In the early 1980s, Apple co-founder Steve Jobs described the computer as “a bicycle for our minds”. He was inspired by a Scientific American graphic he’d encountered as a boy, showing that a human on a bicycle is more energy-efficient than any animal1. The metaphor captured the promise of personal computing: tools that enable people to go further and faster with less effort. But the deeper brilliance of bicycles lies in what they do not do: they do not mimic human biology, nor any form found in nature. The bicycle reimagined motion entirely.
By comparison, I propose that artificial-intelligence agents are aeroplanes for the mind — they can speed things up for humans even more than bicycles do, but they are harder to control and the consequences of mistakes can be huge. And scientists are particularly poised to benefit from these tools. Scientific research is, at its core, a journey into the unknown. Yet working in new terrains brings unexpected challenges2 and frequent failures3.
To push the frontiers of knowledge forwards quickly and responsibly, science and scientists urgently need a playbook for flying these aeroplanes. In my view, effective use of AI in research will probably require the development of AI agents that are grounded in robust, domain-specific scientific information. The real question is not whether machines will replace scientists, but what kind of scientists we will become when we learn to fly them.
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