A review of the issues associated with prospective technological unemployment. This includes the outlook for universal income or guaranteed income funded by robot taxes. It also covers the U.S. fiscal capacity to undertake such a scheme.

1. Technological Unemployment
Gaetan Lion
March 2017 1

2. Historical Perspective
2

3. The Prophets of Technological
Unemployment
3
Keynes anticipated its occurrence back in 1930.
Marx anticipated the related rise in Populism
[Proletariat Revolution] in 1867.

4. The Technology Conundrum:
Technological Unemployment
• Historically, technological innovation has caused rising labor
productivity and living standards.
• Prospectively, it may cause massive unemployment.
John Maynard Keynes was well aware of the problem
back in 1930. “We are being afflicted with a new disease
of which some readers may not yet have heard the
name, but of which they will hear a great deal in the
years to come – namely, technological unemployment.
This means unemployment due to our discovery of means of
economizing the use of labor outrunning the pace at which
we can find new uses for labor.”
John Maynard Keynes
“Economic Possibilities for our Grandchildren.” 1930
4

5. Karl Marx: “Das Kapital” Part I. 1867
Back in 1867, within “Das Kapital”, chapter 15:
‘Machinery and Large-Scale Industry’ Marx has
already much to say about technological
unemployment.
Introducing machinery increases productivity
and profit for capitalists. Machinery implements
automation that enables capitalists to replace
workers. Automation transfers excessive
economic power to capitalists vs. workers
(proletariat).
Marx advanced capitalism was unsustainable
and would be toppled by a proletariat revolution.
5

6. Marx advanced capitalism was unsustainable and
would be toppled by a proletariat revolution
6
“… the emergence of Ms Le Pen matches a pattern of insurgent
populism across Western liberal democracies. A fear of job losses
due to automation…” The Economist March 4th , 2017.
Wilders has tapped into deep fears
among many low-skilled workers over
their jobs in a world of rapid
technological change.

7. Let’s review what happened since the days of
Karl Marx and John Maynard Keynes to two
formerly dominant sectors of the U.S. labor
force, namely Agriculture and Manufacturing…
7

8. Agriculture:
Output is growing, the
sector job share is
collapsing.
8

9. Agriculture:
An International Phenomenon
9

10. Manufacturing:
The output is growing. The
sector job share is collapsing.
The output per worker is
growing rapidly.
10

11. Manufacturing:
An International Phenomenon
11

12. Current Situation
12

13. Could the IT sector be next?
A former Google cloud computing engineer stated that many IT
jobs could be at risk. In the late 90s one IT person was managing 5
servers. Now one IT manager can manage 10,000 servers! That’s a
2000-fold effect in a period shorter than what it took to lose less
than half of the manufacturing jobs.
13
I met a former IT staffer working at
a bike shop. He stated a huge layer
of the IT workforce had been
eliminated in the past few years
due to Cloud Computing that is far
more efficient than pre-Cloud
Computing systems.

14. The Second Machine Age
The Second Machine Age: Work, Progress, and Prosperity
in a Time of Brilliant Technologies is a 2014 book by Erik
Brynjolfsson and Andrew McAfee.
The “Second Machine Age” entails the digitation of
complex cognitive tasks by software-driven machines that
make humans superfluous. This is different from the
"First Machine Age", or Industrial Revolution, which
helped make labor and machines complementary.
Examples of Second Machine Age-machines include
"software that grades students' essays more objectively,
consistently and quickly than humans" and "news articles
on Forbes.com about corporate earnings previews" — "all
generated by algorithms without human involvement.“
Other examples include computers beating world
champions in chess, Go, and Jeopardy.
14
Computer technology (including Big Data, AI, etc.) has the potential of displacing
many “cognitive” workers that were deemed non-displaceable.

15. Robots are taking over
15
In Japan and Russia
where the labor forces
are shrinking rapidly,
robots could be an
economic life saver. But,
in the U.S. with more
favorable demographics,
robots could cause
technological
unemployment.

