LONDON: As artificial intelligence becomes ever more capable, is any job secure?

“I’ve sort of convinced myself that the safest job in the world is probably gardener,” the FT’s chief economics commentator Martin Wolf recently confessed. That seemed right. There are some things the computers just can’t do.

The next morning the FT published The Gardens That AI Grew, describing intelligently automated drip irrigation, pest detectors, laser scarecrow systems and a solar-powered weeding robot. Oof.

It’s not entirely clear how much the laser scarecrow and the robot weeder really will threaten the jobs of human gardeners, but the prospect reminds us that there is a distinction between a job and a task. Most jobs are bundles of interconnected tasks.

A gardener needs to do everything from mowing and weeding to diagnosing a pest infestation, designing an outdoor space, or – hardest of all – communicating with a difficult client. Different AI systems could well help with most of these tasks, although the likely outcome is not that the job of gardener disappears, but that it changes shape.

The question is, how will each new AI application change the shape of what we do? And will we like the reworked jobs available to us on the other side of this transformation?

TECHNOLOGY, BOTH OLD AND NEW

Generative AI may be new but these questions are not. They run all the way back to the Luddite protests of the early 1800s, when highly skilled textile workers saw machines doing the hardest parts of their job, allowing them to be replaced by low-paid labourers with far less expertise.

And the answers to those long-standing questions? They depend both on the technology and on the job. There’s a lesson to be drawn from two contrasting precedents: the digital spreadsheet, and warehouse guidance earpieces such as the “Jennifer unit”.

The digital spreadsheet, which hit the market in 1979, instantly and flawlessly performed work previously done by accounting clerks, but the accounting profession simply moved on to more strategic and creative problems, modelling d...