自動化正在通過各種方式逐漸滲透至職場,，也讓雇員們開始擔心,，科技會對自身工作帶來哪些變化，甚至是否會取而代之,。牛津經(jīng)濟研究所在2019年6月發(fā)布的一篇報道預測,，到2030年，全球8.5%的制造業(yè)崗位,，約2000萬份工作,，將被機器人取代。

位于匹茲堡的卡耐基梅隆大學計算機科學學院的教授兼臨時院長湯姆·米切爾表示,，從這個角度來思考自動化和工作之間的關(guān)系是錯誤的,。相反，人們應該審視自己工作所涉及的任務,，并評估一下讓這些任務實現(xiàn)自動化的難易程度,。

他說：“一些人從事的是單一任務工作，例如收費站[操作人員],。這些人會遇到麻煩,，因為他們的工作將成為自動化的對象,。”當然,，這對于他們來說是個壞消息,，但對其他人而言又意味著什么呢？

面臨風險的任務

一些任務評估起來并不容易,。2013年的調(diào)查《就業(yè)的未來：計算機化對工作的影響》發(fā)現(xiàn),，約47%的工作都會因為人工智能的進步而面臨高風險。

該研究的合著者,、《科技陷阱：自動化時代的資本,、勞動力和電力》（The Technology Trap: Capital, Labor, and Power in the Age of Automation）一書的作者卡爾·本尼迪克特·弗雷博士稱，有關(guān)自動化影響的預測呈現(xiàn)出兩極分化的趨勢：一派人認為機器人將取代諸多工作,，并讓很多人失業(yè),，而另一派則認為它將改變工作的性質(zhì)。

他補充說：“但這也意味著大量的人可能會失業(yè),，因為隨著工作性質(zhì)的改變,，他們的技能成為了一種過剩的事物?！?/p>

這并非是什么帶有未來主義色彩的假想,。麥肯錫全球研究所（MGI）的合伙人邁克爾·楚伊博士表示，幾乎現(xiàn)有工作中的半數(shù)任務在理論上都可以通過科技手段來完成,。

而且工作發(fā)生改變的不僅僅是低收入工作者,。楚伊和他的團隊預測，約60%的工作都含有30%以上可以被自動化的任務,。首席執(zhí)行官,、金融顧問、保險代理和其他一些工作都是如此,。

無論職級高低,，那些工作將因為科技而發(fā)生徹底變化的員工對于自動化的含義漠不關(guān)心,。即便科技不會讓他們完全失業(yè),，但他們?nèi)匀挥斜匾私庾约旱墓ぷ鲿l(fā)生哪些變化，以及何時發(fā)生變化,。

預測變化率

盡管我們很難精確地給出自動化取代員工工作的具體時間表,，但有一些明確的指標會告訴人們接下來會發(fā)生什么，同時,，我們還面臨著可能會拖慢這一流程的障礙,。

在首批指標中，其中一個便是構(gòu)成自身工作的任務類型,。MGI發(fā)現(xiàn),，可預測的體力勞動,、數(shù)據(jù)處理和數(shù)據(jù)自動化均屬于非常容易受到自動化影響的工作。但他們的研究還顯示,，人們很難為其他職務開發(fā)有效的技術(shù)解決方案,，例如不可預測的體力勞動、與股東的互動,、專長運用以及人員管理等,。因此，盡管聊天機器人可以回答一些基本的問題,，機器人可以從倉庫中拿出物件進行打包,，但我們有理由相信，建造工作,、林業(yè)工作或室外動物養(yǎng)殖在短期之內(nèi)不會面臨任何風險,。

楚伊表示，自動化的發(fā)展和采納過程較為緩慢,，然而它在成為主流之后便會迅猛發(fā)展,。他說：“對于過去幾十年中的任何技術(shù)來說，以實際中存在的積極商業(yè)案例為例,，商業(yè)可用性距離該技術(shù)在經(jīng)濟中的采用達到穩(wěn)定時所需的時間大約為10-30年,。我們的模型給出的時間是8-28年?！?/p>

