kolkata, India, currently pursuing a master's degree, works for a company that does annotation and labeling of images and text. "Currently I am doing image classification," he says. "We get images and options—active fire, smoke, foggy, or clear. If a building is burning, I classify it as active fire. Then I move to the next." He also labels points on images—water, roads, trees—so that systems like autonomous cars can recognize objects. "The purpose is to make sure the autonomous vehicle can detect everything around it. Data workers basically label what is a car, what is a bathroom, what is a bicycle, what a pavement looks like, what a shrub is, so the car can identify them easily." The work is continuous because models are built at a specific moment but the world changes daily. "You have to keep feeding the system with information," Tas explains. "AI needs data to build models." ## Targeted Outsourcing and Exploitation The vast majority of data work is outsourced to the Global South. Researcher Milos Micevic states, "It is not random. It is most likely by design. These platforms and BPO companies tend to target specific countries that have economic crisis, low wages. Why is this only happening in the Global South? Because of weak institutions, huge unemployment, workers willing to accept anything, labor rights that don't exist for many. Or perhaps it happens in the Global North, but not by citizens—by refugees or immigrants. They target desperate populations." The pay is never enough to lift workers out of poverty. "They pay just enough for workers to get by for today, but tomorrow? You never know." One case in the documentary shows Finnish female prisoners earning €3 per task, with a total of €462 after two months in prison. The company's AI tool is used for the construction industry. On the platform Mindrift, one task pays $0.83. Workers receive 12 tasks per day, earning about $9. Some work 45 to 60 hours per week. One Ukrainian refugee named Anna, who moved to Bulgaria with her daughter in 2022, says, "I am not allowed to reveal my income. My salary is confidential. I cannot talk about it. It is not easy because I have a child. My salary is often not enough, so I have to find another job. I currently have two jobs just so we can live, not just survive." ## The Human Cost: Mental Health and Secrecy The emotional toll is severe. Fenn Makila, who has worked with AI for over three years as a content moderator, says, "At first it wasn't hard, but over time I realized I had frequent nightmares, especially after reviewing murder or rape cases involving minors or children. If I saw a lot of dead bodies during the day, I couldn't sleep at night. I developed anxiety. I couldn't go out, couldn't go to crowded places. I feel I am no longer myself. I was an outgoing person, but now I stay alone. That contributed to depression, which is why I decided to quit. Today, traces of PTSD remain. I still attend therapy. My colleagues also suffer from the same symptoms—insomnia, anxiety, and PTSD in different ways." Workers sign strict NDAs preventing them from naming the clients they serve. "They made us sign a non-disclosure agreement that limits what I can say," says one worker. "Once I say it, they will spread it, and I could be imprisoned for more than 10 years." The documentary notes that major tech companies such as Amazon, Google, OpenAI, and Meta are the end clients. One particularly toxic case involved workers in Kenya. "At least 90% of the data we reviewed, in terms of toxic content, was from OpenAI. The dataset sent was nearly 100% toxic, 99.99% actually. It was entirely disturbing and very toxic." The documentary argues that this is by design: AI systems need to learn both normal and extreme content, so companies outsource the most gruesome work to the cheapest labor markets. ## Conclusion: The Myth of Autonomy The documentary concludes that the hidden labor behind AI is not a side effect but a deliberate strategy. By keeping the workers invisible, tech companies maintain the myth that AI is autonomous, intelligent, and free of human cost. As Milos Micevic put it, "Hiding the labor is very intentional—it's part of creating a myth around these systems." The irony is that the more "intelligent" the AI appears, the more invisible human work it actually requires. Source: [https://youtu.be/ND7owjmtPNo](https://youtu.be/ND7owjmtPNo)