16. “The Great Decoupling”
by the authors of “The Second Machine Age”
Note
accelerating
of decoupling
after 2000.
16

17. Focusing on “Decoupling” of
Real GDP per Capita vs. Real Wages & Earnings
17

18. Focusing on “Decoupling” of US Labor
Productivity vs. US Private Employment
Notice strong
decoupling since
2000.
18

19. Decoupling of Productivity vs. Hourly
Compensation. See 1973 “Decoupling” Point.
19

20. See accelerating
trend after 2000.
That’s behind
the Populist-
Proletariat
Revolution.
Decoupling of Corporate Profits vs. Wages
20

21. Decoupling by Cognitive vs. Manual Jobs
See the decoupling starting in mid
1980s. That’s when
implementation of desktop
software accelerated. It rendered
routine cognitive jobs superfluous.
21

22. About 50% of jobs could be
replaced by automation
22

23. When this paper came
out in 2013, it was
received with
skepticism. Just over
three years later with
rapid progress in
robotics and artificial
intelligence, the paper is
now viewed as being
realistic.
A McKinsey report of
January 2017 confirms
their findings.
23

24. The probability of
job computerization
by job categories
Those are the 47% of jobs
that are at high risk of being
computerized (prob. > 0.70)
24
Source: “The Future of
Employment” paper. 2013.

25. Job computerization probability:
Engineers & Quants
Engineers Quants
25
Mechanical engineers 1.1%
Engineers (other general) 1.4%
Civil engineers 1.9%
Industrial engineers 2.9%
Mining engineers 14.0%
Petroleum engineers 16.0%
Agricultural engineers 49.0%
Locomotive engineers 96.0%
Large difference in probability of
job computerization between
different engineering specialties.
Operation Research Analysts 3.5%
Mathematicians 4.7%
Physicists 10.0%
Actuaries 21.0%
Statisticians 22.0%
Economists 43.0%
Who needs economists?
Nate Silver would agree.
Source: “The Future of
Employment” paper. 2013.

26. Job computerization probability:
Banking/Finance & HR
Banking/Finance
Human Resource Manager 0.6%
HR training and labor relation specialist 31.0%
Compensation and benefit managers 96.0%
HR
26
Financial Managers 6.9%
Compliance officers 8.0%
Management Analysts 13.0%
Financial examiners 17.0%
Financial Analysts 23.0%
ATMand office machine repair 74.0%
Accountants and Auditors 94.0%
Credit authorizers 97.0%
Real estate brokers 97.0%
Loan officers 98.0%
Insurance appraisers 98.0%
Credit Analysts 98.0%
Tellers 98.0%
Title examiners 99.0%
Insurance underwriters 99.0%
Tax preparer 99.0%
Many jobs in Banking/Finance
associated with very high
probability of computerization.
Source: “The Future of
Employment” paper. 2013.

27. Job computerization probability:
IT & Legal & Other
IT
Legal
Other
27
Athletic trainer 0.7%
Travel Agents 9.9%
Professional Athletes 28.0%
Film and video editors 31.0%
Actors 37.0%
Animal breeders 95.0%
Gaming dealers 96.0%
Umpires, Referees 98.0%
Library technician 99.0%
Professional sports
without umpires and
maybe even without
athletes?!
How come travel
agents still exist?
Computer and Information Research scientists 1.5%
Database administrators 3.0%
Computer and Information Systems Managers 3.5%
Software developers 4.2%
Information Security Analyst 21.0%
Computer hardware engineers 22.0%
Computer programmers 48.0%
Remember
comments by
Google cloud
computing
engineer and
former IT worker
in a bike shop.
Las Vegas without
dealers?!
Hollywood without
actors?!
Lawyers 3.5%
Judicial Law clerks 41.0%
Court reporters 51.0%
Administrative Law Judges 64.0%
Paralegals 94.0%
Still need lawyers
but many jobs in
legal field to be
computerized
Source: “The Future of
Employment” paper. 2013.

28. 28
Job computerization probability:
Education & Healthcare
Elementary school teacher 0.4%
Secondary school teacher 0.8%
Postsecondary teacher 3.2%
Kindergarten teacher 15.0%
Middle school teacher 17.0%
Teacher assistant 56.0%
Education
Physicians and surgeons 0.36%
Nutritionists 0.39%
Psychologists 0.43%
Dentists 0.44%
Podiatrists 0.46%
Orthodontists 2.30%
Chiropractors 2.70%
Dental hygienists 68.00%
Healthcare
Except for teacher assistant, we
still will need educators. Except for dental hygienists, we still
will need “personal” healthcare.
Source: “The Future of
Employment” paper. 2013.

