Carolyn Wilkins: Blame it on the machines?
Remarks by Ms Carolyn Wilkins, Senior Deputy Governor of the Bank of Canada, to the Toronto
Region Board of Trade, Toronto, Ontario, 18 April 2017.
* * *
I would like to thank Rhys Mendes, Ben Tomlin and Stephen Murchison for their help in
preparing this speech.
Introduction
In the 150 years since Confederation, the average income per person in Canada has increased
about 20-fold after adjusting for inflation-all because we have adopted better ways of doing
business. This illustrates the basic economic reality that productivity growth is the only game in
town when it comes to raising the economic and financial well-being of people over a long period.
The arithmetic is simple. Productivity growth, combined with growth in the labour force,
determines how fast activity can expand without stoking inflation pressures-something we call
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potential output growth.
The Bank of Canada updated its estimates of potential output growth in last week's Monetary
Policy Report. Our best estimate is that potential output will rise by an average of 1 1/2 per cent
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per year over the next few years-that is not very impressive relative to history. We are counting
on gains in productivity to deliver fully two-thirds of that growth. And we are not alone; productivity
performance in other industrialized countries is also underwhelming.
The good news is that Canada has the opportunity to make up for lost time. The world is on the
brink of a new industrial revolution. Innovations in artificial intelligence, robotics and other fields
could give productivity a big boost by automating an expanding range of tasks. Some analysts
predict that close to half of all jobs in some advanced economies will be profoundly affected by
automation in the next 20 years. That leaves many of us wondering about the future of work. And
it's personal. We wonder what will happen to our own jobs or those of our friends, or what our
kids should study to succeed in tomorrow's workplace.
Business people like you share a stake with the Bank of Canada in these matters. So I am
pleased to have the occasion to speak on this subject today, and I thank the Toronto Region
Board of Trade for the invitation.
In my remarks, I will speak to three main points:
1. We can expect a future with work for people, not just for machines. Innovation is always a
process of creative destruction, with some jobs destroyed and, over time, even more
created. We have seen this process in action throughout modern history.
2. What will change is the types of workers that will be in demand. We will need people with
highly technical skills to program and repair the technology. We will also need people to
perform tasks that may never be replicated by a machine because they require creativity,
intuitive judgment, inspiration or simply a human touch.
3. Canada should embrace new technologies and their benefits, while proactively managing
their more harmful side effects. Policies that help businesses and workers manage what
could be a difficult transition are essential. So are policies that address the potential for
amplified income inequality and, in some cases, increased market power.
The Bank's job in all of this will be to foster the macroeconomic conditions that will help Canada
adapt and grow.
Were the Luddites right?
Let me dive right into my first point.
In the past couple of centuries, the world has seen revolutionary innovations like the steam
engine, the combine, the jet engine and the assembly-line robot. The resulting increases in
productivity gave us a 20-fold increase in real income per capita in Canada over the past 150
years.
Our underwhelming productivity performance since the early 2000s has cost us dearly. If
productivity had continued to grow at the pace it did in the late 1990s, our gross domestic
product (GDP) would have been 23 per cent higher in 2016, meaning an extra $13,000 for every
Canadian.
Even as we see the benefits of technology, many of us feel uneasy about what automation could
mean for workers. Fears of technological progress are as old as technological progress itself.
Now, there is no doubt that technological improvements have eliminated jobs at the sectoral
level. Take manufacturing, for instance. Innovations such as industrial robots have reduced the
need for workers in that sector. If we were to roll back the clock on Canadian manufacturing
productivity to what it was 20 years ago, three-quarters of a million more people would have been
needed to produce today's level of output in that sector. But the manufacturing jobs lost were
offset with gains elsewhere. Roughly 82 per cent of the prime-age population is now employed,
about 13 percentage points higher than 40 years ago.
Other past technological advances did not lead to a sustained rise in overall unemployment
either. Let me use agriculture to illustrate the economic mechanisms that have helped us adapt
and thrive in the past, which are often underemphasized. Factory farming and the combine
harvester increased labour productivity in the farming sector and reduced the need for
agricultural workers. Higher farm productivity also made food cheaper for all consumers, leaving
them with more money to spend on other goods and services. These positive effects on income
led to higher consumer demand, which helped spur the creation of new jobs outside of
agriculture. Rising productivity in manufacturing also led to widespread industrialization, which
attracted labour from farms to higher-paying factory jobs.
This is how agriculture went from representing more than one-third of all jobs in Canada a
century ago to less than 2 per cent today, without creating a permanent jump in unemployment.
