
? 人工智能對就業市場的影響正逐漸在數據中顯現,為其在下次經濟衰退中可能發揮的作用提供了線索。摩根大通(JPMorgan)警告稱,企業在經濟衰退期間歷來傾向于采用自動化技術,而人工智能可能會對白領知識工作者造成尤為沉重的打擊。
企業在經濟衰退期間通常會借助自動化手段達成“以少博多”的目標,但生成式人工智能的出現或將在下次經濟衰退時顛覆以往贏家與輸家的傳統格局。
摩根大通高級美國經濟學家穆拉特·塔斯奇(Murat Tasci)上周二在一份報告中表示,以往,白領知識工作者并未因經濟衰退引發的大規模裁員或復蘇期的失業潮而受到顯著沖擊,但下一次的情形或許會截然不同。
他寫道:“更確切地講,我們認為,在下次經濟衰退期間,人工智能工具與應用在工作場所的采用速度與覆蓋范圍,可能會導致以非常規認知任務為主的職業出現大規模替代,因此,非常規認知型職業將受到波及。”
塔斯奇指出,自20世紀80年代末以來,受自動化影響,專注于常規任務的崗位持續減少。這包括“常規認知型職業”,如銷售和辦公室工作,以及“常規體力勞動型職業”,如建筑、維護、生產和運輸等領域的工作。
過去四十年間,常規工作崗位在經濟衰退后恢復所需時間越來越長。事實上,常規職業就業水平至今仍未恢復到全球金融危機前的峰值。
相比之下,“非常規認知型職業”——如科學家、工程師、設計師以及律師等白領知識工作者——其周期性波動幅度要小得多,就業率幾乎未曾跌至經濟衰退前的峰值水平以下。塔斯奇觀察到,在大多數情況下,這些職業還引領了此前的就業復蘇進程。
失業模式中的“不祥”信號
然而,失業趨勢前所未有的轉變或許預示著,在人工智能時代,白領知識工作者將面臨截然不同的命運。
非常規認知型職業的失業人員占比首次超過非常規體力勞動型職業的失業人員(如醫療支持、個人護理和食品制備等職業)占比。
塔斯奇稱,“從過往數據來看,非常規認知型職業的失業人員占比一直處于最低水平,然而直至近期,這一情況才發生改變”,他還稱這是一個“不祥之兆”。“這一變化趨勢可能預示著,這些勞動者未來面臨的失業風險正不斷攀升。”
與此同時,越來越多證據表明,人工智能正導致初級崗位數量縮減,而這些崗位通常由應屆大學畢業生填補。
他解釋道,與此同時,人工智能并未給常規型工作崗位或非常規體力勞動型工作崗位帶來更多額外風險,因為后者仍然需要更多的實際人際互動。
白領知識工作者面臨的威脅加劇,給經濟帶來的風險也比以往更為嚴峻,因為他們目前在總就業人數中的占比接近45%,而1980年代初這一比例僅為30%。
塔斯奇警告稱:“這些勞動者面臨的失業風險急劇攀升,復蘇前景極為黯淡,這可能會導致下一輪勞動力市場低迷狀況看起來格外嚴峻。以常規型職業增長疲軟為主導的復蘇期失業現象可能會再次上演,此次主要歸因于非常規認知型職業復蘇乏力。”
但其他人對人工智能與就業市場的看法并不那么悲觀。科技投資者戴維·薩克斯(David Sacks)同時擔任白宮人工智能和加密貨幣事務負責人,他試圖駁斥部分關于通用人工智能的“末日預言”。
上周六他在X平臺上發文稱,“人類與人工智能存在明確的分工”,這意味著人們仍需為人工智能模型提供必要的背景信息、給出詳盡的提示,并對其輸出結果進行驗證。
薩克斯補充道:“這意味著,關于失業的末日預言和通用人工智能本身一樣,都存在過度炒作的嫌疑。相反,‘你不會因人工智能而失業,而是會不敵那些比你更擅長使用人工智能的人’這一真知灼見依然成立。”(財富中文網)
譯者:中慧言-王芳
? 人工智能對就業市場的影響正逐漸在數據中顯現,為其在下次經濟衰退中可能發揮的作用提供了線索。摩根大通(JPMorgan)警告稱,企業在經濟衰退期間歷來傾向于采用自動化技術,而人工智能可能會對白領知識工作者造成尤為沉重的打擊。
企業在經濟衰退期間通常會借助自動化手段達成“以少博多”的目標,但生成式人工智能的出現或將在下次經濟衰退時顛覆以往贏家與輸家的傳統格局。
摩根大通高級美國經濟學家穆拉特·塔斯奇(Murat Tasci)上周二在一份報告中表示,以往,白領知識工作者并未因經濟衰退引發的大規模裁員或復蘇期的失業潮而受到顯著沖擊,但下一次的情形或許會截然不同。
他寫道:“更確切地講,我們認為,在下次經濟衰退期間,人工智能工具與應用在工作場所的采用速度與覆蓋范圍,可能會導致以非常規認知任務為主的職業出現大規模替代,因此,非常規認知型職業將受到波及。”
塔斯奇指出,自20世紀80年代末以來,受自動化影響,專注于常規任務的崗位持續減少。這包括“常規認知型職業”,如銷售和辦公室工作,以及“常規體力勞動型職業”,如建筑、維護、生產和運輸等領域的工作。
過去四十年間,常規工作崗位在經濟衰退后恢復所需時間越來越長。事實上,常規職業就業水平至今仍未恢復到全球金融危機前的峰值。
相比之下,“非常規認知型職業”——如科學家、工程師、設計師以及律師等白領知識工作者——其周期性波動幅度要小得多,就業率幾乎未曾跌至經濟衰退前的峰值水平以下。塔斯奇觀察到,在大多數情況下,這些職業還引領了此前的就業復蘇進程。
失業模式中的“不祥”信號
然而,失業趨勢前所未有的轉變或許預示著,在人工智能時代,白領知識工作者將面臨截然不同的命運。
非常規認知型職業的失業人員占比首次超過非常規體力勞動型職業的失業人員(如醫療支持、個人護理和食品制備等職業)占比。
塔斯奇稱,“從過往數據來看,非常規認知型職業的失業人員占比一直處于最低水平,然而直至近期,這一情況才發生改變”,他還稱這是一個“不祥之兆”。“這一變化趨勢可能預示著,這些勞動者未來面臨的失業風險正不斷攀升。”
與此同時,越來越多證據表明,人工智能正導致初級崗位數量縮減,而這些崗位通常由應屆大學畢業生填補。
他解釋道,與此同時,人工智能并未給常規型工作崗位或非常規體力勞動型工作崗位帶來更多額外風險,因為后者仍然需要更多的實際人際互動。
白領知識工作者面臨的威脅加劇,給經濟帶來的風險也比以往更為嚴峻,因為他們目前在總就業人數中的占比接近45%,而1980年代初這一比例僅為30%。
塔斯奇警告稱:“這些勞動者面臨的失業風險急劇攀升,復蘇前景極為黯淡,這可能會導致下一輪勞動力市場低迷狀況看起來格外嚴峻。以常規型職業增長疲軟為主導的復蘇期失業現象可能會再次上演,此次主要歸因于非常規認知型職業復蘇乏力。”
但其他人對人工智能與就業市場的看法并不那么悲觀。科技投資者戴維·薩克斯(David Sacks)同時擔任白宮人工智能和加密貨幣事務負責人,他試圖駁斥部分關于通用人工智能的“末日預言”。
上周六他在X平臺上發文稱,“人類與人工智能存在明確的分工”,這意味著人們仍需為人工智能模型提供必要的背景信息、給出詳盡的提示,并對其輸出結果進行驗證。
薩克斯補充道:“這意味著,關于失業的末日預言和通用人工智能本身一樣,都存在過度炒作的嫌疑。相反,‘你不會因人工智能而失業,而是會不敵那些比你更擅長使用人工智能的人’這一真知灼見依然成立。”(財富中文網)
譯者:中慧言-王芳
? Signs that artificial intelligence is weighing on the job market are continuing to creep into the data, offering clues on how AI could play a role the next time the economy slips into a downturn. Businesses have historically leaned on automation during recessions, and AI could hit white-collar knowledge workers especially hard, JPMorgan warned.
Businesses trying to do more with less have historically leaned on automation during recessions, but the advent of generative AI could scramble the typical pattern of winners and losers when the next downturn strikes.