29. 29
50% of jobs done by humans today
are vulnerable to replacement by
robots. That could amount to a
loss of $15 trillion in wages
worldwide and $2.7 trillion in the
U.S. This may fully occur by 2055 +
or – 20 years. Thus, this level of
tech unemployment could hit as
soon as 2035.
McKinsey’s report
January 2017.

30. 30

31. Surviving Automation: People Skills
31
Many functions associated with people skills are less likely to be replaced by
automation. Imagine a robot-manager, a robot-lobbyist, or a robot-PR
executive. Not good!. A human has a marked edge in those “hi-touch” fields.
Do you manage people? That's good.
That function is unlikely to be replaced
by a robot.
Are you a key node in a complex
network of parties? That's good.

32. Surviving Automation: Quantitative skills
32
?
Whatever can be replaced by
an algorithm will be. Today’s
“expert” human cognitive
functions can become
tomorrow’s automated ones.
Remember the former IT guy
who felt his job was safe; who
now works in a bike shop
because of the impact of Cloud
Computing.

33. Expertise is a lot more vulnerable
than we think
This is not just about sophisticated robots and
complex Machine Learning models.
It is also about plain software, and simple
methods of aggregating and replacing human
expertise.
33

34. 34
• “There are more monthly visits to the WebMD network, a
collection of health websites, than to all the doctors in the
United States.
• Annually, in the world of disputes, 60 million disagreements
among eBay traders are resolved using “online dispute
resolution” rather than lawyers and judges — this is three
times the number of lawsuits filed each year in the entire U.S.
court system.
• The U.S. tax authorities in 2014 received electronic tax returns
from almost 50 million people who had relied on online tax-
preparation software rather than human tax professionals.”

35. E-Filing is taking over Tax filing
35
Many tax e-filings are
prepared directly by
the taxpayer. This
must have a material
impact on that
accounting tax
preparing profession.

36. Individual Income Tax filing. IRS disclosure. 2014
36
Focusing on individual returns, e-filing accounted for 89.7% of
total returns filed in 2013 and 90.1% in 2014. Of those e-filings,
tax professionals filed 60.8% of those in 2013, and 59.2% in
2014. Based on the depicted yearly trend, tax professionals will
file less than half of such e-filings within less than 6 years.

37. 37
Not only AI is faster.
It is also more
accurate. 89%
accuracy vs. 73% for
doctors in study.
How many expert-type-jobs in various industries will be
displaced by AI?

38. 38
Indexing has taken a huge market share out of overall Wall
Street equity investment management industry
Over the past
decade equities
invested in index
funds have risen
from $868
billion to $4.0
trillions. That
should have
eliminated a lot
of high paying
jobs such as
investment
advisors,
portfolio
managers, and
security analysts

39. Among Retail Financial Investment Providers
market shares are shifting to the Indexers
39
Source: Morningstar
As shown over a
recent 10 year
period, Vanguard
and iShares
focused on index
funds and ETFs
have gained much
market shares from
Fidelity and
American Funds
that are focused on
active investment
management. This trend has dire implications for the mutual fund managers and security
analysts at Fidelity and American Funds.

40. 40
US online travel booking
has grown from very little
in the late 90s to over a
40% market share of the
travel booking business by
2015. This must have had a
material impact on travel
agents.
The online travel booking
business is growing very
rapidly overseas (actual
market share of respective
travel booking business
unknown).

41. 41
When did you last buy a book at a
brick-and-mortar bookseller?
In any given year how many books do
you buy online vs. buy at a retail store?
The trends depicted on the graph must
have much reduced bookselling
employment.

42. Solution to Technological
Unemployment: Labor Union
42

43. A very old problem
43
Henry Ford II
Henry Ford II: Walter, how are you going to get those robots to pay union dues?
Walter Reuther: Henry, how are you going to get them to buy your cars?
1955
Walter Reuther
Robots = No car sales
Labor Union = No Robots = Car sales

44. A Return to Labor Unions as a Solution?
44
The conversation between Henry
Ford II and Walter Reuther took place
near the peak of Labor Union
membership.
You can observe a logical and very
strong negative relationship between
Union membership and share of
income going to the top 10%.
Some economists have
recommended a return to rising
Labor Union membership including
Robert Reich in “Savings Capitalism”
(2016). However, it remains unclear
how such a revival would be possible
given
international
supply chains.
The latter have
much reduced
the influence of
labor unions as
depicted by the
graph.

