In Reversal Because of A.I., Office Jobs Are Now More at Risk
In Reversal Because of A.I., Office Jobs Are Now More at Risk
Technology disruption typically affected blue-collar occupations. Now white-collar workers may feel the brunt of changes.
The American workers who have had their careers upended by automation in recent decades have largely been less educated, especially men working in manufacturing.
But the new kind of automation — artificial intelligence systems called large language models, like ChatGPT and Google’s Bard — is changing that. These tools can rapidly process and synthesize information and generate new content. The jobs most exposed to automation now are office jobs, those that require more cognitive skills, creativity and high levels of education. The workers affected are likelier to be highly paid, and slightly likelier to be women, a variety of research has found.
“It’s surprised most people, including me,” said Erik Brynjolfsson, a professor at the Stanford Institute for Human-Centered A.I., who had predicted that creativity and tech skills would insulate people from the effects of automation. “To be brutally honest, we had a hierarchy of things that technology could do, and we felt comfortable saying things like creative work, professional work, emotional intelligence would be hard for machines to ever do. Now that’s all been upended.”
A range of new research has analyzed the tasks of American workers, using the Labor Department’s O*Net database, and hypothesized which of them large language models could do. It has found these models could significantly help with tasks in one-fifth to one-quarter of occupations. In a majority of jobs, the models could do some of the tasks, found the analyses, including from Pew Research Center and Goldman Sachs.
For now, the models still sometimes produce incorrect information, and are more likely to assist workers than replace them, said Pamela Mishkin and Tyna Eloundou, researchers at OpenAI, the company and research lab behind ChatGPT. They did a similar study, analyzing the 19,265 tasks done in 923 occupations, and found that large language models could do some of the tasks that 80 percent of American workers do.
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This propaganda to constantly scare workers has got to stop already. AI is nowhere near being able to do this, all AI can do is provide better tools.
This kind of 'journalism' is eye-rollingly painful.
"With the release of accounting software, Accountants world over are at risk!!"
And the article content posted is just an excerpt. The rest of the article focuses on how AI can improve the efficiency of workers, not replace them.
Ideally, you’ve got a learned individual using AI to process data more efficiently, but one that is smart enough to ignore or toss out the crap and knows to carefully review that output with a critical eye. I suspect the reality is that most of those individuals using AI will just pass it along uncritically.
I’m less worried about employees scared of AI and more worried about employees and employers embracing AI without any skepticism.
I thought the article was quite clear on that point? If you actually bother to read the full article and not just my preview.
Even the end of the preview notes it's more likely to assist workers than replace them, as it stands now.
The thing is, there is some merit to the idea that some of these jobs will be threatened by AI, but not quite in the ways people seem to be obsessed with, which is being fully replaced. This is just like any other advance in software, with better tools being created that allow fewer people to do the same amount of work. There are certain parts that truly cannot be done yet, and you still need to have someone that knows how it is supposed to work using the AI not just a manager.
Yep, AI ain’t gonna be pulling broken logs out of gang saws.
This propaganda to constantly scare workers has got to stop already.
Well for decades all the talk of "global warming" was dismissed as fear mongering propoganda, and now look where we're at.
Instead of being scared at scary news, let's use it as a call to action to start solving these problems when they're not yet problems, and stop waiting until they're problems.