AI Is a Burnout Machine

Some software engineers are finding that AI is speeding up their work, but at a cost: it’s also accelerating them towards burnout.

Siddhant Khare is one of those programmers. In an interview with Business Insider, he lamented that while AI has made him more productive, it’s also led him to feel that his job was harder than ever.

“We used to call it an engineer, now it is like a reviewer,” Khare told BI. “Every time it feels like you are a judge at an assembly line and that assembly line is never-ending, you just keep stamping those [pull requests].”

AI, he argued, creates a productivity “paradox” by lowering the cost of production, but increasing the cost of “coordination, review, and decision-making,” all of which falls on a human to solve.

“I shipped more code last quarter than any quarter in my career,” he wrote in an essay, titled “AI Fatigue Is Real,” posted on his blog. “I also felt more drained than any quarter in my career.”

Khare’s account echoes the findings of a recent study reported in Harvard Business Review. After closely monitoring the two hundred employees at a US tech company, the researchers observed that AI was actually intensifying work, instead of reducing workloads. Forming a vicious cycle, AI “accelerated certain tasks, which raised expectations for speed; higher speed made workers more reliant on AI,” the researchers wrote. “Increased reliance widened the scope of what workers attempted, and a wider scope further expanded the quantity and density of work.”

AI adoption was voluntary at the company, and the initial enthusiasm for experimenting with the AI tools helped boost productivity. But this caused a nefarious “workload creep,” in which the employees, without realizing it, took on more tasks than was sustainable for them to keep doing. Multitasking also became more common, with some employees finding that they were no longer focusing on one task, and instead were continually switching their attention, creating the sense that they were “always juggling.”

Khare described something similar. Before AI, he wrote in his essay, he might spend a “full day” in “deep focus” over one problem.

“Now? I might touch six different problems in a day,” he wrote. “Each one ‘only takes an hour with AI.’ But context-switching between six problems is brutally expensive for the human brain. The AI doesn’t get tired between problems. I do.”

Khare also blames AI for why his coding skills have seemed to regress.

“It’s like GPS and navigation. Before GPS, you built mental maps. You knew your city. You could reason about routes,” Khare wrote in his blog post. “After years of GPS, you can’t navigate without it. The skill atrophied because you stopped using it.”

That said, Khare isn’t anti-AI. He believes he can find a way to keep using it in a healthy way, which in a different context might be interpreted as the cliché excuse of an addict. He’s experimented with several ways to keep his AI habit in check and recommended some for his readers, too. But some of the onus also falls on AI companies, he argues.

“You need to keep some sort of guardrails for the humans, so they don’t self-destruct themselves,” Khare told BI.

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