45. Union Membership Private vs. Public
45
Although, those trends are very interesting they have little implication on
Technological Unemployment except for the declining influence of private
unions (that will not buffer the impact of Technological Unemployment).
The disparity between the
private and public sector
trends in union membership is
striking. As private union
membership has steadily
dwindled (Globalization,
automation, etc.) since 1950,
public one has risen. And, the
rise of public union
membership has been
especially rapid between 1960
(just over 10%) and 1980
(around 40%).

46. Other Solution to Technological Unemployment:
Guaranteed Income and Robot Tax
46
• In this section we explore the feasibility of a Guaranteed Income
for all, also called Universal Income. Such Income would be on
an unprecedented level (a multiple larger than Social Security),
as it would replace a material portion of Consumer Spending.
• Robot tax is considered as a solution to partly finance
Guaranteed Income and to maintain other Government services
currently financed by payroll taxes and personal income taxes.

47. Tech Unemployment Solution:
Guaranteed Income for all
It is not deemed too socialist. Everyone talks about it
including Silicon Valley.
To review how feasible it is, let’s step back and review
how a basic economy works.
47

48. A Basic Economy
48
$Taxes $Taxes
$ Wages
$ Consumer Spending/Sales
Business
Government
Household/
Consumer
The business sector hires employees (pays wages). The employees
are also the consumers who purchase the goods and services from
the business sector. Both businesses and household/consumers pay
taxes to the Government. And, the latter incurs numerous
Government expenditures (National Defense, Social Entitlements,
Discretionary spending). And, the world goes round just fine.

49. Economy with very high Technological
Unemployment & Guaranteed Income collapses
49
Households do not earn much wages as they are replaced by artificial
intelligent robots (AIRs). So, households can’t buy the goods produced by
the AIRs. Businesses fail. And, no one pays any taxes. The Government
fails too in the absence of adequate tax receipts.
$Taxes Guarant. Inc. $Taxes
$ Wages
$ Consumer Spending/Sales
Business
Government
Household/
Consumer

50. 50
The Solution!

51. The Robot Tax
51
Bill Gates idea of a Robot tax is daring. But
following Walter Reuther’s logic, robots are not
consumers. Without Consumer Spending, you
have nothing, not even a Robot tax.
$Taxes $Taxes
$Taxes Guarant. Inc.
$
$ Consumer Spending/Sales
Business
Government
Household/
Consumer
Robot

52. How to make it work?
Overall framework:
Robot Tax = Guaranteed Income = Consumer Spending = Sales Price
From HH/Consumer standpoint:
Guaranteed Income = Consumer Spending = Sales Price
From Business standpoint:
Cost of Robots to be less than cost of Labor. Otherwise, there is no Robot.
52
=<
Wages
+ Benefits
+ Payroll taxes
Capital Investment in Robots
+ Operating expenses of Robots
+ Robot Tax

53. Robot Tax Conundrum
53
Wages
+ Benefits
+ Payroll taxes
- Capital Investment in Robots
- Operating expense in Robots
Robot Tax
Guaranteed Income
Consumer Spending = Sales Price
=<
=
=
The Robot Tax has to be simultaneously equal to the Sales Price
and less than the difference between using a human labor force
and using Robots. Are those relationships simultaneously even
possible, or mutually exclusive?

54. Robot Tax Summary
54
Difference between
cost of Labor Force
and Robots
Sales Price=
• Unclear how Business could stay in business given the above
equality.
• In view of the above, the Federal Government would probably
have to do much of the heavy lifting in terms of funding a
Guaranteed Income (with a Robot tax playing only a minor
role).
• Next, we will explore what the prospective fiscal costs of
Guaranteed Income would be. And, how feasible it would be.

