Category: Misinformation 101

Have you ever seen someone in a lab coat online making bold health claims?🧑‍⚕️

Whether that person is a doctor or not, the coat makes them appear like an authority on the subject. That’s a classic example of the appeal to authority fallacy (a.k.a. an error in reasoning (1)).

It happens when we accept a claim as true just because an “authority” says so, instead of looking at the actual evidence. That authority could be a celebrity, a “doctor,” or someone who simply looks credible (2,3).

The problem?
Not all authorities are experts. And not all experts speak within their domain of expertise. Someone can be an epidemiologist studying diseases in seal colonies, but that doesn’t make them an expert on COVID-19 in humans. And even real experts can be wrong. What makes a claim reliable isn’t just who says it, but the evidence behind it (4,5,6). 

This tactic works because we naturally trust people who seem knowledgeable or familiar. On social media, that might mean wearing a lab coat, using technical language, or saying “studies show…” without proof.

And it doesn’t just affect people. One recent study found that AI systems were more likely to accept false health info when it was written like a doctor’s note (7).

Think you can always spot an AI image? Think again. It is getting harder.

Older clues like weird hands or uneven eyes are becoming less common with newer AI tools. That means we cannot rely on visuals alone.

Here are a few smarter ways to check:

Look for the original source 🔎
Who posted the image first? Are they a trustworthy source?

Check other sources 📰
Are other outlets reporting the same story or showing the same image? If a major event really happened, multiple sources should be talking about it.

Pause if it triggers strong emotions 😡
Posts that make you feel shocked, angry, or excited are more likely to spread misinformation.

Use fact-checking tools 🧰
Sites like Snopes, FactCheck.org, PolitiFact, and Reuters Fact Check can help verify viral claims. You can also always ask us or use MediaSmarts custom search engine that scans several of the most popular fact checker websites we just mentioned and more! 

You can still treat suspicious visuals as red flags (one extra finger is still a good cue the video is AI generated), but are not reliable proof anymore. AI images do not always look odd, and real photos can look unusual. 

While there is absolutely no evidence that vaccines cause autism, it remains one of the most persistent myths surrounding vaccines to date. 

But where did this myth begin? Who started it? Finally, why is the claim that vaccines cause autism completely unfounded? 

Answers to those questions on this factsheet

The clinical definition of autism is “a lifelong neurodevelopmental condition that affects the way a person communicates and relates to people and the world around them”. All autistic lives are equal in worth to any other life. Autism is not a disease or an illness to be treated or cured. All autistic lives matter.

This resource was made in collaboration with @Immunize.ca and @camhnews.

Have you heard of “The Trolley Problem”?

Five people are tied to a train track. A train is coming. You can pull a lever to divert it to another track, but there is one person tied there too.

What do you do?

Option A: Do nothing. Five people die.
Option B: Pull the lever. One person dies, but five are saved.

If Option A feels “safer” to you, you might be experiencing Omission Bias. 

Omission bias is our tendency to see harmful actions as worse than harmful inaction, even when the outcome is similar, or even worse. In other words, causing harm can feel more morally wrong, more blameworthy, than allowing harm to happen (1,2,3). 

In the trolley problem, pulling the lever means someone dies because of something you did. Not pulling it means more people die, but it can feel less direct and less like your fault (1). 

Have you ever bought a book just because it was on the best-seller list? You might have succumbed to the bandwagon fallacy. 

Also called the appeal to common belief or the appeal to popularity, it is used to convince someone that something is true (or untrue) simply because lots of people think it is (1). There is nothing wrong with popular things (popular things are often popular for a reason!), but the fallacy lies in claiming that because it is popular, then it must be true (1,2,3,4,5). It is a mental shortcut: if many people believe it, it is easier for our brain to assume it must be right than to take the time to question and fact check it (4). 

It’s true that more Americans were watching the Sunday game than Canadians: 8.7 million Canadians vs. 26 million Americans, to be exact (1,2). 

Looking at the stats sheet alone, it may seem like Americans care more about hockey than Canadians. But that would be a base rate fallacy. 

The Base Rate Fallacy is the tendency for people to incorrectly judge the likelihood of a situation by benching relevant data. The way data is presented can greatly influence how we perceive it (3,4).

Yes, only 8.7 million Canadians watched the game last Sunday, but there are also only 41.5 million people living in Canada. Compared to the 342.4 million people living in the United-States of America, that nuance matters. It matters because 8.7 million of 41.5 million is 20.9% of the population, while 26 million of 342.4 million is only 7.6% of the American population. Quite a lot of people, but still, not quite as much as Canada (proportion wise!) (5,6). We will take the percentage win. 💪

We hope the American men’s hockey team enjoys their gold, because based on their track record they won’t see another one until the 2070s… 

Come on, what’s hockey without some chirping?!

And remember: Numbers without context? That is a power play for misinformation.