Layoffs: Will AI replace white-collar workers? Analysts and programmers should be concerned

Layoffs: Will AI replace white-collar workers? Analysts and programmers should be concerned

Layoffs: Will AI replace white-collar workers? Analysts and programmers should be concerned

According to studies, AI technologies are greatly increasing the efficiency of analysts, customer service representatives, and programmers. The IMF issued a warning last month, citing the possibility of less labor demand, lower pay, and fewer hiring in advanced nations where occupations were more vulnerable to AI. Certain occupations can just vanish.

In the US, there were about 39,000 layoffs reported in the technology and banking sectors last month.

Are white-collar workers—analysts, programmers, and even the occasional opinion columnist—dying of old age? According to a poll, the US financial and technology sectors reported about 39,000 layoffs last month. DocuSign Inc. and Snap Inc. have already announced more than 900 layoffs in an effort to "rip off the Band-Aid" and transition to more affordable AI. Points to an ongoing competition. Mechanization. On internet forums, developers are quoting Marks and debating whether or not to retrain as electricians.

Meta Platform Inc.'s recent one-day market-cap rise of $197 billion suggests that neither investors nor politicians seem to be very worried about the tech race. After all, it's simple to discuss how artificial intelligence (AI) may increase productivity and economic development given that demand is robust, there are no Luddites in sight, and unemployment is still low. Andrew Bailey, the governor of the Bank of England, recently told the BBC that technology will not be a "massive job destroyer".

However, wishing for luck is not a sufficient reaction to the possible upheaval in the job market that artificial intelligence may bring about. The effects of integrating AI into the realm of hard labor, or white-collar jobs, are just now being partially explored by a growing corpus of study. All is not beautiful.

Thus far, experiments have concentrated on the kind of standard text-based tasks—such as professional writing, programming, and customer service advice—that generative AI is most suited to do. The good news is that workers benefit more from this technology when it is used as a companion rather than as a substitute. According to a Microsoft Corp. and OpenAI research, programmers who used GitHub Copilot, an AI assistant that offers advice and recommendations, finished tasks on average 55.8% quicker. According to a another research, employees that used ChatGPT for jobs like press releases or analytical plans finished them ten minutes quicker and with higher quality. Another study found that customer service representatives who used AI helpers completed 14% more work in one hour.

These findings also demonstrate that workers with less experience benefit more from AI, which might account for why younger Turks in tech appear more interested in these technologies than more seasoned professionals. This research offers hope that instead than tearing apart the workplace, AI may be a productivity enhancer that helps workers at the bottom of the hierarchy learn and grow while simultaneously giving more senior colleagues more time. In the 1960s, computer scientist J.C.R. Licklider, who dreamed of this perfect "man-computer symbiosis," lamented that he was spending eighty-five percent of his time "thinking," instead of using that time to record, organize, or create graphs. It was devoted to "achieving a condition of

All is not perfect, however. Experiments under control may not always reveal what occurs on a larger scale. Users of Copilot, for instance, have noted the need to look into and find problems since the tool ultimately depends on large-language models, which are not impervious to errors. Skilled programmers will excel in this. According to Noah Gift, a professor at Duke University, "(Copilot) gives everyone a little bit of a leg up, but even if you're a bad programmer you'll still have weaknesses" (MIT Technology Review). The skill threshold for employment rises even more because novice programmers may create negative feedback loops that are so expensive. However, AI's capabilities may also make the greatest employees so much better that they wouldn't need as many people.

Another concern is if the quick production of material devalues producers and lowers incomes rather than raising demand. "Not everyone benefits from AI, even if it helps those with lower skill levels," argues Oxford Martin School Professor Carl-Benedict Frey. He uses Uber Technologies Inc. as an example, which decreased entry barriers for ride-hailing services, encouraging more individuals to join up and decreasing the pay of current drivers. The IMF issued a warning last month, citing the possibility of less labor demand, lower pay, and fewer hiring in advanced nations where occupations were more vulnerable to AI. Certain occupations can just vanish.

All of this is not to argue that we should get alarmed about a labor conflict. We could eventually look back and marvel how we managed without artificial intelligence. However, in light of rising inequality and declining salaries, our short-term management strategies are critical. If computers can write code but can't repair a leaking faucet, then calls to "reskill" or "learn Python" will seem like clichés.

What ought to be the DAC? Three concepts seem to be worthwhile. The first is to prevent workers' data from being needlessly acquired by computers by tightening legislative controls on the leading AI providers that control this "uniquely exploitative" technology, as former StabilityAI CEO Ed Newton-Rex refers to it. is capable of being spared. The second is to expand its revenue streams by developing new uses for AI, maybe by improving its supply chain by producing the chips that drive it. Ensuring the existence of a social safety net, such as universal basic income, for people in need is the third.

And give me that wrench if nothing else works.