mango win A.I. May Change Everything, but Probably Not Too Quickly
mango win A.I. May Change Everything, but Probably Not Too Quickly
“Artificial intelligence (A.I.) is already having a significant impact on the economy, and its influence is expected to grow significantly in the coming years …. Overallmango win, the effects of A.I. on the economy will depend on a variety of factors, including the rate of technological advancement, government policies and the ability of workers to adapt to new technologies.”
OK, who said that? Nobody, unless we’re ready to start calling large language models people. What I did was ask ChatGPT to describe the economic effects of artificial intelligence; it went on at length, so that was an excerpt.
I think many of us who’ve played around with large language models — which are being widely discussed under the rubric of artificial intelligence (although there’s an almost metaphysical debate over whether we should call it intelligence) — have been shocked by how much they now manage to sound like people. And it’s a good bet that they or their descendants will eventually take over a significant number of tasks that are currently done by human beings.
Like previous leaps in technology, this will make the economy more productive but will also probably hurt some workers whose skills have been devalued. Although the term “Luddite” is often used to describe someone who is simply prejudiced against new technology, the original Luddites were skilled artisans who suffered real economic harm from the introduction of power looms and knitting frames.
But this time around, how large will these effects be? And how quickly will they come about? On the first question, the answer is that nobody really knows. Predictions about the economic impact of technology are notoriously unreliable. On the second, history suggests that large economic effects from A.I. will take longer to materialize than many people currently seem to expect.
Consider the effects of previous advances in computing. Gordon Moore, a founder of Intel — which introduced the microprocessor in 1971 — died last week. He was famous for his prediction that the number of transistors on a computer chip would double every two years — a prediction that proved stunningly accurate for half a century. The consequences of Moore’s Law are all around us, most obviously in the powerful computers, a.k.a. smartphones, that almost everyone carries around these days.
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