Stranger than fiction
One of the most important things to do when teaching web literacy is to keep an eye out for weird but true things. What are things that many people, using their normal filtering mechanisms, would see as false? Once you do this, you see that we make a real mistake when we suggest to students the way to figure out whether something is true or false is to think “Does this make sense?”
Here’s today’s example:
How would your students know if this is true or false? In some ways it’s no different than the hundreds of fake scams on Twitter where a fake Elon Musk announces he’ll give free bitcoin to a random 100 retweeters. If you know Mike DeWine, and you know the Ohio situation, maybe it doesn’t seem as absurd. But you can’t really rely on your own intuitions here.
So what do we do? There’s two major SIFT approaches on this. The first is to see if this is really the Governor’s account. You note the blue check, and that’s a pretty good indication here. A blue check doesn’t tell us that something is true, but it should, in most cases, tell us that the person is the person we think it is. And in this case, if it really is the Governor, that’s enough. The entire question here is whether the Governor just announced this. (I.e. it is not a question about a claim the governor is making, this is essentially a version of “confirming a quote”).
We see in a hover what we expect — the Governor (or Governor’s office) has a lot of followers. He is also followed by people I know, and the people that follow him are the people I know to be interested in politics. It looks like it is what I thought it was.
Along with the blue check, that’s probably enough. There is one thing that has happened occasionally though where smaller blue check accounts have been hacked, and then the hackers have changed the name and done stuff somewhat similar to this (though usually about bitcoin, tbh). So if we wanted to be extra careful here (and we really don’t have to be) we could do one other thing. Instead of doing the “I” in SIFT, we could do the “F”. If the governor really just made such an announcement, there should be a whole bunch of coverage on it. So we select on the text and do a web search:
And here we see that even though the governor just put out this tweet there’s many news agencies reporting it. If we want to know more, we can click into those stories.
Notice an important principle here. We’re not really checking if this is “true”. We’re checking whether this thing we’re looking at is what we think it is. We’re putting the assumptions of our reaction under the microscope. (I’ll get into this issue more in later posts, it’s a bit of a nuanced distinction).
If you use this with students, make sure you walk through it incrementally for best effect. I would start by showing the tweet, then warn students that “If they already know if this is true or false, don’t give it away.” Then I would
Ask what the class thinks: true or false? Just your impression.
Then ask, what are some ways we could be sure that this is the governor’s account?
Explain what the check means, and what it doesn’t mean — and that in this case since who he is is highly relevant to the claim, the check means a lot. (In other cases it can mean very little).
If you want to get really fancy, you could talk about this as a class of tweets that are in fact a sort of “speech act” — someone is not just asserting something, they are proclaiming it. So the question of whether they are who they say they are (and whether they have the power to do it) is highly relevant.
Then ask the students how they would use the “F” in SIFT to check this. Let them look up news stories and tell you what they find.
And that’s it.
In a coming post, I’ll talk more about “plausibility filters” — our sense of what is likely and what is not — and how they can lead us astray.
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