“Immune to Evidence”: How Dangerous Coronavirus Conspiracies Spread

Good Q and A that breaks down conspiratorial thinking. At the bottom is a link for the really well done “Conspiracy Theory Handbook.”

Conspiratorial videos and websites about COVID-19 are going viral. Here’s how one of the authors of “The Conspiracy Theory Handbook” says you can fight back. One big takeaway: Focus your efforts on people who can hear evidence and think rationally.

How do we prevent the spread of conspiracy theories?
By trying to inoculate the public against them. Telling the public ahead of time: Look, there are people who believe these conspiracy theories. They invent this stuff. When they invent it they exhibit these characteristics of misguided cognition. You can go through the traits we mention in our handbook, like incoherence, immunity to evidence, overriding suspicion and connecting random dots into a pattern. The best thing to do is tell the public how they can spot conspiracy theories and how they can protect themselves.

https://www.propublica.org/article/immune-to-evidence-how-dangerous-coronavirus-conspiracies-spread?utm_source=pardot&utm_medium=email&utm_campaign=majorinvestigations&utm_content=feature

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The Conspiracy Theory Handbook

Download Conspiracy Theory Handbook

Comic: Fake News Can Be Deadly. Here’s How To Spot It

Interesting cartoon that explains the dangers of fake news and how to combat it in your own mind. Unfortunately I am skeptical about the value of laying out such processes to deal with this problem. How can you stop someone from being “fooled” into believing something that they already believe? That confirms and conforms to their deeper world views? The deeper issue is motivated reasoning rather than an ignorance of how to deal with new information. All that being said, this is a fun cartoon, there is more than just this one panel featured below, click on the image for the full cartoon.

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Click on image for link to full cartoon.

Coronavirus ‘Hits All the Hot Buttons’ for How We Misjudge Risk

When you encounter a potential risk, your brain does a quick search for past experiences with it. If it can easily pull up multiple alarming memories, then your brain concludes the danger is high. But it often fails to assess whether those memories are truly representative.

A classic example is airplane crashes.

If two happen in quick succession, flying suddenly feels scarier — even if your conscious mind knows that those crashes are a statistical aberration with little bearing on the safety of your next flight.

5 Theories About Conspiracy Theories

For people living through a ruinous financial crisis or devastating climate change — or even through rapid social change that has no material effect on their lives — it can be hard to make sense of a cascade of events that seem to have no plainly evident causal chain, or even identifiable human authors. How do you account for a world we’re meant to master, but is so complex its workings seem essentially opaque?

https://nymag.com/intelligencer/2020/02/why-do-people-believe-in-conspiracy-theories.html

Humans are hardwired to dismiss facts that don’t fit their worldview

“Human cognition is inseparable from the unconscious emotional responses that go with it.”

In theory, resolving factual disputes should be relatively easy: Just present the evidence of a strong expert consensus. This approach succeeds most of the time when the issue is, say, the atomic weight of hydrogen.

But things don’t work that way when the scientific consensus presents a picture that threatens someone’s ideological worldview. In practice, it turns out that one’s political, religious, or ethnic identity quite effectively predicts one’s willingness to accept expertise on any given politicized issue.

https://www.niemanlab.org/2020/01/the-fact-checkers-dilemma-humans-are-hardwired-to-dismiss-facts-that-dont-fit-their-worldview/

An algorithm that can spot cause and effect could supercharge medical AI

How do we make better use of this piecemeal information? Computers are great at spotting patterns—but that’s just correlation. In the last few years, computer scientists have invented a handful of algorithms that can identify causal relations within single data sets. But focusing on single data sets is like looking through keyholes. What’s needed is a way to take in the whole view. 

https://www.technologyreview.com/s/615141/an-algorithm-that-can-spot-cause-and-effect-could-supercharge-medical-ai/?utm_source=newsletters