Human knowledge of viruses and human bodies has reached the molecular and even atomic scale, yet the past few months has revealed how vulnerable we remain to pandemics.
This, in turn, illustrates that for all of humanity’s progress in understanding nature and humanity itself over the past centuries, some of the scientific problems and global challenges that have long vexed humanity remain unsolved as we enter the third decade of the 21st century.
One of the key questions we need to address is what transformational changes are needed in research and education to drive breakthroughs in these areas. People form different views from different perspectives. For example, some would argue that artificial intelligence and big data should be prioritised. In my view, though, even greater returns would result from a systemic evaluation of the logic and landscape of human knowledge, identifying the missing links and better exploring how science and technology should interact.
It may not be easy to locate a shared or common problem if we study any discipline or area in isolation. However, by taking a whole-system approach, comparing and analysing different disciplines and technological fields, we can easily identify two characteristics of the existing knowledge system. The first is that the logic and landscape of our knowledge system mirror those of the natural world in that they both contain multiple levels, each of which is multi-scale. Complexity always occurs at the intermediate mesoscale, between the elemental and systemic scales.
These two insights are the key to a more efficient future innovation system, which will break the traditional disciplinary constraints and effectively promote transdisciplinarity and the convergence of knowledge and application. Such a paradigm shift in research and education will help us better understand why changes at the elementary scale have a fundamental impact on the system, revealing the common principles of complexity at different levels.
This shift requires changes in research focus, methodology and domains. Regarding the first, scientific scrutiny should be extended from elementary behaviour and system function to also encompass their interaction. That is, it should extend from static states in equilibrium to dynamic structures, and from local phenomena to system behaviour.
Research methodology, meanwhile, should move beyond traditional theories towards complex science, and from a standard, single-scale analysis to a multiscale structure. It should gradually shift from a fragmented, multi-level disciplinary approach to a transdisciplinary pursuit of integrated knowledge based on universal principles. And traditional qualitative analysis should make way to quantitative prediction, simulated computing to virtual reality and data-processing to artificial intelligence.
I do not deny the importance of AI and big data, but I do not think they will be enough by themselves. In fact, I would argue that the development of AI itself also needs urgently to seek the common principle of complexity.
All of this also has big implications for the education system. The fundamental task of education is not only to preserve and impart knowledge but also to guide future generations to learn the logic and landscape of the knowledge system, thus expanding knowledge frontiers while enhancing the problem-solving capability of humankind.
The current disciplinary structure appears to be set in stone, but its siloed nature – coupled with human and random factors along the way – is responsible for the incomplete, fractured and repetitious nature of our current knowledge system. It has significantly undermined the effectiveness of education and created a gap between education and scientific research.
Therefore, the education system should be mapped according to the logic and landscape of knowledge system. This would allow the common principles, disciplinary knowledge and application fields to be balanced, broadening the knowledge horizon and disseminating the most needed and comprehensive knowledge in the most effective manner.
The paradigm shift I describe will not occur naturally: there is too much intellectual inertia in the scientific and educational communities. It will only come about if there is a high-level global effort to promote a consensus that this is what must happen. I believe that a closer integration of research and education is already a shared ambition among the global scientific community. But we must match words with actions. Funding agencies, international scientific organisations and bilateral or multilateral cooperative protocols should join forces to promote coordination in this respect.
The current Covid-19 pandemic has exposed our lack of knowledge about both the transmission and infection mechanisms of the virus and the complex, multi-level ways in which the immune system responds to them. Harnessing global wisdom and resources via a new paradigm of understanding and investigation will put us in a much better position to respond to this and other challenges to humankind over the next century.
Author Bio: Jinghai Li is president of the National Natural Science Foundation of China.