What can we do to overcome misinformation and build trust?

The past 16 months have been burdened by fears and uncertainties on a global scale in which both data-driven insights and misinformation flourished.

According to a recent article in Fortune, experts who study misinformation say several changes must be made to combat the rise of data being unintentionally misused or misinterpreted.

One of the suggestions made in it was the need to increase public education efforts to help people distinguish between real and fake news. By empowering people to share and engage with data, we provided a critical service to combat intentionally misleading claims and rally our communities to work together.

But the process from data to action is not seamless.

How would you create platforms to distribute both data and visualizations widely? What kinds of public dashboards should we work towards in the near future?

This topic, unfortunately, is laden with heavy political and historical context that are inseparable from the one and only truth out there: we don’t know what’s true and what’s not.

From the days when everyone believed the world was flat and a few were persecuted for saying it was round, to modern day countries whose news is so perfectly controlled that its citizens believe their leader is a god, misinformation has never just been so simple as true vs false.

It’s also propaganda, for political gain, for financial gain, and for power gain, and it goes in both directions - sometimes it’s unsubstantiated claims about health from those peddling snake oil, sometimes it’s unsubstantiated claims about those trying to reveal the truth to us.

It always comes down to this: we don’t know.

In recent years, the world has seen dozens of examples of things called crazy or conspiracy theory turn out to be completely accurate, for example.

So, the only useful data analysis I can think of is an aggregator - organized into hierarchies of categories for easy organization, an aggregator that includes every theory that exists and its connected data in the form of unfiltered references including news articles, studies, expert whitepapers, blogs, wikipedia articles, random musings, etc. On this aggregator, someone wondering if the world is flat can review all the related information about it that has been collected, and make their own decision.

But beyond that, what kind of objective approach is there that doesn’t inadvertently hide possible truths? Worse, how can we know that trying to hide “fake news” isn’t actually hiding the truth? I fear we can’t, and I don’t want the responsibility to try to design something that would tell everyone else what’s true or not.


Absolutely agree with @ken.

Recent events have shown that ‘independent fact checkers’ and censoring done by social media platforms may not be the truth. The only way is to allow everyone to discuss any topic and give any opinion and let people make up their own minds.


That’s an interesting perspective you’ve added, Ken. Something to think about! I like your idea of aggregation. Makes sense!

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Part of our data discussions at work have been including confirmation bias. Ken mentioned that we just don’t know and it’s not as simple as true vs. false and I agree. Truth is generally found in the middle. It’s not always that facts are correct or incorrect, it’s that our interpretations of them are. We talk a lot about this idea of confirmation bias and how it’s very easy to only look for facts and interpretations that confirm what we already think we know. I like to tell people “I can make the data say whatever you want. It’s not that it’s not accurate. It’s just only accurate within the parameters set.” I think that challenging how we consume and process data is a big step in overcoming misinformation


I like how you say that truth is generally found in the middle. Very interesting!

I like to encourage people to “prove themselves wrong” when faced with misinformation. Are you certain something a candidate is telling you is true? Find as many factual things as you can to prove yourself (and them) wrong. Instead of looking for information to prove yourself right - which is easier to do because of confirmation bias - challenge yourself to prove yourself wrong. The point isn’t necessarily even to actually prove yourself wrong, it’s to open your mind up to the possibility of something else being true. While doing this research, you’ll probably find a mix of things, and like Steffany said, the truth you were certain of is probably somewhere inbetween being completely accurate and completely false. Finding WHERE it is along that line is where you find truth. I don’t like referring to it as “in the middle” so much as “in between”, because “in the middle” implies that everything is half true, which it isn’t always. If the extreme ends of the specturm are 100% true and 100% false, you can find the actual truth anywhere in between - 85% true, etc.

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