55. The Fiscal Cost of Guaranteed Income
55

56. Guaranteed Income vs. Consumer Spending
56
Even when
Guaranteed
Income
replaces as
little as 15% of
Consumer
Spending, it
translates into
fiscal costs in
the $trillions.
Source BEA for Consumer Spending annual level as of 2016Q4
Fiscal cost of Guaranteed Income as a % of Consumer Spending
Yearly Guaranteed Income
10,000$ 15,000$ 20,000$ 25,000$ 30,000$ 40,000$
10,000,000 0.8% 1.2% 1.5% 1.9% 2.3% 3.1%
Qualifying 25,000,000 1.9% 2.9% 3.8% 4.8% 5.8% 7.7%
Population 50,000,000 3.8% 5.8% 7.7% 9.6% 11.5% 15.4%
75,000,000 5.8% 8.7% 11.5% 14.4% 17.3% 23.1%
100,000,000 7.7% 11.5% 15.4% 19.2% 23.1% 30.8%
125,000,000 9.6% 14.4% 19.2% 24.1% 28.9% 38.5%
150,000,000 11.5% 17.3% 23.1% 28.9% 34.6% 46.2%
Fiscal cost of Guaranteed Income in $billions
Yearly Guaranteed Income
100.00$ 10,000$ 15,000$ 20,000$ 25,000$ 30,000$ 40,000$
10,000,000 100$ 150$ 200$ 250$ 300$ 400$
Qualifying 25,000,000 250$ 375$ 500$ 625$ 750$ 1,000$
Population 50,000,000 500$ 750$ 1,000$ 1,250$ 1,500$ 2,000$
75,000,000 750$ 1,125$ 1,500$ 1,875$ 2,250$ 3,000$
100,000,000 1,000$ 1,500$ 2,000$ 2,500$ 3,000$ 4,000$
125,000,000 1,250$ 1,875$ 2,500$ 3,125$ 3,750$ 5,000$
150,000,000 1,500$ 2,250$ 3,000$ 3,750$ 4,500$ 6,000$
The red area outlines scenarios where Guaranteed Income represents 15% or more of
Consumer Spending.

57. Guaranteed Income vs. Social Security
57
Source CBO for Social Security in 2016
Fiscal cost of Guaranteed Income as a multiple of Social Security in 2016
Yearly Guaranteed Income
10,000$ 15,000$ 20,000$ 25,000$ 30,000$ 40,000$
10,000,000 0.1 0.2 0.2 0.3 0.3 0.4
Qualifying 25,000,000 0.3 0.4 0.5 0.7 0.8 1.1
Population 50,000,000 0.5 0.8 1.1 1.4 1.6 2.2
75,000,000 0.8 1.2 1.6 2.1 2.5 3.3
100,000,000 1.1 1.6 2.2 2.7 3.3 4.4
125,000,000 1.4 2.1 2.7 3.4 4.1 5.5
150,000,000 1.6 2.5 3.3 4.1 4.9 6.6
Even when
Guaranteed
Income
replaces as
little as 15% of
Consumer
Spending, it
costs more
than twice as
much as Social
Security.

58. Guaranteed Income, Consumer Spending,
and Federal Budget
58
Source CBO for Federal Budget in 2016
Fiscal cost of Guaranteed Income as a % of Federal Budget
Yearly Guaranteed Income
10,000$ 15,000$ 20,000$ 25,000$ 30,000$ 40,000$
10,000,000 2.5% 3.8% 5.0% 6.3% 7.5% 10.1%
Qualifying 25,000,000 6.3% 9.4% 12.6% 15.7% 18.9% 25.1%
Population 50,000,000 12.6% 18.9% 25.1% 31.4% 37.7% 50.3%
75,000,000 18.9% 28.3% 37.7% 47.1% 56.6% 75.4%
100,000,000 25.1% 37.7% 50.3% 62.8% 75.4% 100.5%
125,000,000 31.4% 47.1% 62.8% 78.5% 94.3% 125.7%
150,000,000 37.7% 56.6% 75.4% 94.3% 113.1% 150.8%
Even when
Guaranteed
Income replaces
as little as 15%
of Consumer
Spending, it
represents more
than 50% of the
Federal Budget.

59. U.S. Fiscal Perspective
Even though earlier slides are already discouraging, let’s
explore how much prospective fiscal capacity the U.S. has
in adding an additional major social entitlement program
such as a Guaranteed Income.
59

60. Fiscal Constraints
60
Source: BEA, CBO
In 2016, Consumer Spending at $13
trillion is enormous relative to the
scale of the entire Federal Budget of
$4 trillion. Consumer Spending is
also over 13 times larger than Social
Security (< $1 trillion), the largest
social entitlement program.
Given the scale of Consumer
Spending, it is most challenging for
the Federal Government to
implement a Guaranteed Income
that could replace a material portion
of Consumer Spending.

