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Use data sharing to increase trust in our institutions

Daphne van Hesteren

Can we trust the data that is shared with us? Or more specifically, can we trust the interpretations of data that is shared with us? With companies becoming increasingly dependent on data, trusting data-driven conclusions is more important than ever1. Companies, institutions and the media should find a conclusion that fits the data, not the other way around.

As Mark Twain already pointed out in 1854, statistics don’t lie, but liars use statistics2. This phrase is could not be more accurate today. Although analysts have the best intentions at heart, it turns out that people can draw different conclusions from one dataset. Due to past mistakes, there are groups of people that will always criticise and create disbelief in institutional decisions. For example, the different information that is being spread about the effect of wearing face masks in our combat against the COVID-19 pandemic. More than 50 countries, such as France, Germany and Spain3, have obligated the use of wearing a face mask in public spaces; however, nations such as the Netherlands argue that there is not enough evidence to support the effect of the measure4. Thus, though it may feel frustrating that people ignore the measures implemented by the government, it is hard to trust the data and institutions when different websites, or even government’s5, conclude and recommend something else.

I think that data sharing could take away part of the distrust in (and possibly between) governments, individuals, the media and other public institutions. If someone does not agree with a certain conclusion, the initial analysis should be openly available and completely reproduceable so that everyone can draw their own conclusions.

This poses the question how can we ensure that the shared data is trustworthy, and most importantly interpreted correctly? Share your thoughts with us on the SCDS forum!

Use data sharing to increase trust in our institutions
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