Policymakers need to stop being drawn to the myth of the ‘quick fix’ and focus on long-term and sustained development of research and development as an ecosystem if they really want to solve those wicked problems, Lesley Seebeck writes.
Recent debates over priorities in research and development, over university research, and even the plundering of ideas from universities – Australian and others – by the Chinese government suggest confusion over the nature of R&D and the development of science and technology.
We live in an age of instant gratification, where the fast and the immediate tend to grab people’s attention. And so we’re often misled by a skewed view that technology is easy: start with a bright idea, add a little Silicon Valley, stir, and magic happens.
That’s suited a number of players. Silicon Valley propagates the myth of the heroic founder – almost without exception male – who has a vision and disrupts the normal to create a new world. Those companies are driven by incentives other than the deep, heavy lifting needed for good science and technology, specifically consumer needs and desires.
That’s a massive contrast to the slow, careful, patient work undertaken in government and university labs across the country, and on which much of Silicon Valley’s own products and services are built.
Politicians, too, are strongly attracted to tales of heroic endeavour by the quick, preferably cheap, fix to what are difficult, wicked problems. They’re an easy mark for those who promise fast solutions. But by focusing on the ‘tip of the spear’, they neglect the haft, the weight and balance, and the effort needed to give that tip power when applied.
Reliance on those narratives promotes immediacy, linearity, and single-point solutions—and does untold damage to public policy and national security. The reality is very different.
First, research and development is slow. It has long lead times – training people in complex fields such as mathematics, computer science, physics, and biology as well as anthropology, economics, philosophy, and psychology takes time and, importantly, seasoning. There is no app for that.
Good research may take years, as hypotheses are formed and tested, and new insights gained. Failure is fundamental to progress – something that does not sit well with the popular narrative but is intrinsic to the scientific method. One research proposal does not a capability make.
Unsurprisingly, these are understandings and capabilities that reward long-term thinking and investment. We should not be looking entirely to industry to fund this long, slow, deep research – that’s within the realm of government, which is better placed to bear the risks of such effort. As Mariana Mazzucato argues, such long-term investment in basic capability requires public, not private, financing.
Second, the outcome of deep R&D is not a linear progression to a commercial product or national capability. Despite the myth, it’s a messy process of trial and error, refinement, mixing and emergence.
Similarly, it is hard to point to a single product and draw a straight line back in time to a single R&D project. As Brian Arthur points out, emergent technologies result from the accumulation, interaction and recombination of often disparate sets of earlier technologies.
Further, the development of science and technology, and R&D, is iterative, and tends to obey the Matthew Effect: the more you do, the better you get and the more you will attract others who want to do the same. We need to build and grow capability, not simply fund projects.
Similarly, careers are not linear ‘pipelines’ – that’s an unhelpful metaphor. We need people with good technical depth who are able to bridge into other disciplines, which may be economics or fine arts. Interesting things happen when domains intersect, and diversity brings insights.
To build great science and technology, we need creative individuals who are able to see opportunities across a breadth of possibility.
Third, there are no single-point ‘silver bullets’. Research and development must be understood as an ecosystem. Good research, just like the non-linearity of technological development and progress, has multiple, interconnected dependencies over differing domains and time scales.
That means appreciating the value of the ‘adjacent possible’. There are countless examples of where a researcher or post-doc, pursuing one research question, originated a new insight or technique that generates value in a range of other applications.
That’s a strength of the successful US Defense Applied Research Projects Agency (DARPA). Yes, DARPA expects research it funds to apply at some point to national security and the military. But it funds a wide range of programs that may or may not have direct immediate applications, while training a broad range of skills. When you don’t know what likely outcomes are, what technologies and ideas will beget new technologies and ideas, the best strategy is to explore widely.
An ecosystem approach also means giving the smart, creative, technically-proficient people the support and infrastructure they need. Those supports are more than research assistants and students. They include connectors, who can see the inter-relationships across research silos, and enjoy access to sources of funding and entrepreneurs. It requires experienced managers—a competitive strength of Silicon Valley, incidentally – and a level of sophistication in the understanding of that ecosystem by politicians and bureaucrats.
A nation’s R&D effort is a leading indicator of how seriously a nation takes national security. It is a long-term investment into the nation’s ability to shape its own path in an increasingly contested, technologically-driven world.
Australia’s R&D expenditure is in decline. At 1.88 per cent of GDP in 2015-16, it is well below that of the OECD (2.55 per cent, 2015), East Asian nations (2.46 per cent, 2015) and even the world average (2.23 per cent, 2015), based on World Bank data.
An approach that focuses government efforts on the immediate and an overly narrow definition of research will fail; it will weaken an already emaciated and diffused capability. Rebadging programs in a declining overall effort won’t pass muster, nor will simply constraining Chinese access to Australian R&D.
Instead, the government should be increasing its investment in R&D and in universities, and helping future talent to realise their aspirations in those fields, whether STEM or social science. It needs to understand the time needed to build research, the value of the adjacent possible, and be prepared to invest in building healthy ecosystems that nurture that future capability.