Capitalism in an Age of Robots Adair Turner Chairman Institute for - - PowerPoint PPT Presentation

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Capitalism in an Age of Robots Adair Turner Chairman Institute for - - PowerPoint PPT Presentation

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Institute for Institute for New Economic Thinking New Economic Thinking Capitalism in an Age of Robots Adair Turner Chairman Institute for New Economic Thinking School of Advanced International Studies Washington DC, 10 April 2018

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New Economic Thinking

Capitalism in an Age of Robots

Adair Turner Chairman Institute for New Economic Thinking

School of Advanced International Studies Washington DC, 10 April 2018 ineteconomics.org | facebook.com/ineteconomics

USA 300 Park Avenue South, 5th Floor, New York, NY 10010 | UK 22 Park Street, London W1K 2JB

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New Economic Thinking

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Current automation capability versus humans performance

Sensory perception Sensory perception Cognitive capabilities Recognising known patterns /categories (supervised learning) Generating novel patterns/ categories Logical reasoning/problem solving Optimisation and planning Creativity Information retrieval Coordination with multiple agents Output articulation/presentation Natural language processing Natural language generation Natural language understanding Social and emotional capabilities Social and emotional sensing Social and emotional reasoning Social and emotional output Physical capabilities Fine motor skills/dexterity Gross motor skills Navigation

Mobility

Below median Median Top quartile Capability level Automation capability

Source: A Future that Works, McKinsey Global Institute Report, 2017

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Automation potential by type of activity

9 18 20 26 64 69 81 Manage Expertise Interface Unpredictable physical Collect data Process data Predictable physical

% of time automatable with current technology

% of time in all US occupations 18 16 17 12 16 14 7

Source: McKinsey Global Institute, A Future that Works, 2017

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Automation potential by occupation

% of specific activities automatable

Example occupations Sewing machine operators, graders and sorters

  • f agricultural products

Stock clerks, travel agents, watch repairers Chemical technicians, nursing assistants, Web developers Fashion designers, chief executives, statisticians Psychiatrists, legislators

% of specific roles and time which can be automated

Source: McKinsey Global Institute, A Future that Works, 2017

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Potential to automate by sector

27 35 35 36 40 43 47 53 60 60 73 Education services Management Professionals Health and social care Real estate Finance and insurance Construction Retail trade Transportation and warehousing Manufacturing Accommodation and food services

% of time automatable with current technology

Source: US Bureau of Labor Statistics McKinsey Global Institute Analysis

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Scenarios for automation

Technical automation potential Early scenario Late scenario

Source: McKinsey Global Institute , A Future that Works, 2017

% of time spent o current works

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Productivity growth in the US

% per annum

1.84 2.41 1.77 1.79 2.82 1.62

0.5 1 1.5 2 2.5 3 1870-1920 1920-1970 1970-2014 Output per person

  • utput per hour

Source: Robert Gordon, The rise and Fall of American Growth (Princeton University Press, 2016

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The standard paradigm

Starting Point

100 self-sufficient farmers produce 100 units of food

New position

50 farmers produce 100 units of food

50 workers produce 100 units of cars, washing machines, televisions, etc.

Measured total economy productivity doubles

Technical progress

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Endlessly repeatable progress?

50 farmers produce 100 units of food 50 factory workers produce 100 manufactured goods

  • 25 farmers producing 100 food
  • 50 factory workers producing

200 cars, washing machines, televisions

  • 15 factory workers producing 60

units of computers, mobile phones and software applications

  • 10 service workers producing 40

units of healthcare 400 units of value – productivity doubled again

Further technical progress

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The Baumol Effect

100 farmers produce 100 units of food

50 farmers produce 100 units of food 50 domestic servants paid ½ as much produce 50 units of value

  • Agricultural productivity

doubles

  • Total economy productivity

increased 50%

Technical progress

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Asymptotic rather than endlessly repeatable progress

25 farmers 100 food 75 servants 75 services 50 farmers produce 100 units of food 50 domestic servants produce 50 services 1 farmer 100 food 99 servants 99 services Total measured productivity: +16.6% Asymptotic limit at +100%

Double agricultural productivity Further progress

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The Baumol Effect with high paid artists

100 farmers produce 100 units of food

50 farmers produce 100 units of food 45 domestic servants paid ½ as much produce 45 units of value 5 artists, singers, entertainers and fashion designers paid twice as much produce 20 units of value

Technical progress

Productivity growth still eventually asymptotes

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Twenty first century technology London

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US Jobs growth forecast 2014 – 2024

Occupational categories by speed of job growth Forecast job growth (000s)

