
隨著越來(lái)越多的人開(kāi)始擔(dān)心美國(guó)經(jīng)濟(jì)即將面臨一場(chǎng)“就業(yè)末日”,安德烈·卡帕西利用人工智能分析了美國(guó)哪些職業(yè)最容易受到這項(xiàng)技術(shù)的影響。
近日,OpenAI聯(lián)合創(chuàng)始人、特斯拉(Tesla)前人工智能負(fù)責(zé)人卡帕西在社交平臺(tái)發(fā)布了一張圖表,利用美國(guó)勞工統(tǒng)計(jì)局(Bureau of Labor Statistics)的數(shù)據(jù),展示各類職業(yè)受人工智能和自動(dòng)化影響的程度。不同職業(yè)按照0到10的評(píng)分進(jìn)行排序,10分代表最容易受到人工智能的影響。
盡管整體加權(quán)得分為4.9分,但卡帕西的數(shù)據(jù)顯示,年收入超過(guò)10萬(wàn)美元的職業(yè)平均得分最高,為6.7分;而年收入低于3.5萬(wàn)美元的職業(yè)受影響程度最低,僅為3.4分。
這張圖表很快在網(wǎng)上引發(fā)關(guān)注,不少人據(jù)此預(yù)測(cè)白領(lǐng)崗位將面臨末日。不過(guò)卡帕西隨后刪除了相關(guān)數(shù)據(jù)。
卡帕西在3月15日的早上通過(guò)X平臺(tái)解釋道:“這是3月14日早上花了兩小時(shí)用‘氛圍編程’做的小項(xiàng)目,靈感來(lái)自我正在讀的一本書(shū)。我原本覺(jué)得這些代碼和數(shù)據(jù)可能有助于他人直觀了解美國(guó)勞工統(tǒng)計(jì)局的數(shù)據(jù),或者用不同的方式、不同的提示詞為其著色,或者加入自己的可視化內(nèi)容。結(jié)果它被嚴(yán)重誤讀了(盡管有自述文件,其實(shí)我本該預(yù)料到這一點(diǎn)),所以我把它刪了。”
他沒(méi)有回應(yīng)這些數(shù)據(jù)是如何被誤讀,以及正確解讀應(yīng)當(dāng)是什么等問(wèn)題。
不過(guò),這張圖表的存檔版本其實(shí)并不會(huì)讓人太意外,因?yàn)樗c許多關(guān)于人工智能可能如何改變美國(guó)勞動(dòng)力市場(chǎng)的觀點(diǎn)相呼應(yīng)。
例如,軟件開(kāi)發(fā)人員、計(jì)算機(jī)程序員、數(shù)據(jù)庫(kù)管理員、數(shù)據(jù)科學(xué)家、數(shù)學(xué)家、金融分析師、律師助理、作家、編輯、平面設(shè)計(jì)師以及市場(chǎng)研究人員的得分都達(dá)到了9分。
這是因?yàn)橄冗M(jìn)的人工智能工具正在日益廣泛地被用于處理數(shù)據(jù)和生成內(nèi)容,可以在幾分鐘內(nèi)完成過(guò)去需要知識(shí)型員工花費(fèi)數(shù)小時(shí)、數(shù)天甚至數(shù)周才能完成的任務(wù)。
雖然人工智能被視為能夠提升資深員工生產(chǎn)率的工具,但越來(lái)越多的證據(jù)表明,企業(yè)對(duì)入門級(jí)員工的需求正在減少。越來(lái)越多的公司也在宣布裁員,并將原因歸咎于人工智能。不過(guò)一些懷疑者認(rèn)為,這只是企業(yè)為修正新冠疫情期間過(guò)度招聘所找的“替罪羊”。
與此同時(shí),卡帕西的圖表顯示,建筑工人、屋頂工、油漆工、清潔工、鋼鐵工人以及園林維護(hù)工的得分只有1分。同樣,居家醫(yī)療護(hù)理員、護(hù)理助理、按摩治療師、牙科保健師、獸醫(yī)助理、美甲師、理發(fā)師和調(diào)酒師的得分為2分。
本月早些時(shí)候,人工智能初創(chuàng)公司Anthropic發(fā)布了一份題為《人工智能對(duì)勞動(dòng)力市場(chǎng)的影響:一種新的衡量方式及早期證據(jù)》(Labor market impacts of AI: A new measure and early evidence)的報(bào)告。報(bào)告指出,現(xiàn)實(shí)中人工智能的實(shí)際采用率,與其所能實(shí)現(xiàn)的潛力相比,不過(guò)是冰山一角。
