Dealing with uncertainty

Our Earth is not flat. The Moon orbits the Earth, just as the Earth revolves around the Sun. A ball thrown high in an open field eventually falls towards the ground. An atom stripped of its electrons assumes an electric charge. Heat can only be spontaneously transferred from a warmer body to one that is cooler.

These facts are precisely known through experimental observations. They can be also accurately predicted.

Why do we exert ourselves more while ascending a staircase than when we walk downstairs? How can a rocket reach Mars? What system must we design to cool the interior of a home in summer and heat it in winter? How much steel is required to build a resilient bridge? Why do metals corrode? How long will it be before all icebergs melt? Is there a plausible method to print cells, tissue and organs in future.

Some of these questions can be answered with certainty. However, other facts, such as how climate change will impact icebergs, are more uncertain. Whether facts are exact or tentative, we can build models to understand them.

Models are representations of reality. Some models are precise while others are less exact. The purpose of using a model is multifold. It could be employed to accurately describe what could occur, explain how a process will unfold, predict an outcome, or design a product. Model results can be entirely certain, or tentative or uncertain.

Uncertainty should not be misconstrued as wrongness.  Often, the more complex a system is, not all of its conditions are well known. This lack of complete information about a problem or phenomenon prompts the development of uncertain models.

Consider climate change. We are well aware of the physics of greenhouse gases like carbon dioxide and methane, and how they enter the atmosphere. We understand the water cycle that is driven by the Sun’s energy and its influence on the weather. However, we do not yet have precise models for climate change since the exact linkages between all of its underlying influences are not yet fully known.

Because the impact and cost of climate change on humanity is expected to be particularly acute, it has become necessary to use uncertain scientific models to develop public policy. Otherwise, the consequences of inaction could be catastrophic for our world.

Models can be imprecise not only due to the poor quality of information on which they are based, but also because of the modeller’s opinion and experiential learning. The Indian parable about six blind men separately touching the different sides of an elephant is instructive. After each man feels a different part, such as an ear or a tusk, all six are in complete disagreement about the elephant’s form and morphology.

As the story shows, factual knowledge and logic can be inadequate while framing a complex problem or model. Here, the philosopher Martha Nussbaum notes that citizens cannot relate to the world around them by factual knowledge alone. She asks us to have “the ability to be an intelligent reader of another person’s story.”

This offers a way forward through scientific crowdsourcing to develop complex models of lower uncertainly. Doing so, would improve our “narrative imagination,” which is our ability to know what it’s like to be in someone else’s shoes, seeing the world through another person’s eyes.

Professor Nussbaum is more concerned with law, citizenship and democracy and I with issues related to science, engineering and technology. Nevertheless, it is possible to construe her approach as advocacy for interdisciplinary undertakings that seek to understand complex scientific phenomena and solve intricate engineering problems.

See the world through another scientist’s or engineer’s eyes, walk in their shoes. Learn the languages of their disciplines and thus become scientifically and technically multilingual.


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