By+John+Naughton
If the robots are coming for our jobs, make sure they pay their taxes.如果機器人搶了我們的工作,那么必須向它們征稅。
The problem with the future is that its unknowable. But of course that doesnt stop us trying to second-guess1 it. At the moment, many people—and not just in the tech industry—are wondering about the impact of automation on employment. And not just blue-collar employment—the kind of jobs that were eliminated in the early phase of automating car production, for instance—but also the white-collar jobs that hitherto2 seemed secure.
Economists found that because computers could now be substituted for low-skill workers performing routine tasks (book-keeping, clerical work and repetitive production and monitoring activities) we were going to see a “hollowing-out” of middle-skilled, middle-wage jobs and “a corresponding rise in employment at both the high and low ends of the skills spectrum3”. And in a 2015 study, two Oxford researchers took the 702 categories that the US Labour Department uses to classify jobs and tried to estimate which of them might be vulnerable to automation using the “smart” technologies that are now commonplace. Their conclusion: almost half (47%).
If these predictions are accurate, then there is trouble ahead because the existence of a stable middle class seems to be a prerequisite4 for a liberal democracy. But because of the aforementioned problem with the future, we dont know how immediate the threat of high-end automation is. It could be that getting to this particular future will take a lot longer than the technologys boosters and Cassandras5 think. But no one doubts that it will happen.
The standard riposte to concerns about automation is to pooh-pooh them.6 This is an old story, sceptics7 contend. Anxiety about the rise of the machines goes back to Elizabeth I and the stocking frame8. And each time the fears have been overblown: the new technology did indeed destroy jobs; but the new industries that it enabled eventually created even more jobs. So calm down: it will come good in the end.
And maybe it will. But theres still a problem. What both the boosters and the sceptics ignore is that waves of automation have always involved periods of traumatic disruption. In a fascinating recent article the economist Tyler Cowen pointed out the problem with blithe9 assumptions about a better future—they miss out on the history of what actually happened in the great industrial transformations of the past. “The shift out of agricultural jobs,” he writes, “while eventually a boon10 for virtually all of humanity, brought significant problems along the way. This time probably wont be different, and thats why we should be concerned.”
Estimates for private per-capita consumption from 1760 to 1831, for example, suggest that it rose only by about 22%. And Cowen cites estimates by the economic historian Gregory Clark that “English real wages may have fallen about 10% from 1770 to 1810, a 40-year period. Clark also estimates that “it took 60 to 70 years of transition, after the onset of industrialisation, for English workers to see sustained real wage gains at all”.
Translate that to the present and you can see the dangers. If the people hitherto known as middle-class were to experience this kind of income suppression, we would expect political trouble. Yet, says Cowen, that may be the track the US is on. Median11 household income is down since 1999, and median male wages were probably higher in 1969 than they are today. His conclusion: transition costs from automation will be higher than many economists—and everyone in the tech industry—like to think.
Then there is the question—also avoided by the tech industry—of who pays those transition costs. Conventional thinking says that the owners of the machines should reap the rewards, while the state picks up the costs of the ensuing human wreckage.12 So when Bill Gates pitched into the debate recently with a proposal that robots should be taxed, just like human workers are, you can imagine the splutters of outrage from the neoliberal fortresses of Silicon Valley.13 “Right now,” he said, “the human worker who does, say,$50,000 worth of work in a factory, that income is taxed and you get income tax, social security tax, all those things. If a robot comes in to do the same thing, youd think that wed tax the robot at a similar level.” And the money raised should be used to retrain people the robots have replaced, with “communities where this has a particularly big impact” first in line for support. I never thought Id write this, but here goes: good for you, Mr Gates.
