新浦京www81707con美利哥老工业营地的复兴

原标题:美国老工业基地的复兴 | 麻省理工技术评论

Review by 新浦京www81707con美利哥老工业营地的复兴。Edward
Luce

  By: Queenie, wu    6th grade 

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.

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.

Have you ever thought about robot taking your job? I say, “No! It
won’t!” In 2016 Alpha Go under Google won against Li Shi Shi in 4:1.
Many scientists in the tech circle think that AI will result in human
jobless, some even thought that it was the end of human beings. My claim
is, AI will not make human lose their job.

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.

新浦京www81707con 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.

  Form the history of the industrial revolution, machines were used in
textile the most. People ever since had used machines instead of hand
work. But the massive used of machines more job for machines more job
have been created for humans. The amount of workers in the manual age
was only a few thousand in the machine age the number of workers had
increase to about 320,000 workers in the factory. The used of machines
has created more industry, and more industry there is there is more
workers. In late 19th century the main means of transport in the city
was the carriage. After the invention of cars, it had soon replace the
importance of carriages. Although pass drivers has lost their job, there
are many more jobs. Such as car drivers have been added. New technology
may have eliminate old jobs, but it will also provide new jobs for
people to follow.

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?

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.

  The used of new machines will lead to the emergence of more related
industry. Such as the advent of computers, it had increased many related
industry. Manufacturing, supporting, service and education industry. New
technology continue to replace old industry, and new jobs to continue to
emerge. For an example, the industry of mobile device, it form a lot of
other industry like phone case, earphones, data line and a lot of
related industry. These industry also need workers to run. More
industry—more workers. Therefore, the increasing number of workers had
proven that the used of new machine would not let human lose their jobs.

(Laughter)

莫农加希拉河畔的大块空地是匹兹堡过去几十年工业辉煌的伤疤。这里曾是琼斯和劳克林钢铁厂旧址,那是钢铁还是当地主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.

  Some people said that the AI is different from other technology,
AlphGo win professional player and said AI is going yo make human
jobless. No! Is wrong! AlphaGo are invented by human, all the order are
given by human. There has to have a programmer to put the order Coad in.

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.

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.

  AI will not make human jobless, it actually provide more job for human
to do. The increased of the workers had proven my claim there will be
more industries. So, even the people that had lost their job can find a
better job to follow. AI will not make human lose their job, actually
leads to more job for human.   

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.

多数大型设备早已不见了,只剩下空地,到处是炼钢留下的残渣和些许怪异的建筑,凝望着下游的匹兹堡老城。

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.

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 —

大片杂乱的废地旁是匹兹堡最贫困的住宅区黑泽尔伍德,这里一栋房子不到5万美元。沿河一路向南到西弗吉尼亚州的许多城镇,像麦基斯波特和迪凯纳等,其存在的经济原因——钢铁和煤炭——都已成往事。

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)

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.

如今,被开发商成为“黑泽尔伍德绿色”的老钢厂区正在恢复生机。一边是优步自动驾驶汽车的试验场,拦起来防人窥探。一条还未开放的新路穿过178英里的老钢厂区,装有许多停车标志、消防龙头、自行车道和人行道。用不着脑补就可以想象计划中的河滨公园中游人如织的景象。

(Laughter)

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.

在开发项目的精华是19车间,以前是焦炭车间。这是跨度400多米的建筑,坐落在空地之中,现在已被抛光为一个三层的金属骨架。大量工人正在清理剩下的废料,准备再造这一建筑。如果一切按计划进行,明年春天,第一批商家将入住:先进机器人制造研究所。

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.

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)

机器人进入曾经的炼钢厂,这所城市中几乎没有人会忽视这种象征意义。匹兹堡重生,使用来自其大学中的自动化、机器人和人工智能,尤其是卡内基梅隆大学,正在构建一种高科技经济。

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.

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.

距离黑泽尔伍德5英里的劳伦斯维尔已成为美国自动驾驶汽车发展的中心。优步先进技术使用了多个工业建筑;自动驾驶初创企业阿尔戈AI和欧若拉创新都在附近,连卡特彼勒都开设车间,开发自动反铲挖掘机和其他重型设备,它们有一天可以自动运行。

(Laughter)

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.

这吸引了来自硅谷等地的数十亿美元,在一个几十年来经济萎靡不振的城市中,这是让人欢迎的进展。效果是明显的。试验场开出来的自动驾驶汽车司空见惯,在高档饭店外排队,被当地支持者称为“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.

