Text A What Jobs Will the Robots Take?
Derek Thompson
Nearly half of American jobs today could be automated in“a decade or two,”according to new research.The question is:Which half ?
It is an invisible force that goes by many names:computerization,automation,artificial intelligence,technology,innovation,and everyone's favorite,ROBOTS.
Whatever name you prefer,some form of it has been stoking progress and killing jobs—from seamstresses to paralegals—for centuries.But this time is different:Nearly half of American jobs today could be automated in“a decade or two,”according to a new paper by Carl Benedikt Frey and Michael A.Osborne,discussed recently in The Economist.The question is:Which half?
Another way of posing the same question is:Where do machines work better than people?Tractors are more powerful than farmers.Robotic arms are stronger and more tireless than assembly-line workers.But in the past 30 years,software and robots have thrived at replacing a particular kind of occupation:the average-wage,middle-skill,routine-heavy worker,especially in manufacturing and office admin.
Indeed,Frey and Osborne project that the next wave of computer progress will continue to shred human work where it already has:manufacturing,administrative support,retail,and transportation.Most remaining factory jobs are“likely to diminish over the next decades,”they write.Cashiers,counter clerks,and telemarketers are similarly endangered.On the far right side of this graph,you can see the industry breakdown of the 47 percent of jobs they consider at“high risk.”
And,for the nitty-gritty breakdown,here's a chart of the ten jobs with a 99-percent likelihood of being replaced by machines and software.They are mostly routine-based jobs(telemarketing,sewing)and work that can be solved by smart algorithms(tax preparation,data entry keyers,and insurance underwriters).At the bottom,I've also listed the dozen jobs they consider least likely to be automated.Health-care workers,people entrusted with our safety,and management positions dominate the list.
If you wanted to use this graph as a guide to the future of automation,your upshot would be:Machines are better at rules and routines;people are better at directing and diagnosing.But it doesn't have to stay that way.
The Next Big Thing
Predicting the future typically means extrapolating the past.It often fails to anticipate breakthroughs.But it's precisely those unpredictable breakthroughs in computing that could have the biggest impact on the workforce.
For example,imagine somebody in 2004 forecasting the next ten years in mobile technology.In 2004,three years before the introduction of the iPhone,the best-selling mobile device,the Nokia 2600,looked like this:
Many extrapolations of phones from the early 2000s were just“the same thing,but smaller.”It hasn't turned out that way at all:Smartphones are hardly phones,and they're bigger than the Nokia 2600.If you think wearable technology or the“Internet of Things”seem kind of stupid today,well,fine.But remember that ten years ago,the future of mobile appeared to be a minuscule cordless landline phone with Tetris,and now smartphones sales are about to overtake computers.
Breakthroughs can be fast.
We might be on the edge of a breakthrough moment in robotics and artificial intelligence.Although the past 30 years have hollowed out the middle,high-and low-skill jobs have actually increased,as if protected from the invading armies of robots by their own moats.Higher-skill workers have been protected by a kind of social-intelligence moat.Computers are historically good at executing routines,but they're bad at finding patterns,communicating with people,and making decisions,which is what managers are paid to do.This is why some people think managers are,for the moment,one of the largest categories immune to the rushing wave of AI.
Meanwhile,lower-skill workers have been protected by the Moravec moat.Hans Moravec was a futurist who pointed out that machine technology mimicked a savant infant:Machines could do long math equations instantly and beat anybody in chess,but they can't answer a simple question or walk up a flight of stairs.As a result,menial work done by people without much education(like home health-care workers,or fast-food attendants)have been spared,too.
But perhaps we've hit an inflection point.As Erik Brynjolfsson and Andrew McAfee pointed out in their book Race Against the Machine(and in their new book The Second Machine Age),robots are finally crossing these moats by moving and thinking like people.Amazon has bought robots to work its warehouses.Narrative Science can write earnings summaries that are indistinguishable from wire reports.We can say to our phones I'm lost,help and our phones can tell us how to get home.
