Shining light on our ignorance: Data science for complex futures Cedric Le Bescont
Learning is exciting because of the paradoxical nature of knowledge: “the more we know, the more we realise the extent of our ignorance” (Grayling, 2021). As a teacher, the question about which I am passionate is how to teach ignorance? How to safely guide students at the frontier of their own knowledge? How to empower them to explore what they don’t know yet? The scientific method is arguably the most prolific way of creating knowledge. The first principle and, at the same time, the real discovery of any modern scientific inquiry, is ignorance. Science produces questions worth investigating. Galileo was the first to use mathematics to model the variability of firsthand observations. In return, technology was developed to record ever more observations to validate this model. This creative loop was responsible for the unprecedented development of technology in the past three hundred years. Today, we face a deluge of data that is challenging our capacity to make sense of the world. It is important, in my view, that students learn and apply the scientific method to big data sets so they can face the complexity of our world with confidence.
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Illuminate Research and Innovation | Edition 6 2021
APPRENTICE SCIENTISTS At school, Science is often perceived as a definitive explanation of the complexity of the world when it is an incomplete and often incoherent set of models. Even though scientific theories are proven to be very powerful in rationally gauging our ignorance, the field of investigation will remain infinite. Science can make accurate predictions about simple systems but when it comes to more complex understanding, the so-called scientific knowledge showcased in textbooks is, in fact, hypothetical. Apprentice scientists should be enticed to investigate scientific knowledge and its inherent uncertainty.