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.

尽管许多老居民抱怨技术公司总部和试验场周围的房价暴涨,他们也会告诉你,这是他们这辈子看到这个城市的最佳岁月。

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 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.

尽管这些活动生机勃勃,匹兹堡的经济在许多方面依然困难。尽管城市人口已不再大量流出,1970年到1980年间,人口降低了月五分之一,可如今也没有增长,并且在快速老龄化。过去五年间,近7万35岁到54岁之间的人口离开该地区。

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?

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.

距离城市和城市的顶尖大学不远,那些经济发展的主要希望主要依赖煤炭和页岩气而非自动驾驶汽车的地区,高薪工作很少,阿片药物成瘾正在毁灭者城镇。

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.

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.”

这让匹兹堡不仅成为美国产业心脏地带的缩影,也表现出每个拥抱新数字技术的城市和国家面临的问题:人工智能、先进机器人、自动驾驶汽车和其他最新突破能否将繁荣带给广大人口,抑或它们只是把财富集中在企业家、投资人和一些高技术工人手中?

(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.”

国家城市联盟的斯科特·安德斯说,要繁荣起来,匹兹堡“不能只是接触人才和思想的生产者,这些无法转化为就业”。他说,“匹兹堡是21世纪经济体的一个伟大实验,因为它正开始撬动研究实力,将其转化为经济价值。”

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,没有比讨论机器人和人工智能是否会消灭工作岗位或者反过来会创造大量工作岗位这一问题更可笑或更虚伪的了。事实上,结果要看许多经济因素。随着人工智能加速发展,结果会如何没人知道。

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.

过去几十年,自动化和机器人肯定消除了许多工作,尤其在制造业领域。最早一些量化工业机器人的影响的研究包括麻省理工许愿的达龙·阿西莫格鲁及其同事根据1990年到2007年的数据所做的分析,分析发现车间中每出现一个机器人,大约6个人失去工作。那意味着1990年到2007年流失了67万个岗位,以2016年机器人在美国使用水平计算,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.

衡量机器人和人工智能导致的岗位净增加或净流失很复杂,但显而易见,工作岗位需求在发生变化,对体力劳动的需求在降低,对数字和脑力技能的需求在增加。

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.

麦肯锡全球研究所估计,我们经济体中约50%的的工作将实现自动化。但这些统计结果经常被误读。研究所主席詹姆斯·曼伊卡说,50%仅仅描述了在现有和新兴技术水平下可被自动化的“技术可能性”。真正流失岗位的数量要看机器取代人力的成本和收益。

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.

可以创造出多少新岗位更难以确定。许多技术人士,尤其是机器人开发者,他们相信进步会长造出大量新岗位。尽管迄今为止,这并未发生,在美国经济的最大部门中几乎没有取得任何突破,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.

可能我们要有耐心,技术进步总能增加收入,然后增加对商品和服务的需求,最后创造更多岗位。

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.

但比尔·克林顿总统的首席经济顾问和加州大学伯克利分校教授劳拉·泰森问出所有人心中的问题:万一这回人们想要的商品和服务偏偏不需要太多人力生产又该如何?“我们想,这是技术第一次减低对工人的净需求,”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.”

“几十年来,宏观经济学家天真的认为技术永远可以创造岗位,”阿西莫格鲁说。“让人引发惊慌的是这一次不一样了,技术消灭工作。”尽管过去经济受益于新技术,创造出来的岗位总比流失的多,他说,“最近,因为各种原因,技术消灭工作的一面更强大”。

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.

他描述的部分内容是所谓的生产力悖论:理论上说,大数据、自动化和人工智能让商业活动生产力更高,促进经济并创造出更多岗位,抵消流失的岗位,可这尚未发生。有些经济学家认为这不过是时间问题,尽管需要很多年。

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.

可对到底能创造或流失多少岗位的讨论让人们忘记更重要的一点。岗位在何处以及它们需要什么岗位,两者在发生变化,这是人们和当地经济受到的真正冲击。

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.

在美国,仓库和饭店等工作地点的低收入岗位需求在增加,编程等需要大量技术技能的高薪职位也在增加。同时,许多制造业和数据处理等传统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.”

这些动向导致了收入空前不平等。“人们基本同意,技术改变了对技能和职业的需求,”泰森说。“这会进一步增进收入不平等。”

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.