有時候,，你甚至可能會成為這個流程的一部分。埃森哲正在讓自家員工與其客戶尋找那些能夠被自動化的關(guān)鍵任務,。例如,，埃森哲的運營部門在其田納西諾克斯維爾中心舉行黑客馬拉松比賽。通常在周五下班之后,，雇員們可以留下來享用比薩晚餐,，然后與人工智能專家和數(shù)據(jù)科學家會面，討論如何解決自動化解決方案中的問題,，每月舉行一次,。

埃森哲運營部門的首席執(zhí)行官德比·珀里舒克稱，雇員們對于其工作的自動化并不感到害怕,，因為領導層鼓勵他們通過各種方式來創(chuàng)造更多價值,，讓工作更加有趣。此舉也打消了雇員對自己工作將被取代的顧慮,。她說：“是否會有那么一天,，任何事情都已經(jīng)100%的自動化，無需監(jiān)控,，無需進行額外的培訓,？在我看來這一天是不存在的,，要讓工作中的每個單一流程都實現(xiàn)自動化是不現(xiàn)實的?！?/p>

珀里舒克的團隊還與客戶展開合作,，使用技術(shù)工具來實現(xiàn)工作流程的自動化。埃森哲的雇員負責開發(fā)監(jiān)控客戶雇員工作的人工智能工具,。珀里舒克表示,，整個流程是透明的，許可由客戶授予,，雇員也知道自己處于被監(jiān)控的狀態(tài),。埃森哲的人工智能和技術(shù)專家發(fā)現(xiàn)了可實現(xiàn)自動化的領域，并在這一過程中征求雇員的意見,。雇員甚至可以參與幫助“培訓”實現(xiàn)其工作自動化的人工智能技術(shù),，繪制流程并制定結(jié)果標準。

自動化道路上的障礙

楚伊指出,，除了技術(shù)開發(fā)以及培訓其如何正確工作所面臨的挑戰(zhàn)之外,，人工智能的廣泛采用還面臨著一些典型的障礙。成本是其中一個,。他表示,，即使流程得以確認，而且也存在自動化的商業(yè)案例,，但大多數(shù)新技術(shù)都有著相對較高的價格,。

楚伊說：“人們對美國200萬的卡車司機感到擔憂?！奔幢氵@一技術(shù)做好了部署的準備,，而且存在積極的商業(yè)案例，但他估計,，要取代美國所有的卡車,，其成本可能會達到數(shù)千億美元。這類成本是一個很大的障礙,。

其次,，人們對于技術(shù)變革存在一些善意、傳統(tǒng)的抵觸觀念,。當然,，無人駕駛卡車可能在很多方面是一個不錯的解決方案,，然而,，對于在路上以70英里/時的速度行駛的無人駕駛交通工具，并非所有人都能夠接受,。

米切爾提到了在快餐店實現(xiàn)眾多任務自動化的現(xiàn)有技術(shù),。他說：“事實在于,，我依然喜歡與人打交道。我并不覺得人們意識到,，自己在任何一家零售店面支付貨款時有多大一部分價值應該歸屬于這種人際互動,。客戶對于與全自動化的機器打交道會有多大的抵觸情緒,？”

他還指出,，很多領域在很長一段時間內(nèi)將采用部分自動化。因此,，關(guān)注自身所在行業(yè)的發(fā)展以及已開發(fā)技術(shù)的類型,，對于預測工作如何變化以及何時變化至關(guān)重要。（財富中文網(wǎng)）

譯者：馮豐

審校：夏林

Automation is increasingly making its way into the workplace, raising concerns among employees about the ways technology will change their jobs—or eliminate them entirely. A June 2019 report by Oxford Economics predicts that 8.5% of the world’s manufacturing positions alone—some 20 million jobs—will be displaced by robots by 2030.

But that’s the wrong way to think about automation and jobs, says Tom Mitchell, professor and interim dean of Pittsburgh-based Carnegie Mellon University’s School of Computer Science. Instead, you should look at the tasks involved in your job and evaluate how easily those tasks can be automated.

“Some people have a single task job, like toll booth [operators],” he says. "Those people are in trouble because their job is going to be automated.” That’s bad news for them, of course, but what does it mean for you?

Tasks that are at risk

Some tasks aren’t easy to evaluate. A 2013 paper, “The Future of Employment: How Susceptible are Jobs to Computerisation?” found that roughly 47% of jobs were at high risk of being automated with advances in artificial intelligence.

