This article is part of the Forum Network series on Digitalisation
Some aspects of the ongoing production transformation are receiving considerable coverage in mainstream media, particularly the promises and perils of automation. But the debate less frequently touches on the pivotal role of science and research. Microelectronics, advanced robotics, synthetic biology, new materials and nanotechnology, among many others, have arisen because of advances in scientific knowledge and instrumentation.
Public support is vital for basic and applied research
Publicly financed research, basic and applied, has been critical. For decades, for example, public funding has supported progress in Artifical Intelligence (AI), to the point where AI today attracts huge private investment (Google, for instance, paid a reported £400 million in 2014 to purchase the AI start-up Deep Mind) and has growing uses in production. Indeed, the complexity of many emerging production technologies exceeds the research capacities of even the largest individual firms, and requires a spectrum of public-private research partnerships.
Artificial intelligence startups see record high in deals and funding
Source: CB Insights - The 2016 AI Recap
In a fiscal climate where Ministries responsible for science and research are often pressed to justify their spending, it is relevant to note that many advances have come from basic science, where the practical applications were not initially foreseen. For example, Clustered Regularly Interspaced Short Palindromic Repeat associated protein 9 (CRISPR-Cas9), was nominated by Science as the “Breakthrough of 2015”. This technology can be traced to an accidental discovery during research on the Escherichia coli (E.coli) gene in the late 1980s. CRISPR-Cas9 permits changes in a DNA sequence at precise locations on a chromosome. This makes the design and construction of organisms with desired traits easier and cheaper. The use of CRISPR-Cas9 has spread quickly across industries and fields. In a similarly fortuitous way (even if less impactful than CRISPR-Cas9), greater understanding of the principles of biological self-construction is finding unexpected application in bottom-up intelligent self-assembly of devices.
Not all countries or companies can be major investors in research. For many, the diffusion and use of technology must be the primary objectives. But countries with greater research capabilities could enjoy first-mover advantages in a number of industries. As the OECD report shows, the invention of technologies related to data-driven innovation is concentrated in only a few countries (with the United States leading in terms of the number of filed patents, followed by Canada, France, Germany, Korea, Japan and the United Kingdom, as well as China).
A key issue is the scale of public support for research, which has fallen in recent years in some OECD countries. Not only does public research expand knowledge, enlarging opportunities for innovation, it often supports private-sector innovation and absorption of technology. For instance, researchers and students move between public and private institutions and bring their knowledge and know-how with them. While debates exist over the merits of basic versus applied research, for countries of different sizes and research capabilities, declining commitment to public research would be detrimental to competitive success for individual countries, and undermine progress globally. Indeed, in the United States, prominent figures in the technology sector have recently argued for more federal spending on basic R&D for AI.
Addressing multidisciplinary challenges
Many policy choices determine the strength of science and research systems and their impacts on production. One issue, stressed in the new publication, is that many of the research challenges critical for future production are multidisciplinary. Many research challenges will need to draw on traditionally separate manufacturing-related research fields (such as advanced materials, production tools, ICT, and operations management). And many government-funded research institutions and programmes have been limited to carrying out research, without the freedom to adopt complementary innovation activities or connect to other innovation actors.
As a result, government-funded research institutions and programmes are sometimes unable to bring together the right combination of capabilities, partners and facilities to address challenges of technological convergence and the eventual scaling-up of technological innovations. Manufacturing research programmes need to create close linkages between key innovation system actors, have more explicit requirements for interdisciplinary and inter-institutional collaborations, and provide innovation infrastructure (tools, enabling technologies and facilities) to support convergence and scale-up.
GOT A FEW MORE MINUTES?
OECD (2017), The Next Production Revolution: Implications for Governments and Business, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264271036-en
OECD (2016), OECD Science, Technology and Innovation Outlook 2016, OECD Publishing, Paris. http://dx.doi.org/10.1787/sti_in_outlook-2016-en
OECD (2017), Gross domestic spending on R&D (indicator). doi: 10.1787/d8b068b4-en (Accessed on 29 May 2017)
ABOUT THE AUTHOR
Alistair Nolan is a Senior Policy Analyst in the OECD Directorate for Science, Technology and Innovation, where he focuses on public policies to foster innovation. He managed the publication of the The Next Production Revolution report, which examines the impacts of recent technologies on production and their policy implications.