61. CBO Baseline Long-Term Outlook depicts
an unsustainable fiscal position
61
16
18
20
22
24
26
28
30
2017
2019
2021
2023
2025
2027
2029
2031
2033
2035
2037
2039
2041
2043
2045
2047
CBO Long Term Outlook: Fed Gov. Revenues
(Taxes) and Outlays (Spending) as % of GDP
Revenues Outlays
70
80
90
100
110
120
130
140
150
2017
2019
2021
2023
2025
2027
2029
2031
2033
2035
2037
2039
2041
2043
2045
2047
CBO Long Term Outlook:
Debt held by Public as % of GDP
-10.0
-9.0
-8.0
-7.0
-6.0
-5.0
-4.0
-3.0
-2.0
-1.0
0.0
CBO Long Term Outlook:
Budget Deficit as % of GDP
Gov. spending far
outpaces tax receipts.
Resulting Budget
Deficits rise from 3% of
GDP in 2017 to 9% in
2047.
Rising Budget
Deficits cause the
Debt/GDP ratio to
rise from 77% in
2017 to 145% in
2047.

62. Social Entitlements are
pushing up Budget Deficits
62
0
1
2
3
4
5
6
7
Social Security. Revenues &Expenditures
as % of GDP
Revenues Expenditures
0
1
2
3
4
5
6
7
8
Medicare. Revenues&Expenditures
as % of GDP
Revenues Expenditures
-7
-6
-5
-4
-3
-2
-1
0
ContributiontoBudget Deficit:SS &Medicare
as % of GDP
Social Security Medicare
The Deficits associated with SS and Medicare
increase from about – 2% of GDP in 2017 to –
6% of GDP in average over the 2038-2047
period.

63. U.S., and many countries, are in no position to
implement a Guaranteed Income
63
The majority of
advanced economies are
in a similar situation
with current Debt-to-
GDP ratios close to or
higher than U.S.
Other advanced
economies have
demographics
associated with more
rapid population aging
that renders long term
fiscal outlook weaker
than U.S.

64. Fiscal Perspective Conclusion
• The Government has known for decades that the U.S. fiscal position
(Debt/GDP) is heading towards unsustainability due to rapid rise in
social entitlements.
• The past several Administrations, regardless of parties, have paid little
attention to this issue. The current one is no different.
• Now, society is considering a Guaranteed Income given prospective
massive Technological Unemployment.
• Guaranteed Income would easily cost a multiple of Social Security.
• Given that Social Security and Medicare are already causing an
unsustainable rise in Debt/GDP ratio, Guaranteed Income
considerations do not appear realistic.
64

65. Will we experience Technological Unemployment
as a result of Technological Disruption?
65
• We have already experienced massive historical and current Technological
Disruption as reviewed*. However, Technological Unemployment has not
left much of a footprint in the economic data. The U.S. economy has
suffered bouts of high unemployment rate (Great Depression, Oil Shock
recessions, Great Recession). Spain, Greece, and South Africa have all
currently suffered Great Recession-like unemployment rate levels for
nearly a decade. But, none of those very high unemployment rate periods
have been associated with much Technological Unemployment.
• Thus, Technological Disruption does not necessarily equate to
Technological Unemployment.
*Remember the rapidly declining labor market share of Agriculture and Manufacturing
shown earlier. As indicated the same is happening in white collar professions ranging
from certain IT sectors (Cloud Computing), booksellers (Amazon), tax accountants
(Turbo Tax), travel agents (Expedia, etc.), investment managers & security analysts
(indexing), and many other fields.

66. Back to the McKinsey Report
66
McKinsey indicated that over the next
20 to 60 years 50% of current jobs
could be automated. Their mean
expected outcome being around 40
years from now.
Given the above speculation, the actual
rate of change is a more interesting
consideration than the overall change (-
50% reduction in current jobs due to
automation).

67. What is the % of new jobs created yearly necessary to
neutralize a – 50% decrease in jobs due to automation
over several decades?
67
To neutralize the mentioned -50% jobs contraction due to automation over a 20 year period,
the yearly creation of new jobs is 3.5%; over a 40 year period it is 1.7%; and over a 60 year
period it is 1.2%. As shown, the time horizon has a huge influence on the necessary yearly
new job creation rate.

