This post is part of the conference on "Truth in numbers: the role of data in a world of fact, fiction and everything in between"

truth

The latest scandal over the misuse of private Facebook data has alerted the general public to the fact that when it comes to using a social media service, there is no such thing as a free lunch. The business models of the “data refineries” , such as Facebook, Google, etc., involve collecting data from users and selling them to advertisers who mash that data up with other sources to target us with tailor-made ads. But this is only the tip of the iceberg: we trust social media data without realising that they are not in fact representative – they speak more to our opinions than being objective facts. Attention has become a prime asset and this fundamentally changes our relationship to numbers.  

For a start, we are flooded by figures, numbers and statistics, and it is challenging for us to discern which are fake and which we should pay attention to. We are forced to become the judge of which numbers can be trusted and which cannot – yet we lack the tools we need to do this on our own. What we do is follow those we trust – usually those who think like us – to guide us in what to believe. Distinguishing feelings from facts has become part of this game, though we end up putting more store in fake and attention-grabbing information than in what is actually true, often because it is less captivating. 

We are easy prey for manipulation, and manipulators the world over know it. They have realised the potential of spreading dubious numbers, statistical propaganda and disinformation. One good example is the 350 million pound per week gain promised by the Brexit campaigners if the UK leaves the EU. Opportunistic narratives such as these, and not the facts, are becoming the basis for debate, opinon formation and even legislation.     

What can be done to address the proliferation of statistical humbug, misused data and propaganda?

Identifying and overcoming manipulation requires a concerted effort by our governments and us as citizens. We could start by valuing more highly the production of reliable, comparable and high-quality data – those which meet international standards – as a necessary input to democracy. We should provide our national statistical offices with the resources and equipment they need to play their role as standard setter and co-ordinator across the national statistical system. Governments also need to ensure that their national statistical office is free from political influence so that citizens can trust them as guardians of the facts. 

Our national statistical offices should transform themselves from mere technical entities to institutions that engage actively in data dissemination and keep in regular contact with citizens. Switzerland shows how this can be done, by bringing together various stakeholders from politics, civil society and science to discuss issues affecting the country. This dialogue is a necessary part of the mutual construction process of modern societies, in which quality statistics are an accepted requirement for decisions based on facts and evidence.

Yet none of these efforts would be useful if we do not learn how to distill the truth from the flood of data and statistics that surround us. We need to become data literate.  In the end it's the user who decides to trust a number or not. Our public institutions could start addressing this need for data-literate citizens by discussing and engaging with all concerned to decide the best way forward.

Finally, public authorities need to start thinking hard how best to regulate the data and information market and strengthen the rights of users. It is high time that users claimed ownership of their data, took back their digital authority and renegotiated the conditions of their digital citizenship on social media.  A promising step forward is the EU’s Data Protection Regulation, which from May 2018 intends to protect the users of social media, rather than the social media companies.

At the end of the day, we are all like gamblers in a casino – if nothing changes we will inevitably lose. Either we start changing the model or we stop playing.

Authors:

Prof. Vincent Hendricks, Professor of Formal Philosophy, University of Copenhagen

Dr. Johannes Jütting, Manager, Partnership in Statistics for Development in the 21st Century (PARIS21)

 

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