Artificial general intelligence is a worthwhile goal: Getting it right will lead to enormous breakthroughs in science, research, welfare, and how we live our lives. But the way we get there matters.

Ten years ago, generating a photorealistic image or video from scratch, accurately predicting protein structures, rapidly detecting various forms of cancer, asking language models to summarize a book, and using intelligent robots in surgery were all virtually unthinkable. These applications, while still in early stages, are rapidly being used by cutting-edge companies and researchers. Advances like these are often discounted as not really being ‘intelligence’ – as the Australian roboticist Rodney Brooks has said, ‘Every time we figure out a piece of it, it stops being magical; we say, “Oh, that’s just a computation”’.

But while increases in performance and efficiency are hard to dismiss, there are of course also plenty of things we haven’t achieved yet that we’d hoped we would. We still don’t have fully self-driving cars after over a decade of promises that these were only a few years away. A medical chatbot based on the AI language software GPT-3 advised a mock patient to commit suicide. Even so, the rate of progress across the board seems faster than many would have predicted, and researchers increasingly think that artificial general intelligence is not only possible, but could happen in the next few decades. Let’s consider progress made in a selection of fields.

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