Capitalism in an Age of Robots

65 Pages·2017·1.68 MB·English

by  Christopher Sealey

Institute for
Institute for
New Economic Thinking
New Economic Thinking
Capitalism in an Age of Robots
Adair Turner
Chairman
Institute for New Economic Thinking
Resurrecting the Public
Lecture Series
Azim Premji University
Bangalore, October 2, 2017
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Automation of everything? When not If
The Solow paradox: explicable and inevitable?
Challenges for advanced economies: “Average is over”?
Challenges for emerging economies: ending the
demographic denial
Limits to markets: implications for economics
Institute for
2
New Economic Thinking
ICT – not just another
technology
Moore’s Law • doubling every two years
• = 1000 times in 20 years, 1 million in 40
• in processing speed, memory, bandwidth
• infinitely replicable at almost zero
Software
marginal cost
Artificial intelligence super intelligence
Big data analysis
Machine learning and robotics
Institute for
3
New Economic Thinking
Current automation capability versus humans performance
Automation capability
Sensory Sensory perception Below median
perception
Median
Cognitive Recognising known patterns /categories (supervised learning)
7 capabilities Top quartile
1 Generating novel patterns/ categories
0
2
,t Logical reasoning/problem solving
r
o
p
e
R Optimisation and planning
e
t
u
tit Creativity
sn C
I la Informationretrieval pa
b a
o b
lG Coordination with multiple agents i
l
y ti
e y
s Output articulation/presentation
n l
iK ve
cM Natural Natural language generation e
l
s ,
k language
r
o Natural language understanding
W processing
t
a
h
t Social and Social and emotional sensing
e
r
u emotional
t
u
F Social and emotional reasoning
A capabilities
e : Social and emotional output
c
r
u
o
S Physical Fine motor skills/dexterity
capabilities
Gross motor skills
Navigation
Institute for
4
New Economic Thinking
Mobility
Automation potential by type of activity
% of time automatable with current technology
% of time in all
US occupations
Predictable physical 81 18
Process data 69 16
Collect data 64 17
Unpredictable physical 26 12
Interface 20
16
Expertise 18
14
Manage 9
7
Source: McKinsey Global Institute, A Future that Works, 2017
Institute for
5
New Economic Thinking
Automation potential by occupation
% of specific activities automatable
Example occupations
%
Sewing machine operators, graders and sorters
o
f

s
of agricultural products p
e
c
i
f
i
c

r
o
Stock clerks, travel agents, watch repairers el
s

a
n
d

t
i
m
Chemical technicians, nursing assistants,
e

w
Web developers
h
i
c
h

c
a
n
Fashion designers, chief executives, statisticians
b
e

a
u
t
Psychiatrists, legislators o
m
a
t
e
d
Source: McKinsey Global Institute, A Future that Works, 2017
Institute for
6
New Economic Thinking
Potential to automate by sector
% of time automatable with current technology
Accommodation and food services 73
Manufacturing 60
Transportation and warehousing 60
Retail trade 53
Construction 47
Finance and insurance 43
Real estate 40
Health and social care 36
Professionals 35
Management 35
Education services 27
Source: US Bureau of LaborStatistics McKinsey Global Institute Analysis
Institute for
7
New Economic Thinking
Scenarios for automation
Technical automation Early scenario
potential Late scenario
s
k
r
o
w

t
n
e
r
r
u
c

o

t
n
e
p
s

e
m
i
t

f
o

%
Source: McKinsey Global Institute , A Future that Works, 2017
Institute for
8
New Economic Thinking
Automation of everything? When not If
The Solow paradox: explicable and inevitable?
Challenges for advanced economies: “Average is over”?
Challenges for emerging economies: ending the
demographic denial
Limits to markets: implications for economics
Institute for
9
New Economic Thinking
Productivity growth in the US
% per annum
3
2.82
2.5 2.41
2
1.84
1.79 1.77
1.62
1.5
1
0.5
0
1870-1920 1920-1970 1970-2014
Output per person output per hour
Source: Robert Gordon, The rise and Fall of American Growth(Princeton University Press, 2016
Institute for
10
New Economic Thinking