Why does 2020 feel jinxed?
Why Does 2020 Feel Jinxed?
If you’re like me, you’ve probably had at least one conversation in the last month about why the madness of 2020 just won’t let up. Ok, you say, maybe facing a global pandemic like COVID-19 was inevitable (this isn’t our first rodeo), but did it have to come with massive uncontrolled wildfires in the West and the death of a Supreme Court justice weeks before a presidential election? Not to mention reports of murder hornets spotted in Washington State. It’s hard to shrug that all off as a coincidence.
But is there really something crazy going on? Today’s newsletter is focused on the way our minds are wired to see patterns in data, even when there aren’t any, which might just explain that unshakable feeling I have that there’s something truly peculiar about 2020...
Before I dive into today’s featured Q&A and sate your curiosity, however, here are some other tidbits you might enjoy.
Recommended Listens and Reads
A Successful Failure: Earlier this season on Choiceology, I interviewed Harvard Law School professor and best-selling author Cass Sunstein as well as Northwestern University economics professor Kirabo Jackson about how checklists can bring order to complexity.
How Stereotypes Work and Why It Matters: Columbia Business School professor and host of the TED Business podcast Modupe Akinola and I discussed her research on stereotypes and how to combat them in this Scientific American article.
Using Behavioral Science to Get Fit: On Slate’s popular podcast, How To!, I chatted with host and best-selling author Charles Duhigg about tactics from behavioral science that can help anyone hoping to improve their physique.
Tips from a Behavioral Scientist on Getting out the Vote: Don’t miss this guide from CNN on to how to vote and make sure everyone else does too penned by my friend and collaborator, Harvard Kennedy School of Government professor Todd Rogers.
Q&A: The Patterns We See, Even When There’s Nothing To See
Today I’m sharing an interview I conducted for Choiceology with Cornell psychology professor Tom Gilovich about the peculiar way we see patterns in data, even when there aren’t any to find. Tom is an expert on why people misread evidence, draw erroneous conclusions, and form questionable beliefs.
Me: I want to start by asking you to explain what randomness looks like in the world, since it seems most of us get this wrong.
Tom: Well, randomness is lumpier than we expect. Statisticians refer to this as the clustering illusion. Imagine you got a bag of only yellow M&Ms and another bag of brown M&Ms and you randomly mix them together and you showed them to people. They're not going to look random to most people. People will say, "There's a big cluster of brown over there and there's another cluster of the yellow ones over here." That's what randomness looks like. It's very clustered and lumpy, more than we expect. So when we see the amount of clustering that chance provides, we reject it and say, "No, there's something systematic going on."
Me: Interesting. I love the M&M example, but where else can we see this play out?
Tom: One of the best applied examples of this is when Apple first came out with their iPod shuffle that would randomly choose songs from your collection of music. People objected, saying, "This isn't random. I was just listening to the Rolling Stones and now they're back on again." Well again, random selection is going to have more repeats than you’d expect.
Apple looked at the algorithms and realized they were producing random selections, but they just didn't seem random to people. So they created an option where you could make your songs more random seeming by making the selections actually less random.
Me: Ahh, so the new version wasn’t a random number generator?
Tom: Yup, it made the selections truly alternate to sample from different bins more often than you get with true random selections.
Me: Can you explain why those true random selections felt off to people?
Tom: This is part and parcel of a broader tendency of people to structure their world and see more order in it than is actually the case. Then there's a whole perceptual phenomenon: It's called pareidolia, that when we look at complex visual stimuli, we often see images that aren't there. A famous example is what's come to be known as the nun bun. One cinnamon bun produced in a bakery just had a remarkable resemblance to Mother Teresa. People noted that resemblance and said, "Hey this is amazing. There must be something mysterious, magical, spiritual going on." So it sold for a fair amount of money.
Me: I was thinking about the Jesus toast.
Tom: The Jesus toast. There's all sorts of examples — a Kate Middleton jelly bean. There's a certain moment at the billowing clouds of smoke coming out of one of the twin towers where it really looks like there's a demonic face there and people see the face of the devil or even the face of Osama bin Laden. And, of course, astronomers know about this phenomenon. The average person looking at the moon sees the man in the moon. You see canals on Mars and all sorts of ordered, structured things that on inspection aren't there.
Me: What’s behind this tendency people have to look for recognizable patterns in the world around them?
Tom: Our job is to find the order in the world and take advantage of it. So evolution has built this machinery to do just that. No machine is built perfectly. But if it's really important to find those patterns, it's going to overshoot sometimes and, lo and behold, it does overshoot in some predictable ways. As many people have noted, we tend to see faces in clouds. We don't see clouds in faces. That suggests a certain type of order to how we're taking complex stimuli like a cloud and seeing some order in it.
Me: That’s fascinating, and it helps explain why 2020 feels jinxed to so many of us. I think you said you have a great parlor trick you use when teaching people about the ways we misperceive chance. Could you share that just for kicks?
Tom: Let's say there's 20 people. What you do is, you have them all pretend they’re flipping a coin 20 times and write down the imaginary sequence of heads and tails, so they've all generated a pretend sequence of heads and tails. And then you say, “I'm going to leave and I want you guys to pick one person to tear theirs up and then actually flip a coin and write down the sequence of heads and tails." You come back in and they shuffle them all together and you pick out the one that is the real coin flip.
Me: So how do you pick? What’s the real one?
Tom: It's the one with the longest streak. No one's going to write a streak of even four in a row. The overwhelming majority of the time, just by looking for the longest streak of either heads or tails, you'll find the one that was generated by a true coin.
To learn more about the disorderly way we expect chance events to unfold and the implications of our tendency to see patterns even when there aren’t any to see, check out Tom Gilovich’s book How We Know What Isn’t So: The Fallibility of Human Reason in Everyday Life or listen to the episode of Choiceology about the mystery of chance.
This interview has been edited for clarity and length.
That’s all for this month’s newsletter. See you in November!
Katy Milkman, PhD
Professor at Wharton and host of Choiceology, an original podcast from Charles Schwab