Joel Blit

Automation and the future of work
Scenarios and policy options
Joel Blit
Assistant Professor of Economics, University of Waterloo
Senior Fellow at the Centre for International Governance Innovation
Waterloo Artificial Intelligence Institute

Outline
▪ Technological context
▪ Impacts of AI on employment
▪ Impacts of AI on inequality
▪ Substitute and Complementary skills
▪ Policy
▪ Conclusion
Automation and the future of work PAGE 2

Technological Context
▪ Exponential growth in computing power and the
digitization of processes and data have finally
made AI/ML a practical solution to real-world
problems
▪ Computing power (Moore’s law, quantum computing,
specialized processors, cloud computing)
▪ Digitization (Data generation, host for AI systems)
▪ Robots that are more dexterous, flexible,
trainable, and intelligent
Transistors per Microprocessor (1971-2017)
Data Source: ourworldindata.org

Real-World Applications

Impacts of AI
▪ AI is a general purpose technology (GPT)
(Bresnahan and Trajtenberg, 1995)
▪ Pervasive
▪ Will continue improving
▪ Will spawn complementary innovations
▪ Like for other GPTs (steam engine, electricity,
semiconductors) it will take time to feel AI’s full
impacts
▪ Productivity growth
▪ Unemployment and inequality
U.S. TFP and Labour Productivity Growth (%) by Decade
Source: Brynjolfsson, Rock, Syverson, 2017.

Employment
▪ Frey and Osborne (2013)
▪ 47% of U.S. jobs are susceptible to being automated in the
next 10-20 years
▪ Note: Just because a job can be feasibly
automated does not mean it will
▪ It may not be economic to do so
▪ Organizations change slowly
▪ Laws and regulations change slowly
▪ Arntz, Gregory, Zierahn (2016)
▪ 9% of jobs are automatable (21 OECD countries)
Source: Arntz, M., T. Gregory and U. Zierahn (2016)

Example: Radiologists
▪ In addition to analyzing images, radiologists also
decide which images to take, assist in
procedures, discuss diagnoses with other
specialists, discuss treatments with patients, etc.
▪ If analyzing images is 50% of their time, then
perhaps the demand for radiologists will be
halved
▪ But as radiologists become more productive the
demand for their services will increase. And if it
increases enough, we could even see a net
increase in employment.

Rising Industry Productivity Lowers Industry Employment
Source: Autor Salomons

But Spillover Effects Cancel it Out
Source: Autor Salomons

H
L
Skill-Biased Technical Change
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Skill-Biased Technical Change
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slope = -wL'/wH’
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C
S
AI with Small Marginal Cost
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slope = -wS/wC
slope = -wS
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AI with 0 Marginal Cost
slope = -wS/wC
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ADVICE
“Seek to be an indispensable complement to something that’s
getting cheap and plentiful”
Attributed to Hal Varian, Chief Economist at Google
Source: Brynjolfsson, McAfee, “The Second Machine Age”

Complementary Skills
▪ Judgement/Instinct/Intuition
▪ Critical thinking (of the broad kind)
▪ Creativity
▪ Communication
▪ Leadership
▪ Empathy
▪ Computer skills
▪ Entrepreneurial skills

Entrepreneurial Skills Are Worth More Than Ever Before
▪ YouTube (founded in 2005)
▪ By 2006:
▪ 20M unique users per month, 100M videos per day, only 30 employees
▪ Acquired by Google for US$1.65B
▪ Instagram (founded in 2010)
▪ Acquired by Facebook in 2012 for US$1B (it had 13 employees)
▪ WhatsApp (founded in 2009)
▪ Acquired by Facebook in 2014 for US$19B (it had 55 employees)

Techno-Optimists v. Doomsday Sayers
▪ Default position of most economists is that technology will destroy some jobs but
create others
▪ But this ignores the fact that technological disruption can result in a long
adjustment period
▪ Even if the jobs exist, low wages and inequality are likely to be an issue

Average Real Wages in England during the Industrial Revolution
Source: Blit, St. Amand, Wajda (2018) - Data from Allen (2007)

Short to Medium Run
▪ Significant disruption with large number of losers
▪ Moral/ethical question
▪ Political upheaval
▪ Threat to democracy
▪ Downward Consumption spiral?
▪ Automation could result in a temporary increase in output but a permanent
decrease in the standard of living if the returns accrue to the few who own the
technology (Sachs, Benzell, LaGarda, 2015)
▪ ”Threat is not technology per se but misgovernance” (Autor 2015)

Policy
▪ Promote these technologies to generate gains
▪ Ensure that gains are broadly shared
▪ Education and training
▪ Social safety net
▪ Broad taxation
▪ Nudge toward human-enhancing (vs. human-replacing) technology?

Education and Training
▪ Invest in early years education (empathy, self-awareness, interpersonal skills)
▪ Focus on transferable skills in Primary, Secondary, and Tertiary education
▪ Problem solving, critical thinking, decision making, creativity, communication
▪ Applied skills should be spread over working life (self-directed learning, on-the-
job learning, training, retraining)
▪ Computer skills (including programming)

Entrepreneurship
▪ Entrepreneurial skills (recognizing opportunities, thinking creatively, problem
solving, executing)
▪ Entrepreneurial culture

Social Safety Nets
▪ Challenges
▪ Large increase in number of unemployed
▪ Gig economy
▪ Solutions
▪ Universal basic income pilots are ongoing
▪ More flexible eligibility for employment insurance programs?
▪ Extend employee benefits to contractors and freelances?

Taxation
▪ Broad taxation will become more challenging due to
▪ Increasing capital mobility (including intellectual capital)
▪ Changing nature of production
▪ Increasing concentration of income and wealth
▪ Tax policy needs to be addressed multilaterally
▪ And it needs to be addressed now!

Conclusion
▪ Uncertain labour markets
▪ Significant disruption, at least in the short to medium run
▪ Some unemployment, large distributional impacts
▪ Need to prepare for some of the more dire scenarios
▪ Education and skills, Entrepreneurship, Taxation

Joel Blit

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