原标题:美利坚独资国老工业营地的复兴 | 南洋理工技术评论

Review by Edward
Luce

Here’s a startling fact: in the 45 years since the introduction of the
automated teller machine, those vending machines that dispense cash, the
number of human bank tellers employed in the United States has roughly
doubled, from about a quarter of a million to a half a million. A
quarter of a million in 1970 to about a half a million today, with
100,000 added since the year 2000.

Technology and innovation may be ‘‘overhyped’’ according to the director
of the Centre for Future Work at the Australia Institute, Jim Stanford.

From rust belt to robot belt: Turning AI into jobs in the US
heartland

Martin Ford has seen the future, and it doesn’t work. To be more
precise, it generates wealth while obliterating demand for work. “Go
West, young man”, was the career advice of the 19th century. Today’s
equivalent is “get an engineering degree”. Alas, the latter is not as
rewarding as the former. A third of Americans who graduated in STEM
subjects (science, technology, engineering and maths) are in jobs that
do not require any such degree. Up and down the US there are programmers
working as fast-food servers. In the age of artificial intelligence,
they will only drift further into obsolescence, says Ford.

These facts, revealed in a recent book by Boston University economist
James Bessen, raise an intriguing question: what are all those tellers
doing, and why hasn’t automation eliminated their employment by now? If
you think about it, many of the great inventions of the last 200 years
were designed to replace human labor. Tractors were developed to
substitute mechanical power for human physical toil. Assembly lines were
engineered to replace inconsistent human handiwork with machine
perfection. Computers were programmed to swap out error-prone,
inconsistent human calculation with digital perfection. These inventions
have worked. We no longer dig ditches by hand, pound tools out of
wrought iron or do bookkeeping using actual books. And yet, the fraction
of US adults employed in the labor market is higher now in 2016 than it
was 125 years ago, in 1890, and it’s risen in just about every decade in
the intervening 125 years.

As we grapple with the advent of technological change – with
developments in areas such as artificial intelligence, machine learning,
the Internet of Things coming apace – it is easy to conclude that the
workplace of the future will be unrecognisable from that of the present.

金沙网址 1

Though Ford is a software entre­preneur, it is easy to dismiss his
prognosis as the rantings of a latter-day Luddite. That is how many
responded to his last book The Lights in the Tunnel (2009), which warned
of a future in which even highly skilled occupations were vulnerable.
Rise of the Robots is Ford’s answer to those critics. Unlike his first
book, which was based on a thought experiment about tomorrow’s world,
this one is grounded in today’s economy. It is well researched and
disturbingly persuasive.

This poses a paradox. Our machines increasingly do our work for us. Why
doesn’t this make our labor redundant and our skills obsolete? Why are
there still so many jobs?

But Stanford is not convinced that is the case.

The vast vacant lot along the Monongahela
River has been a scar from Pittsburgh’s industrial past for decades. It
was once the site of the Jones and Laughlin steelworks, one of the
largest such facilities in the city back when steel was the dominant
industry there.

Ford’s contention is that our current technological revolution is
different from earlier ones. Most economists would disagree. Their view
is that today’s displacement is similar to the shift from agriculture to
industry. Roughly half of Americans were employed on farms in 1900.
Today they account for just 2 per cent of the workforce. Just as ex-farm
labourers found work in the factories, so laid-off manufacturing workers
were re-employed in the service industries. The IT revolution will be no
different, economists say. It is all part of the natural cycle of
creative destruction.

(Laughter)

‘‘Sure, there are some incredible devices, some incredible technology,
that will affect how we work, but we’ve experienced continual
technological change for the last 200 years,’’ he says.

莫农加Sheila河畔的大块空地是长沙归西几10年工业辉煌的疤痕。那里曾是琼斯和劳克林钢铁厂旧址,那是坚强还是本地首要产业时最大的一家工厂。

Ford finds two big holes in this Panglossian outlook. In contrast to
earlier disruptions, which affected particular sectors of the economy,
the effects of today’s revolution are “general-purpose”. From janitors
to surgeons, virtually no jobs will be immune. Whether you are training
to be an airline pilot, a retail assistant, a lawyer or a financial
trader, labour-saving techno­logy is whittling your numbers — in some
cases drastically so. In 2000, financial services employed 150,000
people in New York. By 2013 that had dropped to 100,000. Over the same
time, Wall Street’s profits have soared. Up to 70 per cent of all equity
trades are now executed by algorithms.

I’m going to try to answer that question tonight, and along the way, I’m
going to tell you what this means for the future of work and the
challenges that automation does and does not pose for our society.

‘‘Regularly there have been predictions that work is going to disappear
because of technology, and our biggest problem will be working out what
to do with all our leisure time. That doesn’t ever seem to pan out.

Most of the massive structures are long
gone, leaving behind empty fields pocked with occasional remnants of
steelmaking and a few odd buildings. It all stares down the river at
downtown Pittsburgh.

Or take social media. In 2006, Google bought YouTube for $1.65bn. It had
65 employees. The price amounted to $25m per employee. In 2012, Facebook
bought Instagram, which had 13 employees, for $1bn. That came to $77m
per employee. In 2014, it bought Whats­App, with 55 employees, for
$19bn, at a staggering $345m per employee.

Why are there so many jobs? There are actually two fundamental economic
principles at stake. One has to do with human genius and creativity. The
other has to do with human insatiability, or greed, if you like. I’m
going to call the first of these the O-ring principle, and it determines
the type of work that we do. The second principle is the
never-get-enough principle, and it determines how many jobs there
actually are.

‘‘In the real world, there’s more obstacles to technology replacing
labour than we give credit for.’’

