ai, robotics and the future of work -...
TRANSCRIPT
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@ITIFdc
AI, Robotics and the Future of Work
Dr. Robert D. Atkinson President, ITIF
March 23, 2017
@RobAtkinsonITIF
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About ITIF
One of the world’s top science and tech policy think tanks
Formulates and promotes policy solutions that accelerate innovation and boost productivity to spur growth, opportunity, and progress
Focuses on a host of issues at the intersection of technology innovation and public policy:
– Innovation processes, policy, and metrics
– Science policy related to economic growth
– E-commerce, e-government, e-voting, e-health
– IT and economic productivity
– Innovation and trade policy
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Today’s Presentation
Signs we’ve entered the 4th Industrial Revolution
Why AI-Robotics technology will destroy jobs
Why the pace of change will only accelerate
The solution: tax robots and establish universal basic income
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Unprecedented Change and Risk
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2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
U.S. Labor Productivity
-
0.02
0.04
0.06
0.08
0.10
0.12
0.14
0.16
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
Risk of Losing Job
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Many Share This Anxiety
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Today’s REAL Presentation
We aren’t in the midst of a 4th Industrial Revolution
Employment loss projections are wrong
We shouldn’t panic
Privacy concerns are overblown
What to do
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Actually Productivity Growth Rates Have Fallen
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Since 2008 U.S. productivity
growth was half the rate from
1995 to 2008. (1.2%).
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EU Productivity Growth is Even Slower
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0
0.2
0.4
0.6
0.8
1
1.2
EU US
Source: Conference Board, “Total Economy Database,” Labor productivity per person employed in 2014 US$
Annual Growth in Labor Productivity, 2005-2015
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U.S. Worker Dislocation Rates Have Actually Fallen
Source: Bureau of Labor Statistics, Business Employment Dynamics (gross jobs gains, seriesBDS0000000000000000110001LQ5
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0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Quarterly Job Losses as a Share of Total Employed
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Today’s Presentation
We aren’t in the midst of a 4th Industrial Revolution
Employment loss projections are wrong
We shouldn’t panic
Privacy concerns are overblown
What to do
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Past Predictions of Employment Doom Have Been Wrong
Marvin Minsky (1970): “in from 3 to 8 years we will have a
machine with the general intelligence of an average human
being.”
Gail Garfield Schwartz (1982): “perhaps as much as 20% of
the work force will be out of work in a generation.”
Nil Nilson (1984): “We must convince our leaders that they
should give up the notion of full employment. The pace of
technical change is accelerating.”
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Current Ones Are Either Inconsequential or Wrong
World Economic Forum’s predication of 5 million
jobs lost from AI-robots equals 0.25% of jobs (1
out of every 400 workers).
Frey and Osborne’s estimates that technology will
eliminate 47% of U.S. jobs are vastly overstated.
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Occupations at High Risk According to Frey and Osborne
Terrazo Workers and Finishers
Carpet Installers
Veterinary Assistants and Laboratory Animal Caretakers
Insulation Workers
Property, Real Estate and Community Association Managers
Barbers
Shoppers
Drywall and Ceiling Tile Installers
Aircraft Mechanics
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Dental technicians
Models
Manicurists and pedicurists
Bicycle Repairers
Radio and Cellular Tower Installers
and Repairers
Fence Erectors
Electrical and Electronics Installers
School Bus Drivers
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A More Accurate Picture: Fewer Than 9% of Jobs At Risk
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8% High
33% Medium-High
16% Medium
28% Medium-Low
[VALUE] Low
Source: ITIF analysis of U.S. Bureau of Labor Statistics Occupational Data.
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Most Occupations Are Actually Very Hard to Automate
Brick masons and block masons
Machinists
Cartographers and photogrammetrists
Dental laboratory technicians
Social science research assistants
Firefighters
Pre-school teachers
– (Randomly selected U.S. occupations)
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Today’s Presentation
We aren’t in the midst of a 4th Industrial Revolution
Employment loss projections are wrong
We shouldn’t panic
Privacy concerns are overblown
What to do
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Technological Change Has Always Been Gradual
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“Misled by suitcase words, people are making
category errors in fungibility of capabilities—
category errors comparable to seeing the rise
of more efficient internal combustion engines
and jumping to the conclusion that warp drives
are just around the corner.”
