Measuring the Infinite

This piece is an abridged version of an original article which appeared in Dimensions, the in-house magazine of IHDP (International Human Dimensions Programme on Global Environmental Change). The original article is available to download.

Once upon a time there lived a princess who loved indicators. She measured, monitored and treasured every resource in her kingdom. When it came time for the princess to get married, she set a strange condition for her husband to be: she would marry the man who could measure the lake in front of her palace more accurately than anyone else, using only a long rope as a measuring instrument. The physicists, mathematicians and economists all rejoiced, already running models in their heads. Little did they know, they were about to receive a profound lesson in what it means to measure something.

— • —

In 1935, the great inventor and visionary Nikola Tesla said in an interview with Liberty Magazine:

“[In the] twenty-first century… it will be more glorious to fight against ignorance than to die on the field of battle.”

Most noted intellectuals of that time envisaged a future in which intelligence and the pursuit of knowledge would be cherished above all else.

That unfortunately is not the world we have built for ourselves. Today, governments are chosen and rejected not on the basis of how they enhance the human potential of their populace, but on how much “growth” they achieve. All this, while the defining – some would say existential – problem of our civilization, global climate change, continues to be ignored.

If Tesla were alive today, he would say that we are not measuring the progress of our society in the right way. To put it in development jargon, we have an indicator problem. The indicator problem spreads across nations, continents and governing systems, with no consensus emerging at any level of governance.

This obsession with GDP growth started with the post-war reconstruction of Europe. To measure progress on that front, GDP was a good enough indicator. But it wasn’t long before the hidden costs of GDP-oriented development started coming to the fore – primarily the costs to the environment and finite resources of the planet we called home.

GDP was criticized for its myopic focus on economic activity as a measure of well-being. A major development towards reform on that front was the publication and release of the Human Development Index (HDI) in 1990, which included well-being measures such as literacy rates and life-expectancy in its analysis of development status of a nation.

Efforts to define alternative indicators that included externalities and estimated shadow costs for things in the commons were also set in motion. Examples include the comprehensive wealth accounts published by the World Bank, and more recently the Inclusive Wealth Index (IWI) developed by the International Human Development Programme (IHDP) and the United Nations Environment Programme (UNEP). The IWI estimates the increase in a nation’s inclusive wealth by subtracting the cost of exhaustible natural resource consumption and adding human capital, among other considerations.

While the use of well-being indicators such as HDI and inclusive wealth indicators such as IWI has gained ground in policy analysis, their use in practical policy development continues to be limited, with most governments of the world continuing to focus on GDP growth as a measure of success. One reason for that is that – just like GDP – indicators like IWI and HDI do not take into account the transitory nature of human need. In different states of well-being, we need different things to make us happy. Any development indicator aspiring for universal appeal must have parameters built in to capture the transitory nature of human need. What has been missing is an attempt at a universal indicator which takes into account this evolution of needs from the physical, “hard” needs of food security and so on, to “softer” needs such as knowledge and social connectivity. A universal indicator with the potential to replace GDP must give weight to all considerations of development.

— • —

The news of the princess’ contest spread far and wide, and mathematicians, physicists, naturalists, economists and all manner of sages came from all over the world. Finally an old philosopher came along. He cut the rope into smaller pieces and, putting them end to end, arrived at a measure of the lake’s perimeter which took into account all the bends around the edges. And then he said, “I can keep doing this forever, cutting the rope into smaller pieces measuring the circumference more and more accurately.  Since the rope can be cut into an infinitely small length, the circumference and hence the size of this lake, is in fact infinite.”

— • —

Human societies, economies, cities, nation states and environments are all complex systems. Indicators, like the rope in our fable, are by their very nature reductionist. It is not the lake that they measure but an idea of the lake; that idea, very much dependent on the nature of the instrument of measurement. Like fractals, complex systems have an infinitude to them which no indicator ever will perhaps truly capture, but we must continue to refine our indicators and our measurements to capture more and more of the complexity of the system we are trying to measure.

We already have some complexity-based indicators, such as the economic complexity index, and their detectors, but what such indicators show for certain is the folly of continuing to measure the lake that is the development of complex human societies with the rope-like linear instrument that is GDP.

In due time, we may come to a stage where we will be able to identify the resilience – or lack-thereof – of complex systems, perhaps through analysis of the scaling of elements within the system. But until then, it would do us well to never forget that an indicator, no matter how good, presents only a part of a part of the picture and in focusing on one number alone, be it GDP, IWI or HDI, we risk missing some important variable, and that could turn out to be the most important variable of them all.