当然,这种情形以前也发生过。1900年,约40%的美国工人在农场,可今天不到2%的人务农。1950年,约24%的岗位在制造业,今天大约9%。这种变化也发生在其他发达国家。但今天的变化发生得更迅猛、更广泛,没有时间让人们做出调整。

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.

许多人干脆不再找一份体面工作了。劳动力参与率下降,尤其是25岁到54岁的人口,这令人担忧。

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.

马里兰大学经济学家梅丽莎·科尔尼和凯瑟琳·亚布拉罕研究背后的原因。他们认为有几个原因,但机器人和自动化是最重要的。许多没有大学学位的人干脆认为找到高薪工作的机会太渺茫了,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.

尽管人工智能和机器人技术取得进步,生产力却进步不大,受益的人较少。为了在劳动力增长放缓的情况下促进增长,我们需要更多的人工智能,我们需要学习如何更好的应用它。

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.

普林斯顿经济学家安妮·凯斯和共同作者安格斯·迪顿指出可能与此有关的一种趋势。他们发现高中文凭及以下的美国中年白人,他们的死亡率在增加。

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.

原因:高自杀率、药物成瘾和酗酒,凯斯和迪顿认为这是“失望病”,因为他们看起来和自身贫穷无关,而是失望。期望发生逆转,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.

自动化可能要部分为这些社会问题负责。但如果阿西莫格鲁这样的经济学家说得对,创造更多好工作的钥匙并非减少这些进步,而是推行更好的版本,让它们更加迅速地在整个经济体得以应用。

新浦京www81707con ,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.”

说到底,这正是匹兹堡要重建的自我。迄今为止,结果喜忧参半。“在人工智能和机器人部门工作的年轻人给城市带来的变化令人惊讶,”卡内基梅隆大学计算机科学系主任安德鲁·摩尔说。“但这更多是一种贵族化的方式,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丰富的进步主义政治史、以工人阶级城市为傲的地方而言引发了共鸣。市长威廉·佩杜托把优步引进过来,但他对这家旧金山公司并没有什么好感。

“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.”

“硅谷模式没有把人考虑在内。它考虑的是风险投资能获得多大回报,”他最近接受《麻省理工技术评论》采访时说。“像底特律和匹兹堡这种地方,我们考虑工作的未来时,我们想要知道工人的未来是什么。”

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.

最近民调显示,超过一半的匹兹堡居民强烈支持亚马逊将匹兹堡定为第二总部。这比亚马逊名单上的其他城市多得多,在奥斯汀和波士顿,只有大概三分之一的人口欢迎这一举动。

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. 这并不令人吃惊:亚马逊承诺创造5万个工作岗位,投资50亿美元,这可以彻底改变匹兹堡。据传该城市拿出莫农加希拉河畔的一块地吸引亚马逊,其中就包括19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.”

可如果亚马逊选择了匹兹堡,有可能加深当地居民就如何与高技术岗位对接引起的焦虑。“这个城市和地区技术水平高的人不够,”卡内基梅隆大学的摩尔说。“我们并不缺乏天才领导者,但真正需要的是当地人口也有能力参与其中。”

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.

这所城市和全国各地面临的挑战不仅是让更多人加入到高技术队伍中来,还包括增加高薪岗位的供给。先进机器人可以是匹兹堡等城市的工厂现代化,使制造业更有竞争力。

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.

但这些年失去的工厂岗位不会回来了。我们很难想象如何构建一个经济体,人工智能和自动化带了许多好岗位。

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.

站在劳伦斯维尔街区的建筑房顶上可以远眺未来。一层是欧若拉自动驾驶汽车的停车区,草地外是一台卡特彼勒反铲机,这是该公司的自动驾驶研发中心。更远处是拦起来的测试场,旁边是另一家旧钢铁厂,建筑属于卡内基机器人,该公司正为陆军开发炸弹清除机器人。背景是国家机器人中心——另一栋雄伟的建筑,此前是先进机器人制造研究所所在地,后者搬进了19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.

这个场景让人印象深刻,如果你找对角度,可以看到世界上最先进的机器人和自动化研究。但这里死一般静谧。停车场里只有不多几辆车,都是供职于各种机器人企业的工程师和程序员,可能还有一些游客。除此之外,没有工人的迹象。返回搜狐,查看更多

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