大部重型设施已经不见了,只剩余空地,到处是炼钢留下的沉渣和多少稀奇的建造,凝望着下游的苏州老城。

【金沙网址】美利哥老工业集散地的复兴。Such riches are little comfort to the thousands of engineers who cannot
find work. Facebook’s data servers are now managed by Cyborg, a software
programme. It requires one human technician for every 20,000 computers.
Almost any job that involves sitting in front of a screen and
manipulating information is either disappearing, or will do soon.
Offshore workers in India are just as vulnerable as their counterparts
in the west. China is the fastest- growing market for robots. No human
can compete with the relentlessly falling costs of automation. Software
can now drive cars and mark student essays.

Let’s start with the O-ring. ATMs, automated teller machines, had two
countervailing effects on bank teller employment. As you would expect,
they replaced a lot of teller tasks. The number of tellers per branch
fell by about a third. But banks quickly discovered that it also was
cheaper to open new branches, and the number of bank branches increased
by about 40 percent in the same time period. The net result was more
branches and more tellers. But those tellers were doing somewhat
different work. As their routine, cash-handling tasks receded, they
became less like checkout clerks and more like salespeople, forging
relationships with customers, solving problems and introducing them to
new products like credit cards, loans and investments: more tellers
doing a more cognitively demanding job. There’s a general principle
here. Most of the work that we do requires a multiplicity of skills, and
brains and brawn, technical expertise and intuitive mastery,
perspiration and inspiration in the words of Thomas Edison. In general,
automating some subset of those tasks doesn’t make the other ones
unnecessary. In fact, it makes them more important. It increases their
economic value.

A highly influential 2013 study by the Oxford Martin School (a research
and policy unit based in the Social Sciences Division of Oxford
University) predicted that 47 per cent of all jobs could be automated by
2033 – a study whose fame is unfortunate, in Stanford’s eyes.

Next to the sprawling site is one of
Pittsburgh’s poorer neighborhoods, Hazelwood, where a house can go for
less than $50,000. As with many of the towns that stretch south along
the river toward West Virginia, like McKeesport and Duquesne, the
economic reasons for its existence—steel and coal—are a fading
memory.

Almost any job that involves sitting in front of a screen and
manipulating information is threatened
But it is Ford’s second point that is the clincher. By skewing the gains
of the new economy to a few, robots weaken the chief engine of growth —
middle-class demand. As labour becomes uneconomic relative to machines,
purchasing power diminishes. The US economy produces more than a third
more today than it did in 1998 with the same-sized labour force and a
significantly larger population. It still makes sense for people to
obtain degrees. Graduates earn more than those who have completed only
high school. But their returns are falling. The median pay for US
entry-level graduates has fallen from $52,000 in 2000 to $46,000 today.
It has stagnated for postgraduates. Education is by no means a catch-all
solution, says Ford. Not everyone can get a PhD. Assuming that highly
skilled jobs can take up the slack is “ana­logous to believing that, in
the wake of the mechanisation of agriculture, the majority of displaced
farm workers would be able to find jobs driving tractors,” he says.

Let me give you a stark example. In 1986, the space shuttle Challenger
exploded and crashed back down to Earth less than two minutes after
takeoff. The cause of that crash, it turned out, was an inexpensive
rubber O-ring in the booster rocket that had frozen on the launchpad the
night before and failed catastrophically moments after takeoff. In this
multibillion dollar enterprise that simple rubber O-ring made the
difference between mission success and the calamitous death of seven
astronauts. An ingenious metaphor for this tragic setting is the O-ring
production function, named by Harvard economist Michael Kremer after the
Challenger disaster. The O-ring production function conceives of the
work as a series of interlocking steps, links in a chain. Every one of
those links must hold for the mission to succeed. If any of them fails,
the mission, or the product or the service, comes crashing down. This
precarious situation has a surprisingly positive implication, which is
that improvements in the reliability of any one link in the chain
increases the value of improving any of the other links. Concretely, if
most of the links are brittle and prone to breakage, the fact that your
link is not that reliable is not that important. Probably something else
will break anyway. But as all the other links become robust and
reliable, the importance of your link becomes more essential. In the
limit, everything depends upon it. The reason the O-ring was critical to
space shuttle Challenger is because everything else worked perfectly. If
the Challenger were kind of the space era equivalent of Microsoft
Windows 2000 —

‘‘That’s nonsense, it won’t happen. There are certain jobs and
occupations that will be turned upside down by technology, but we humans
have a tendency to believe that just because something can happen, it
will become widespread. That is not necessarily the case.’’

大片杂乱的废地旁是马普托最贫困的住宅区黑泽尔伍德,那里一栋房子不到50000法郎。沿河合伙向东到马里金华的重重城市和市镇,像McGee斯Porter和迪凯纳等,其设有的经济原因——钢铁和煤炭——都已成以往的事情。

What, then, is to be done? Peter Thiel, co-founder of PayPal, said: “We
were promised flying cars, and instead what we got was 140 characters.”
He was right of course; Twitter is not comparable to the invention of
printing. Yet in another sense, he was wrong. We live in a world where
everyone with a grievance wields more power in the palm of their hands
than the computers that sent Apollo 14 into orbit. Ours is a
super-democratic age. Ford does not believe technological progress can
be stopped, nor that it would it be desirable to try. Yet the robot
economy is inexorably squeezing our rewards in the jobs market. Ford’s
answer is to pay every adult a minimum basic income — or a “citizen’s
dividend”. There is logic to his remedy but not much realism. My
forecast is that cars will fly before that happens.