未來的問題就在于其不可知性,但這當然不會阻止我們?nèi)ヮA測未來。當下,許多人——不止技術界人士——都在試圖探究自動化對就業(yè)的影響:不僅僅是藍領工作崗位——在汽車生產(chǎn)自動化初期就被淘汰的那類工作——還有迄今為止似乎未被殃及的白領工作崗位。
經(jīng)濟學家發(fā)現(xiàn),由于計算機目前可以替代那些負責日常工作(記賬、行政工作以及重復性的生產(chǎn)與監(jiān)控活動)的低技能工作人員,我們會看到中等技能、中等收入的工作崗位被“掏空”以及“分布在高端與低端技術這兩極的工作機會的相應增長”。在2015年的一項研究中,兩名牛津大學的研究人員依照美國勞工部分類的標準選取了702個工作類別,并試圖估計哪些工作可能更容易受到當下常見的“智能”技術自動化帶來的沖擊。他們的結論是:接近一半(47%)。
如果這些預測準確的話,那么未來就有麻煩了,因為擁有穩(wěn)定的中產(chǎn)階級似乎是一個自由民主國家存在的前提。但由于未來的不可知,我們無法得知高端自動化的威脅會在哪一刻降臨。也許這一天的到來還需要相當長的時日,遠比技術擁護者以及卡桑德拉式的先知們預計的還要久。但沒有人會懷疑這一天的到來。
對于自動化的擔憂,通常的對策就是對其嗤之以鼻。這是老生常談了,懷疑派如此反駁。對于機器崛起的憂慮可以追溯到伊麗莎白一世與織襪機時期。而每次擔憂都被過度夸大:新技術確實會讓一些工作崗位消失;但新技術催生的新產(chǎn)業(yè)最終會創(chuàng)造更多的就業(yè)。所以冷靜下來:最終一切都會好的。
也許最終真的會好起來,但還有一個問題:擁護者和懷疑者都忽略了一點,那就是自動化浪潮總會帶來痛苦的動蕩時期。在最近一篇很有意思的文章里,經(jīng)濟學家泰勒·科文指出了隨意展望美好未來所產(chǎn)生的問題,其原因就是這些臆斷忽略了歷史上重大工業(yè)變革發(fā)生時的實際情況?!皩⑷藗儚膭辙r(nóng)中解脫出來,”他寫道,“雖然對于幾乎全人類而言是一件幸事,然而這場變革也帶來了不少嚴重的問題。這一次或許不會有什么差別,而這正是我們應當關注的原因。”
舉例來說,估算數(shù)據(jù)顯示,自1760年到1831年,私人人均消費僅僅增長了22%??莆囊昧私?jīng)濟歷史學家格雷戈里·克拉克的估算,數(shù)據(jù)表明“從1770年到1810年這40年間,英國人的實際工資可能下降了10%。”克拉克還估計“工業(yè)化開始后,經(jīng)過了60到70年的過渡期,英國工人的實際工資才真正開始持續(xù)全面增長”。
把這一情況放到今天,你就會發(fā)現(xiàn)危險所在了。如果目前為止被劃為中產(chǎn)階級的人群要經(jīng)歷這種收入的緊縮,我們就要擔心政治動蕩的發(fā)生了。然而科文表示,這或許就是美國正在走的道路。中等家庭的收入從1999年開始就在減少,而1969年中產(chǎn)階級男性的工資或許比現(xiàn)在還要高。他的結論就是:自動化所需的過渡成本比許多經(jīng)濟學家——以及所有技術界人士——愿意相信的要高得多。
接下來的問題——這也是技術界人士避而不談的問題——就是過渡成本由誰來承擔。人們傳統(tǒng)上認為機器的擁有者應當獲益,而由國家來收拾爛攤子。因此,當前不久比爾·蓋茨提出機器人應該和人一樣被征稅的提案時,他卷入了一場始料未及的論戰(zhàn),你可以想象出硅谷這座新自由主義堡壘發(fā)出了各種怎樣的怒斥?!艾F(xiàn)在,”他說,“一個工人如果在工廠完成,比方說價值五萬美金的任務,對這部分收入征稅的話我們就可以得到收入稅、社保稅等等。而如果機器人代替人來完成同樣的工作,我們就可以向機器人征收類似額度的稅?!倍愂账脩斢脕頌槟切┍粰C器人替代的人們進行再培訓,優(yōu)先幫助那些“受到極大沖擊的群體”。我從沒想過我會這么寫,但我還是要說:好樣的,蓋茨先生。
1. second-guess: 預測。
2. hitherto: 到目前為止,迄今。
3. spectrum: 范圍。
4. prerequisite: 前提。
5. Cassandra: 卡桑德拉式的人物。卡桑德拉是希臘、羅馬神話中特洛伊的公主、阿波羅的祭司,她能預卜未來但無人相信。
6. standard: 通常的,普遍的;riposte:機敏的回答;pooh-pooh: 發(fā)呸聲。
7. sceptic: 懷疑者,持懷疑態(tài)度的人。
8. 英國青年威廉·李(William Lee)在1589年發(fā)明了“織襪機(stocking frame)”。他向伊麗莎白一世(Elizabeth I)展示這部機器時女王的反應很糟糕,并拒絕授予他專利,理由是擔心機械化會造成失業(yè)與政治動亂,危及王室權力。
9. blithe: 漫不經(jīng)心的。
10. boon: 恩惠,有用之物。
11. median: 中間的。
12. reap: 收獲,獲得;ensuing: 隨之產(chǎn)生的。
13. pitch into: 置(某人)于新形勢中(尤指出乎意料的情形中);splutter: 雜亂的聲音;neoliberal fortress: 新自由主義的堡壘。新自由主義(Neoliberalism)是一種政治經(jīng)濟哲學,強調(diào)自由市場的機制,反對國家對于國內(nèi)經(jīng)濟的干預和對商業(yè)形為的管制。