68. Job Turnover in the US is very high
68
In any single month 3% to 4% of jobs are eliminated (separations that include voluntary and
involuntary leaving jobs) and recreated (job openings). Given that, the U.S economy can
easily create 1.2% to 3.5% new jobs per year to replace existing jobs lost. See below
monthly rates of Job openings and Separations for the overall U.S. economy (nonfarm
sector) and for the Information sector*.
*Per BLS, this includes publishing, software publishing, motion picture, sound recording, broadcasting,
telecommunication, web search portals, data processing, and information services industries.
Source: BLS
Source: BLS

69. Over decades the composition of the Labor
force can change drastically
69
From 1900 to 1950, % of labor force
engaged in farm jobs dropped from 40%
to just over 10%.
From 1973 to 2012, % of labor engaged
in manufacturing dropped from 25%
down to under 10%.
The US labor force adapted well to wrenching changes as it moved progressively over
time from the agriculture sector onto manufacturing and finally onto services.

70. The concern over Technological Unemployment:
What’s next?
70
Agriculture Manufacturing Information Services
Few companies
dominating Cloud
Computing, e-
Commerce, and
everything else.
Dystopian Future

71. Labor Force is already adapting to a
“dystopian” Present
71
Cloud computing and e-commerce is already dominated by just a few companies
(Amazon, Google, etc.). Many industries have been materially disrupted (book
publishing, music industry, travel industry, TV broadcasting).
As mentioned software and aggregation mechanisms such as online tax filing and
investment indexing have already taken a huge share of related professional activities
(tax accountants, portfolio managers, etc.). And, employment is still growing.

72. Can you find the footprint of Technological
Unemployment within our Dystopian Present?
72
The only recent major correction in employment growth was during the Great
Recession associated with the Subprime Crisis that had little to do with
Technological Unemployment.
Great
Recession

73. How about the “Decoupling” since 1970s
73
As reviewed, there has been a
“decoupling” between Real GDP
growth (even on per capita basis) and
wages since the early 70s. Much of
that trend may be due to the rising
labor supply as women labor force
participation rate skyrocketed from
50% in 1972 to 77.5% by 1998.

74. How about the “Decoupling” since 2000
74
The decoupling since 2000 is not explainable due to women labor force participation
rate as the latter has remained stable over that period.
This more recent decoupling may be due to the impact of technological disruption.
And, that is the major concern of the authors of “The Second Machine.”

75. Reframing the Technological
Unemployment issue
• Considerations of Guaranteed Income substituting for a material share of
Consumer Spending given existing fiscal constraints do not appear realistic.
• The concern may not be massive unemployment. If 50% of today’s jobs are
eliminated over several decades, our economy may well create the new jobs
necessary to sustain growing employment. It has done so in the past with shifts
away from agriculture and manufacturing.
• Whether 50% of today’s jobs are eliminated is not as important a consideration
vs. how rapidly such jobs would be eliminated. If they are eliminated over 20
years, the stress on employment trends will be twice as great as if over 40 years.
• Our inability to foresee future employment sectors is not to be confused with
inevitable unemployment related to the progressive elimination of current
employment sectors.
• The “decoupling” trend since 2000 is associated with rising labor productivity
with companies (rising profits) capturing more of the economic gains than
employees (stagnant wages). This does not preclude employment from rising.
However, for economic power to partly shift back to employees you need
prospective labor shortages.
• Only a few years back, the concern was of emerging labor shortage associated
with the upcoming retiring of the Baby Boomers. Now, it is no more a concern.
Things change… 75

76. 76
Summary of evolution of a concept over time while conducting this research
1) Ouch, we are all going to be replaced by intelligent robots.
2) Well, maybe not if we have special expertise.
3) Woops, special expertise is vulnerable too. We are going to lose our jobs after all.
4) Wait, it is not the overall job replacement that matters (-50%), it is over what time
period (20, 40, or 60 years, etc.). The economy should have time to progressively
create new job sectors we do not know off today.
5) In view of item 4), we won’t need to implement concepts such as Guaranteed
Income and Robot Tax that were unfeasible anyway (fiscally and politically,
respectively). Return of private labor unions is equally unlikely.
6) Prospect for long term employment looks better than as first expected under item
“1 & 3”. However, prospect for wages looks rather stagnant. “Decoupling” likely to
continue for a while… until things change…