(Laughter)

A good example is the driverless vehicle, he says. ‘‘We can do it, in a
controlled environment, the technology is there – but in order to make
it happen everywhere around us, there are going to be huge challenges in
infrastructure, communications and regulation, in public acceptance, in
capital investment. Just because these things can be done by engineers
in controlled environments, it doesn’t mean they are going to become
widespread.’’

These days the old steel site, called
Hazelwood Green by its developers, is coming back to life. At one edge,
fenced off from prying eyes, is a test area for Uber’s self-driving
cars. A new road, still closed to the public, traverses the 178 acres of
the site, complete with parking signs, fire hydrants, a paved bike path,
and a sidewalk. It doesn’t take much imagination to picture it bustling
with visitors to the planned park along the riverfront.

the reliability of the O-ring wouldn’t have mattered because the machine
would have crashed.

The other thing that we tend to forget, he says, is that technological
advancements often create as many jobs as they remove. ‘‘If we look at
history there have been previous periods of very wide-ranging
technological change that didn’t necessarily cause mass unemployment.

当今,被开发商成为“黑泽尔伍德天蓝”的老钢厂区正在苏醒。一边是优步自动驾乘小车的试验场,拦起来防人窥探。一条还未开放的新路穿过17捌公里的老钢厂区,装有许多停车标志、消防龙头、自行车道和中国人民银行道。用不着脑补就能够想像陈设中的河滨公园中过多的场景。

(Laughter)

金沙网址 2

The gem of the redevelopment effort is
Mill 19, the former coke works. A structure more than a quarter-­mile
long, sitting amid the empty fields, it has been stripped clean to a
three-story metal skeleton. Crews of workers are clearing away remaining
debris and preparing the building for its reincarnation. By next spring,
if all goes according to plan, its first occupant will move in: the
Advanced Robotics for Manufacturing Institute.

Here’s the broader point. In much of the work that we do, we are the
O-rings. Yes, ATMs could do certain cash-handling tasks faster and
better than tellers, but that didn’t make tellers superfluous. It
increased the importance of their problem-solving skills and their
relationships with customers. The same principle applies if we’re
building a building, if we’re diagnosing and caring for a patient, or if
we are teaching a class to a roomful of high schoolers. As our tools
improve, technology magnifies our leverage and increases the importance
of our expertise and our judgment and our creativity.

Artificial intelligence is expanding, but jobs will continue to be
created in areas such as human and caring services.

在支付品种的精华是1玖车间,在此之前是木炭车间。那是跨度400多米的修建,坐落在空地之中,现在已被投掷为3个三层的五金骨架。大量工友正在清理剩下的废料,准备再造那第二建工公司筑。假如整个按安排举办,二〇二〇年春季,第3堆公司将入住:先进机器人创造商讨所。

And that brings me to the second principle: never get enough. You may be
thinking, OK, O-ring, got it, that says the jobs that people do will be
important. They can’t be done by machines, but they still need to be
done. But that doesn’t tell me how many jobs there will need to be. If
you think about it, isn’t it kind of self-evident that once we get
sufficiently productive at something, we’ve basically worked our way out
of a job? In 1900, 40 percent of all US employment was on farms. Today,
it’s less than two percent. Why are there so few farmers today? It’s not
because we’re eating less.

‘‘If the technologies tend to spur stronger business investment, then
you have a chance of growing jobs from them. All of these technologies
have got new work associated with them – yes, they do displace some
jobs, but they create other jobs, jobs that are required to operate,
develop, manufacture and maintain the new machinery, that involve doing
things that weren’t possible before the machinery was invented.’’

The symbolism of robots moving into a
former steelworks is lost on few people in the city. Pittsburgh is
reinventing itself, using the advances in automation, robots, and
artificial intelligence coming out of its schools—particularly Carnegie
Mellon University (CMU)—to try to create a high-tech economy.

(Laughter)

Stanford says it is too easy for people to conclude that there are
relatively unskilled tasks – which will be automated away – and skilled
tasks, which will not. ‘‘There isn’t a perfect correlation between the
level of skills in your job and whether or not you can be replaced by a
machine. There is a kind of shorthand that says, ‘if you’ve got skills
you’re going to be safe,’ but I’d be very cautious about assuming
that.’’

机器人进入曾经的炼钢厂,那所城市中差不离一直不人会忽略这种象征意义。台中重生,使用来源其高校中的自动化、机器人和人造智能,尤其是Carnegie梅隆高校,正在创设1种高科技(science and technology)经济。

A century of productivity growth in farming means that now, a couple of
million farmers can feed a nation of 320 million. That’s amazing
progress, but it also means there are only so many O-ring jobs left in
farming. So clearly, technology can eliminate jobs. Farming is only one
example. There are many others like it. But what’s true about a single
product or service or industry has never been true about the economy as
a whole. Many of the industries in which we now work — health and
medicine, finance and insurance, electronics and computing — were tiny
or barely existent a century ago. Many of the products that we spend a
lot of our money on — air conditioners, sport utility vehicles,
computers and mobile devices — were unattainably expensive, or just
hadn’t been invented a century ago. As automation frees our time,
increases the scope of what is possible, we invent new products, new
ideas, new services that command our attention, occupy our time and spur
consumption. You may think some of these things are frivolous — extreme
yoga, adventure tourism, Pokémon GO — and I might agree with you. But
people desire these things, and they’re willing to work hard for them.
The average worker in 2015 wanting to attain the average living standard
in 1915 could do so by working just 17 weeks a year, one third of the
time. But most people don’t choose to do that. They are willing to work
hard to harvest the technological bounty that is available to them.
Material abundance has never eliminated perceived scarcity. In the words
of economist Thorstein Veblen, invention is the mother of necessity.

