AI Is a Human Product, Not a Magic Force. A New Book Wants You to Know the Difference.

Key points

• Eleanor Drage's book argues that AI is built on human labour, from mining raw materials to labelling training data, not on any mysterious intelligence.
• Drage says big tech companies cannot deliver their utopian promises while prioritising profit over public interest.
• The cultural obsession with AI-caused extinction, she argues, distracts from practical fixes that could make AI safer right now.
• Demystifying marketing language, such as "the cloud" and "hallucination", is a concrete way citizens can push back against tech company narratives.

The word "artificial intelligence" carries a lot of weight. It conjures images of something vast and unknowable, almost supernatural. Eleanor Drage, an AI ethicist at the University of Cambridge, wants to dissolve that impression entirely.

Her new book, reviewed by The Guardian, argues that AI is not a mystical force. It is the product of workers in silicon and quartz mines, microchip factories, and data labelling centres, where people are paid to tag images and text so that machine learning systems, the software that learns patterns from enormous datasets, can be trained. Understanding that human chain, Drage says, is how citizens begin to reclaim power from the companies building these systems.

What does the jargon actually mean?

Drage's plainest and most useful move is attacking the language itself. "The cloud" sounds like a natural phenomenon. It is just someone else's computer. An AI "hallucination", the term used when a chatbot confidently states something false, is really a system error or a data labelling mistake. Calling it a hallucination implies the machine has a mind that occasionally wanders. It does not.

"Intelligence" is the biggest sleight of hand. The word is broad, loaded, and, Drage argues, potentially misleading when applied to software that predicts the next word in a sentence.

Should people worry about AI wiping out humanity?

Drage is sceptical that apocalyptic framing helps ordinary people at all. Silicon Valley's dominant story, that AI will either deliver a golden age or destroy civilisation, is compelling but convenient. It pulls attention away from practical questions: Who controls the data feeding these systems? How should AI be regulated? What rights do workers and users have?

Apocalypse talk also creates a false hierarchy of problems. Climate change, geopolitical instability, and economic inequality already cause enormous harm to real people today. Drage points out that fixing those problems would reduce many AI-linked risks too.

The book's sharpest argument is simple. Big tech cannot honestly promise utopia while it is chasing profit and serving a narrow group of shareholders. The two goals are in direct tension.

What can an ordinary person actually do?

Drage's practical advice centres on informed scepticism. Question the marketing terms. Ask who benefits when a company describes its product as "intelligent" or its mistakes as "hallucinations". Demand clearer rules about how personal data is collected and used to train AI models.

None of that requires a computer science degree. It requires the same critical reading skills people apply to any other industry making large promises.

Common questions

What is a data labelling centre?

It is a workplace where people are paid to review and tag content, such as marking which images contain a cat or flagging harmful text, so that AI systems have clean, organised information to learn from.

Why does the language tech companies use matter?

Words like "hallucination" or "intelligence" shape how the public thinks about accountability. If a chatbot "hallucinates", it sounds like a glitch beyond anyone's control. If it makes a labelling error, someone is responsible for fixing it.