朗读

朗读，选自本学期所有章节的朗读任务点“Reading Aloud”。

1. Remote Learning

The coronavirus is causing massive disruption to education in China

Could teacher-pupil relations change for the better?

“Don’t delete your browser history,” Lin Kai warns his 11-year-old son, who is supposed to be live-streaming lectures delivered by his schoolteachers. Mr Lin has reason to be anxious. To curb the spread of covid-19, the authorities have closed schools and universities indefinitely. But “study must not stop”, says the education ministry. Under its orders, the country’s biggest exercise in remote learning is under way, watched over by parents. Mr Lin, who lives in the eastern city of Hangzhou, has caught his son being distracted by online games. He wants his son to know that he will inspect the browser for evidence of such naughtiness.

There are other ways to enforce discipline. Liu Weihua, who teaches at Wuhan University of Technology, cold-calls his students during live streams. With sit-down exams now impossible, his grading system places more emphasis on how students perform in classroom discussions, Mr Liu explains. These are conducted using video-conferencing platforms such as Dingtalk by Alibaba, a tech giant, and Ketang by Tencent, a competitor.

Slow internet speeds at home are no excuse for shirking, says Yue Qiu, a secondary-school teacher in Beijing. If connections are too wobbly for video calls, students can download audio files and assignments. Parental supervision is encouraged. The municipal government of Beijing has decreed that, in households with two working parents, one is entitled to stay home without any loss of pay.

In poor rural areas, where some households lack internet access, instruction by television fills the void. Since February 17th China Education Network, a state-run service, has been broadcasting classes every weekday from 8am to 10pm. The first lesson of the day is aimed at pupils in the first year of primary school. Programmes for older children air in the afternoon and evening. All core subjects, such as mathematics and Chinese, are covered.

The disruption is felt most keenly by pupils in the final year of secondary school. That is the year leading up to the gaokao, the notoriously hard university-entrance exam. Many parents fret that online learning is a poor substitute for classroom instruction. Hou Kaixuan, who will sit the gaokao in the northern city of Zhangjiakou this summer, eagerly awaits the re-opening of his school. “I’m simply more productive in a physical classroom,” he says.

Not all his classmates agree. Kaixuan observes that some of them study just as hard at home as in school, and take perverse pleasure in the fact that others must be slacking off. (It helps that very little new material is taught in the last year of secondary school. The emphasis is on revision.)

When schools and universities eventually re-open, classrooms may be different, says Mr Yue, the teacher in Beijing. The teacher-student relationship will become “less hierarchical”, he predicts. That is because China’s prolonged experiment with online learning is reducing the typical reserve between instructor and pupil. Teachers who were previously reluctant to give out their contact details on WeChat, a messaging app, now rely on it to respond to students’ queries. At Mr Yue’s school, students may even call their teachers to ask for feedback. If he is right, such a breaking-down of barriers could be one of the few happy by-products of the epidemic. 

2. The ravages of time

Throughout history, pandemics have had profound economic effects.

Pandemics are the inevitable attendants of economic progress. Interconnected trade networks and teeming cities have made societies both richer and more vulnerable, from the empires of antiquity to the integrated global economy of the present. The effects of covid-19 will be very different from those of past pathogens, which struck populations far poorer than people today, and with less knowledge of things like viruses and bacteria. The toll should be on a different scale than that exacted by the Black Death or Spanish flu. Even so, the ravages of the past offer some guide as to how the global economy may change as a result of the coronavirus.

Though the human costs of pandemics are dreadful, the long-run economic effects are not always so. The Black Death carried off an astounding one-third to two-thirds of the population of Europe, leaving lasting scars. But in the wake of the plague there was far more arable acreage than workers to farm it. The sudden scarcity of workers raised labourers’ bargaining power relative to landlords and contributed to the breakdown of the feudal economy.

It seems also to have ushered parts of north-west Europe onto a more promising growth path. Real incomes of European workers rose sharply following the pandemic, which struck the continent from 1347 to 1351. In pre-industrial times, higher incomes usually enabled faster population growth, which eventually squeezed incomes back to subsistence levels (as observed by Thomas Malthus). But in parts of Europe, Malthusian rules did not reassert themselves after the pandemic receded. Nico Voigtländer, of the University of California, Los Angeles, and Hans-Joachim Voth, now of the University of Zurich, argue that the high incomes induced by plague led to more spending on manufactured goods produced in cities, and thus to higher rates of urbanisation. The plague effectively shoved parts of Europe from a low-wage, less urbanised equilibrium on a path more congenial to the development of a commercial, and then an industrial, economy.

Something similar occurred in the aftermath of the Spanish flu, which killed between 20m and 100m people from 1918 to 1920. The industrial economies of the early 20th century were no longer bound by Malthusian constraints. Even so, reckon Elizabeth Brainerd, now at Brandeis University, and Mark Siegler, of California State University, American states harder hit by the disease grew faster in its aftermath. After controlling for a range of economic and demographic factors, they find that one additional death per thousand people was associated with an increase in average annual growth of real income per person over the next decade of at least 0.15 percentage points. Though the toll of covid-19 is likely to be too low to boost real wages, it may force firms to embrace new technologies in order to operate while warehouses and offices are empty, with lasting effects on growth and productivity.

