The hiring nightmare of Gen Z is real, but the AI ​​is a “lightning strike” not a “house fire”, says the economist of Yale

It has been particularly alarming for many AI effects on entry -level work. A successful study by Stanford in August has particularly clicked, because it claimed to find a “significant and disproportionate impact” on entry -level jobs most exposed to AI automation – such as software development and customer service – which have experienced strong relative employment cuts. This died near the MIT study which said that 95% of AI generative pilots failed and the somewhat sudden awareness that AI could be built towards a bubble. Even the president of the federal reserve Jerome Powell sees something happening, commenting that “children who come out of the university and young people, the minorities, find it difficult to find a job.”

But according to a new study by researchers from Yale and Brookings, these cases are “lightning blows”, as opposed to “home fires”. The American labor market simply shows no sign of wide disturbance and led by AI, at least not yet.

Martha Gimbel, Yale economist and main author of the newspaper, hopes that understanding these data helps people relax. “Take a step back. Enter a deep inspiration,” said Gimbel Fortune. “Try to respond to AI with data, not on emotion.”

No apocalypse yet

The new study has examined several measures to disrupt the labor market, based on data from the Bureau of Labor Statistics on job losses, unemployment spells and changes in a broader professional composition. The conclusion: there is movement, but nothing ordinary.

Although the mixture of professions has been slightly moved in recent years, the authors have emphasized that this change is still good in historical standards. Currently, the forces that lead these changes seem to be macroeconomic rather than technological.

“The greatest forces hitting the labor market at the moment are a slower economy, an aging population and a drop in immigration – not an AI,” said Gimbel.

It is easy to confuse noise in the economy with the impact of AI, especially for young workers, who can already feel the pinch of a cooling labor market. But Gimbel stressed that these effects are “very specific impacts in very targeted populations” and that AI does not have a broad impact on young workers, whose job search is probably more affected by a macroeconomic slowdown.

Economists – including the President of the Fed, Jerome Powell, described the current labor market conditions as a “low -hike and low -fire” environment, where layoffs are rare, but the same goes for new opportunities. The recent university graduates have taken the blow: they find it difficult to find entry -level roles in sectors of white collars such as technological and professional services, and the unemployment rate of young people has climbed to 10.5%, the highest since 2016. But the effect has also struck older workers: more than a quarter of Americans of unemployment has been out of work for more than six months, the higher level of 2010, the higher level of 2010. Pand.

Exposure to AI does not mean job loss

It is therefore not surprising that many workers assume that AI must already be responsible. But Gimbel maintains that one of the biggest false ideas is to confuse the exhibition at AI with the trip. Radiologists illustrate the point. Once considered the main victims of automation, they are more numerous and better paid than ever, even if their workflows are strongly based on imaging tools powered by AI.

“Exposure to AI does not mean that your work disappears,” she said. “It could mean that your work is changing.”

The same goes for coders and writers, who dominate AI adoption rates on platforms like Claude, have noted the researchers. The use of tools does not automatically train your livelihood – this could simply reshape the way the work is done.

Molly Kinder, the co -author of Gimbel in Brookings, added another layer: geography. Americans are used to thinking of automation as something that devastates factory cities at the heart. With a genetive AI, said Kinder, geography has returned.

“This is not the automation of your grandparents,” said Kinder Fortune. “The AI ​​generation is more likely to disrupt – for example or negatively – cities with knowledge clusters and technological jobs, not the industrial heart.”

In his opinion, cities like San Francisco, Boston and New York, dense with coders, analysts, researchers and creatives, are much more exposed to generative AI than small towns. But if this exhibition turns into devastation or growth depends on the future.

“If humans stay in the loop, these cities could enjoy the most advantages,” said Kinder. “Otherwise, they will feel the worst pain.”

The key, she underlines, is that the exhibition does not tell us if the jobs will be really eliminated, but but only tell us which tasks could change. The real story will depend on whether companies treat AI as help or replacement.

Lightning strikes, not a house fire

Kinder, like Gimbel, stressed that the broadcast takes time. Even when the AI ​​systems improve quickly, most organizations have not redesigned their workflows around them.

“Even if I have the impression that AI becomes so good, transforming this into a change at work is long,” she said. “It’s messy. It’s uneven. ”

This is why Yale-Brooke’s analysis is deliberately wide. “This can say if the house is on fire,” said Kinder. “He can’t take a stove fire in the kitchen. And for the moment, the labor market as a house is not on fire. ”

However, this does not mean that there is nothing to do here.

Kinder called today’s changes, such as those that Stanford’s study picked up, “love at first sight” in specific industries such as software development, customer service and creative work. These first tremors serve as canaries in the coal mine. But they did not bring together the type of disturbance which reshapes official employment statistics.

“Our article does not say that there was no impact,” she said. “A translator could be without work, a creation could have trouble, a customer service representative could be moved. These are real. But it is not big enough to add up to the people of the apocalypse on the scale of the economy. ”

Kinder and Gimbel said they expect the first clear and systemic effects to take years, not months, appear.

What comes then

If and when a real trip arrives, the two authors think that it will come from the AI ​​integrated into corporate workflows, not from individual workers using chatbots.

“This is when you will see the trip,” said Kinder. “Not when a worker turns to a chatbot, but when the company rethinks the workflow with AI.”

This process begins, because more and more companies integrate APIs of AI into basic systems. But organizational change is slow.

“Three years are nothing for a technology for general use,” said Kinder. “Gen ai did not challenge gravity. It takes time to redo the workflows, and it takes time to spread in the workplace. It could end up being a phenomenal transformer, but it does not happen overnight. ”