Each week, I write for a tech company worth billions of dollars. Alongside me are novelists, academics and other freelance journalists. The workload is flexible, the pay better than we are used to, and the assignments never run out. But what we write will never be read by anyone outside the company.
That's because we aren't even writing for people. We are writing for an AI.
Large language models (LLMS) such as ChatGPT have made it possible to automate huge swathes of linguistic life, from summarising any amount of text to drafting emails, essays and even entire novels. These tools appear so good at writing, they have become synonymous with the very idea of artificial intelligence.
But before they ever risk leading to a godlike superintelligence or devastating mass unemployment, they first need training. Instead of using these chatbots to automate us out of our livelihoods, tech companies are contracting us to help train their models.
The core part of the job is writing pretend responses to hypothetical chatbot questions. This is the training data the model needs to be fed. The "AI" needs an example of what "good" looks like before it can try to produce "good" writing.
As well as providing our model with such "gold standard" material, we are also helping it attempt to avoid "hallucinating" - a poetic term for telling lies. We do so by feeding it examples that use a search engine and cite sources. Without seeing writing that does this, it cannot learn to do so by itself.
Hold on. Aren't these machines trained on billions and billions of words and sentences? What would they need us fleshy scribes for?
Well, for starters, the internet is finite. And so too is the sum of every word in every book ever written. So what happens when the last pamphlet and papyrus have been digitised and the model is still not perfect? What happens when we run out of words?
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