3. Chinese technology 

With the state’s help, Chinese technology is booming But it will not be a smooth road to global dominance, says Hal Hodson.

FOR MOST of human history, China was the world’s most advanced technological power. The blast furnace originated there, and thus so, too, did cast iron. Other breakthroughs included porcelain and paper. Its gunpowder propelled the first military rockets farther than javelin or arrow could fly; its compasses magically revealed magnetic north when the stars were hidden. 

Only in the Middle Ages did Europe began to match Chinese ingenuity and capacity in these fields, doing so largely through imitation. Only with the growth of European mechanical industries and overseas empires in the 18th century did the Westerners become its rivals. In the centuries that followed, hampered by its own stifling education system, China was defeated in the opium wars, then suffered terrible civil unrest and a disastrous revolution that reduced the country to a technological bystander and “Made in China” to a byword for gimcrackery. 

Now China is back, trailing clouds of smartphones, high-speed trains, stealthy aircraft, bitcoin mines and other appurtenances of high-tech flair. The parts of the world that overtook it are worried. In 2015 its leaders announced a ten-year, $300bn plan, “Made in China 2025”, designed to make its semiconductor, electric-vehicle and artificial-intelligence industries (and many others) as good as any in the world, if not better. This declaration that China was no longer content with being a factory for American high-tech products created a new tension between the world’s two largest economies. As the plan approaches its halfway point, this conflict seem to be worsening. 

America accuses China of stealing and spying its way up the technology supply chain and hobbling American technology by keeping it out of the Chinese market. Its defence department worries about running military operations through networks stuffed with Chinese components. Senators are troubled by how China is using technology to oppress its own people. The American policy establishment fears that the trend for connecting previously unconnected objects like trains and cars to computer networks will offer the Chinese government increased geopolitical leverage at the very least—and at worst, direct control of parts of other countries’ infrastructure. China’s perspective is more straightforward: America is unfairly using its existing power to curtail China’s rightful technological return. 

Much thinking about these issues focuses on what technological capabilities China has and what it lacks, where it is ahead of America and where it is lagging behind. But that piecemeal account offers little help in understanding China’s ability to foster new technologies or to dominate the supply chains and standards that underpin them. The vital question is not what technologies China has access to now, but how it built that access and how its capacity for fostering new technologies is evolving. 

The process of gaining that understanding starts with looking at older technologies, such as high-speed trains and nuclear-power plants. The work of indigenising these technologies is almost complete, and the Chinese firms and state-owned enterprises behind them are poised to export to the world. As such, they represent a model of successful state-led development that has used the state’s repressive power over its citizenry and the sway it holds over the economy to deploy technology on a massive scale. 

4. The covid network

Well-networked areas tend to have more infections than their average incomes and population densities suggest

NOW THAT the first wave of covid-19 infections has crested, governments are starting to relax their lockdowns. In Italy shops will open their doors from May 18th. Parts of Germany and America are also reopening on a state-by-state basis. Mobile-phone data show that people are buzzing around a bit more than they did in April.

Greater mobility raises the risk of a second wave of cases. For countries where policies are set locally, a big worry is that outbreaks could begin in areas with lax rules and spread elsewhere. In theory, this risk should mirror “interconnectedness”—the amount of travel to and from each region. One possible explanation for why Lombardy was hit so hard by covid-19 is that it is the best-networked part of Italy.

Teralytics, a Swiss technology firm, has compiled data from Germany, Italy and America that support this hypothesis. Each time a mobile phone leaves one location and arrives at a new one for an hour or more—whether such travel is within a city or for longer distances—Teralytics logs the journey. In the week before lockdowns began, the firm recorded 5.7bn trips. Travel fell by 40% once they were implemented.

To test how interconnectedness affects vulnerability to covid-19, we built two statistical models to predict local infection rates during the period just before lockdowns. The first relied solely on each area’s population density and income. The second added on two measures of propensity for travel: its number of journeys and its “network centrality”, or how many other places it tends to exchange visitors with.

The more elaborate model fared better, with 30% more explanatory power than relying on population density and income alone. Interconnectedness matters a lot. In all three countries, better-networked areas had more infections than the simple model predicted. Less-networked ones had fewer.

Governments should treat travel hubs with caution. So far, many German cities have seen surprisingly few infections—perhaps because the country tests widely, and began locking down earlier in its epidemic (as measured by the death toll) than Italy did. Now that Germany is easing restrictions, its infection rate may rise again. Well-networked Frankfurt is probably at greater risk than, say, comparatively disconnected Hanover, and should reopen relatively slowly. Milan in Italy, and Houston in America, should be cautious, too.

