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Humans, Machines, and Work:
The Future is Now
Moshe Y. Vardi
Rice University
vardi@cs.rice.edu
Follow me on social media!
Birth of Artificial Intelligence
 Alan M. Turing, 1902-1954
“Computing Machinery and Intelligence”
 Turing, 1950: “ I believe that at the end of
the century the use of words and general
educated opinion will have altered so much
that one will be able to speak of machines
thinking without expecting to be
contradicted.”
Crux of paper: A compelling philosophical
analysis for the feasibility of intelligent
machines.
 1958, H. A. Simon and A. Newell: "within ten
years a digital computer will be the world's
chess champion”
 1967, M. Minsky: "Within a generation ... the
problem of creating 'artificial intelligence' will
substantially be solved."
AI: Early Optimism
 The first AI winter 1974−1980: slow progress
and dearth of research funding
 The second AI winter 1987−1993: the
“Japanese Fifth-Generation bust” and dearth
of research funding
“AI Winters”
 1997: IBM’s Deep Blue beats Kasparov.
AI Breakthroughs, I
 2011: IBM’s Watson defeats the two greatest
Jeopardy! champions, Brad Rutter and Ken
Jennings, by a significant margin.
AI Breakthroughs, II
 2016: AlphaGo beats Lee Se-dol to take
Google DeepMind Challenge series!
AI Breakthroughs, III
 “AlphaGo combines tree-search techniques
with search-space-reduction techniques that
use machine learning.”
 In other words, AlphaGo develops “intuition”
for Go playing.
 Machine learning provides a response to
Polanyi’s Paradox (1966): "We can know more
than we can tell... The skill of a driver cannot
be replaced by a thorough schooling in the
theory of the motorcar"
AI Develops Intuition
 2005: DARPA Grand Challenge - Stanford
autonomous vehicle drives 131 miles along an
unrehearsed desert trail.
Automated Driving, I
 2007: DARPA Urban Challenge - CMU
autonomous vehicle drives 55 miles in an urban
environment while adhering to traffic hazards
and traffic laws.
AI Breakthroughs, II
Automated Driving, III
Transportation Revolutions, I
Approx. 5000BC: invention of the wheel
Transportation Revolutions, I
Transportation Revolutions, II
Approx. 3500BC: domestication of the horse
Transportation Revolutions, II
Transportation Revolutions, III
1804: Steam Locomotive
Transportation Revolutions, III
Transportation Revolutions, IV
1908: Ford Model T
Transportation Revolutions, IV
Transportation Revolutions, IV
Transportation Revolutions, IV
The Automobile
The most important industrial product of the
20th Century:
 Shaped US urban geography
 Gave rise to a mighty American industry
 Led to victory in WWII
 “Car Culture” –
 Adulthood and
freedom!
Automobiles: Societal Cost I
 1901: The “Lucas Gusher”,
Spindletop, TX
 1908: Energy source for the
Model T – Steam? Electricity?
Gasoline!
 2011: Road transport
absorbs some 90% of global oil.
Worldwide:
 1.25M deaths in 2013, 20-50M were injured or
disabled
 More than half of all road traffic deaths
occur among young adults ages 15-44
 Road crashes are the leading cause of death
among young people ages 15-29,
 Road crashes annually cost > $0.5T
Automobile: Societal Cost II
Automobile: Societal Costs, III
Human error accounts for more than 90% of
car crashes!
Top Driving Behavior in Fatal Crashes (US,2014):
 Driving too fast – 18.8%
 Under the influence – 12.3%
 Failure to keep in lane – 8.5%
 Failure to yield way – 6.9%
 Distracted – 6.7%
 Careless driving – 4.8%
Humans: Unsafe at Any Speed
 30 companies are now making self-driving cars
– estimated market: $2-5T over next decade
 Technical issues to be resolved within 10 yrs
 Many legal issues need to be resolved
 Profound business disruption:
 Major industrial contraction (cars are now idle
90% of the time)
 “Major loss of business” for insurance, legal,
and medical industry
 Huge societal benefit: reduce accidents,
liberate elders and the disabled
The Automation of Driving
The Most Common Jobs (2014)
 4M truck+taxi drivers in the US
 15M US jobs involve operating a vehicle
 Automation of the whole supply chain is
expected: cargo ships, ports, trucking,
warehouses, delivery, …
 Bottom Line: Massive loss of jobs!