Computers that can drive cars,in particular,were never supposed to happen.Even ten years ago,many engineers said it was impossible.Navigating a crowded street isn't mindlessly routine.It needs a deft combination of spacial awareness,soft focus,and constant anticipation—skills that are quintessentially human.But I don't need to tell you about Google's self-driving cars,because they're one of the most over-covered stories in tech today.
And that's the most remarkable thing:In a decade,the idea of computers driving cars went from impossible to boring.
The Human Half
In the 19th century,new manufacturing technology replaced what was then skilled labor.Somebody writing about the future of innovation then might have said skilled labor is doomed.In the second half of the 20th century,however,software technology took the place of median-salaried office work,which economists like David Autor have called the“hollowing out”of the middle-skilled workforce.
The first wave showed that machines are better at assembling things.The second showed that machines are better at organizing things.Now data analytics and self-driving cars suggest they might be better at pattern-recognition and driving.So what are we better at?
If you go back to the two graphs in this piece to locate the safest industries and jobs,they're dominated by managers,health-care workers,and a super-category that encompasses education,media,and community service.One conclusion to draw from this is that humans are,and will always be,superior at working with,and caring for,other humans.In this light,automation doesn't make the world worse.Far from it:It creates new opportunities for human ingenuity.
But robots are already creeping into diagnostics and surgeries.Schools are already experimenting with software that replaces teaching hours.The fact that some industries have been safe from automation for the last three decades doesn't guarantee that they'll be safe for the next one.As Frey and Osborne write in their conclusion:
While computerization has been historically confined to routine tasks involving explicit rule-based activities,algorithms for big data are now rapidly entering domains reliant upon pattern recognition and can readily substitute for labor in a wide range of non-routine cognitive tasks.In addition,advanced robots are gaining enhanced senses and dexterity,allowing them to perform a broader scope of manual tasks.This is likely to change the nature of work across industries and occupations.
It would be anxious enough if we knew exactly which jobs are next in line for automation.The truth is scarier.We don't really have a clue.
(1,204 words)
New Words＆Expressions
1.invisible［In΄vIzəbl］adj.impossible to see
2.artificial intelligence(AI)n.a type of computer technology concerned with making machines work in an intelligent way,similar to the way that the human mind works
3.stoke［stəʊk］v.to add fuel to a large fire and move the fuel around with a stick so that it burns well and produces a lot of heat
4.seamstress［΄siːmstrIs］n.a woman whose job is sewing and making clothes
5.paralegal［pærə΄liːg(ə)l］n.someone who is paid to help lawyers with their work but is not qualified as a lawyer律师助理
6.automate［΄ɔːtəmeIt］v.to make a process in a factory or office operate by machines or computers,in order to reduce the amount of work done by humans and the time taken to do the work
7.pose［pəʊz］v.to ask a question,especially in a formal situation such as a meeting
8.assembly line［ə΄semblI］［lɑIn］n.a line of machines and workers in a factory that a product moves along while it is being built or produced
9.thrive［θrɑIv］v.to grow,develop,or be successful
10.shred［ʃred］v.to cut or tear something roughly into thin strips
11.diminish［dI΄mInIʃ］v.to reduce or be reduced in size or importance
12.cashier［kæ΄ʃIə；kə-］n.a person whose job is to receive and pay out money in a shop,bank,restaurant,etc.
13.nitty-gritty［΄nItI΄grItI］n.the basic facts of a situation.
14.algorithm［΄ælgərIð(ə)m］n.a set of mathematical instructions or rules that,especially if given to a computer,will help to calculate an answer to a problem(尤指计算机程序中的)演算法
15.underwriter［΄ʌndəˌraItə］n.an organization,or someone working for one,that underwrites insurance policies(保险业)保险承保人
16.entrust with:to give someone a thing or a duty for which they are responsible
17.upshot［΄ʌpʃɒt］n.something that happens as a result of other actions,events,or decisions
18.extrapolate［Ik΄stræpəleIt；ek-］v.to guess or think about what might happen using information that is already known
19.anticipate［æn΄tIsIpeIt］v.to imagine or expect that something will happen
20.moat［məʊt］n.a deep,wide channel dug around a place such as a castle and filled with water,in order to protect the place from attack
21.menial［΄miːnIəl］adj.(of work)not requiring much skill and lacking prestige
22.inflection point n.a time of sudden,noticeable,or important change in an industry,company,market,etc.拐点
23.warehouse［΄weəhpʊs］n.a large building for storing things before they are sold,used,or sent out to shops
24.quintessential［ˌkwIntI΄snʃ(ə)l］adj.being the most important part of something.
