機器人時代的人類工作

In recent months, anthropologists have been rummaging through the grassroots of America’s workforce jungle in search of an answer to one of the great questions of our time: what happens to human jobs when robots arrive?

最近幾個月，人類學家一直在考察整個美國勞動力群體，以尋找我們這個時代最重要問題之一的答案：如果機器人來臨，人類就業(yè)會怎樣?

You might expect the answer to be very depressing. If there is one thing on which almost all economists agree, it is that digital technologies are performing many jobs once done by humans.

你可能會猜，答案非常令人沮喪。如果有一件事是幾乎所有經(jīng)濟學家都同意的，那就是數(shù)字技術正在完成曾經(jīng)由人類完成的很多工作。

Manufacturing offers a particularly stark example of this. A study by Ball State university suggests that 5.6m US manufacturing jobs were lost between 2000 and 2010 — almost nine in 10 thanks to automation, not trade. It could be worse: McKinsey, a consultancy, estimates that 45 per cent of the tasks currently done by humans could be automated as the pattern spreads into the service sector. This equates to $2tn in annual wages — and millions of jobs.

制造業(yè)提供了一個尤為明顯的例子。波爾州立大學(Ball State university)的一項研究顯示，2000年至2010年，有560萬個美國制造業(yè)崗位消失，幾乎十分之九是因為自動化，而非貿易。情況還可能更糟：咨詢公司麥肯錫(McKinsey)估計，隨著自動化模式擴大到服務業(yè)，在目前由人類完成的工作中，有45%可能會實現(xiàn)自動化。這相當于數(shù)以百萬計的就業(yè)崗位和2萬億美元的年薪。

That sounds scary. There is, however, an intriguing twist. When anthropologists have conducted “participation observation” among American workers — that is, observing at what is actually happening in people’s everyday lives, rather than looking at top-down statistics — they discovered a more complex story than the raw numbers suggest.

這聽上去很可怕。然而，其中有一個有趣的轉折。當人類學家對美國勞動者進行“參與觀察”(即觀察人們每天的實際日常生活，而不是考察自上而下的統(tǒng)計數(shù)字)時，他們發(fā)現(xiàn)了一個比原始數(shù)據(jù)揭示的更復雜的情況。

Yes, machines are wiping out some human jobs but people are also working with robots in new roles. That more upbeat story tends to be obscured, yet it deserves a great deal more attention — particularly when president-elect Donald Trump takes office next month.

確實，機器正消滅一些人類的工作，但人們還在新的崗位上與機器人合作。這種更樂觀的情況往往不那么直觀，但應獲得更多關注，特別是美國當選總統(tǒng)唐納德•特朗普(Donald Trump)下月上臺之時。

Consider the findings of Benjamin Shestakofsky, an anthropologist who spent 19 months inside a California company that uses digital technologies to connect buyers and sellers of domestic services. Mr Shestakovsky initially assumed that his research would show how machines were replacing human workers. When he did grassroots analysis he realised that the company was growing so fast, with such big and complex computing systems, that it was constantly drafting more humans — not robots — to monitor, manage and interpret the data. “Software automation can substitute for labour but it also creates new human-machine complementaries,” he told an American Anthropological Association meeting recently, noting that companies “are creating new types of jobs”.

考慮一下人類學家本杰明•舍斯塔科夫斯基(Benjamin Shestakofsky)的研究結果吧，他曾在一家加州公司待過19個月，該公司利用數(shù)字技術為家政服務的買家和賣家搭橋。他起初認為，他的研究將展示出機器正如何取代人類勞動者。在他進行基礎分析時，他發(fā)現(xiàn)，該公司增長非常迅速，有著巨大且復雜的計算系統(tǒng)，它正不斷選派更多人類(而非機器人)監(jiān)控、管理和解讀這些數(shù)據(jù)。“軟件自動化可以取代勞動力，但它也會產(chǎn)生新的人機互補，”他最近在美國人類學協(xié)會(American Anthropological Association)的一次會議上表示。他指出，企業(yè)“正創(chuàng)造新的工作種類”。

Shreeharsh Kelkar, another anthropologist, saw the same pattern in the education world. Until recently it was presumed that the rise of digital teaching tools would make human teachers less important. But watching educators in action, Mr Kelkar found that human teachers are working with these digital tools to be more efficient. The issue is not that computers are automating jobs away, he says, but that “assemblages of humans and computers are emerging”.

另一位人類學家施里哈什•克爾卡(Shreeharsh Kelkar)在教育行業(yè)也看到了同樣的情況。直到不久前，人們還認為，數(shù)字教學工具的出現(xiàn)將讓人類教師的重要性降低。但在實際觀察教育者的過程中，克爾卡發(fā)現(xiàn)，人類教師正利用這些數(shù)字工具提高效率。他表示，問題不是電腦自動化正讓工作消失，而是“人類與電腦正在合作”。

An obvious response is that it is far from clear whether these anecdotes are typical, nor does anyone know whether these new “assemblages” of human and machine will create enough jobs to offset those lost to automation. In addition, new digitised jobs may seem less attractive than the old roles since they are often structured as “contingent work”, with self-employed workers who provide services on demand.