 But there will be new jobs. Right?
What about the Drivers?
The Neclassicals
 K. Rogoff: “Since the dawn of the industrial
age, a recurrent fear has been that
technological change will spawn mass
unemployment. Neoclassical economists
predicted that this would not happen, because
people would find other jobs, albeit possibly
after a long period of painful adjustment. By
and large, that prediction has proven to be
correct.”
The Neoluddites
 P. Krugman: “Can innovation and progress really
hurt large numbers of workers, maybe even
workers in general? The truth is that it can,
and serious economists have been aware of
this possibility for almost two centuries.”
The Debate in A Nutshell
 Neoluddites: “This time it is different.”
 Neoclassicals: “This time it is not different.”
Who is right?
 McKinsey believes as much as 45% of current
jobs could be replaced using technology that
already exists;
 Gartner predicts one in three jobs will be
converted to software, robots and smart
machines by 2025;
 According to an Oxford University Study,
about 47 percent of total US employment is at
risk;
 OECD: across the 21 OECD countries, only 9%
of jobs are automatable.
Future of Work, I
Why so many different predictions?
 “Predictions are easy, especially about the far
future!”
 Paraphrasing Albert Einstein, Nils Bohr, Mark
Twain, or Yogi Berra
 “Correct predictions are hard, especially about
the far future!”
 Let’s consider the past!
Future of Work, II
Case Study: US Manufacturing
US Manufacturing
Manufacturing: Output vs. Jobs
Manufacturing: GDP vs. Jobs
Driving Force: Automation
Tesla Model S Factory Floor
 Over the past 40 years, automation has had a
very harsh impact on middle- and working-
class Americans!
 William Galston, WSJ, July 6, 2016: “Educated
professionals—including most politicians—live
in an economic and cultural bubble, and they all
too easily assume that what they see and hear
around them represents the entire country.”
The Future is Now!
The Great Coupling
The Great Decoupling
Real Hourly Earnings
Growing Inequality
Inequality vs Social Mobility
Inequality vs Growth
The middle class is shrinking
Poverty
 “The Secret Shame of Middle-Class
Americans”: Nearly half of Americans would
have trouble finding $400 to pay for an
emergency. (The Atlantic, May 2016)
 “Americans Living on the Financial Edge”:
two-thirds of Americans would have trouble
immediately paying an unanticipated bill of
$1,000. (Associated Press, May 2016)
The Age of Precariousness
Labor-Force Participation - Men
Men without Work
Labor Share of National Income
Job Polarization
Routine vs Non-routine Jobs
Jobs Lost and Gained
Real Hourly Wages by Education
US White Mortality, 45-54
 Washington Post, March 4, 2016:
“Eerie correlation in the voting data: it seems
that Donald Trump performed the best in places
where middle-aged whites are dying the
fastest.”
Death vs Trump
 “All that is solid melts into air, all that is holy
is profaned, and man is at last compelled to
face with sober senses, his real conditions of
life, and his relations with his kind.”
 K. Marx, F. Engels, 1848: The Manifesto of the
Communist Party
All That Is Solid
“Information technology and automation are a
central reason why median wages have been
stagnant in the US over the past decade,
despite rising productivity.”
 Agree: 43%
 Uncertain: 30%
 Disagree: 24%
 Strongly disagree: 4%
2014 Economists Opinion Poll
 Technology has been destroying jobs
since the start of the Industrial
Revolution, yet new jobs have continually
been created.
 But we have never faced machines that
may be able to outcompete us in almost
everything!