與卡帕西的數(shù)據(jù)類似,Anthropic的研究指出,從理論上看,人工智能可以覆蓋商業(yè)與金融、管理、計(jì)算機(jī)科學(xué)、數(shù)學(xué)、法律以及辦公室行政等崗位中的大部分任務(wù)。盡管人工智能的應(yīng)用仍然滯后,但Anthropic表示,面臨最大風(fēng)險(xiǎn)的員工往往是年齡較大、受教育程度較高且收入較高的人群。
今年早些時(shí)候,Citrini Research一篇廣為傳播的文章描繪了一幅人工智能摧毀經(jīng)濟(jì)的災(zāi)難性圖景,引發(fā)股市拋售。
但Citadel Securities隨后在一份措辭嚴(yán)厲的報(bào)告中迅速反駁了這一末日論調(diào),指出Indeed的招聘數(shù)據(jù)表明,截至2026年,目前軟件工程師職位需求同比實(shí)際增長(zhǎng)11%。
Citadel Securities還說(shuō),生成式人工智能在工作中的使用規(guī)模依然“出乎意料地穩(wěn)定”,并未出現(xiàn)顯著上升,因此目前“幾乎沒(méi)有任何證據(jù)表明存在迫在眉睫的大規(guī)模崗位替代風(fēng)險(xiǎn)”。美國(guó)經(jīng)濟(jì)并未崩潰,反而新企業(yè)的創(chuàng)立數(shù)量正在迅速增長(zhǎng),而大型人工智能數(shù)據(jù)中心的建設(shè)也正在推動(dòng)局部地區(qū)建筑行業(yè)招聘熱潮。
此外,如果自動(dòng)化真如Citrini所擔(dān)心的那樣以極快速度擴(kuò)張,對(duì)算力的需求必然就會(huì)上升,從而推高其邊際成本。
Citadel Securities表示:“如果算力的邊際成本在某些任務(wù)上高于人力的邊際成本,那么崗位替代就不會(huì)發(fā)生,這將形成一道自然的經(jīng)濟(jì)邊界。”(財(cái)富中文網(wǎng))
譯者:劉進(jìn)龍
隨著越來(lái)越多的人開(kāi)始擔(dān)心美國(guó)經(jīng)濟(jì)即將面臨一場(chǎng)“就業(yè)末日”,安德烈·卡帕西利用人工智能分析了美國(guó)哪些職業(yè)最容易受到這項(xiàng)技術(shù)的影響。
近日,OpenAI聯(lián)合創(chuàng)始人、特斯拉(Tesla)前人工智能負(fù)責(zé)人卡帕西在社交平臺(tái)發(fā)布了一張圖表,利用美國(guó)勞工統(tǒng)計(jì)局(Bureau of Labor Statistics)的數(shù)據(jù),展示各類職業(yè)受人工智能和自動(dòng)化影響的程度。不同職業(yè)按照0到10的評(píng)分進(jìn)行排序,10分代表最容易受到人工智能的影響。
盡管整體加權(quán)得分為4.9分,但卡帕西的數(shù)據(jù)顯示,年收入超過(guò)10萬(wàn)美元的職業(yè)平均得分最高,為6.7分;而年收入低于3.5萬(wàn)美元的職業(yè)受影響程度最低,僅為3.4分。
這張圖表很快在網(wǎng)上引發(fā)關(guān)注,不少人據(jù)此預(yù)測(cè)白領(lǐng)崗位將面臨末日。不過(guò)卡帕西隨后刪除了相關(guān)數(shù)據(jù)。
卡帕西在3月15日的早上通過(guò)X平臺(tái)解釋道:“這是3月14日早上花了兩小時(shí)用‘氛圍編程’做的小項(xiàng)目,靈感來(lái)自我正在讀的一本書(shū)。我原本覺(jué)得這些代碼和數(shù)據(jù)可能有助于他人直觀了解美國(guó)勞工統(tǒng)計(jì)局的數(shù)據(jù),或者用不同的方式、不同的提示詞為其著色,或者加入自己的可視化內(nèi)容。結(jié)果它被嚴(yán)重誤讀了(盡管有自述文件,其實(shí)我本該預(yù)料到這一點(diǎn)),所以我把它刪了。”
他沒(méi)有回應(yīng)這些數(shù)據(jù)是如何被誤讀,以及正確解讀應(yīng)當(dāng)是什么等問(wèn)題。
不過(guò),這張圖表的存檔版本其實(shí)并不會(huì)讓人太意外,因?yàn)樗c許多關(guān)于人工智能可能如何改變美國(guó)勞動(dòng)力市場(chǎng)的觀點(diǎn)相呼應(yīng)。
