Companies are “over-investing in generative AI and then regretting it.”
Too Dumb
Concerns over an AI bubble are continuing to grow.
Major selloffs at the beginning of this week had experts worried that the dam was breaking, although markets have since stabilized significantly.
Nonetheless, the conversation surrounding tech giants losing hundreds of billions of dollars in market capitalization continues, with critics arguing that AI hype is unsustainable in the long run.
In an interview with NPR, MIT economist and leading AI skeptic Daron Acemoglu made a case that the tech is simply far too dumb to have a major impact.
When asked if generative AI would usher in revolutionary economic changes, Acemoglu had a straightforward answer.
“No. No. Definitely not,” Acemoglu told NPR. “I mean, unless you count a lot of companies over-investing in generative AI and then regretting it, a revolutionary change.”
Clippy on Speed
Generative AI is still struggling with many of the same challenges as when ChatGPT was first made available to the public in late 2022. For one, AI chatbots still have a strong tendency to “hallucinate,” meaning that their connection to reality is tenuous at best.
As NPR points out, experts have also argued that claims of generative AI intelligence are likely exaggerated, and aren’t much more than “autocorrect on steroids“: a statistical model that does little more than recognize patterns in data.
Despite being available to the public for several years now, the rate of meaningful corporate use remains dubious. While individual workers are using the tech on a regular basis, companies have yet to incorporate it into their business en masse, as the Economist reported last month.
Acemoglu argued that AI isn’t capable of most tasks in a modern office. According to the economist, generative AI will only ultimately impact less than five percent of human tasks.
He also predicted that the tech will only boost the gross domestic impact by roughly 1.5 percent over the next decade. While that’s “nothing to be sneered at,” he told NPR, “it’s not revolutionary in any shape or form.”
“So a lot of people in the industry don’t recognize how versatile, talented, multifaceted human skills and capabilities are,” Acemoglu told NPR. “And once you do that, you tend to overrate machines ahead of humans and underrate the humans.”
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