 Thought experiment: Suppose that
machines can do everything we can do.
What is our comparative advantage?
This Time It May Be Different!
 Take water at room temperature and
heat it up one degree per minute. It gets
warmer and warmer, and then it
suddenly boils!
 Malcolm Gladwell, 2005: “The tipping
point is that magic moment when an idea,
trend, or social behavior crosses a
threshold, tips, and spreads like
wildfire.”
The Tipping Point
Tipping Point: Industrial Revolution
W. Leontief, 1983: Imagine a pair of
horses in the early 1900s talking about
technology. One worries all these new
mechanical muscles will make horses
unnecessary. The other reminds him that
everything so far has made their lives
easier: “Even if this car thingy takes off,
there will be new jobs for horses we can't
imagine.”
Fact: The horse population peaked in 1915
-- from that point on it has been nothing
but down.
Neoclassical Horses
 A: Will technology destroy or downscale
jobs? Yes!
 B: Will technology create jobs or upscale
jobs? Yes!
 Will B offset A?
 What is the relative speed of A and B?
It’s All about Relative Speed
T. Berger and C.B. Frey: “Industrial
Renewal in the 21st Century: Evidence
from US Cities”:
 The magnitude of workers shifting into new
industries is strikingly small: in 2010, only
0.5% of the US labor force was employed in
industries that did not exist in 2000.
 Relative to major corporations of the early
computer revolution, the companies leading
the digital revolution have created few
employment opportunities.
November 2014 Oxford Study
 Detroit 1990: The three largest
companies had a combined market value
of $65 billion (real), with 1.2 million
workers.
 Silicon Valley 2016: The three largest
companies had a combined market value
of $1.5 trillion, with about 190,000
workers.
New Jobs?
The Past and the Future
Jason Furman, Chairman, Council of Economic
Advisers, July 2016:
“My worry is not that this time could be
different when it comes to AI, but that this
time could be the same as what we have.”
Obama on Automation
June 13, 2016: Bloomberg News
 “As we move toward an economy where,
because of automation, you need fewer and
fewer people to make more and more stuff,
more and more of us are going to have to move
into the service sector. The service sector
historically has been a low-wage sector.”
 “Because of automation, because of
globalization, we’re going to have to examine
the social compact, the same way we did early
in the 19th century and then again during and
after the Great Depression.”
 delange.rice.edu
Humans, Machines, and the Future of Work

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Humans, Machines, and Work: The Future Is Now!

  • 1. Humans, Machines, and Work: The Future is Now Moshe Y. Vardi Rice University vardi@cs.rice.edu Follow me on social media!
  • 2.
  • 3.
  • 4. Birth of Artificial Intelligence  Alan M. Turing, 1902-1954
  • 5. “Computing Machinery and Intelligence”  Turing, 1950: “ I believe that at the end of the century the use of words and general educated opinion will have altered so much that one will be able to speak of machines thinking without expecting to be contradicted.” Crux of paper: A compelling philosophical analysis for the feasibility of intelligent machines.