例如,軟件開(kāi)發(fā)人員、計(jì)算機(jī)程序員、數(shù)據(jù)庫(kù)管理員、數(shù)據(jù)科學(xué)家、數(shù)學(xué)家、金融分析師、律師助理、作家、編輯、平面設(shè)計(jì)師以及市場(chǎng)研究人員的得分都達(dá)到了9分。
這是因?yàn)橄冗M(jìn)的人工智能工具正在日益廣泛地被用于處理數(shù)據(jù)和生成內(nèi)容,可以在幾分鐘內(nèi)完成過(guò)去需要知識(shí)型員工花費(fèi)數(shù)小時(shí)、數(shù)天甚至數(shù)周才能完成的任務(wù)。
雖然人工智能被視為能夠提升資深員工生產(chǎn)率的工具,但越來(lái)越多的證據(jù)表明,企業(yè)對(duì)入門級(jí)員工的需求正在減少。越來(lái)越多的公司也在宣布裁員,并將原因歸咎于人工智能。不過(guò)一些懷疑者認(rèn)為,這只是企業(yè)為修正新冠疫情期間過(guò)度招聘所找的“替罪羊”。
與此同時(shí),卡帕西的圖表顯示,建筑工人、屋頂工、油漆工、清潔工、鋼鐵工人以及園林維護(hù)工的得分只有1分。同樣,居家醫(yī)療護(hù)理員、護(hù)理助理、按摩治療師、牙科保健師、獸醫(yī)助理、美甲師、理發(fā)師和調(diào)酒師的得分為2分。
本月早些時(shí)候,人工智能初創(chuàng)公司Anthropic發(fā)布了一份題為《人工智能對(duì)勞動(dòng)力市場(chǎng)的影響:一種新的衡量方式及早期證據(jù)》(Labor market impacts of AI: A new measure and early evidence)的報(bào)告。報(bào)告指出,現(xiàn)實(shí)中人工智能的實(shí)際采用率,與其所能實(shí)現(xiàn)的潛力相比,不過(guò)是冰山一角。
與卡帕西的數(shù)據(jù)類似,Anthropic的研究指出,從理論上看,人工智能可以覆蓋商業(yè)與金融、管理、計(jì)算機(jī)科學(xué)、數(shù)學(xué)、法律以及辦公室行政等崗位中的大部分任務(wù)。盡管人工智能的應(yīng)用仍然滯后,但Anthropic表示,面臨最大風(fēng)險(xiǎn)的員工往往是年齡較大、受教育程度較高且收入較高的人群。
今年早些時(shí)候,Citrini Research一篇廣為傳播的文章描繪了一幅人工智能摧毀經(jīng)濟(jì)的災(zāi)難性圖景,引發(fā)股市拋售。
但Citadel Securities隨后在一份措辭嚴(yán)厲的報(bào)告中迅速反駁了這一末日論調(diào),指出Indeed的招聘數(shù)據(jù)表明,截至2026年,目前軟件工程師職位需求同比實(shí)際增長(zhǎng)11%。
Citadel Securities還說(shuō),生成式人工智能在工作中的使用規(guī)模依然“出乎意料地穩(wěn)定”,并未出現(xiàn)顯著上升,因此目前“幾乎沒(méi)有任何證據(jù)表明存在迫在眉睫的大規(guī)模崗位替代風(fēng)險(xiǎn)”。美國(guó)經(jīng)濟(jì)并未崩潰,反而新企業(yè)的創(chuàng)立數(shù)量正在迅速增長(zhǎng),而大型人工智能數(shù)據(jù)中心的建設(shè)也正在推動(dòng)局部地區(qū)建筑行業(yè)招聘熱潮。
此外,如果自動(dòng)化真如Citrini所擔(dān)心的那樣以極快速度擴(kuò)張,對(duì)算力的需求必然就會(huì)上升,從而推高其邊際成本。
Citadel Securities表示:“如果算力的邊際成本在某些任務(wù)上高于人力的邊際成本,那么崗位替代就不會(huì)發(fā)生,這將形成一道自然的經(jīng)濟(jì)邊界。”(財(cái)富中文網(wǎng))
譯者:劉進(jìn)龍
Andrej Karpathy used AI to gauge which U.S. professions are most vulnerable to the technology amid growing fears that a jobs apocalypse may be headed for the economy.