Governments helped ease the transition away from agriculture by making some bold decisions.
One example is promoting education in the late 1800s and early 1900s through publicly funded
schools. This helped prepare the next generation for jobs outside the agricultural sector, although
the period of adjustment could not have been easy.
OK computer
This leads me to my second point. Technological advances have always been a key driver of
growth and rising income per capita, yet some fear that this time will be different. In the past,
automation was largely restricted to simple manual or procedural tasks. Today's technology
makes it possible to automate an increasing number of cognitive and non-routine tasks across a
wide range of industries.
Machine learning is one way to do that. Feeding computers large sets of data teaches them to
mimic the human brain's ability to infer rules from previous experiences and adapt to changing
circumstances. Artificial intelligence (AI) allows computers to read scans and x-rays with
precision and self-driving cars to react to any number of unique situations on the road. AI also
allows businesses to automate many of the routine cognitive tasks performed by accountants,
investment advisors and lawyers.
This has raised the spectre of technological unemployment-the dystopian vision of an economy
in which machines make many workers obsolete. You have probably heard estimates that
suggest that around 40 per cent of tasks performed by humans in Canada and the United States
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could be automated using current technology.
Even so, it is difficult to imagine that the adjustment mechanisms I described earlier are now
obsolete. An intuitive way to think about it is to observe that people's spending appetite tends to
grow along with productivity. With 20 times more income, people would only have to work 20
times less than they did before to earn the same amount. The reality is that people generally
work a little more than half the time that they used to, with the rest of the gains going toward
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increased consumption. This phenomenon is observed not only in Canada but also in other
advanced economies.
As technologies raise productivity, labour market dislocations occur over the transition period, but
eventually new jobs are created to supply the goods and services that people buy with the extra
income.
The fact is that we do not know exactly which new sectors will be important employers 50 years
from now. Who in the early 1900s could have imagined the boom in health care, tourism and
software development jobs? There are also many tasks that machines will not be capable of
doing any time soon. An academic expert in this area of economics, David Autor, maintains that
humans will likely retain an advantage in jobs that require interpersonal interaction, flexibility,
problem solving and common sense. These include personal care workers, plumbers,
consultants and, I am hoping, central bankers.
What is particularly important to consider this time is the impact that technological progress
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could have on income inequality. Technological advances may lead to higher incomes for
workers whose skills are complemented by the technology, but not for those whose skills are
substituted by it. The first wave of information technology in the 1980s and 1990s is a case in
point. Educated professionals like scientists and architects could use their skills more
productively, while many less-educated workers, like bank tellers and travel agents, saw their
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jobs being displaced by technology. This led to bigger employment shares for high- and
lowskilled jobs at the expense of middle-skilled jobs in Canada, along with a modest increase in
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income inequality.
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The hollowing out of the middle could be further accentuated by automation. Moreover, the
polarizing effect of technology on income distribution could be heightened by a winner-takes-all
effect-this comes from the market power that new technologies can often bestow on their
inventors. In parts of the information and communication technology (ICT) sector, economies of
scale such as network effects are already prominent.
That said, for all the hype around the current wave of automation, we have yet to see the kind of
productivity growth that is consistent with a technological revolution. While we sometimes see
fast technological change in specific industries-fracking in the oil sector is one example-
economy-wide technological transitions often play out over long periods. After the first central
power station opened in the 1880s, electrification took four decades to have an impact on
productivity in the United States. Power grids had to be built, machines had to be replaced and
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new applications took years to develop. For similar reasons, it could take many years for
selfdriving vehicles to completely displace human-driven taxis, trucks and buses. The length of the
transition will depend on how fast existing vehicles depreciate, prices for the new technology
decline, and required infrastructure is updated.
What does all of this mean for the Bank of Canada's economic projections? It is simply
impossible to quantify the impact of these innovations before they happen. That is why the Bank
assumes no additional boost from automation. While the Bank is projecting a rebound in trend
labour productivity growth from 0.6 per cent in 2016 to 1.1 per cent in 2020, this mainly reflects a
cyclical pickup in investment spending from the lows witnessed following the oil price shock. Our
work to date suggests the greatest productivity benefits will occur in firms with high-quality
people-management and decision-making processes and high levels of human capital. With big
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data, smart contracts and robo advisors, financial companies could be at the head of the pack.
