This article first appeared in Forum, The Edge Malaysia Weekly on December 6, 2021 - December 12, 2021

I recently read a book called Anxious People by Fredrik Backman, where he describes a father-son police duo as follows. When the father “writes a report, he hits every key all the way down very deliberately, then checks the screen at once to make sure it hasn’t tricked him, and only then does he press the next key”. The son, on the other hand, “types the way young men who’ve never lived in a world without the internet do, he can do it blindfolded”.

This generational gap in technology use is not new. We can all surely remember a time when our Luddite elders — at home or at work — just refused to try out a new smartphone or a new app. But here’s the thing. Nearly everyone becomes that Luddite one day. I have a goddaughter who is just over two years old and a niece who is just over three months old. There will come a time where they will look at me with a combination of disdain and pity as I ask them for some technology support.

The generational gap in technology use does not really need to be “generational”. Differences in abilities to use technology can occur for any kind of reason. For instance, some people may want to learn how to code, and some may not. Another reason is access. Many may not have the resources or opportunities to learn how to use new technologies. Whatever the reason, it is not a stretch to say that, at the micro, individual level, this may result in a large gap between technological skills and abilities.

How does that translate at the macro level, especially on wages? This may, on the one hand, seem obvious — if you are less technologically skilled, you are deemed less productive, especially in a digitalised world, and you are likely to have lower wages. Only those who are technologically skilled will get the higher wages, and therefore there is a growing wage gap, and growing wage inequality.

The reality is more complex than that. In fact, this wage-inequality scenario is true if technology grows at a much quicker pace than the skills or abilities of the general population. This is what prominent Harvard economists Claudia Goldin and Lawrence Katz call “the race between technology and education”, coined initially by Dutch economist Jan Tinbergen.

Briefly, the idea is as follows — technology is essentially the demand for higher and higher skill levels from workers, whereas education is the supply side of that equation. If technology far outpaces education, and therefore if demand is higher than supply (technology wins), then wage inequality increases, as the wages of higher-skilled workers relative to lower-skilled workers increases disproportionately. On the other hand, if educational access and quality for the general population increases far more quickly than technological growth, and therefore if supply is higher than demand (education wins), then wage inequality decreases because the wages of higher-skilled workers relative to lower-skilled workers do not grow as quickly.

The movement of wages in the US in the 20th century bears out the race between technology and education. After World War II, the US saw reduced wage inequality, owing to its high school movement in the early 20th century bearing fruit. It supplied enough adequately skilled workers for the technology at the time, which was prior to mass computerisation. After the 1980s, however, as computerisation and the internet became more prominent, that wage inequality widened as the supply of workers for new technologies failed to keep up with demand, leading to a premium in wages for university graduates.

This is not to say the race between education and technology explains all of the wage movements in the US during that time period. Post-1980s, with Reaganism and Thatcherism taking hold, the strength of unions — historically a force for lower inequality — waned. Globalisation moved production centres around, leaving those who were “left behind” with stagnating or reduced incomes. Nonetheless, the explanatory power of the race remains strong for the time.

Turning to Malaysia, it is worth asking where we are in that race. The context for Malaysia is different relative to the US in several respects. For one, the bulk of our economy remains in low-cost goods and services, where the demand for technology is not especially strong. Second, on the supply side, Malaysia’s universities churn out more than 200,000 new graduates a year, but graduate unemployment and underemployment remain pervasive. Thus, with low demand and high supply, the equilibrium price — wages, in this case — will be low.

There are several layers to this. On the demand side, if the structure of our economy remains as is, without transitioning towards an economy that has much greater demand for more technology-skilled, higher productivity-type jobs, then it is difficult to imagine a case where the general wage level would tend to increase. If we continue to base our economic competitiveness on a de facto low-cost structure advantage — where we might, for instance, worry about competing with Vietnam as opposed to trying to catch up with South Korea — it will be challenging to improve general wage levels.

On the supply side, even if we manage to manufacture greater demand for technology, if the quality of the labour supply meets that demand, not only will we see a greater increase in general wage levels, but we will also see a reduction in wage inequality. Wage inequality happens when only a small group of individuals are deemed qualified for those high-skilled jobs. Thus, it is not enough to simply churn out graduates; we need to ensure that those graduates are adequately prepared for the technology that is present and that is to come.

Taking a step back, when we think of the race between education and technology, we need to recognise a deep assumption that underpins this relationship — that of technological determinism, the idea that technology is some unstoppable, inexorable force of nature that we cannot manage, but can only react to. And, consequently, governments or nations can only seek to mitigate the worst of its effects and ride the wave of the best of it.

This need not be the case. Technology need not be predestined, and technology policy is something policymakers can influence. Governments can and should shape the kinds of digital technology they believe their countries can adopt and deploy. For instance, the German government released a Work 4.0 report that states that part of the technological response calls for a greater collaborative and collective bargaining arrangement between firms and workers, which enables workers to influence how technology might be adopted and then rolled out.

Working out the race between education and technology is not easy for Malaysia. We need to increase the growth of technology- and productivity-based jobs in Malaysia to increase wage levels, while also ensuring adequate quality and supply of labour to meet that demand, lest wage inequality grows out of hand. At the same time, we need to figure out our technology policy, the rules of the race as it were — automation sounds great, but what if it displaces workers? Can we not think of labour-augmenting technology instead of labour-replacing ones? Whatever the case, the choice is ours and there is every opportunity not just to have the race between technology and education increase our economic growth, but we may also make it fairer.

Nicholas Khaw is an economist and head of research at Khazanah Nasional Bhd

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