Rare events have a bizarre effect on the mind: The rarer the event, the more memorable it can be. A normal outcome fades from memory in a few minutes, while an unusual one may stay in our minds for years. That phenomenon is one of the most common errors in probability perception: remembering events that are likely to have happened, but didn’t.
This is about more than gambling. This same cognitive bias shows up when people judge financial markets, viral trends, online shopping, health stories, or random events in everyday life.
Six Extraordinary Stories Before Breakfast
Can you envision six extraordinary stories in your social stream before breakfast? One is about a sudden money windfall, another about a remarkable sporting upset, and the third about an exceptionally big discount.
It is unlikely that any of these events will be common. However, the more you see them, the more your brain begins to take them for granted as something that you see all the time.
The Availability Heuristic
This is very similar to the “availability heuristic.” People tend to judge the probability of something by how easily examples come to mind. This is especially true with digital media, where algorithms are adept at identifying unusual content. If you get ordinary results, you will get a few thousand shares, but if your results are extraordinary, you will get thousands of shares.
This can result in a skewed version of reality in your information world.
Examples Versus Evidence
Someone surfing a brand-new site might come across reviews, figures, anecdotes, and odd experiences. A simple search like “ROYALXO Finland” may result in a combination of factual information and individual accounts. The prudent approach is to consider examples rather than overall frequency.
The Brain Prefers Patterns to Randomness
Seeing Patterns That Aren’t There
Humans are great pattern-matching machines! It comes in handy when crossing a street or spotting a familiar face, but it becomes a problem when there is no rhyme or reason: patterns can appear even when they don’t exist.
The sequence A-B-A-B-A seems like there is a message, whereas a truly random sequence can have unexpected runs that feel ‘too organized’ to be by chance.
The Gambler’s Fallacy
This is where cognitive bias comes into play. A classic example is what is known as the “gambler’s fallacy”: after a series of similar events, another event of the opposite type might seem like it’s “due”. Mathematically independent events have nothing to do with that, but it’s not something that intuition relishes: the concept of “randomness with no memory.
It is the same behavior we see online. Someone observes some unusual suggestions, transactions, or hashtags and begins to research a secret mechanism behind them.
Why the Brain Remembers the Unexpected
Prediction and Learning
There’s neuroscience as well. The brain constantly compares what happens with what it predicted, and when it doesn’t, it captures attention.
Neural learning systems react to discrepancies that occur when the outcome is significantly different from an expectation. It’s a prediction-and-learning process, and that’s why something unexpected can be so important.
Dopamine and Variable Rewards
This is NOT to say that dopamine is just “pleasure. The role is more complex; it relates to motivation, learning, and updating of expectations.
This distinction matters because digital environments offer many rewards, and they’re variable. Notifications arrive unpredictably. All of a sudden, your content goes viral. A recommendation happens out of the blue that you are interested in. This is the little dopamine loop that can be an ordinary scroll: check, find something interesting, check again, repeat.
After a certain number of repetitions, unusual events may consume a great deal of mental space when compared to their actual incidence.
Digital platforms bring rare things into the common.
Algorithms and Attention
The Internet has created a worldwide platform to showcase exceptions.
Recommendation algorithms aim for attention-grabbing digital engagement, not a perfectly representative statistical sample of anything. It is more interesting to read about a man who had a very normal Tuesday than a story about his dramatic success.
This creates a significant gap between what is and what we see.
This is the same for information resources. For example, a casino account guide might cover the time frame of language used, the sign-up process, or the features of an account. Still, nothing from it tells us anything about the odds of an unassociated unusual outcome. The information about a process and evidence about probability are two different things.
A Better Way to Think About Rare Events
Move Away From the Iconic Example
The easiest remedy is to move away from the iconic example and ask a few simple questions.
Four Questions to Ask
What is the rate of interest before tax?
What is the rate of this event in the population of interest?
What is the value of n?
A single impressive case doesn’t offer much insight into thousands of run-of-the-mill cases.
Is there any relationship between the events?
Just because several unusual outcomes occur together doesn’t mean that there is a causal connection.
Have I sampled a representative sample?
Social feeds, viral posts, and recommendation systems are very selective.
Intuition and Decision Fatigue
This also helps reduce decision fatigue. We can use a limited number of statistical questions to explain a surprising event rather than trying to understand every unexpected thing. The objective is NOT to get rid of intuition, but to realize when intuition is likely to be “misled”.