There are many low-skilled jobs that will remain safe, he says. ‘‘That
includes so-called lower-skilled jobs in private services – like
cleaning and hospitality work – and also in a lot of the hands-on work
that is required in those human services like healthcare.

Lawrenceville, five miles from Hazelwood,
has become a center for US development of self-driving cars. Uber
Advanced Technologies occupies a handful of industrial buildings;
self-driving startups Argo AI and Aurora Innovation are nearby. Even
Caterpillar has set up shop, working on autonomous backhoes and other
heavy machines that could one day operate themselves.

Now … So if you accept these two principles, the O-ring principle and
the never-get-enough principle, then you agree with me. There will be
jobs. Does that mean there’s nothing to worry about? Automation,
employment, robots and jobs — it’ll all take care of itself? No. That
is not my argument. Automation creates wealth by allowing us to do more
work in less time. There is no economic law that says that we will use
that wealth well, and that is worth worrying about. Consider two
countries, Norway and Saudi Arabia. Both oil-rich nations, it’s like
they have money spurting out of a hole in the ground.

‘‘But by the same token, there’s a lot of traditionally
higher-knowledge, higher-status jobs where the risks of automation are
quite severe – for example, lawyers, accountants, engineers and
geologists.’’

相差黑泽尔伍德5公里的Lawrence维尔已变为美利哥机动驾乘小车发展的主旨。优步先进技术应用了多少个工业建筑;自动驾乘初创集团阿尔戈AI和欧若拉立异都在左近,连Carter彼勒都设置车间,开发自动反铲挖掘机和其他大型设备,它们有壹天能够活动运维。

(Laughter)

Where jobs will continue to be created, he says, is in areas that are
more service-oriented: in particular, public services – human and caring
services – such as healthcare and social services, education and public
administration.

This has drawn billions of dollars from
Silicon Valley and elsewhere, a welcome development in a city whose
economy has been moribund for decades. And the effects are visible.
Self-driving cars out for a test ride are a common sight, as are lines
outside the trendy restaurants in what civic boosters call “Robotics
Row.”

But they haven’t used that wealth equally well to foster human
prosperity, human prospering. Norway is a thriving democracy. By and
large, its citizens work and play well together. It’s typically numbered
between first and fourth in rankings of national happiness. Saudi Arabia
is an absolute monarchy in which many citizens lack a path for personal
advancement. It’s typically ranked 35th among nations in happiness,
which is low for such a wealthy nation. Just by way of comparison, the
US is typically ranked around 12th or 13th. The difference between these
two countries is not their wealth and it’s not their technology. It’s
their institutions. Norway has invested to build a society with
opportunity and economic mobility. Saudi Arabia has raised living
standards while frustrating many other human strivings. Two countries,
both wealthy, not equally well off.

‘‘Those areas are growing as a share of total work. Where jobs have been
created in the last five years – and the forecasts of where they’re
going to be created in the next five years – public services are very
disproportionately important. In fact, about half of all jobs in the
next five years will be public services. That suggests that as society
both ages and gets richer, people are going to want more of those types
of services,’’ says Stanford.

那引发了来自硅谷等地的数10亿先令,在1个几十年来经济一泻百里不振的都会中,那是令人欢迎的开始展览。效果是明显的。试验场开出来的自发性驾车汽车屡见不鲜,在高档酒馆外排队,被本地帮忙者称为“机器人队列”。

And this brings me to the challenge that we face today, the challenge
that automation poses for us. The challenge is not that we’re running
out of work. The US has added 14 million jobs since the depths of the
Great Recession. The challenge is that many of those jobs are not good
jobs, and many citizens cannot qualify for the good jobs that are being
created. Employment growth in the United States and in much of the
developed world looks something like a barbell with increasing poundage
on either end of the bar. On the one hand, you have high-education,
high-wage jobs like doctors and nurses, programmers and engineers,
marketing and sales managers. Employment is robust in these jobs,
employment growth. Similarly, employment growth is robust in many
low-skill, low-education jobs like food service, cleaning, security,
home health aids. Simultaneously, employment is shrinking in many
middle-education, middle-wage, middle-class jobs, like blue-collar
production and operative positions and white-collar clerical and sales
positions. The reasons behind this contracting middle are not
mysterious. Many of those middle-skill jobs use well-understood rules
and procedures that can increasingly be codified in software and
executed by computers. The challenge that this phenomenon creates, what
economists call employment polarization, is that it knocks out rungs in
the economic ladder, shrinks the size of the middle class and threatens
to make us a more stratified society. On the one hand, a set of highly
paid, highly educated professionals doing interesting work, on the
other, a large number of citizens in low-paid jobs whose primary
responsibility is to see to the comfort and health of the affluent. That
is not my vision of progress, and I doubt that it is yours.

Most work in society will still be doing the ‘‘traditional, hands-on,
mundane’’ things that society needs – and will continue to need, he
says. ‘‘Instead of viewing that as a drain or a cost, we should
celebrate it, and recognise that this type of work is producing the
things that people want, and then value it accordingly.’’

While many longtime residents complain of
skyrocketing home prices near the tech firms’ headquarters and test
facilities, they’ll also tell you these are the best days the city has
seen in their lifetimes.

But here is some encouraging news. We have faced equally momentous
economic transformations in the past, and we have come through them
successfully. In the late 1800s and early 1900s, when automation was
eliminating vast numbers of agricultural jobs — remember that tractor?
— the farm states faced a threat of mass unemployment, a generation of
youth no longer needed on the farm but not prepared for industry. Rising
to this challenge, they took the radical step of requiring that their
entire youth population remain in school and continue their education to
the ripe old age of 16. This was called the high school movement, and it
was a radically expensive thing to do. Not only did they have to invest
in the schools, but those kids couldn’t work at their jobs. It also
turned out to be one of the best investments the US made in the 20th
century. It gave us the most skilled, the most flexible and the most
productive workforce in the world. To see how well this worked, imagine
taking the labor force of 1899 and bringing them into the present.
Despite their strong backs and good characters, many of them would lack
the basic literacy and numeracy skills to do all but the most mundane
jobs. Many of them would be unemployable.

