A new book by Cambridge researcher Eleanor Drage argues that artificial intelligence isn't magic—it's the product of exploited labour in mines, factories, and data centres around the world. What If We Got AI Right? challenges citizens to see through the marketing hype and recognize that the "cloud" is just someone else's computer, and AI "hallucinations" are system errors caused by poor data labelling.
The Human Labour Behind the Machine
Drage, an assistant research professor at the University of Cambridge's Leverhulme Centre for the Future of Intelligence, insists that humans need to recognize AI's "humanity." She means the hours of human labour required to extract silicon and quartz, manufacture microchips, and label the vast datasets that train AI models. "It's merely an illusion that the labour force is disappearing: work is simply shifting, from artists to data labellers and from marketeers to engineers," Drage wrote, though The Guardian's reviewer questioned that claim.
Her critique of big tech is comprehensive. AI algorithms perpetuate and entrench pre-existing biases. Tech giants have become too big to care about ethics. A handful of executives have amassed too much power. AI is being rolled out without consent and without consideration for planetary health. If citizens want to wrest power from the companies building AI, Drage argues, they need to understand what those companies are actually selling.
Big Tech Can't Deliver Utopia While Chasing Profit
Drage's central argument is blunt: big tech cannot deliver on utopian promises while it continues to chase profit and power above all else and serve the interests of a narrow few. She believes the cultural obsession with AI-induced apocalypse distracts from practical conversations about making AI safer—by giving citizens more power over how their information is used and how AI models are trained and regulated.
Her research background includes AI-powered recruitment and the dangers of AI in law enforcement. She co-designed a toolkit to help AI companies act ethically and comply with EU regulations, which she described as a "cornerstone of utopianism" because it shifts the focus to how AI is built and made. For Drage, utopia isn't a destination but the "process of working together to develop a fairer world."
What Ethical AI Could Look Like
The book includes examples of AI designed with community needs in mind. Mumkin is an app that facilitates difficult conversations about female genital mutilation in India. Kuini is an AI chatbot built to help Māori women quit smoking. These projects suggest what's possible when AI development prioritizes social outcomes over shareholder returns.
The Guardian's reviewer noted that Drage doesn't mention AI's potential to improve drug discovery and disease detection. The review ended by asking, "What if we got AI right?" After reading the book, the reviewer said, they couldn't say they really knew.
Why This Matters:
Drage's book arrives as the European Union finalizes AI regulation and citizens across the continent demand greater accountability from tech platforms. Her argument that AI is built on hidden human labour—from mine workers to data labellers—challenges the narrative that automation will simply replace jobs with leisure. Instead, she shows how work is being reorganized in ways that obscure exploitation. Her call for citizens to reclaim power over AI development speaks directly to Europe's regulatory ambitions: the EU AI Act aims to set global standards, but enforcement depends on public pressure and democratic oversight. If big tech continues to prioritize profit over ethics, the gap between regulatory promise and lived reality will only widen. Drage's insistence that utopia is a process, not a destination, reframes AI governance as an ongoing democratic project—one that requires transparency, consent, and a willingness to challenge corporate power at every turn.