AI gains and losses
Roy Amara once said, "We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run." I think this applies to AI.
Loud and warranted have been the concerns around what AI is doing to our mental health, our brains (PDF), our jobs, our democracies, our relationships, our students, our environment, and myriad other facets of life. It's a catastrophe! Or is it? Kwame Anthony Appiah, a professor of philosphy at New York State University takes the long view on the subject, in the Atlantic.
Appiah reminds us that every technological advancement since speech was committed to papyrus, has resulted in losses and gains, with some innovations heralding hitherto undiscovered territories. There are pros and cons, but ultimately, those who survive the changes adapt and carry on. So too will it be with AI:
Once a machine enters the workflow, mastery may shift from production to appraisal. A 2024 study of coders using GitHub Copilot found that AI use seemed to redirect human skill rather than obviate it. Coders spent less time generating code and more time assessing it—checking for logic errors, catching edge cases, cleaning up the script. The skill migrated from composition to supervision.
That, more and more, is what “humans in the loop” has to mean. Expertise shifts from producing the first draft to editing it, from speed to judgment. Generative AI is a probabilistic system, not a deterministic one; it returns likelihoods, not truth. When the stakes are real, skilled human agents have to remain accountable for the call—noticing when the model has drifted from reality, and treating its output as a hypothesis to test, not an answer to obey. It’s an emergent skill, and a critical one. The future of expertise will depend not just on how good our tools are but on how well we think alongside them.
This brave new world will reward those who can mark AI's homework, instead of producing it themselves. Humans are still required, but for a different purpose.
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