— (Rodney Brooks, MIT)
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Moore’s Law is Not a Law
Speed increases are slowing, while transistors per dollar are decreasing.
Even Gordon Moore’s says his law “can't continue forever. The nature of exponentials is that you push
them out and eventually disaster happens.”
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Annual % change in processor speed
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Our Robot Overlords Are Not Here Yet
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No
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Yes
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=
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No Correlation Between Productivity Growth and Unemployment
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ARG
AUS
AUT
BELCAN
CHE
CHL
DNK
ESP
EST
FINFRA
GBR
GRC
HKG
IRLITA
JAM
JPN KORLUX
NLDNOR
NZL
PER
PRTSWE
TUR
USA
VEN
5
10
15
0.0 0.5 1.0 1.5 2.0
Change in Productivity
Aver
age
Une
mpl
oym
ent
Average unemployment rate and total change in productivity in select nations, 1990-2011 (%) (World Bank and Penn World Tables)
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US and EU Need More Productivity
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Every 1 percentage point increase in
productivity adds $500 billion to U.S. federal
budget.
EU working age-to-old person ratio drops
from 3.5 to 2.2 by 2040. Productivity would
have to increase 13% to keep after-tax
incomes from declining.
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Increased Productivity Creates Demand Which Creates Jobs
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U.S. Bureau of Labor Statistics shows
that automation lowers prices which
increases demand for products.
– Savings are spent.
– Spending creates demand.
– Demand creates jobs.
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Can You Order the Occupation By U.S. Job Change: 2010-2015?
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Network and Computer Systems Administrators
Computer Operators
Economists and market researchers
Taxi Drivers & Chauffeurs
Reservation and Transportation Ticket Agents and Travel Clerks
Shoe and Leather Workers and Repairers
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Can You Order the Occupation By U.S. Job Change: 2010-2015?
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Shoe and Leather Workers and Repairers
Taxi Drivers & Chauffeurs
Reservation and Transportation Ticket Agents and Travel Clerks
Network and Computer Systems Administrators
Economists and market researchers
Computer Operators
27%
17%
4%
-11%
-17%
-34%
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Many Workers Want Better Jobs
40% of EU workers are
overqualified.
—European Commission, Skills Panorama, “Skills under-utilisation across countries in 2014.”
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Much of AI Will Boost Quality, Not Eliminate Jobs
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Health care diagnosis
Fraud prevention
Student feedback
Disability access
Reduced human trafficking
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Human Wants and Needs Are Far From Being Satisfied
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Today’s Presentation
We aren’t in the midst of a 4th Industrial Revolution
Employment loss projections are wrong
We shouldn’t panic
Privacy concerns are overblown
What to do
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Myth: AI Will Destroy Privacy
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AI systems “could be tuned to listen for a few hundred key words, which would increase the effective surveillance power of any single human monitor by orders of magnitude.”
—Daniel Crevier
“AI can be said to threaten privacy according to a specific pattern: AI substitutes for humans at various stages of observation or surveillance, allowing such activity to reach a previously impracticable scale.”
—W Ryan Calo
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Reality: AI Will be Bound by Laws and Regulations
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Lots of data is already “out there.” AI doesn’t
change that.
Companies using AI will be bound by rules already
covering existing data.
Governments don’t need AI to spy.
Technologies can de-identify data. And companies
are working on privacy-preserving deep learning.
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Today’s Presentation
We aren’t in the midst of a 4th Industrial Revolution
Employment loss projections are wrong
We shouldn’t panic
Privacy concerns are overblown
What to do
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4
3
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Speed Development of AI/Robotics
Embrace the innovation principle. Bringing AI and robotics to market is risky; preemptive
regulation raises risks and lowers return.
Increase government support of AI/robot research.
Be agnostic to nationality of AI/robot firms.
Help workers adjust.
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