Over the weekend, the OpenAI cofounder and former director of AI at Tesla posted a graphic showing how susceptible every occupation is to Al and automation, using Bureau of Labor Statistics data. Different jobs received scores on a scale of 0 to 10, with 10 being most exposed.
While the overall weighted exposure was 4.9, Karpathy’s data also showed that professions earning more than $100,000 a year had the worst average score (6.7), while the those earning less than $35,000 had the lowest exposure (3.4).
His chart quickly drew attention online, with many predicting doom for white-collar workers. But Karpathy soon removed the data.
“This was a March 14 morning 2 hour vibe coded project inspired by a book I’m reading,” he explained on X on March 15 morning. “I thought the code/data might be helpful to others to explore the BLS dataset visually, or color it in different ways or with different prompts or add their own visualizations. It’s been wildly misinterpreted (which I should have anticipated even despite the readme docs) so I took it down.”
He didn’t respond to questions about how it’s been misinterpreted and what the correct interpretation should be.
Still, an archived version of the chart may not be much of a shocker as it echoes what others have been saying about how AI could shape the U.S. labor market.
For example, software developers, computer programmers, database administrators, data scientists, mathematicians, financial analysts, paralegals, writers, editors, graphic designers, and market researchers got scores of 9.
That’s as sophisticated AI tools are increasingly being used to crunch numbers and produce content, performing tasks in minutes that used to require knowledge workers hours, days, or even weeks to do.
While AI is seen as a productivity enhancer for experienced employees, evidence is mounting that companies have less need for entry-level workers. More companies are also announcing layoffs and citing AI, though skeptics see it as a scapegoat to correct pandemic-era overhiring.
Meanwhile, Karpathy’s chart showed that construction laborers, roofers, painters, janitors, ironworkers, and grounds maintenance workers got scores of just 1. Similarly, home healthcare aides, nursing assistants, massage therapists, dental hygienists, veterinary assistants, manicurists, barbers, and bartenders got scores of 2.
Earlier this month, AI startup Anthropic issued a report entitled “Labor market impacts of AI: A new measure and early evidence,” that found actual AI adoption is just a fraction of what AI tools are feasibly capable of performing.
Like Karpathy’s data, Anthropic’s paper said AI can theoretically cover most tasks in business and finance, management, computer science, math, legal, and office administration roles. While AI adoption is still lagging, Anthropic said the workers most at risk are older, highly educated and well paid.
And earlier this year, a viral essay by Citrini Research painted a catastrophic picture of an economy destroyed by AI, sparking a stock market selloff.
But Citadel Securities swiftly debunked the doomsday scenario in a blistering report, pointing out that Indeed job posting data shows demand for software engineers is actually up 11% year over year so far in 2026.
Citadel Securities also noted that the daily use of generative AI for work remains “unexpectedly stable” and currently “presents little evidence of any imminent displacement risk.” Instead of a collapsing economy, new business formation in the U.S. is rapidly expanding, and the construction of massive AI data centers is currently driving a localized boom in construction hiring.
Furthermore, if automation expanded at the breakneck pace Citrini fears, demand for compute would inherently rise, pushing up its marginal cost.
“If the marginal cost of compute rises above the marginal cost of human labor for certain tasks, substitution will not occur, creating a natural economic boundary,” Citadel Securities said.