“Artificial intelligence (AI) is already having a significant impact on the economy and its influence is expected to grow considerably in the coming years…
In general, the effects of AI 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.
Well, now, who said that? None, unless we’re willing to start calling great language patterns.
What I did was ask ChatGPT to describe the economic effects of AI;
this is just an excerpt.
Many of us who have played with large language models – which are talked about a lot under the rubric of artificial intelligence – have been struck by how much they can look like people.
And it is very likely that in time they or their descendants will take over many of the tasks that humans now perform.
Like previous technological advances, this will make the economy more productive, but it’s also likely to hurt some workers with skills that have lost value.
What will be the magnitude of these effects?
And how quickly will they occur?
As for the first question, nobody knows for sure.
Forecasts of the economic impact of technology are notoriously unreliable.
As for the latter, history suggests that the large economic effects of AI it will take longer to materialize what many expect.
Consider the effects of previous advances in computing.
Gordon Moore, One of the founders of Intel, the company that introduced the microprocessor in 1971, predicted that the number of transistors on a computer chip would double every two years, an astonishingly accurate prediction for half a century.
The consequences of Moore’s Law are all around us, especially in the smartphones that almost everyone today carries with them.
However, for a long time, to the surprise of many, the economic benefits of this dramatic increase in computing power were elusive.
For at least two decades after Moore’s Law came into effect, the United States, far from experiencing a productivity boom, suffered from a prolonged slowdown Of the same.
The boom didn’t come until the 1990s and even then it was a bit disappointing.
Why did a huge and sustained increase in computing power take so long to pay off the economy?
In 1990, the economic historian Paul David published one of my favorite economics articles, “The Dynamo and the Computer”.
In it he drew a parallel between the effects of information technology and those of an earlier technological revolution, electrification.
As David has noted, the availability of electric motors became widespread in the 1890s.
However, having a technology is not enough.
you must too know what to do with it.
To get the most out of electrification, manufacturers have had to rethink factory layouts.
Pre-electrification factories were multi-story buildings with cramped working spaces, because this was necessary to make efficient use of a basement steam engine that drove the machines through a system of rods, gears and pulleys.
It took a long time for them to realize that if each machine ran on its own engine, it was possible to have huge one-story factories with wide corridors that facilitated the movement of materials and assembly lines.
As a result, the large productivity gains from electrification did not materialize until after World War I.
Unsurprisingly and essentially anticipated by David, the economic benefits of information technology finally kicked in in the 1990s, as archivists and dictation-taking secretaries gave way to cube farms.
The lag of these economic benefits even came to be similar to the lag of electrification benefits.
However, this story continues to present some puzzles.
One is why the first IT productivity boom (perhaps there is another one nearby, if the enthusiasm for chatbots is warranted) was so short-lived;
essentially, it only lasted for about a decade.
And even while it lasted, productivity growth during the IT boom was no higher than that of the intergenerational boom after WWII, which was remarkable because no radically new technology seemed to be driving it.
The great boom from the 1940s to the 1970s appears to have been largely based on the use of technologies, such as the internal combustion engine, that had been around for decades, which should make us all the more skeptical about trying to use recent developments technologies to predict economic growth.
That’s not to say AI won’t have huge economic impacts.
However, history suggests they won’t happen quickly.
ChatGPT and what comes next will likely be an economic story for 2030, not the next few years.
c.2023 The New York Times Society
Source: Clarin
Mary Ortiz is a seasoned journalist with a passion for world events. As a writer for News Rebeat, she brings a fresh perspective to the latest global happenings and provides in-depth coverage that offers a deeper understanding of the world around us.