Nor is Stanford a big believer in the ‘‘gig economy’’. Where it is
available, he says some people do prefer the flexibility and the
autonomy – but too often, that is in the context of a world where it is
very hard to find a traditional job.

即便不少老居民怨声载道技术公司总部和试验场周围的房价猛涨,他们也会告诉您,那是她们那辈子看到那个都市的特级时间。

What this example highlights is the primacy of our institutions, most
especially our schools, in allowing us to reap the harvest of our
technological prosperity.

But for most people, that is ‘‘an incredibly insecure way of trying to
support yourself’’, he says. ‘‘I think young people are interested in
full-time jobs. They want to have a mortgage and a house and a family
one day. They know full well that you can’t do that on a series of
gigs.’’

But despite all this activity,
Pittsburgh’s economy is struggling by many measures. Though the city’s
population is no longer hemorrhaging away—between 1970 and 1980 it fell
by roughly a fifth—it isn’t growing, either, and is aging quickly. During the last half-decade, almost 70,000
people aged 35 to 54 have left the region.

It’s foolish to say there’s nothing to worry about. Clearly we can get
this wrong. If the US had not invested in its schools and in its skills
a century ago with the high school movement, we would be a less
prosperous, a less mobile and probably a lot less happy society. But
it’s equally foolish to say that our fates are sealed. That’s not
decided by the machines. It’s not even decided by the market. It’s
decided by us and by our institutions.

Nor, he suggests, will we all be working from home, or from coffee
shops. ‘‘Again, the technology gives us far greater flexibility than we
have ever had, but ironically, in the real world, people value
face-to-face contact and networking – perhaps more than ever,’’ says
Stanford.

就算这几个活动扶摇直上,纽伦堡的经济在成千成万地点照旧困难。固然城市人口已不复大量流出,一玖陆6年到一玖七六年间,人口降低了月6分之1,可最近也绝非增进,并且在高速老龄化。过去5年间,近七万3四岁到五十四虚岁时期的人口离开该地段。

Now, I started this talk with a paradox. Our machines increasingly do
our work for us. Why doesn’t that make our labor superfluous, our skills
redundant? Isn’t it obvious that the road to our economic and social
hell is paved with our own great inventions?

‘‘If you could do your job from anywhere, why on earth would a business
pay Sydney or Melbourne prices for real estate, in order to establish
there? They do so because proximity actually does matter, in all kinds
of ways, including face-to-face contact in business services and public
services,’’ he says.

And not far from the city and its elite
universities, in areas where the main hope for prosperity lies in coal
and natural gas from fracking rather than self-driving cars,
well-­paying jobs are scarce and towns are being devastated by opioid
addiction.

History has repeatedly offered an answer to that paradox. The first part
of the answer is that technology magnifies our leverage, increases the
importance, the added value of our expertise, our judgment and our
creativity. That’s the O-ring. The second part of the answer is our
endless inventiveness and bottomless desires means that we never get
enough, never get enough. There’s always new work to do. Adjusting to
the rapid pace of technological change creates real challenges, seen
most clearly in our polarized labor market and the threat that it poses
to economic mobility. Rising to this challenge is not automatic. It’s
not costless. It’s not easy. But it is feasible. And here is some
encouraging news. Because of our amazing productivity, we’re rich. Of
course we can afford to invest in ourselves and in our children as
America did a hundred years ago with the high school movement. Arguably,
we can’t afford not to.

‘‘Unless someone has a very unique skill and a very high reputation, an
employer doesn’t want to just pay you to sit at home. They actually want
to see that you’re part of a team, that you’re doing what they want you
to be doing. Again, I don’t see a whole lot of change in the way that we
have to physically go to work, as part of our lives,’’ Stanford says.

相差城市和城市的一流高校不远,那多少个经济腾飞的严重性意在首要正视煤炭和页岩气而非自动开车小车的地域,高薪工作很少,阿片药物成瘾正在毁灭者城市和集镇。

Now, you may be thinking, Professor Autor has told us a heartwarming
tale about the distant past, the recent past, maybe the present, but
probably not the future. Because everybody knows that this time is
different. Right? Is this time different? Of course this time is
different. Every time is different. On numerous occasions in the last
200 years, scholars and activists have raised the alarm that we are
running out of work and making ourselves obsolete: for example, the
Luddites in the early 1800s; US Secretary of Labor James Davis in the
mid-1920s; Nobel Prize-winning economist Wassily Leontief in 1982; and
of course, many scholars, pundits, technologists and media figures
today.

金沙网址 3

This makes Pittsburgh not only a
microcosm of the US industrial heartland but a test case for the
question facing every city and country with access to new digital
technologies: Can AI, advanced robotics, self-driving cars, and other
recent breakthroughs spread prosperity to the population at large, or
will they just concentrate the wealth among entrepreneurs, investors,
and some highly skilled tech workers?

These predictions strike me as arrogant. These self-proclaimed oracles
are in effect saying, “If I can’t think of what people will do for work
in the future, then you, me and our kids aren’t going to think of it
either.” I don’t have the guts to take that bet against human ingenuity.
Look, I can’t tell you what people are going to do for work a hundred
years from now. But the future doesn’t hinge on my imagination. If I
were a farmer in Iowa in the year 1900, and an economist from the 21st
century teleported down to my field and said, “Hey, guess what, farmer
Autor, in the next hundred years, agricultural employment is going to
fall from 40 percent of all jobs to two percent purely due to rising
productivity. What do you think the other 38 percent of workers are
going to do?” I would not have said, “Oh, we got this. We’ll do app
development, radiological medicine, yoga instruction, Bitmoji.”

