When AI produces a text, a plan or a piece of code in a few seconds, the value does not disappear: it shifts to judgement. Spotting an error, assessing an edge case and standing behind a decision all require real skills.
Producing is not verifying
An AI output can be convincing while being wrong, incomplete or unsuited to the context. The easier production becomes, the more important the ability to assess it. And you can only verify well what you understand well enough to question its assumptions.
This phenomenon recalls the “ironies of automation” described by Lisanne Bainbridge: when the machine handles the routine case, the human is left with the hardest exceptions, while risking the loss of the practice that would let them deal with them.
How to use AI without giving up your know-how
- Keep exercises where the skill is practised without assistance.
- Ask for the sources, the reasoning and the limits of a generated answer.
- Compare the AI output with an independent reference.
- Make an identifiable human accountable for the final decision.
FAQ
Does AI replace skills?
It can speed up certain tasks, but it does not replace the judgement needed to verify, adapt and stand behind the result.
Why keep learning without AI?
Because independence lets you detect an error and avoid blindly delegating a decision to a tool.
Sources
Gary S. Becker, Human Capital; Lisanne Bainbridge, “Ironies of Automation”, Automatica, 1983.