5. Will a robot really take your job?

A notorious forecast about the automation of jobs has been hugely misunderstood, says one of its authors

Jun 27th 2019

IT IS ONE of the most widely quoted statistics of recent years. No report or conference presentation on the future of work is complete without it. Think-tanks, consultancies, government agencies and news outlets have pointed to it as evidence of an imminent jobs apocalypse. The finding—that 47% of American jobs are at high risk of automation by the mid-2030s—comes from a paper published in 2013 by two Oxford academics, Carl Benedikt Frey and Michael Osborne. It has since been cited in more than 4,000 other academic articles. Meet Mr Frey, a Swedish economic historian, in person, however, and he seems no prophet of doom. Indeed, Mr 47% turns out not to be gloomy at all. “Lots of people actually think I believe that half of all jobs are going to be automated in a decade or two,” he says, leaving half the population unemployed. That is, Mr Frey stresses, “definitely not what the paper says”.

So what does it say? Its authors modelled the characteristics of 702 occupations and classified them according to their “susceptibility to computerisation”. This classification was, ironically, itself automated—using a machine-learning system built by Mr Osborne, which was trained using 70 hand-labelled examples. After crunching the numbers, the model concluded that occupations accounting for 47% of current American jobs (including those in office administration, sales and various service industries) fell into the “high risk” category. But, the paper goes on, this simply means that, compared with other professions, they are the most vulnerable to automation. “We make no attempt to estimate how many jobs will actually be automated,” the authors write. That, they underscore, will depend on many other things, such as cost, regulatory concerns, political pressure and social resistance.

The paper was intended for an academic audience, says Mr Frey, and got “more attention than we would ever have expected”. Chinese whispers and exaggerated headlines meant the carefully caveated, theoretical and highly unlikely upper bound of 47% came to be seen by some as a firm prediction—sometimes even a target. In April one striking dockworker in Los Angeles carried a placard that read “47% of American jobs are planned to be automated by 2034”. Needless to say, they are not.

Such misperceptions, irksome as they are to Mr Frey, are also telling. For, he says, they reflect the polarised nature of the debate about the nature of automation and the future of jobs.

At one extreme are the doom-mongers. They warn of mass technological joblessness just around the corner. One advocate of this position, Martin Ford, has written two bestselling books on the dangers of automation. Mr Ford worries that middle-class jobs will vanish, economic mobility will cease and a wealthy plutocracy could “shut itself away in gated communities or in elite cities, perhaps guarded by autonomous military robots and drones”. The unemployed masses will subsist on a universal basic income. At the sanguine end of the spectrum, classical economists argue that in the past new technology has always ended up creating more jobs than it destroyed. Everything will work out fine in the long run, these optimists reckon, though the short term is likely to be bumpy, as it was during the Industrial Revolution, unless governments take action to smooth the transition.

Mr Frey is often assumed to be in the first camp. So plenty of people are stunned to discover that he is, in fact, closer to the second. He has now laid out his position in more detail in a new book, “The Technology Trap”. This has allowed him, he says, to put the 47% figure in “the right context”. That context is largely historical. Building on his original paper, he revisits the history of industrialisation and asks what lessons it provides today.

One is that new technologies take time to produce productivity and wage gains. It was several decades before industrialisation led to significantly higher wages for British workers in the early 1800s, a delay known as Engels’s pause, after the theorist of communism who observed it. Another lesson is that, even though it eventually increases the overall size of the economic pie, automation is also likely to boost inequality in the short run, by pushing some people into lower-paid jobs. Mr Frey is concerned that automation will leave many people worse off in the short term, leading to unrest and opposition, which could in turn slow the pace of automation and productivity growth. Everyone would then be worse off in the long run. This is the titular “technology trap”. Whereas many people assume he worries about a world with too many robots, Mr Frey is in reality more concerned about a future with too few.

To avoid the trap, Mr Frey argues, today’s policymakers should take advantage of the fact that this time around it is possible to see how things might play out, and manage the transition accordingly. In particular that means making greater use of wage insurance, to compensate workers who have to move to jobs with a lower salary; reforming education systems to boost early-childhood education and support retraining and lifelong learning; extending income tax credit to improve incentives to work and reduce inequality; removing regulations that hinder job-switching; providing “mobility vouchers” to subsidise relocation as the distribution of jobs changes; and changing zoning rules to allow more people to live in the cities where jobs are being created.

Boom or gloom

These are all sensible suggestions. Will anyone pay attention? Messrs Frey and Osborne had an unexpected smash hit with their study. But the bestselling books on artificial intelligence, robots and automation are the bleak ones, like Mr Ford’s. In part that is because fear sells, particularly if stoked by misunderstanding, whereas pragmatic expositions of policy proposals do not—or not nearly as well. “The Technology Trap” may well ensnare doom-seekers’ attention with its ominous-sounding title. But it should ultimately hearten anyone who reads it. Provided, that is, they read it more carefully than they read Mr Frey’s earlier work.