We are presented with a constant and ever increasing flow of information and data, in work and at home. Knowing what to believe and what to dismiss can be difficult and confusing.
The Covid-19 pandemic has illustrated these challenges for us all. You can be forgiven for feeling lost, most of us do.
So what can you learn from this example so that you can better understand information and data you see and use everyday?
Fear of the unknown source
The pandemic has laid bare what happens when the unknown strikes. A new virus which causes illness and death in a way that we at first didn’t understand and are only slowly beginning to get to grips with.
However, as we collectively search for ways to deal with the virus, to balance its health effects and the wider impacts on social and economic life, the emergence of the virus has witnessed a pandemic of information.
Over 12,000 scientific papers alone were published in the first 6 months of the emerging pandemic up to May 2020. Our understanding of the virus remains at best opaque. Few of these articles will provide definitive conclusions with such speed yet together with (un)informed commentary create a lot of noise around the problem.
Which of these articles provide valuable insights and which are merely conjecture with the circumstantial evidence?
Collection and interpretation
For Covid-19 the full picture remains unclear. Bits of information are constantly being pulled together as and when they are available.
The responsible information user couches conclusions with caveats and caution - Professor Sarah Gilbert who is leading the Oxford University Vaccine trials is a excellent example. But in a world of media with infinite column inches that caution can too often be lost.
A recent report that the second wave of infections might levelling off offers a good example. This story was based on the results of 3 separate studies each of which pointed to a similar conclusion. Yet the same article highlights the dismissive tone of other scientists whose opinion (based on different data one assumes though without reference) is the opposite. So is it the methods used to collect the data, the data itself or the judgements made in conclusion that are contentious?
How important is the context?
Objective v subjective
Through this pandemic we have been “guided by science”. But as much as the political decisions being made are a balance of judgement, the scientific approach that generates the information can be eroded by the way the conclusions of studies are employed. Research is incentivised, monetised and politicised (with a small as well as a capital P). As these factors creep in the reliability of the conclusions, the arguments and the stories being told becomes more subjective.
This is not written as a criticism of any one set of actors during the Covid-19 pandemic. However this situation we are in today is an illustration of the problems we all face on a daily basis in trying to understand and use the constant flows of data and information put in front of us.
“Data literacy” is critical for interpreting the stories we are told and the way we tell our stories to others.
How to navigate the flow
So how can you start to improve your navigation of this flow and understand the reliability and accuracy of claims made?
Whenever you see information or data ask the following 3 questions:
- Where does the evidence come from and how trustworthy is the source?
- Can you see and trust how the information was collected?
- Do the conclusions match both the data and the context?
Combined, these elements provide a greater clarity, insight and context to what is presented.
Taking a step back to objectively consider the evidence and story before you draw a conclusion can not only limit the panic but enable you to get a better grip on the response you need to make.
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