In my last article in this column titled “Realistic science fiction scenarios and the questions they hold for society” (Issue 1578, June 9), I wrote about three kinds of up-and-coming technologies with the potential to, with some slight exaggeration, revolutionise life on earth. These are genetic modification to reverse ageing; biomimicry in battling climate change; and asteroid mining in shifting resource extraction beyond our planet. If indeed these technologies are as revolutionary as I imagine them to be, then countries are likely to race to achieve some form of technological dominance in these spaces to boost their own economic dominance.
This has been the core theme around a concept in international relations called the Leading Sector perspective, which argues that during major technological shifts, the global balance of economic power — hence potential monopoly power — tips towards “the states which were the first to introduce the most important innovations”.
In particular, the innovations that any global power should want to control are “General Purpose Technologies”. GPTs are generally defined as powerful innovations that spread across many industries, continuously improve and enable widespread productivity and economic transformation. Examples from history typically include the steam engine, which enabled mechanised production; electricity, which powers cities and nations; and computers (kind of goes without saying); and sometimes include, more debatably, the internal combustion engine and semiconductors.
The Leading Sector view argues that for a country to become a dominant power, it needs to be the creator and first mover of these GPTs. This perspective explains why artificial intelligence, a potential GPT, is so hotly contested by today’s dominant powers, namely the US and China. For a middle-income country such as Malaysia, where we also aspire to some form of technological dominance to strengthen our resilience, how realistic is it for us to develop a GPT of our own?
It is an important question for technology and industrial policy. We have a pretty good track record in the semiconductor industry, but to what extent should we allocate scarce capital expenditure to further develop our semiconductor industry, given that it is such a winner-takes-all industry? The profit pools are dominated by global giants such as Taiwan Semiconductor Manufacturing Co Ltd in fabrication, ASML Holding in equipment and NVIDIA Corp in design. Should we maybe reallocate to find the next “GPT” (let’s say, biomimicry or asteroid mining) and try to be the first leader there?
There is an alternative pathway. Jeffrey Ding, a professor of political science at George Washington University, writes, in his book, Technology and the Rise of Great Powers, that it is not being the first to innovate that leads countries to be dominant technologically; it is how well those countries diffuse and adopt these GPTs across a wide range of economic sectors. Ding provides historical examples. During the Industrial Revolution, Britain’s take-off relative to competitor nations happened only in the 1820s after technology was diffused, despite the major innovations in textile production, steam engine and iron production taking place in the late 1700s. In the late 19th century, Germany became an industrial power by dominating the chemical industry, as represented by its control of more than 90% of global production of synthetic dyes. However, the US achieved leadership in chemicals because it was far more effective in broadening the base of chemical engineering talent and coordinating information flows between the scientific breakthroughs and industrial applications.
Ding summarises his core argument brilliantly. He writes: “In sum, industrial competition among great powers is not a sprint to determine which one can create the most brilliant Silicon Valley; it is a marathon won by the country that can cultivate the closest connections between its Silicon Valleys and its Iowa Citys.” In the Malaysian context, this is the equivalent of being able to cultivate the closest connection between Penang’s advanced manufacturing industrial base and smaller cities such as Tawau.
A more realistic goal for Malaysia is not necessarily to be a “great power” per se, but certainly a middle power — we can take the definition of the European Council on Foreign Relations, where a middle power is simply defined as a country willing to take a bigger role in global issues, which fits Malaysia well. And to be that middle power, supported by our technological growth, maybe we do not need to be the first to invent, but can we be the first to diffuse new technologies across industries, not just for domestic consumption but also for exporting to global markets. Can we just be the most ready?
Ding’s book highlights “Skill Infrastructure” as the key to diffusion, emphasising the role of education and training systems that broaden the base of engineering skills linked to a particular GPT. Malaysia is already attempting this by doubling down on STEM education as well as TVET education in preparing for technicians and engineers, particularly to serve our semiconductor industry. But I do wonder whether we could do with a mindset shift — one that is less “depth-based”, where we focus less on gaining dominance in a particular industry, to one that is more “breadth-based”, where we focus more on transferable engineering skills, capable of imitation and cross-sector application. As Ding argues, “Divergences in the long-term economic growth of countries at the technological frontier are shaped more by imitation than innovation.”
Having broad engineering capabilities alone is a necessary, but certainly insufficient, condition for broad diffusion. If Malaysia — or any country — is to be a leader in diffusion, it requires other institutional mechanisms such as standards settings — usually very difficult, as it requires significant government coordination, systematic intellectual property regimes that reward both original and adaptive innovation, procurement policies and incumbent firms realising the need to adopt new technologies (which is not always a given), among others.
This is not to say that we should completely avoid attempts to innovate and be a first mover in a new GPT. If we believe that, say, asteroid mining is a real GPT in the years to come, it is worth spending resources there as well. After all, there may be sectors in which diffusion alone is insufficient and much of diffusion is also path-dependent, based on upstream innovation. It is just that, for a middle power such as Malaysia, we may get far more bang for our buck by focusing on how well we diffuse technology broadly, as opposed to how well we invent the next big thing. Borrowing a concept from Khazanah chief investment officer Hisham Hamdan, we could consider thinking of it in a 70:20:10 way — where 70% of our time is focused on mining our core and focusing on broad-based diffusion applications, 20% is on expanding to adjacencies such as the National Semiconductor Strategy’s attempts to move Malaysia more into the IC design space, and the final 10% is for moonshots and chasing the next GPT.