25.encompass［In΄kʌmpəs］v.to include different types of things
26.ingenuity［ˌIndʒə΄nʊətI］ability to think of clever new ways of doing something
27.creep［kriːp］v.to move slowly,quietly,and carefully,usually in order to avoid being noticed
28.dexterity［dek΄sterItI］n.the ability to perform a difficult action quickly and skilfully with the hands,or the ability to think quickly and effectively
Notes
1.Derek Thompson is a senior editor at The Atlantic,where he writes about economics,labor markets,and the entertainment business.This essay was published by The Atlantic on January 23,2014.
2.The Atlantic is an American magazine,founded in 1857 as The Atlantic Monthly in Boston,Massachusetts.Since 2006,the magazine is based in Washington,D.C.It was created as a literary and cultural commentary magazine,growing to achieve a national reputation as a highquality review with a moderate worldview.The magazine has notably recognized and published new writers and poets,as well as encouraged major careers.It has published leading writers’commentary on abolition,education,and other major issues in contemporary political affairs.The magazine has won more National Magazine Awards than any other monthly magazine.
3.Artificial intelligence(AI)is intelligence exhibited by machines.In computer science,an ideal“intelligent”machine is a flexible rational agent that perceives its environment and takes actions that maximize its chance of success at some goal.Colloquially,the term“artificial intelligence”is applied when a machine mimics“cognitive”functions that humans associate with other human minds,such as“learning”and“problem solving”.
4.Carl Benedikt Frey is Oxford Martin Citi Fellow at Oxford University where he directs the programme on Technology and Employment at the Oxford Martin School.He is one of the most widely cited scholars in the field of workforce automation and industrial renewal,researching the transition of industrial nations to digital economies.
5.Michael Osborne,associate professor of machine learning at the University of Oxford and the co-director of the Oxford Martin Programme on Technology and Employment.
6.Internet of things(IoT)is the network of physical devices,vehicles,buildings and other items—embedded with electronics,software,sensors,actuators,and network connectivity that enable these objects to collect and exchange data.In 2013 the Global Standards Initiative on Internet of Things(IoT-GSI)defined the IoT as“the infrastructure of the information society.”
7.Hans Moravec(born November 30,1948,Kautzen,Austria)is an adjunct faculty member at the Robotics Institute of Carnegie Mellon University.He is known for his work on robotics,artificial intelligence,and writings on the impact of technology.Moravec is also a futurist with many of his publications and predictions focusing on transhumanism.Moravec developed techniques in computer vision for determining the region of interest(ROI)in a scene.
8.The Economist is an English-language weekly newspaper owned by the Economist Group and edited in offices based in London.Continuous publication began under founder James Wilson in September 1843.For historical reasons,The Economist refers to itself as a newspaper,but each print edition appears on small glossy paper like a news magazine.In 2006,its average weekly circulation was reported to be 1.5 million,about half of which were sold in the United States.
Reading Comprehension
Ⅰ.Questions for discussion
1.The chart“% Chance of Automation”lists a dozen jobs that Frey and Osborne consider least likely to be replaced by machines and software.Can the present human holders of these jobs feel justifiably secure?
2.Why does the author comment that it is a most remarkable thing that the idea of computers driving cars went from impossible to boring within a decade?
3.Imagine a situation where all jobs are taken over by robots and AI.How would human beings survive this take-over?
4.How will you think of a proposal to put some brake on the development of robots and AI?What ethical hypothesis is behind your objection or support?Whatever your stand,discuss what might serve as that brake.
Ⅱ.Judge,according to the text,whether the following statements are true(T)or false(F).
1.In the past 30 years,a particular kind of occupation:the average-wage,high-skill,routine-heavy worker,especially in manufacturing and office admin,has been replaced by software and robots.
