AI Will Soon Put Creators Out of Work. How Should We Adapt?

A review of Daniel Susskind’s ‘A World Without Work’

Matthew McFarlane
6 min readApr 26, 2022

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Cover Design by Nicolette Seeback

It wasn’t long ago that “creatives” were told automation would finally validate our life choices. Those of us who chose to major in the liberal or fine arts would have the last laugh, as our less remunerative careers would still be around while the accountants and lawyers of the world were automated straight into the history books.

Our creative, non-routine jobs would survive the purge and we could shake our heads and chuckle as we performed creative work that AI, no matter how advanced, could never do.

Today, that story looks more like a sophomoric pipedream. Algorithms write more than passable articles now. Need a logo for your business? There are a multitude of AI-generated options at your fingertips. In short, a lot of the things we were told AI could never do as well as a human are now being accomplished by artificial intelligence.

As Daniel Susskind explains in A World Without Work, this mistaken prophecy was due to a fundamental misunderstanding of how AI actually works. For decades, economists and pundits have told us that AI will never be able to mimic the workings of the human mind. And they weren’t wrong — it can’t (yet).

An economist himself, as well as a former public servant in the British government, Susskind has spent the past decade thinking about the relationship between technology and work — both its past and its future.

And he noticed that most economists had made their predictions about what could never be automated while missing a sea change in the field of artificial intelligence. Susskind dubs this shift “the pragmatist revolution.” Instead of attempting to create a general artificial intelligence that would mimic the human brain, AI researchers shifted their focus: away from replicating human intelligence and toward the more mundane goal of accomplishing specific tasks.

As Susskind explains, AI is no longer about getting a machine to perform a task in the way a human would. It’s simply about getting the machine to perform that task as well as, or better, than a human. For example, the AlphaZero program learned both chess and the Chinese board game Go by playing…

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Matthew McFarlane

Reader, writer, content provider. Fan of hand-made guitars, racket-based sports, and houseplants. You can find me in St. Louie.