那让苏州不单变成美利坚同盟国家私心脏地带的缩影,也表现出各种拥抱新数字技术的城池和江山面临的难点:人工智能、先进机器人、自动开车小车和其余流行突破能不可能将繁荣带给周围人口,抑或它们只是把财物集中在公司家、投资人和局地高技能工人手中?

金沙网址,(Laughter)

To prosper, says Scott Andes at the
National League of Cities, Pittsburgh “can’t just be a producer of
brilliant talent and ideas that then don’t turn into job generation.” He
adds, “Pittsburgh is a great case study for the 21st-century economy,
because it is beginning to leverage research strengths into economic
value.”

I wouldn’t have had a clue. But I hope I would have had the wisdom to
say, “Wow, a 95 percent reduction in farm employment with no shortage of
food. That’s an amazing amount of progress. I hope that humanity finds
something remarkable to do with all of that prosperity.”

国家城市联盟的Scott·安德斯说,要繁荣起来,长沙“无法只是接触人才和思量的劳动者,那个不能转正为就业”。他说,“长沙是二一世纪经济体的2个宏大实验,因为它正初阶撬动商讨实力,将其转会为经济价值。”

And by and large, I would say that it has.

Changing jobs

Thank you very much.

There is no sillier—or more
disingenuous—debate in the tech community than the one over whether
robots and AI will destroy jobs or, conversely, create a great abundance
of new ones. In fact, the outcome depends on various economic factors.
And how it will play out as the pace of AI intensifies, no one
knows.

在技术界,未有比商讨机器人和人工智能是还是不是会消灭工作岗位只怕反过来会创制大批量工作岗位那1题材更可笑或更虚伪的了。事实上,结果要看许多划算因素。随着人工智能加速前行,结果会怎么样没人知道。

Automation and robots have certainly
wiped out many jobs over the last few decades, especially in
manufacturing. In one of the first attempts to quantify the impact of
industrial robots, research by Daron Acemoglu at MIT and his colleagues,
based on data from 1990 to 2007, found that for every robot on the
factory floor, some six jobs are lost. That means as many as 670,000
jobs for the years that they looked at, and as many as 1.5 million jobs
at 2016 levels of robot usage in the US.

千古几10年,自动化和机器人终将解决了过多做事,特别在创建业领域。最早一些量化学工业业机器人的震慑的研商包涵哈工业余大学学种下愿望的达龙·阿Simon格鲁及其同事依照一9玖零年到200七年的数额所做的剖析,分析发现车间中每出现一个机器人,大概八个人失掉工作。那表示一玖9〇年到200柒年不复存在了6七万个地方,以201陆年机器人在美利坚合众国利用程度总计,150万岗位流失。

Automation is changing work

Gauging the net gain or loss of jobs due
to robotics and AI is a tricky business. But it’s clear that the kinds
of jobs in demand are changing as the need for manual labor declines and
that for digital and human skills soars.

权衡机器人和人为智能导致的地方净扩充或净流失很复杂,但肯定,工作岗位必要在发生变化,对体力劳动的要求在下跌,对数字和血汗技能的急需在追加。

The McKinsey Global Institute estimates
that about 50 percent of tasks done in our economy could be automated.
But such statistics are often misinterpreted. The 50 percent merely
describes the “technical feasibility” of what can be automated with
existing and emerging technologies, says James Manyika, the institute’s
chairman. The number of actual jobs lost will depend on the costs and
benefits of replacing people with machines.

麦肯锡全世界研讨所测度,我们经济体中约二分之一的的工作将落到实处自动化。但那么些总括结果平常被误读。探讨所主席James·曼伊卡说,2/4然则描述了在存活和后来技术水平下可被自动化的“技术大概”。真正消失岗位的数据要看机器取代人工的资金财产和低收入。

Even more uncertain is how many new jobs
will be created. Many technologists, especially roboticists, assert that
advances will lead to a wealth of new kinds of work. So far, though,
that hasn’t happened, and few of the breakthroughs have reached the
largest sectors of the US economy, such as health care.

能够创设出有个别新岗位更难以分明。许多技能人员,尤其是机器人开发者,他们相信提升会长造出大批量新岗位。就算迄今甘休,那并未有发生,在美利哥经济的最大机关中差不多未有获取任何突破,如健康卫生领域。

Perhaps we just need to be patient;
technology advances have always increased incomes, which then increased
demand for goods and services, which then led to more jobs.

只怕大家要有耐心,技术发展总能增收,然后扩展对货物和劳动的急需,最终创制更多岗位。

But Laura Tyson, a top economic advisor
to President Bill Clinton and a professor at the University of
California, Berkeley, asks the question that is on everyone’s mind: What
if, this time around, the goods and services that people want just don’t
require much human labor to produce? “This is the first time that
technology, we think, could on net reduce the demand for human workers,”
she says.

但Bill·Clinton总统的上位经济顾问和加州高校Berkeley分校教师洛拉·Tyson问出全数人心中的题材:万一这回人们想要的货色和劳务偏偏不供给太多少人力生产又该怎么?“大家想,那是技术率先次下跌对工人的净要求,”她说。

“The naïve view among macroeconomists for
several decades has been that technology will always create jobs,” says
Acemoglu. “The alarmists’ is that this time is different and it will
destroy jobs.” Though in the past the economic benefits from new
technologies have always been enough to create more jobs than were lost,
he says, “lately, for a variety of reasons, there has been a much more
job-destroying face to technology.”