1 Personal care aides 458 2 Registered nurses 439 3 Home health aides 348 4 Food preparation and serving workers 343 5 Retail sales persons 314 6 Nursing assistants 262 7 Customer services reps 253 8 Cooks, restaurant 158 9 General and operations managers 151 10 Construction labourers 147 Total top 10 2873 (29%) 13 Janitors and cleaners 136 14 Software developers, applications 135

Median annual wage May 2014 ($000s)

20 67 21 21 18 25 22 31 97 31 23 95 1 2 3 4 5 6 7 8 9 1… 1… 2…

Source: Bureau of Labor Statistics, www.bls.gov; Projections of Occupational Employment, 2014 – 2024

All sector average: 36

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A manager explains what will happen when he

  • pens the crates:

The Baumol effect in India:

Automation of tea packing

His job will go. And his over there; and that one’s too

But the manager insists that, as in the past, he will somehow find jobs for everyone – as drivers or even watchmen if necessary

India’s Economy: Just the job. The Economist, 16 September 2017

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Zero-sum activities in the simple model

100 farmers produce 100 units of food

50 farmers produce 100 food

  • Total measured productivity

increases 25%

  • But no human welfare benefit
  • f increased consumption

25 criminals 25 police paid same as farmers

Technical progress

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Wonder drug contribution to nominal GDP

With private development and patent protection

$ Contribution to nominal GDP

Research + Development

  • Positive if R+D

capitalised

  • Nil if expensed

Patent protection period

Generic manufacturing with relentless automation

Time

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Wonder drug contribution to nominal GDP

If government or charitable development

$ Contribution to nominal GDP

Research + Development Generic manufacturing with relentless automation

Time

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Three effects combined: An illustrative scenario

Assumptions

% of employment

Non-automatable low productivity 10% 20% Automatable 90% 80%

  • f which:

Zero-sum 20% 30% Non zero-sum 80% 70% … with 50% of zero-sum activity in GDP and 50% not Productivity growth in automatable sectors: 2% p.a. in 80% of activities 5% p.a. in 20% of activities Under-recorded benefits = 33%

  • f growth in the high growth

sectors

Breakdown of Employment

14 11 58 45 18 24 10 20

Year 0 Year 25

Low productivity non-automatable Zero-sum activities — 2% productivity growth Non zero-sum activities — 2% productivity growth Non zero-sum — 5% productivity growth

Productivity growth

Of automatable sectors: 2.5% increasing to 2.7% Of all sectors: constant around 2.05% Of measured GDP: 1.9% declining to 1.5%

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The standard assumption

Technological advance drives productivity improvement across the economy Which shows up in GDP measures of

  • utput per hour

worked and per capita Which provides a good measure of improvements in human welfare

Imperfect but adequate assumption in farm factory transition … but becomes more imperfect in face of information technology goes and proliferation of zero- sum activities Imperfect but adequate assumption as income grows from $1000 to $20000 per capita … but becomes more imperfect as incomes rise and basic needs satiated

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Capital in France 1700 – 2010

0% 100% 200% 300% 400% 500% 600% 700% 800% 1700 1750 1780 1810 1850 1880 1910 1920 1950 1970 1990 2000 2010 % national income Net foreign assets Other domestic capital Housing Agricultural land

Source: Capital in the Twenty First Century, T. Piketty (2013)

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The rising importance of non-produced assets

UK National Balance Sheet 2000 – 2016

1.6 5 2.4 4.8

1 2 3 4 5 2000 2016

£ Trillion

Source: UK Office for National Statistics: Statistical Bulletin on the UK National Balance Sheet

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UK Household land and buildings

0.0 1.0 2.0 3.0 4.0 5.0 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

£Trillion

Land Assets

  • verlying

land

Source: ONS, Statistical Bulletin on the UK National Balance Sheet: 2017 estimates, Fig. 3

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Average income increases US

(1980=100)

50 100 150 200 250 300 350 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

bottom 20% top 5% top 1%

S

Source: US Census Bureau; World Top Incomes Database

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Wealth and employment in software application businesses

Market Value ($bn) (27 Apr 2018) Employees (000s) (2017) 736 ͠ 124,000 716 ͠ 72,000 502 ͠ 25,000 455 51,000 472 45,000

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Population aged 20-64

Millions

2000 2015 Projected 2050 Projected 2100 Japan 79 71 50 35 China 774 928 733 482 Europe 441 454 382 325 Americas 459 582 684 610 India 532 736 1029 867 Africa 352 536 1298 2485

Source: UN Population Database: Medium Fertility projection: 2015. un.org/popin

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Different marginal utility of different “goods”

Utility / Happiness Utility / Happiness Utility / Happiness Income Income Income

Good health? Branded fashion goods? Congestion and environmental damage?