Garbage In, Intelligence Out: Why Reason Beats Curation

Humans learn slowly.

We spend years studying, specialising, and narrowing our field of vision until we can say we truly know something. A good physicist often knows little about law, and a great lawyer rarely writes code. This limitation shapes how we think about intelligence. We divide people into generalists and specialists because our minds are bounded. There is only so much we can hold and process.

When artificial intelligence arrived, we extended this same mental map to machines.We spoke about AI models for medicine, AI for law, AI for finance. We assumed that specialisation was a sign of progress, that if humans become experts by focusing, machines must do the same. The logic felt intuitive: garbage in, garbage out. If we fed the right data, we would get the right expertise.

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