The Bank of Canada has a research program to better understand these issues. We have
created a new digital economy team that focuses on how automation is unfolding and affecting
the economy, including inflation dynamics and the transmission of monetary policy. We are
reviewing the measurement issues that are exacerbated by the proliferation of digital and
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services-oriented technologies. We are also developing our macroeconomic models to better
account for changes in the distribution of income and wealth.
Proactive beats reactive
Let me now turn to my final point. Canada is well positioned to succeed in a digital world, and we
should embrace it. Canada has a flourishing information technology sector and is becoming an
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important player in the AI field. Major Canadian firms have teamed up to provide funding for the
development of AI start-ups through a program called NextAI. And some international companies
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are moving their AI divisions to Canada.
To get the most out of the new technologies, we will need to work together to proactively mitigate
the more harmful side effects that I have mentioned: the transition period and the potential effects
on the distribution of income.
There are many promising approaches to managing the first side effect-the transition period.
Let me highlight just one. As with previous technological transitions, education, skills training and
continuous learning will be key. Universities across Canada are working with students and
businesses to bring the best ideas in science, machine learning and AI to market. A great local
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example is the Rotman School of Management's Creative Destruction Lab. A positive aspect is
that students will gain practical experience early on.
Canada and its fellow G20 countries have committed to supporting strong, sustainable and
inclusive growth. Today more than ever, it is important to preserve the gains that have been
made. Trade is a great driver of productivity, and so the risk of growing protectionism concerns
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me. More open trade with the United States and Mexico in the 1990s gave Canadian firms
access to much bigger markets and therefore greater incentives to invest-in both
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physical and human capital. Disrupting supply chains and reducing incentives to compete will
not create more jobs and income in the long run. Canada remains committed to free trade and
the most recent example of that is the interprovincial agreement that was signed earlier this
month. While we will not know its full impact for some time, we flagged it as an upside risk to
productivity in our April Monetary Policy Report.
The second side effect, distribution of income, is equally important. While gains in productivity
will increase the size of the pie, there is no guarantee that these gains will be evenly distributed.
This is the purview of governments, who can use tools such as taxation and transfers to address
these issues. And they involve difficult trade-offs related to preserving the incentives to invest
while also avoiding increased polarization of income. Cross-border taxation will also be
challenging, given how easy it can be to move intellectual property to low-tax jurisdictions.
Aside from taxation, increased market power for some players may raise important systemic
issues, many of which are cross-border in nature. These issues are likely to arise in sectors
where barriers to entry or economies of scale are prominent. An example that is top of mind from
my work on fintech issues is related to cloud computing and storage. As we move away from
decentralized on-site storage and computing systems, we may see a trend toward greater
concentration in market structure. These service providers are largely outside the regulatory
framework, and this raises issues related to adequate legal foundations, governance,
transparency and risk controls. All of these are critical to a stable economic foundation for
workers and businesses.
As a central banker, I care about income inequality, even if we do not control the tools to address
it. Worsening income inequality can lead to weaker macroeconomic outcomes and financial
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instability. It is more difficult for people with low incomes to weather economic shocks. If we
see an increasing proportion of people at the lower end of the income distribution, recessions
and other negative events could result in more financial stress.
Shifts in income distribution can also affect the transmission of monetary policy since interest
rates do not affect everyone in the same way. For example, people with lower incomes are likely
to be sensitive to interest rate changes because of the potential effects on their employment
income and their debt-service costs. These effects may be less prominent at the other end of the
income scale. That said, people with higher incomes and higher net worth tend to be sensitive to
the impact of interest rates changes on asset prices. An increase in income dispersion, then,
could alter the channels through which monetary policy actions affect the economy.
The Bank of Canada's monetary policy accomplishes a simple, yet vital, task: it manages the
level of demand over the business cycle in order to meet our inflation target. In turn, an
environment of low, stable and predictable inflation allows productivity-enhancing investments in
physical and human capital. This is the perfect complement to the structural policies that
governments at all levels in Canada are working to strengthen.
Conclusion
Time to wrap up.
If we want to continue to prosper, we have to improve our productivity.
Clearly, blaming the machines is not the way forward. If we seek out and embrace new
technologies while successfully managing their harmful side effects, we will create inclusive
prosperity. That means proactively managing the transition period and the longer-term
implications for the distribution of incomes. In many respects, we have a head start in Canada.
Our policy-makers are working to implement measures that will achieve strong, sustainable and
inclusive growth.
What you can do on your side is equally ambitious: keep building competitive and dynamic
businesses; keep the collaboration going between educational institutions and companies; and
keep sharing your good ideas with policy-makers.