“几10年来,宏观史学家天真的认为技术永远能够成立岗位,”阿Simon格鲁说。“令人抓住恐慌的是那贰次不1致了,技术消灭工作。”固然过去经济收益于新技巧,创建出来的地方总比流失的多,他说,“方今,因为各类原因,技术消灭工作的一方面更强有力”。

Part of what he’s describing is the
so-called productivity paradox: while big data, automation, and AI
should in theory be making businesses more productive, boosting the
economy and creating more jobs to offset the ones being lost, this
hasn’t happened. Some economists think it’s just a matter of time—though
it could take many years.

他叙述的壹对内容是所谓的生产力悖论:理论上说,大数据、自动化和人为智能让商业活动生产力更高,促进经济并创造出越多岗位,抵消流失的地方,可那未有发生。某些医学家认为那但是是岁月难题,固然须求很多年。

But the debate about how many jobs are
gained or lost obscures a much more important point. The location of
jobs and the kind of work they involve are changing, and that’s what’s
causing real pain to people and to local economies.

可对到底能成立或消灭多少岗位的议论让芸芸众生遗忘更关键的一些。岗位在何方以及它们须要什么样岗位,两者在发生变化,那是大千世界和本地经济遭逢的着实冲击。

In the US, demand for low-­paying work in
places like warehouses and restaurants is growing; so is demand for
well-paying work in occupations requiring lots of technical skills, such
as programming. At the same time, many
traditionally middle-class jobs in areas like manufacturing and data
processing are shriveling.

在U.S.,仓库和酒馆等工作地方的入账岗位必要在加码,编制程序等急需大批量技艺技能的高薪职位也在追加。同时,许多成立业和数据处理等观念中产阶级岗位却在萎缩。

These trends have contributed to record
levels of income inequality. “There is not a lot of disagreement that
technology is changing the skills and occupations in demand,” says
Tyson. “And that will continue to increase income inequality.”

这一个动向导致了低收入空前不一致。“人们基本同意,技术转移了对技术和职业的要求,”Tyson说。“那会尤其进步收入分化等。”

This movie has, of course, played out
before. In 1900, about 40 percent of US workers were on farms; today
fewer than 2 percent are. In 1950, about 24 percent of the jobs were in
manufacturing; today around 9 percent are. Similar shifts are occurring
in other developed countries. But today’s changes are happening faster
and more broadly than before, leaving little time for people to
adapt.

理所当然,那种状态从前也时有发生过。一九零零年,约五分二的美利坚合众国工人在农场,可前几日不到贰%的人务农。1947年,约贰4%的地方在创立业,明日天津大学学约九%。那种转变也发出在其他发达国家。但后天的转移产生得更火速、更普遍,没有时间令人们做出调整。

Many are simply giving up on finding a
decent job. Labor-force participation—basically, the proportion of
people working or seeking work—is showing a troubling drop, especially
for men aged 25 to 54.

众三个人干脆不再找一份光荣工作了。劳重力参预率下落,特别是二四周岁到伍十一岁的人数,那让人担忧。

Melissa Kearney and Katharine Abraham,
economists at the University of Maryland, have looked at why. They think
there may be several causes, but they say robots and automation are a
critical one. Many people without a college degree simply think the
prospects of finding a well-­paying job are too slim to make it worth
looking.

南卡罗来纳高校管军事学家梅Lisa·Kearney和凯瑟琳·亚布拉罕商讨背后的缘由。他们觉得有多少个原因,但机器人和自动化是最关键的。许多未曾大学学位的人大约认为找到高薪工作的火候太模糊了,干脆就别去找了。

Inequality is up as growth
slows

Despite advances in AI and robotics,
productivity is sluggish, and fewer people are enjoying the benefits. To
boost growth, especially as workforce growth slows, we will need more
AI, and we’ll need to learn how to deploy it better.

即便人工智能和机器人技术取得升高,生产力却发展十分小,收益的人较少。为了在劳重力增加缓慢的情景下拉动进步,大家供给更多的人为智能,大家需求学习怎么样更好的利用它。

Princeton economist Anne Case and her
coauthor Angus Deaton have identified what’s likely a related trend.
They found that mortality is rising among middle-aged white people in
the US with a high school diploma or less.

Prince顿法学家Anne·凯斯和1块小编Angus·迪顿提出大概与此有关的一种倾向。他们发觉高粤语凭及以下的United States中年白种人,他们的病逝率在扩大。

The culprits: high rates of suicide, drug
addiction, and alcoholism, which Case and Deaton call “diseases of
despair” because they don’t seem related to poverty per se, but rather
to disappointment; in a reversal of expectations, people are realizing
they won’t be better off than their parents.

由来:高自杀率、药物成瘾和无节制饮酒,凯斯和迪顿认为那是“失望病”,因为他们看起来和本人贫穷非亲非故,而是失望。期望产生翻盘,人们正在发现他们不会比父母过得更好了。

Automation might be partly to blame for
these social problems. But if economists like Acemoglu are right, the
key to creating more good jobs is not fewer of these advances but better
versions of them that are deployed faster throughout the economy.

自动化恐怕要有的为这一个社会难点担当。但壹旦阿Simon格鲁那样的文学家说得对,创建更加多好干活的钥匙并非裁减这几个进步,而是进行更好的版本,让它们更是快捷地在任何经济体得以利用。

Pittsburgh reborn

That, in essence, is what Pittsburgh’s
attempt at reinventing itself is about. So far the results are mixed.
“The transformation of the city by new, young people working in AI and
robotics has been spectacular,” says Andrew Moore, dean of computer
science at CMU. “But it has been more of an approach of gentrification
rather than an inclusion of the community.”

