EmilyMiller
Steinbeck of Smut
- Joined
- Aug 13, 2022
- Posts
- 12,320
All of our [interminable] debates about AI seem to assume some sort of benefit to the technology. Arguments instead talk about ethics and loss of human jobs. But what if AI doesn’t actually boost productivity?
This is an excerpt from an article on The Atlantic. It’s behind a paywall (I subscribe), but someone normally finds a free version.
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If there is any field in which the rise of AI is already said to be rendering humans obsolete—in which the dawn of superintelligence is already upon us—it is coding. This makes the results of a recent study genuinely astonishing.
In the study, published in July, the think tank Model Evaluation & Threat Research randomly assigned a group of experienced software developers to perform coding tasks with or without AI tools. It was the most rigorous test to date of how AI would perform in the real world. Because coding is one of the skills that existing models have largely mastered, just about everyone involved expected AI to generate huge productivity gains. In a pre-experiment survey of experts, the mean prediction was that AI would speed developers’ work by nearly 40 percent. Afterward, the study participants estimated that AI had made them 20 percent faster.
But when the METR team looked at the employees’ actual work output, they found that the developers had completed tasks 20 percent slower when using AI than when working without it. The researchers were stunned. “No one expected that outcome,” Nate Rush, one of the authors of the study, told me. “We didn’t even really consider a slowdown as a possibility.”
No individual experiment should be treated as the final word. But the METR study is, according to many AI experts, the best we have—and it helps make sense of an otherwise paradoxical moment for AI. On the one hand, the United States is undergoing an extraordinary, AI-fueled economic boom: The stock market is soaring thanks to the frothy valuations of AI-associated tech giants, and the real economy is being propelled by hundreds of billions of dollars of spending on data centers and other AI infrastructure. Undergirding all of the investment is the belief that AI will make workers dramatically more productive, which will in turn boost corporate profits to unimaginable levels.
On the other hand, evidence is piling up that AI is failing to deliver in the real world. The tech giants pouring the most money into AI are nowhere close to recouping their investments. Research suggests that the companies trying to incorporate AI have seen virtually no impact on their bottom line. And economists looking for evidence of AI-replaced job displacement have mostly come up empty.
This is an excerpt from an article on The Atlantic. It’s behind a paywall (I subscribe), but someone normally finds a free version.
—
If there is any field in which the rise of AI is already said to be rendering humans obsolete—in which the dawn of superintelligence is already upon us—it is coding. This makes the results of a recent study genuinely astonishing.
In the study, published in July, the think tank Model Evaluation & Threat Research randomly assigned a group of experienced software developers to perform coding tasks with or without AI tools. It was the most rigorous test to date of how AI would perform in the real world. Because coding is one of the skills that existing models have largely mastered, just about everyone involved expected AI to generate huge productivity gains. In a pre-experiment survey of experts, the mean prediction was that AI would speed developers’ work by nearly 40 percent. Afterward, the study participants estimated that AI had made them 20 percent faster.
But when the METR team looked at the employees’ actual work output, they found that the developers had completed tasks 20 percent slower when using AI than when working without it. The researchers were stunned. “No one expected that outcome,” Nate Rush, one of the authors of the study, told me. “We didn’t even really consider a slowdown as a possibility.”
No individual experiment should be treated as the final word. But the METR study is, according to many AI experts, the best we have—and it helps make sense of an otherwise paradoxical moment for AI. On the one hand, the United States is undergoing an extraordinary, AI-fueled economic boom: The stock market is soaring thanks to the frothy valuations of AI-associated tech giants, and the real economy is being propelled by hundreds of billions of dollars of spending on data centers and other AI infrastructure. Undergirding all of the investment is the belief that AI will make workers dramatically more productive, which will in turn boost corporate profits to unimaginable levels.
On the other hand, evidence is piling up that AI is failing to deliver in the real world. The tech giants pouring the most money into AI are nowhere close to recouping their investments. Research suggests that the companies trying to incorporate AI have seen virtually no impact on their bottom line. And economists looking for evidence of AI-replaced job displacement have mostly come up empty.