The Bank of Canada will continue to focus on what it does best: supporting the economic and
financial well-being of Canada by achieving low, stable and predictable inflation; by keeping core
financial market infrastructure safe; and by giving sound advice on financial sector policies so
that vulnerabilities do not get in the way of sustainable, productive growth for all Canadians.
of jobs are currently fully automatable. C. Lamb, The Talented Mr. Robot, Brookfield Institute, June 2016.
4
See T. Boppart and P. Krusell, "Labor Supply in the Past, Present, and Future: A Balanced-Growth Perspective,"
NBER Working Paper number 22215 (May 2016).
5
See P. Krusell, L. E. Ohanian, J.-V. Ríos-Rull and G. L. Violante, "Capital-Skill Complementarity and Inequality: A
Macroeconomic Analysis," Federal Reserve Bank of Minneapolis Research Department Staff Report No. 239 (1
September 1997).
6
D. Acemoglu and D. Autor, "Skills, Tasks and Technologies: Implications for Employment and
Earnings," Handbook of Labor Economics, Vol. 4B, edited by D. Card and O. Ashenfelter, 1043-1171 (Elsevier,
2011).
7
This is a phenomenon across many advanced economies. For more on Canada, see D. A. Green and B. M.
Sand, "Has the Canadian Labour Market Polarized?" in Income Inequality: The Canadian Story, edited by D. A.
Green, W. C. Riddell and F. St-Hilaire, 217-227 (Institute for Research on Public Policy, 2015). For an
international comparison, see OECD, "Income Inequality Update," (November 2016).
8
A related issue is the impact of technology on labour's share of income. An analysis by the International
Monetary Fund (IMF) found that automation has contributed to the decline of the labour share of national income
in advanced economies. This was accompanied by a rise in income inequality, partly because of the effects of
automation on middle-income workers. See IMF, World Economic Outlook, "Chapter 3, Understanding the
Downward Trend in Labor Income Shares," (Washington, April 2017).
9
P. David, "The Dynamo and the Computer: An Historical Perspective on the Modern Productivity
Paradox," American Economic Review, 80, no. 2 (January 1990): 355-361.
10
C. D'Souza and D. Williams, "The Digital Economy," Bank of Canada Review (Spring 2017-forthcoming).
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Recent work at the Organisation for Economic Co-operation and Development (OECD) suggests that gross
domestic product (GDP) remains a good measure of the sum of all market transactions. Nevertheless, GDP is
an imperfect measure, and many of the challenges are more prevalent in a digital and services-oriented
economy, such as the distinction between quality and price change, consumers acting as producers, and price
measurement. Investment and productivity estimates are also becoming more problematic. While digitalization
intensifies these challenges, it could also provide useful data that will help solve them. In addition, GDP
statistics are often criticized in the context of digitalization because they do not account for the related welfare
gain, but it is important to bear in mind that GDP is not a measure of welfare. That said, digitalization has
probably widened the gap between GDP and welfare, which reinforces the importance of complementing GDP
with indicators of well-being, like the United Nations Development Program's Human Development Index and
the Canadian Index of Wellbeing produced by the University of Waterloo.
12
W. Dong, J. Fudurich and L. Suchanek, "The Digital Economy-Insight from a Special Survey with IT Service
Exporters," Bank of Canada Staff Discussion Paper No. 2016-21 (November 2016).
13
See J. Jacobs, T. Poutanen, R. Zemel, G. Hinton and E. Clark, "Artificial Intelligence is the Future, and Canada
Can Seize It," The Globe and Mail, 7 January 2017.
14
The Creative Destruction Lab program targets early-stage, science-based technology companies. It also offers
a specialized machine-learning stream for companies that focus on machine learning or artificial intelligence.
The program expanded to Vancouver in collaboration with the University of British Columbia's Sauder School of
Business.
15
For a history of how Canada has benefited from trade openness, see S. S. Poloz, "Canada at 150: It Takes a
World to Raise a Nation," (speech to Durham College for its 50th anniversary, Oshawa, Ontario, 28 March 2017).
16
There is evidence that following trade liberalization agreements, many lower-productivity firms shed workers or
do not survive. Others can flourish and raise productivity. See, for example, D. Trefler, "The Long and Short of the
Canada-US Free Trade Agreement," American Economic Review 94, no. 4 (2004): 870-895.
17
See M. Kumhof, R. Rancière, P. Winant, "Inequality, Leverage, and Crises," American Economic Review 105, no.
3 (March 2015):1217-45.