The Nobel Prize for Physics in 2021 has been awarded, according to the citation, to Syukuro Manabe, Klaus Hasselmann, and Giorgio Parisi for “groundbreaking contributions to our understanding of complex systems”, and for “the physical modelling of Earth’s climate, quantifying variability and reliably predicting global warming, and the discovery of the interplay of disorder and fluctuations in physical systems from atomic to planetary scales”. The Nobel Prize in Economics was awarded to Joshua Angrist and Guido Imbens for improving economists’ tools for understanding complex systems and to David Card for insights into wages and labour markets using those tools. Thus, the awards in both physics and economics are for contributions to methods of modelling complex systems.

Complex systems fall into three broad categories. The first is ‘engineerable complex systems’ which can be objectively understood. An engineer views a system from outside it. He improves its design and cleverly finds levers in the system to make it more efficient in converting inputs into outputs. Systems models developed at Massachusetts Institute of Technology and other engineering schools are suitable for mathematical computation because they do not include fuzzy, qualitative forces such as human emotions.

The second category of systems is ‘complex adaptive systems’. Engineers can design systems on clean sheets of paper. They can predict what the system they design will do because they can control its starting conditions. Moreover, their models are bounded; they are limited to the machine they are designing. On the other hand, processes of biological and ecological evolution don’t begin with clean sheets of paper. They are ‘path dependent’: what was there before determines what follows. Farmers must understand the potential of their land and its surroundings to improve its productivity sustainably. Moreover, natural systems are not bound tightly: what is around any subsystem affects what is in it. Plants and pests in neighbouring farms affect the conditions of a farm. The weather is an even more open system, with weather in close-by areas dynamically affecting the weather in our area. Also, what the weather will become in a few hours depends on what the weather is right now. To an engineer, the weather and climate are dynamically adaptive (and potentially chaotic) systems.

A common feature of both, engineerable complex systems and complex adaptive systems, is the exclusion of human intentionality as a primary force of change within them. Climate change has been caused by misguided human interventions. Mankind’s “little jokes” are backfiring on the survival of humans themselves. An accurate model of climate change must include human agency as a force within the model.

A hundred years ago, path-breakers shook physics out of its Newtonian paradigm that had ruled this academic discipline for two centuries. In the Newtonian world-view, the universe is a machine composed of distinct parts. Einstein, Planck, Heisenberg and Bohr took physics into the realms of relativity, uncertainty and unknowability. Whereas these path-breakers had pointed out a need to understand the relationships among various parts, including human minds, a large stream within physics continues to search for a ‘final explanation’ of the universe within the composition of its tiniest particles (wondering whether they are infinitesimal lumps, waves or strings).

A search for an ultimate explanation of how humans think, in the physics of the brain and the flows of chemicals and pulses within it, has infected the science of the mind too. A century ago, paradigm-changing winners of physics’ Nobel prizes had proven that the human mind can never fully understand reality. Because it is a very small part of a vast system that shapes it. The ways we think are formed by our histories—they are ‘path dependent’. They are also shaped by what is happening around us: such as the ‘cultures’ in which live.

The third category of systems is ‘complex self-adaptive systems’, within which human agency is a principal force. Humans have self-consciousness and a capacity for deliberate action. With human agency come complications of egos and ethics. Humans want to have power over nature and over other humans too. Even when their actions are well-intended, they are ill-informed because they do not understand the system. This is the problem with ‘scientific’ solutions for climate change based on models of only the physical and biological world.

Macro-economists’ tend to model economies as machines, with inputs and outputs, and with nature and human labour as resources, and with levers to increase economic growth by pulling these (like the cost of finance). However, complex socio-economic-ecological systems are not machines whose all-round well-being can simply be improved with a universal goal for carbon reduction and by fixing a price of carbon, for example. Policies to solve systemic problems and achieve Sustainable Development Goals must be guided by models of self-adaptive systems that factor in the egos and ethics of human beings as well as the limitations of our minds.

New insights in physics, as Nobel laureates noted a 100 years ago, had already been expressed in ancient Vedic and Buddhist knowledge traditions. Humans are only parts of complex ecological systems; human perspectives are always subjective; and it is never possible for humans to be detached observers. The time has come for another modern enlightenment founded on ancient wisdom to save the world from a scientific apocalypse.

Arun Maira is chairman, HelpAge International and author of ‘Transforming Systems: Why the World Needs a New Ethical Toolkit’