When CEOs talk to investors about layoffs, they usually blame economic uncertainty or business “headwinds.” Now, a new term is starting to appear in these announcements: AI.
In recent months, shipping giant UPS announced plans to cut 12,000 office jobs, but CEO Carol Tomé said the company is increasingly using AI to automate tasks performed by its employees. He said it was unlikely that administrative jobs would return because of the current situation. Meanwhile, financial giant BlackRock announced it would cut about 600 positions, highlighting the job cuts as an effort to prepare for upcoming changes in the wealth management industry, one of which is driven by AI. And Google recently laid off ad sales staff as new AI tools help customers manage their own ad campaigns. And IBM CEO Arvind Krishna said Big Blue will pause hiring for 7,800 roles because AI can now do the work for them.
For some commentators, these developments are early confirmation that long-held predictions that AI will cause widespread unemployment and perhaps usher in an era of “mass unemployment” are coming true. This narrative of AI-induced unemployment is so ingrained in the public consciousness that people often see it despite the absence of evidence of it.
The U.S. unemployment rate rose slightly to 3.9% in February, but remains near historic lows. But when executive search firm Challenger, Gray & Christmas released a report finding 4,600 U.S. layoffs between May and January directly attributable to AI, some commentators questioned the comparison. They interpreted the low numbers as evidence that companies were hiding the true scale of AI casualties. He feared the public's backlash.
One day, a significant number of jobs may be lost to AI. Goldman Sachs predicts that AI software could automate the equivalent of 300 million full-time roles worldwide by 2030. But that day has not yet arrived, economists and business analysts say. “This is not the moment,” said Daniel Susskind, a professor of economics at King's College London and author of several books on the impact of technology on work. Growth: history and calculations.
Currently, large-scale AI adoption is hampered by several factors. Many companies are still figuring out how to use it in a way that can justify the exorbitant cost. Additionally, Boston Consulting Group recently found that most executives are wary of using AI across their organizations, given the risk of “hallucinations” in which AI software produces dangerously inaccurate information. I reported it.
So why are some CEOs talking about AI in the same breath as cutting jobs? Experts say some of it is just marketing spin. Erin Lin, an assistant professor specializing in AI and the future of work at the University of Surrey in the UK, says AI is often a convenient cover for layoffs that result from poor business conditions, business distress, and worsening economic conditions. He said that there are many cases. Grace Laudan, an economist and professor of behavioral science at the London School of Economics, said that for publicly listed companies, the bad news of having to cut staff due to financial difficulties has become “somewhat good news thanks to AI.” “It was,” he says. He said, “Sounds like smart cost-cutting.''
This certainly seems to be the case for UPS. The company announced job cuts and mentioned its growing use of AI, while also delivering unpleasant news to Wall Street: it missed sales and earnings expectations and lowered its earnings outlook for next year. Package delivery volume is also declining. AI was just about the only positive thing Tomé mentioned.
300 million
Number of full-time jobs that will be fully automated worldwide by 2030.Source: Goldman Sachs
The situation for Google and other technology companies is more nuanced. They're not just trying to hone their tech street credentials here. They already have enough of it. Rather, the headcount cuts are aimed at cutting costs and investing more in AI development, as the required computing resources and human machine learning talent are prohibitively expensive. So in these cases, AI is indeed associated with job losses, but not for the reasons that people have feared for a long time.
Karl Benedict Frey, an economist at the University of Oxford who co-authored the first groundbreaking study on the potential impact of AI on employment, said people are probably worried about the job losses that generative AI will cause in the short term. He says that it may be overestimated. “Generative AI is not a fully automated technology,” he says, noting that humans are still needed to create the prompts that are fed into the software and check the quality of its output. “Most of the time, humans need to be involved.”
He is one of those who believe that AI could lead to a big “Uber effect.” The technology allows workers with less skill and experience to take on higher-level tasks. Uber allowed anyone with a driver's license and a car to become a taxi driver. As a result, more people became hired drivers.
Similarly, AI “co-pilots” could help more individuals perform legal, financial, or software coding tasks. Rather than eliminating jobs in these fields, the technology could help them skyrocket, Frey said. This is because all evidence suggests that there is currently a huge unmet demand for professional services, partly because such services are too expensive and unaffordable for many customers. ing.
But just as Uber was bad news for taxi drivers struggling in the face of lower price competition, some existing employees may see their wages decline or at least stagnate due to AI. However, even these reduced wages could exceed what unskilled workers can earn in other fields today. Therefore, overall economic inequality may be reduced.
But Frey is less optimistic about AI's long-term impact. He says AI may now be at the “igniter” stage. When street lights were powered by gas, a person was employed to light each lamp at dusk each day using a wick on a long pole. Even with the introduction of light bulbs, lamplighters continued their work, as each street light had to be lit individually. But soon, cities began installing switches that controlled entire city blocks, and eventually timers and light sensors eliminated the need for human intervention at all. Frey believes AI is likely to follow a similar path. Because times like today, when job losses are relatively low, lull us into a false sense of security.
Almost everyone agrees that AI is ushering in an era of uncertainty and disruption, and that employees need to be prepared to learn new skills and change roles. Many experts argue that governments should do more to encourage lifelong education and retraining. And Susskind argues that governments should eliminate tax incentives that encourage companies to use AI to replace workers rather than augment them.
Taking these steps now may mean that the doomsday scenario of mass unemployment due to AI never materializes. At the very least, we should stop panicking about CEO announcements about AI and layoffs and get back to work.
This article is published in the April/May 2024 issue of the magazine. luck.