While white-collar knowledge workers have previously not suffered from severe recession-induced layoffs or jobless recoveries, the next time could be different, JPMorgan senior U.S. economist Murat Tasci said in a note Tuesday.
“More specifically, we think that during the course of the next recession the speed and the breadth of the adoption of the AI tools and applications in the workplace might induce large-scale displacement for occupations that consist of primarily non-routine cognitive tasks; henceforth non-routine cognitive occupations,” he wrote.
Since the late 1980s, jobs that focus on routine tasks have been disappearing because of automation, Tasci said. That includes “routine cognitive occupations” like sales and office jobs, as well as “routine manual occupations” such as jobs in construction, maintenance, production and transportation.
Over the past four decades, it’s taken longer and longer for routine jobs to bounce back after recessions. In fact, employment in routine occupations has still not returned to its peak before the Great Financial Crisis.
By contrast, “non-routine cognitive occupations”—white-collar knowledge workers like scientists, engineers, designers, and lawyers—were much less cyclical and barely dipped below pre-recession peaks. They have also led prior employment recoveries most of the time, Tasci observed.
‘Ominous’ sign in unemployment pattern
But an unprecedented shift in unemployment trends could indicate that white-collar knowledge workers will suffer a much different fate in the age of AI.
For the first time ever, workers from non-routine cognitive occupations now account for a greater share of the unemployed than workers from non-routine manual jobs (i.e. healthcare support, personal care, and food preparation).
“Workers who were last employed in non-routine cognitive jobs have always accounted for the smallest share of the unemployed in the data, until recently,” Tasci said, calling it an “ominous” sign. “This changing pattern might be indicative of rising unemployment risk for these workers going forward.”
That’s as evidence has been mounting that AI is already limiting the number of entry-level jobs that have typically been filled by recent college graduates.
Meanwhile, AI doesn’t pose much more additional risk to routine jobs or to non-routine manual jobs that will still require more physical personal interaction, he explained.
The increased threat to white-collar knowledge workers also poses a greater risk to the economy than in the past as they now account for nearly 45% of total employment, up from 30% in the early 1980s.
“A much larger unemployment risk and anemic recovery prospects for these workers might cause the next labor market downturn to look pretty dismal,” Tasci warned. “The jobless recoveries led by anemic growth in routine occupations might repeat again, this time primarily due to an anemic recovery in non-routine cognitive occupations.”
But others aren’t so gloomy about AI and the job market. Tech investor David Sacks, who also serves as the White House czar on AI and crypto, sought to debunk several “Doomer narratives” about artificial general intelligence.
In an X post on Saturday, he said there’s a “clear division of labor between humans and AI,” meaning that people still need to feed AI models necessary context, give them extensive prompts, and verify their output.
“This means that apocalyptic predictions of job loss are as overhyped as AGI itself,” Sacks added. “Instead, the truism that ‘you’re not going to lose your job to AI but to someone who uses AI better than you’ is holding up well.”