For me, the key insight was obvious from the headline: “Kenyans Made a Living Writing College Essays. Then A.I. Arrived.” It hadn’t occurred to me that these folks would be out of work, but of course they would be. AI’s grip on the outsource-your-homework market is near total.
No matter how unsympathetic we find these victims, we should reckon with the implications of their experience, because there’s a lot of contradictory talk about whether AI is creating more jobs than it destroys or vice versa.
I think the most important observation is that the Jevons Paradox applied, but it didn’t save the Kenyans’ jobs. I last wrote about Jevons in May. If you need the refresher:
In the early 1860s, economist William Stanley Jevons argued that demand for coal in England wasn’t going to fall as a result of efficiency gains in engines and furnaces. Instead, he predicted the opposite: that by making coal a more efficient fuel, these advancements would make coal power viable for many more uses, greatly increasing demand. He was right.
As schoolwork completion processes have become more efficient, demand for this product has indeed gone through the roof. There’s more cheating than ever before from students who never would have paid $40 to $70 for an artisanal, hand-crafted, Made-in-Kenya paper.
But this hasn’t created more work than ever for Kenyans managing fleets of chatbots. It has cut them out of the loop entirely. (The article says that the little essay work left in Kenya is for humanizers who tweak papers to evade detection tools.)
This is a problem for the popular argument “You won’t lose your job to AI, but to a human who learns to use AI.” That argument relies on Jevons, and the fall of the essay-mill industry shows us that Jevons only benefits workers occupying a bottleneck that demand must pass through. Ghostwriters hold no such terrain. Neither do the justifiably nervous mathematicians, insurance claims adjusters, entertainers, and content creators.
There are stronger bottlenecks in fields with legal moats. Where only a select few are allowed to sign off on the work, we may indeed see humans orchestrating fleets of agents for at least a short time: medicine, law, civil engineering.
This is small comfort. If the AI race isn’t halted, anyone who isn’t already out of work probably ends up dead. But if the race is halted such that models even a little bit stronger than the current state-of-the-art remain legal, then I think most people still end up out of work. You only need so many humans atop accountability pyramids, and demand for services provided by fields with legal moats is finite.
We also have to consider the enormous pressure the AI industry would apply to get its technology approved for the licensed work that remains. The very gatekeeping that insulates licensed jobs creates upsetting shortages for their services, driving up costs; that’s often the whole point. There will be no running from the moral argument that an AI doctor statistically better than a human doctor, accessible 24/7 to the most rural and least privileged, should be allowed to practice medicine.
In survivable futures with significant AI job destruction, wealth distribution programs will probably be needed to prevent social upheaval. This is true even if we’re not ready to start writing checks to people who used to write Johnny’s essays.
The analyses and opinions expressed on AI StopWatch reflect the views of the individual contributors and the sources they cover, and should not be taken as official positions of the Machine Intelligence Research Institute.