The Artificial Intelligence Illusion: How Invisible Workers Fuel the “Automated” Economy

While AI is celebrated as a driver of automation, its success hinges on an invisible workforce performing low-paid, precarious tasks under challenging conditions. This article unpacks the hidden realities of AI’s “human-in-the-loop” model and its profound implications for workers and society.

Artificial intelligence (AI) is often presented as a revolutionary force poised to automate vast swathes of the economy, displacing workers, and ushering in a “post-work” era. However, behind the sleek interfaces and impressive capabilities of many AI systems lies a hidden workforce of humans. This “human-in-the-loop” model reveals a more complex reality, one where AI is less about replacing humans and more about relying on workers with decent work deficits, such as low earnings, lack of social protection benefits and occupational safety and health to sustain the AI system. This is what we look at in our AI-enabled business model and human-in-the-loop (deceptive AI) article, which examines how these workers power automated systems and the implications for labour markets, society, and for the workers themselves.

Invisible labour in the development and deployment of AI

From self-driving cars to virtual assistants, the AI industry thrives on data. This data needs to be meticulously labelled, categorised, and annotated. This requires human intelligence and labour – both of which still cannot be replaced by machines. Such tasks are often outsourced to crowdworkers on digital labour platforms or to Artificial Intelligence-Business Process Outsourcing (AI-BPO) companies. These platforms fragment complex tasks into microtasks and offer small payments for each completed task. Crowdworkers, whom are also known as invisible workers because they often work behind the scenes, are essential for training AI algorithms on several functions, such as text prediction and recognition of objects.

Similarly, virtual assistants, marketed as autonomous tools, often rely on invisible workers who may be transcribing audio, verifying the virtual assistant’s understanding, or even performing tasks like scheduling meetings that AI may struggle with. Even sophisticated large language models with impressive capabilities rely heavily on human trainers to fine-tune their responses and mitigate biases, toxicity, and disturbing content. As a result, workers are routinely exposed to graphic violence, hate speech, child exploitation and other objectionable material. Such constant exposure can take a toll on their mental health and trigger post-traumatic stress disorder, depression, and reduced ability to feel empathy.[…]