By Yixiao Zhou*
Automation has grown quickly in the Asia Pacific, with the region catching up to Europe and North America in robot density. Significant diversity exists between countries, with high levels of robotics adoption in Japan, South Korea and, increasingly, China, but much lower levels in other economies, such as India and Indonesia. Automation can help maintain the international competitiveness of firms and combat the headwinds of ageing populations and slowing labour productivity growth.
Asia Pacific economies are experiencing a demographic transition towards older populations, and automation could help compensate for the slowdown in the growth of the labour force as it enables physical capital to substitute for labour. Since the global financial crisis, the fall of unit labour costs has slowed as developing Asia’s labour productivity has gradually plateaued compared with labour costs per worker.
This trend threatens Asia’s international competitiveness, and firms are investing in automation to boost labour productivity. The need for social distancing to reduce virus transmission during the COVID-19 pandemic has accelerated developments in the automation and digitisation of production tasks.
Although automation boosts competitiveness, there are also dark sides such as potentially causing unemployment and aggravating income inequality. There are two mechanisms with opposite effects on employment, with automation replacing low-skilled labour and reducing employment while also creating new high-skilled jobs and raising employment. Income inequality is likely to rise in the short run if the labour-replacing effect dominates before new industries, tasks and jobs are generated.
As many economies in the Asia Pacific are export oriented or are looking to increase exports for the purposes of economic development, if future international competition hinges on automation, then they have reasons to be concerned. First, the increased use of robots in developed countries risks eroding the traditional labour-cost advantage of developing countries. Second, robot use may work to the advantage of countries with established industrial capacity. Third, since the share of occupations that could be automated is higher in developing countries than in more advanced ones — where many of these jobs have already disappeared — this could lower growth prospects in developing countries that are already experiencing ‘premature deindustrialisation’.
How can countries in the Asia Pacific prepare for the challenges and opportunities associated with automation?
First, education policies must nurture in-demand skills and ensure that replaced workers retrain to gain new skills for new tasks. Workers must develop the mindset of continuous learning to face rapid technical change and job changes. Automation may demand more workers who have skills in programming, maths, science and engineering.
New technologies may even, in the long run, reach a stage of maturity where artificial intelligence can replace humans in the performance of most tasks and people no longer need advanced maths or programming skills to utilise new technologies. At that time, skills in the liberal arts and emotional and communication skills will become more important, with abilities such as critical thinking, artistic creativity, philosophical understanding and social sensitivity becoming more important as well.
Second, countries should seek to leapfrog existing technologies and move straight towards more advanced ones. Thegeography of future innovation is uncertain. It is not yet decisively clear whether innovation will cluster around places such as Silicon Valley in the United States or Shenzhen in China, or whether new technologies will be used and developed into specialised frontier technologies in local economies.
A geographically distributed model of innovation would mean that firms could develop niche technologies for domestic markets by leveraging and integrating into the existing automation platforms of technologically advanced countries. There may also be the ‘servicification’ of manufacturing, where manufacturing firms not only buy more services than before but also sell and export more services as integrated activities.
Third, as inputs used in production include not only labour, capital and land but also information, future global comparative advantages will be reshaped. It is important that economies maintain open channels for information flows, including international trade, the international flow of capital, international migration and international knowledge flows, such as access to academic research. This also requires investment in infrastructure such as broadband and mobile networks, human capital, institutional quality and the business environment.
Establishing a business environment friendly for entrepreneurship will stimulate the growth of new firms based on cutting-edge technologies and generate employment opportunities. Unlike traditional routes to industrialisation, the new model of industrialisation is likely to see more frequent disruptive technological changes and continuous creative destruction, referred to as Schumpeterian growth.
Finally, government policymakers and regulators should properly regulate new technologies. One policy approach in response to the opportunities and risks associated with emerging technologies is the regulatory sandbox — a ‘safe space’ where businesses can test innovative products, services, business models and delivery mechanisms with regulators.
These strategies will help maximise the chance that automation lifts total factor productivity (TFP) growth. Higher TFP growth will help alleviate the negative impacts of automation on employment and the burden on the economy when tax and transfer policies are implemented to reduce income inequality.
We have not yet seen much of the effects of automation on TFP growth, which has slowed in several economies in the Asia Pacific since the global financial crisis. Like other general-purpose technologies, the full effects of automation on TFP growth may not be realised until complementary innovative technologies are developed and implemented. But the key aspects discussed above are crucial in allowing automation to bring about TFP growth.
*About the author: Yixiao Zhou is a Senior Lecturer in the Arndt-Corden Department of Economics, Crawford School of Public Policy, the Australian National University.
Source: This article is published by East Asia Forum and is based on ‘Automation, the future of work and income inequality in the Asia-Pacific’, Chapter 6 in Achieving Inclusive Growth in the Asia Pacific edited by Adam Triggs and Shujiro Urata.