Yesterday, I found a fantastic illustration of what data literacy means in practice and how essential it is for decision making.
For the past year, we have all been watching graphs about the pandemic: number of infected, number of hospitalisations, number of deaths, number of people vaccinated... In rich countries, we have taken for granted both that authorities publish understandable data and graphs and that everyone could understand them. Data about Covid were explained on the websites of the public health services such as FHI in Norway, SPF in France and NHS in England. For sure, they were not at the cutting edge of data visualisation. Happily, journalists made a great educational effort to make data understandable to most people. But what people have really understood remains to be proven. Exponential developments are not intuitive, for example. We have heard peculiar interpretations, sometimes, or those who doubt their interpretations often remain cautious or even silent.
Still, we are lucky. It would have been a completely different story if we had lived in Argentina... The authorities only published raw data in awful tables or very basic visualized information while the situation was very complex. This made it almost impossible for people to understand how the situation was evolving. To fulfill the data-driven information white space left by the government, data savvy individuals like chemists, engineers and accountants took upon themselves to make graphs and explain them. In an interview with the French newspaper Le Monde, they talk about the difficulties in interpreting epidemiologic data, as they are not specialists. They talk about possible biases due to their own preferences for political action. One told about his dilemma when he understood that data indicated a necessity to close schools while he was himself against it. They talk about the pedagogical challenges of communicating numbers to people who are not used to read statistics and graphs. And best of all, they talk about the importance of data literacy. Having a large number of people understanding data and being able to interpret and question it, is essential. It is so easy to mix ideology when interpreting data or simply misinterpret what it says. Florencia Serale, economist and consultant at Open Data Institute, asserts that: "Data is not reserved for engineers! The first challenge is education: it is important to pass on data-related skills, starting already at school".
I think this story should inspire us to think about our own data literacy. What are we really able to read and interpret? Which level should we reach as citizens and to stay relevant in our jobs?
Please feel free to post comments and engage a discussion.
Here is the original article from Le Monde.