  • 6.  1958, H. A. Simon and A. Newell: "within ten years a digital computer will be the world's chess champion”  1967, M. Minsky: "Within a generation ... the problem of creating 'artificial intelligence' will substantially be solved." AI: Early Optimism
  • 7.  The first AI winter 1974−1980: slow progress and dearth of research funding  The second AI winter 1987−1993: the “Japanese Fifth-Generation bust” and dearth of research funding “AI Winters”
  • 8.  1997: IBM’s Deep Blue beats Kasparov. AI Breakthroughs, I
  • 9.  2011: IBM’s Watson defeats the two greatest Jeopardy! champions, Brad Rutter and Ken Jennings, by a significant margin. AI Breakthroughs, II
  • 10.  2016: AlphaGo beats Lee Se-dol to take Google DeepMind Challenge series! AI Breakthroughs, III
  • 11.  “AlphaGo combines tree-search techniques with search-space-reduction techniques that use machine learning.”  In other words, AlphaGo develops “intuition” for Go playing.  Machine learning provides a response to Polanyi’s Paradox (1966): "We can know more than we can tell... The skill of a driver cannot be replaced by a thorough schooling in the theory of the motorcar" AI Develops Intuition
  • 12.  2005: DARPA Grand Challenge - Stanford autonomous vehicle drives 131 miles along an unrehearsed desert trail. Automated Driving, I
  • 13.  2007: DARPA Urban Challenge - CMU autonomous vehicle drives 55 miles in an urban environment while adhering to traffic hazards and traffic laws. AI Breakthroughs, II
  • 15. Transportation Revolutions, I Approx. 5000BC: invention of the wheel
  • 17. Transportation Revolutions, II Approx. 3500BC: domestication of the horse
  • 25. The Automobile The most important industrial product of the 20th Century:  Shaped US urban geography  Gave rise to a mighty American industry  Led to victory in WWII  “Car Culture” –  Adulthood and freedom!
  • 26. Automobiles: Societal Cost I  1901: The “Lucas Gusher”, Spindletop, TX  1908: Energy source for the Model T – Steam? Electricity? Gasoline!  2011: Road transport absorbs some 90% of global oil.
  • 27. Worldwide:  1.25M deaths in 2013, 20-50M were injured or disabled  More than half of all road traffic deaths occur among young adults ages 15-44  Road crashes are the leading cause of death among young people ages 15-29,  Road crashes annually cost > $0.5T Automobile: Societal Cost II
  • 29. Human error accounts for more than 90% of car crashes! Top Driving Behavior in Fatal Crashes (US,2014):  Driving too fast – 18.8%  Under the influence – 12.3%  Failure to keep in lane – 8.5%  Failure to yield way – 6.9%  Distracted – 6.7%  Careless driving – 4.8% Humans: Unsafe at Any Speed
  • 30.  30 companies are now making self-driving cars – estimated market: $2-5T over next decade  Technical issues to be resolved within 10 yrs  Many legal issues need to be resolved  Profound business disruption:  Major industrial contraction (cars are now idle 90% of the time)  “Major loss of business” for insurance, legal, and medical industry  Huge societal benefit: reduce accidents, liberate elders and the disabled The Automation of Driving
  • 31. The Most Common Jobs (2014)
  • 32.  4M truck+taxi drivers in the US  15M US jobs involve operating a vehicle  Automation of the whole supply chain is expected: cargo ships, ports, trucking, warehouses, delivery, …  Bottom Line: Massive loss of jobs!  But there will be new jobs. Right? What about the Drivers?
  • 33. The Neclassicals  K. Rogoff: “Since the dawn of the industrial age, a recurrent fear has been that technological change will spawn mass unemployment. Neoclassical economists predicted that this would not happen, because people would find other jobs, albeit possibly after a long period of painful adjustment. By and large, that prediction has proven to be correct.”
  • 34. The Neoluddites  P. Krugman: “Can innovation and progress really hurt large numbers of workers, maybe even workers in general? The truth is that it can, and serious economists have been aware of this possibility for almost two centuries.”
  • 35. The Debate in A Nutshell  Neoluddites: “This time it is different.”  Neoclassicals: “This time it is not different.” Who is right?
  • 36.  McKinsey believes as much as 45% of current jobs could be replaced using technology that already exists;  Gartner predicts one in three jobs will be converted to software, robots and smart machines by 2025;  According to an Oxford University Study, about 47 percent of total US employment is at risk;  OECD: across the 21 OECD countries, only 9% of jobs are automatable. Future of Work, I
  • 37. Why so many different predictions?  “Predictions are easy, especially about the far future!”  Paraphrasing Albert Einstein, Nils Bohr, Mark Twain, or Yogi Berra  “Correct predictions are hard, especially about the far future!”  Let’s consider the past! Future of Work, II
  • 38. Case Study: US Manufacturing
  • 43. Tesla Model S Factory Floor
  • 44.  Over the past 40 years, automation has had a very harsh impact on middle- and working- class Americans!  William Galston, WSJ, July 6, 2016: “Educated professionals—including most politicians—live in an economic and cultural bubble, and they all too easily assume that what they see and hear around them represents the entire country.” The Future is Now!