Carl Benedikt Frey, Ph.D., co-author of that paper and author of The Technology Trap: Capital, Labor, and Power in the Age of Automation says predictions around automation’s impact have become very polarized: Either you believe that the robots are coming for many jobs—leaving many with no employment—or you believe it’s going to change the nature of work.

“But that also means that lots of people are probably going to lose their jobs because their skillsets are becoming redundant even as the nature of work changes,” he adds.

This isn’t some futuristic hypothetical. Michael Chui, Ph.D., a partner at McKinsey Global Institute (MGI), says roughly half of the tasks people perform at work could theoretically be done by technology that exists today.

And it’s not just low-income workers whose jobs will change. Chui and his team estimate that roughly six out of 10 jobs are made up of 30% or more tasks that can be automated. CEOs, financial advisors, insurance agents, and others all fall into this category.

Regardless of their title, those whose jobs will be transformed by technology care little about the semantics of automation. Even if technology won’t leave them entirely unemployed, they still need to keep abreast of how their jobs will change—and when.

Predicting the rate of change

While it’s difficult to accurately pinpoint a specific window of when automation will encroach workers’ jobs, there are some good indicators of what’s coming, as well as some obstacles that can slow down the process.

One of the first indicators is the type of tasks that make up your job. MGI finds that predictable physical work, data processing, and data automation are all highly susceptible to automation. But their research also shows it’s tougher to find effective technology solutions for other roles, like unpredictable physical work, interactions with stakeholders, applying expertise, and managing others. So, while chatbots may be able to answer basic questions, and robots may be able to pick items out of a warehouse for packing, it's safe to assume that construction, forestry work, or raising outdoor animals likely aren’t at risk any time soon.

Chui says that automation develops and is adopted slowly, but comes on fast once it’s hit the mainstream. “For any technology in the past few decades, the time between commercial availability—say that there’s an actual positive business case—and the plateau in adoption of this technology across the economy, is roughly one to three decades,” he says. “We model it out as eight to 28 years.”

Sometimes, you may be even be part of the process. Accenture involves its own employees and those of its clients in identifying key tasks to be automated. For example, Accenture’s operations department holds hack-a-thons at its Knoxville, Tennessee center. Once a month, usually after work hours on a Friday, employees can stay for a pizza dinner and meet with AI specialists and data scientists to figure out how to address problems with automation solutions.

According to Debbie Polishook, group chief executive at Accenture Operations, employees aren’t afraid to automate parts of their jobs because of leadership encouraging them to find ways to add more value and do more interesting work. This alleviates fears that their roles will be eliminated. “Do I see a day when everything is 100% automated with no supervision, no additional training required? I really don’t see a day where that's true for every single process in the workplace,” she says.

Polishook’s team also works with clients, using technology tools to automate work processes. Accenture’s employees oversee A.I.-powered tools that monitor how clients’ employees work. The process is transparent—permission is granted by the client and employees know they’re being monitored, Polishook says. Accenture’s A.I. and technology specialists identify areas that could be automated, consulting employees along the way. Employees may even be enlisted to help “train” the A.I. that will automate their work, mapping processes and setting outcome standards.

Barriers to automation

Beyond the challenges of developing and training the technology to work properly, a number of barriers typically stand in the way of widespread adoption, Chui says. Cost is one. Even when the process has been identified and there’s a business case for automating it, most new technology has a relatively high price tag, he says.

“People worry about two million truck drivers in the U.S.,” Chui says. Even if the technology was ready to deploy and there was a positive business case for them, he estimates it would cost hundreds of billions of dollars to replace every truck in the U.S. That kind of cost is a big barrier.

Then, there’s good, old-fashioned resistance to technological change. Sure, autonomous trucks may be a great solution in many ways. But not everyone is comfortable with the thought of vehicles without drivers barreling down the road at 70 miles per hour.

Mitchell points to the existence of technology to automate many tasks in fast food restaurants. “The truth is, I still like interacting with humans,” he says. “I don’t think we know how much of the value that we’re paying for in any given, say, retail outlet, [is in the interaction]. How much customer resistance would there be to dealing with full automation?”

He adds that there will be a long path of partial automation in many sectors. So, paying attention to developments in your sector and the types of technology being developed is essential to predicting how and when your job will change.