This article can be found in its entirety on Wired.com. It is a good read if are interested in earthquake predictions or just using big data to make predictive statements of the future. However, it is the introduction that stood out to me. Interesting behavioral finance implications
Yesterday’s post was a ringer. What you were actually looking at was a random distribution of earthquakes that I generated using the R statistical package. The earthquakes themselves are real (at least the magnitude), representing the 3,776 earthquakes over magnitude 4 between January 1 and May 24. However, I had R assign a random day between 1 and 144 (1/1-5/24) to each earthquake. Many of you saw through my ruse, but did some of you start to convince yourself that there was a coherent pattern in this data? Maybe that some of the larger earthquakes occurred within a few days of the new moon? Maybe that lulls were happening during full moons? Did it seem plausible?
That is because humans love to find patterns, especially in large data sets. We don’t even know we’re doing it (notice how Mary can show up on a potato chip?) Yet, here we are, always looking for patterns and an explain for the distribution of events or objects.
In geology, there is probably no bigger a subject than “pattern recognition” (or lack thereof) in earthquake prediction, to the point that some claim they can predict when and where an earthquake will strike. Sadly, we just can’t do that with our current technology and knowledge of the Earth, but people still fall prey to believing in these false patterns.
Human brains are good at seeing patterns, whether it be to see the ripe fruits to pick in a tree, to notice the snake ready to strike or to see that elephant in the sky when you’re looking at clouds. Our ancestors were those who survived and thrived because they were able to see the patterns in their environment to find food, avoid predators, and get a mate. One idea is that our brains want to see patterns, even false ones, so as not to miss the right pattern when it comes along — because if you miss that pattern for “snake”, you might end up dead. This ability mixed with culture became superstition, which in itself is pattern recognition, although the patterns can be false.
Work by Foster and Kokko (2009) models the behavior of people when it comes to superstitious beliefs (i.e., patterns that are false) and found that people should be apt to accept a false pattern if the cost of accepting that pattern is lower than the cost of not accepting the false pattern. Foster and Kokko (2009) sum this up by saying:
So, your brain is hypersensitive to patterns because you inherited this ability from your ancestors. If great great great Grandma Ape wasn’t hyper about patterns, she wouldn’t have survived long enough to be your ancestor. However, the cost is that we tend to try to see things that aren’t always there. That is what happened when you looked at the random 2013 earthquake data. We can’t actually see the causal probabilities for the distribution of earthquakes because they are so complex, so instead we try to fit them to easier relationships, like the phase of the moon.
Yesterday’s post was a ringer. What you were actually looking at was a random distribution of earthquakes that I generated using the R statistical package. The earthquakes themselves are real (at least the magnitude), representing the 3,776 earthquakes over magnitude 4 between January 1 and May 24. However, I had R assign a random day between 1 and 144 (1/1-5/24) to each earthquake. Many of you saw through my ruse, but did some of you start to convince yourself that there was a coherent pattern in this data? Maybe that some of the larger earthquakes occurred within a few days of the new moon? Maybe that lulls were happening during full moons? Did it seem plausible?
That is because humans love to find patterns, especially in large data sets. We don’t even know we’re doing it (notice how Mary can show up on a potato chip?) Yet, here we are, always looking for patterns and an explain for the distribution of events or objects.
In geology, there is probably no bigger a subject than “pattern recognition” (or lack thereof) in earthquake prediction, to the point that some claim they can predict when and where an earthquake will strike. Sadly, we just can’t do that with our current technology and knowledge of the Earth, but people still fall prey to believing in these false patterns.
Human brains are good at seeing patterns, whether it be to see the ripe fruits to pick in a tree, to notice the snake ready to strike or to see that elephant in the sky when you’re looking at clouds. Our ancestors were those who survived and thrived because they were able to see the patterns in their environment to find food, avoid predators, and get a mate. One idea is that our brains want to see patterns, even false ones, so as not to miss the right pattern when it comes along — because if you miss that pattern for “snake”, you might end up dead. This ability mixed with culture became superstition, which in itself is pattern recognition, although the patterns can be false.
Work by Foster and Kokko (2009) models the behavior of people when it comes to superstitious beliefs (i.e., patterns that are false) and found that people should be apt to accept a false pattern if the cost of accepting that pattern is lower than the cost of not accepting the false pattern. Foster and Kokko (2009) sum this up by saying:
The evolutionary rationale for superstition is clear: natural selection will favour strategies that make many incorrect causal associations in order to establish those that are essential for survival and reproduction … the inability of individuals—human or otherwise—to assign causal probabilities to all sets of events that occur around them will often force them to lump causal associations with non-causal onesOr, in other words, it is better to believe wrong and right things (and thus get all the right things) than accidentally miss some of the right things. For example, many traditional cultures have pregnancy taboos. Many pregnancies don’t make it, and the causes aren’t often clear. However, people try to see some sort of pattern. It is low cost to believe that women should not eat certain foods, avoid the full moon, and never butcher an alligator if any of those things just might aid in the survival of her child. Low cost for believing in some good and some bad stuff in trade for high evolutionary rewards. Thus, cultures adopt taboos for pregnant women that may seem silly, because it was difficult to see which of the few taboos actually has a causal relationship (if any). Granny wants you to do them all, just to be on the safe side.
So, your brain is hypersensitive to patterns because you inherited this ability from your ancestors. If great great great Grandma Ape wasn’t hyper about patterns, she wouldn’t have survived long enough to be your ancestor. However, the cost is that we tend to try to see things that aren’t always there. That is what happened when you looked at the random 2013 earthquake data. We can’t actually see the causal probabilities for the distribution of earthquakes because they are so complex, so instead we try to fit them to easier relationships, like the phase of the moon.
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