终归,这正是巴尔的摩要重建的本人。迄今截止,结果喜忧参半。“在人工智能和机器人部门办事的小伙给城市拉动的变通令人惊呆,”Carnegie梅隆高校总括机科学系主管Andrew·Moore说。“但那越来越多是一种贵族化的格局,缺少社区包容性。”

That criticism resonates in a place that
prides itself as a working-class city with strong unions and a rich
history of progressive politics. Mayor William Peduto helped attract
Uber to the city, but he has since soured on the San Francisco–based
company.

这种批评在一个有着强大工会和拉长的提高主义政治史、以无产阶级城市为傲的地点而言引发了共鸣。参谋长威尔iam·佩杜托把优步引进过来,但她对这家斯德哥尔摩公司并从未怎么青眼。

“The Silicon Valley model doesn’t [put]
people in the equation. It is based on what return will be derived for
VCs,” he said in a recent interview at city hall with MIT Technology
Review. “In places like Detroit and Pittsburgh, when we look at the
future of work, we want to know what the future of the worker
is.”

“硅谷情势尚未把人设想在内。它驰念的是风险投资能获取多大回报,”他不久前收受《耶路撒冷希伯来州立技术评论》采访时说。“像马斯喀特和莱比锡那种地点,大家思索工作的前途时,大家想要知道工人的前途是何许。”

According to a recent poll, more than
half of Pittsburgh residents would strongly support Amazon’s building
its second headquarters there. That’s far more than in many cities on
Amazon’s shortlist—in Austin and Boston only around a third of the
population would welcome the move.

近年民意侦查展现,超过四分之三的巴尔的摩居民肯定帮衬亚马逊(亚马逊)将武汉定为第一总部。那比亚马逊(Amazon)名单上的其余城市多得多,在奥斯汀和布达佩斯,只有大致三分之一的人口欢迎这一举措。

It’s hardly surprising: Amazon is
pledging 50,000 jobs and $5 billion in investment, which would be
transformative for Pittsburgh. It’s rumored that the city is tempting
the company with the site along the Monongahela River that includes Mill

  1. 那并不令人吃惊:亚马逊(亚马逊)承诺创立五万个工作岗位,投资50亿英镑,那足以彻底改变台中。据传该城市拿出莫农加Sheila河畔的1块地吸引亚马逊(Amazon),个中就归纳1九车间。

But if Amazon picks Pittsburgh, that’s
likely to exacerbate the anxiety over how to match residents with new
high-tech jobs. “There is nowhere near enough people in the city and the
region with the technical skills,” says CMU’s Moore. “We’re great in
terms of the rare genius leaders, but [Pittsburgh] really needs to
skill up the local population to take part in this.”

可1旦亚马逊(亚马逊)选用了弗罗茨瓦夫,有一点都不小恐怕激化本地居民就什么与高技能岗位对接引起的焦虑。“那些都市和地域技术水平高的人不够,”Carnegie梅隆高校的Moore说。“我们并不贫乏天才领导者,但实在必要的是本土人口也有能力到场在那之中。”

The challenge facing the city and the
rest of the country, though, is not only to include more people in the
high-tech workforce but to expand the supply of those well-paying jobs.
Advanced robotics can modernize the factories in a city like Pittsburgh
and help make manufacturing more competitive.

那所城市和全国各州面临的挑衅不仅是让更多少人投入到高技能队5中来,还包括扩大高薪岗位的要求。先进机器人能够是莱比锡等都会的厂子现代化,使创制业更有竞争力。

But the factory jobs lost through the
years aren’t coming back. As a country, we’re struggling to imagine how
to build an economy with plenty of good jobs around AI and
automation.

但那一个年失去的工厂岗位不会回到了。大家很难想象怎么样创设二个经济体,人工智能和自动化带了众多好岗位。

A person standing on the flat roof of a
building in the Lawrenceville neighborhood can get a glimpse of the
future. On the first floor is a large garage housing several of Aurora’s
self-driving cars. Off in some weedy fields is a Caterpillar backhoe
belonging to the company’s research outpost for autonomous machines.
Beyond that is a fenced-in testing area
next to yet another former steel facility—this one housing Carnegie
Robotics, which is working on a bomb-clearing robot for the Army. In the
background is the National Robotics Center, another imposing building
and home—until it moves into Mill 19—of the Advanced Robotics for
Manufacturing Institute.

站在Lawrence维尔街区的建筑房顶上得以眺望今后。一层是欧若拉自动开车小车的停车区,草地外是一台Carter彼勒反铲机,那是该店铺的全自动驾乘研究开发焦点。更远处是拦起来的测试场,旁边是另一家旧钢铁厂,建筑属于Carnegie机器人,该商厦正为海军开发炸弹清除机器人。背景是国家机器人中央——另壹栋宏伟的建造,之前是先进机器人成立商讨所所在地,后者搬进了1九车间。

It’s an impressive scene highlighting
signs, if you know where to look, of some of the world’s leading
research into robotics and automation. But it is also almost deadly
quiet. There are a few cars in the parking lots—those of the engineers
and programmers involved in the various robotic ventures, and probably
some visitors. Beyond that, there are no signs of workers
anywhere.

以此场景令人印象深切,若是您找对角度,能够看看世界上初始进的机器人和自动化钻探。但那里死一般寂静。停车场里唯有不多几辆车,都以供职于各种机器人公司的工程师和程序员,只怕还有1些旅行者。除外,未有工人的迹象。回去年今年日头条,查看越来越多

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