一種可以預見的反應是，認為現(xiàn)在還遠不清楚，這些軼聞是否典型，人們也不知道這些人類與機器的新“合作”是否會創(chuàng)造足夠多的就業(yè)，來抵消自動化導致的就業(yè)損失。另外，新的數(shù)字化工作似乎不如舊工作那樣吸引人，因為它們通常被設置成“臨時工作”，由自由職業(yè)者按需提供服務。

Still, the findings of the anthropologists should not be ignored. For one thing, they suggest that there is a burning need for policymakers to obtain much better data on what is really happening in the American workplace. Anthropological studies are small scale, while the macro-level data are surprisingly weak, partly because the Bureau of Labor Statistics tends to collect data through traditional channels. “We don’t know what is going on with contingent work today,” says Mary Gray, an anthropologist who works at Microsoft. “The tech companies don’t track labour any better than the BLS.”

然而，人類學家的發(fā)現(xiàn)不應被忽視。首先，這些發(fā)現(xiàn)意味著，政策制定者亟需獲取有關美國勞動場所實際狀況的更全面信息。人類學研究的規(guī)模較小，而宏觀層面的數(shù)據(jù)驚人地薄弱，部分原因是美國勞工統(tǒng)計局(Bureau of Labor Statistics)往往通過傳統(tǒng)渠道收集數(shù)據(jù)。“我們不知道目前臨時工作的情況，”在微軟(Microsoft)工作的人類學家瑪麗•格雷(Mary Gray)表示，“科技公司對勞動力狀況的追蹤并不比勞工統(tǒng)計局好。”

Second, if anyone does manage to paint an accurate portrait of that labour force, they need to show this to Mr Trump. In recent months the president-elect has repeatedly stated that he is determined to keep more manufacturing business in America, partly because he — wrongly — likes to blame the loss of manufacturing jobs to competition from China or Mexico. But if he does succeed in this goal of America First he will — paradoxically — only accelerate the automation trend as companies will scramble to cut costs. This is not necessarily a bad thing but it suggests that Mr Trump’s hopes of recreating old-style American jobs is wrong-headed.

其次，如果有人成功準確描繪了勞動力狀況，他們還需要向特朗普說明這點。最近幾個月，這位當選美國總統(tǒng)多次表示，他決定將更多制造業(yè)留在美國，部分原因是他(錯誤地)喜歡將制造業(yè)就業(yè)損失歸咎于來自中國或墨西哥的競爭。但如果他成功實現(xiàn)了“美國優(yōu)先”的目標，他反而只會加快自動化趨勢，因為企業(yè)急于降低成本。這并不一定是壞事，但它表明，特朗普恢復舊式美國就業(yè)的希望是錯誤的。

That leads to the third point: the urgent need for a bigger policy debate about how to prepare workers for this new world. Workforce training needs to change to instil more digital skills.

接下來是第三點：迫切需要就如何讓勞動者適應新的世界展開更大的政策辯論。需要改革勞動力培訓，讓勞動者掌握更多數(shù)字技能。

New types of social security, health and pension systems are necessary to accommodate contingent workers. Some policymakers understand this. Senators such as Mark Warner, a Democrat, for example, are pushing for new safety nets for contingent workers. But if this debate is to secure any serious traction, it is imperative that the technology sector itself steps in. Hitherto, Silicon Valley has not been particularly vocal on these questions, but Mr Trump seems intent on pulling them into the spotlight: last week he summoned tech leaders to Trump Tower to “reassure” them about his plans.

新型的社會保障、健康和養(yǎng)老體系是容納臨時工作者的必要舉措。一些政策制定者明白這點。例如民主黨人馬克•沃納(Mark Warner)等參議員正推動為臨時工作者建立新的保障網(wǎng)絡。然而，如果這場辯論要獲得巨大支持的話，科技行業(yè)本身必須介入。到目前為止，硅谷在這些問題上并不特別積極，但特朗普似乎決心把他們推到聚光燈下：最近，他召集科技界領袖到特朗普大廈(Trump Tower)，讓他們對他的計劃“放心”。

So Silicon Valley should seize this chance and start a dialogue about how to help humans deal with all those robots in the workforce. Otherwise, the day will come when Silicon Valley itself could find itself being blamed for American job losses.

因此，硅谷應抓住這個機會，就如何幫助人類應對勞動力中的所有那些機器人展開對話。否則，硅谷終有一天會發(fā)現(xiàn)自己將因為美國就業(yè)損失而受到指責。