2.According to Frey and Osborne,human work like manufacturing,administrative support,retail,and transportation will be influenced by the next wave of computer progress.
3.The jobs which are most probably being replaced by robots are mainly routine-based jobs.
4.In the past 30 years the middle,high-and low-skill jobs have actually decreased because of the development of robots and AI.
5.According to Hans Moravec,menial work done by people without much education(like home health-care workers,or fast-food attendants)will be replaced by robots soon.
Vocabulary
Fill in the blanks with words that best complete the sentences.
( )1.She was________in the dusk of the room.
A.invisibility B.invisible
C.reflection D.intelligent
( )2.She was________the stove with sticks of maple.
A.stokes B.stoking C.stroked D.stroking
( )3.In the last ten years________has reduced the work force here by half.
A.automation B.automate C.automatic D.automatics
( )4.When I finally________the question,“Why?”he merely shrugged.
A.poses B.post C.posed D.possess
( )5.A business cannot________without good management.
A.thriving B.thrive C.tearing D.infiltrating
( )6.Time will not________our friendship.
A.shortcoming B.shortage C.disappear D.diminish
( )7.At the time we couldn't have________the result of our campaigning.
A.anticipated B.anticipating C.anticipation D.anticipates
( )8.A________is a large building where raw materials or manufactured goods are stored until they are exported to other countries or distributed to stores to be sold.
A.home B.warehouse C.shop D.market
( )9.A________is a deep,wide channel dug around a place such as a castle and filled with water,in order to protect the place from attack.
A.wall B.canal C.moat D.hedge
( )10.They persuade customers to entrust them________cards—as both Amazon and Apple have done.
A.to B.at C.with D.in
Cloze
Of the four choices given below for each blank,choose the one that best fits into the passage.
“Billy!It is February 25,2099,seven o'clock.Time to 1 and go to school,”said the clock-robot 2 a mental voice.Then the kitchen-robot gave him toast and eggs.Billy was 3 .While he was eating,the whole wall 4 a TV screen and Billy thought that it was great having robots to do 5 for him.Billy ate his meal watching a TV 6 .When he finished eating,the 7 gave him his clothes very fast and 8 him.Then Billy went off to school.
When Billy went outside,he saw a car with no 9 waiting for him.The car said,“Hello,I will be 10 you to school every day.Now would you please 11 your school ID card?”said the car.So Billy showed the car his school ID card and got in.The 12 began to talk to Billy about his school and his schoolwork.After that the car said,“I will 13 your homework today 14 you will have a very,very important lesson to 15 in school today.Please put your homework on the blackboard.”Billy did so.
The car checked Billy's homework and then said,“You are a(n) 16 student.All of your homework is 17 .”When they 18 the school,Billy said to the car,“Goodbye.See you later.”The car said to Billy,“Good luck in your school.”Billy got into the classroom and 19 his seat in the front of the room.Then his teacher came in and said,“Welcome,children!Today we will have a hard but 20 lesson—‘How do robots help a human being’…”
( )1.A.get up B.show up C.take up D.dress up
( )2.A.in B.on C.with D.by
( )3.A.angry B.amazed C.worried D.quick
( )4.A.changed for B.became of C.looked like D.turned into
( )5.A.something B.anything C.everything D.nothing
( )6.A.show B.screen C.set D.box
( )7.A.driver-robot B.clock-robot C.kitchen-robot D.clothes-robot
( )8.A.dressed B.cleaned C.pushed D.pleased
( )9.A.teacher B.student C.robot D.driver
( )10.A.driving B.accommodating C.loading D.holding
( )11.A.give B.show C.send D.lend
( )12.A.teacher B.driver C.robot D.car
( )13.A.check B.prepare C.inspect D.do
( )14.A.if B.when C.but D.because
( )15.A.miss B.learn C.study D.check
( )16.A.energetic B.optimistic C.great D.handsome
( )17.A.easy B.difficult C.correct D.wrong
( )18.A.rushed in B.got to C.turned to D.left off
( )19.A.took B.found C.made D.kept
( )20.A.easy B.important C.boring D.influential