The ‘de-skilling’ of AI
“Will AI stretch our minds — or stunt them?” asks an article in The Atlantic by Kwame Anthony Appiah, a professor of philosophy and law at New York University and the author of “Captive Gods: Religion and the Rise of Social Science.”
“To grasp what’s at stake, we have to look closely at the ways that skill frays, fades, or mutates when new technologies arrive,” he says.
The fear a new technology will make us dumber goes back to ancient times, Appiah says. The development of writing meant that human history no longer needed to be carried in people’s heads.
In the 2000s, researchers asked what search engines were doing to us, he says. A widely cited study found that, in some circumstances, people would remember where a fact could be found rather than the fact itself.
When people talk about de-skilling, they usually picture a person who’s lost a knack for something, such as a doctor who misses tumors without an AI assist, Appiah says.
For example, after performing AI-assisted colonoscopies, gastroenterologists saw their unaided rate of polyp detection drop by six percentage points. But another study of pooled data from 24,000 patients showed that AI assistance raised overall detection rates by about 20 percent. Because higher detection rates mean fewer missed cancers, this approach clearly was beneficial, regardless of whether individual clinicians became fractionally less sharp.
“The issue isn’t how humans compare to bots but how humans who use bots compare to those who don’t,” Appiah says.
When a machine enters the workflow, mastery may shift from production to appraisal, Appiah says. A 2024 study of coders using GitHub Copilot found that use of AI seemed to redirect human skill rather than obviate it. Coders spent less time generating code and more time assessing it, such as checking for logic errors, catching edge cases, and cleaning up the script. The skill changed from composition to supervision.
Occupational de-skilling could be democratizing, increasing the pool of who gets to do a job, Appiah says. For example, scientists who struggle with English could use chatbots to improve the drafting of institutional-review-board statements, clearing a linguistic hurdle that has little to do with the quality of their research.
“The future of expertise will depend not just on how good our tools are but on how well we think alongside them,” he says.
Reserve skills will be needed, he says. Somebody in a fleet will need to know celestial navigation in case the GPS goes down.
The most concerning prospect of all is what might be called constitutive de-skilling: the erosion of the capacities that make us human, Appiah says.
“If people were to learn to frame questions the way the system prefers them, to choose from its menu of plausible replies, the damage wouldn’t take the form of spectacular failures of judgment so much as a gradual attenuation of our character: shallower conversation, a reduced appetite for ambiguity, a drift toward automatic phrasing where once we would have searched for the right word, the quiet substitution of fluency for understanding,” he says.
The most pressing question, he says, is how to keep our agency intact: how to continue to be the authors of the systems that now are poised to take on so much of our thinking.
“Each generation has had to learn how to work with its newly acquired cognitive prostheses, whether stylus, scroll, or smartphone,” Appiah says. “What’s new is the speed and intimacy of the exchange: tools that learn from us as we learn from them. Stewardship now means ensuring that the capacities in which our humanity resides — judgment, imagination, understanding — stay alive in us.”
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