Machines have already outsmarted humans at playing chess, identifying birdsong and predicting complex protein structures. But when it comes to the really clever and intuitive stuff, like original scientific research, we humans like to think that we still have the advantage.
We may need to think again. At the RAAIS artificial intelligence conference in London earlier this month, Daniel Cohen, president of the Canadian drug discovery company Valence Labs discussed the tantalising, if slightly unnerving, possibility of “autonomous scientific discovery”. Trained on specialist data, sophisticated AI models might soon be able to generate hypotheses, design and run experiments, learn from the results and rinse and repeat 24/7. “Our mission is to industrialise scientific discovery,” he said.
You do not need to talk to people in computational biology for long to understand their excitement about AI. The AI research company Google DeepMind has even spun off a separate company, Isomorphic Labs, to exploit this domain after its AlphaFold program modelled 200mn protein structures.