  • 51. The middle class is shrinking
  • 53.  “The Secret Shame of Middle-Class Americans”: Nearly half of Americans would have trouble finding $400 to pay for an emergency. (The Atlantic, May 2016)  “Americans Living on the Financial Edge”: two-thirds of Americans would have trouble immediately paying an unanticipated bill of $1,000. (Associated Press, May 2016) The Age of Precariousness
  • 56. Labor Share of National Income
  • 59. Jobs Lost and Gained
  • 60. Real Hourly Wages by Education
  • 62.  Washington Post, March 4, 2016: “Eerie correlation in the voting data: it seems that Donald Trump performed the best in places where middle-aged whites are dying the fastest.” Death vs Trump
  • 63.  “All that is solid melts into air, all that is holy is profaned, and man is at last compelled to face with sober senses, his real conditions of life, and his relations with his kind.”  K. Marx, F. Engels, 1848: The Manifesto of the Communist Party All That Is Solid
  • 64. “Information technology and automation are a central reason why median wages have been stagnant in the US over the past decade, despite rising productivity.”  Agree: 43%  Uncertain: 30%  Disagree: 24%  Strongly disagree: 4% 2014 Economists Opinion Poll
  • 65.  Technology has been destroying jobs since the start of the Industrial Revolution, yet new jobs have continually been created.  But we have never faced machines that may be able to outcompete us in almost everything!  Thought experiment: Suppose that machines can do everything we can do. What is our comparative advantage? This Time It May Be Different!
  • 66.  Take water at room temperature and heat it up one degree per minute. It gets warmer and warmer, and then it suddenly boils!  Malcolm Gladwell, 2005: “The tipping point is that magic moment when an idea, trend, or social behavior crosses a threshold, tips, and spreads like wildfire.” The Tipping Point
  • 68. W. Leontief, 1983: Imagine a pair of horses in the early 1900s talking about technology. One worries all these new mechanical muscles will make horses unnecessary. The other reminds him that everything so far has made their lives easier: “Even if this car thingy takes off, there will be new jobs for horses we can't imagine.” Fact: The horse population peaked in 1915 -- from that point on it has been nothing but down. Neoclassical Horses
  • 69.  A: Will technology destroy or downscale jobs? Yes!  B: Will technology create jobs or upscale jobs? Yes!  Will B offset A?  What is the relative speed of A and B? It’s All about Relative Speed
  • 70. T. Berger and C.B. Frey: “Industrial Renewal in the 21st Century: Evidence from US Cities”:  The magnitude of workers shifting into new industries is strikingly small: in 2010, only 0.5% of the US labor force was employed in industries that did not exist in 2000.  Relative to major corporations of the early computer revolution, the companies leading the digital revolution have created few employment opportunities. November 2014 Oxford Study
  • 71.  Detroit 1990: The three largest companies had a combined market value of $65 billion (real), with 1.2 million workers.  Silicon Valley 2016: The three largest companies had a combined market value of $1.5 trillion, with about 190,000 workers. New Jobs?
  • 72. The Past and the Future Jason Furman, Chairman, Council of Economic Advisers, July 2016: “My worry is not that this time could be different when it comes to AI, but that this time could be the same as what we have.”
  • 73. Obama on Automation June 13, 2016: Bloomberg News  “As we move toward an economy where, because of automation, you need fewer and fewer people to make more and more stuff, more and more of us are going to have to move into the service sector. The service sector historically has been a low-wage sector.”  “Because of automation, because of globalization, we’re going to have to examine the social compact, the same way we did early in the 19th century and then again during and after the Great Depression.”
  • 74.  delange.rice.edu Humans, Machines, and the Future of Work