What Is… a Heuristic in Psychology

In this series, I dig a little deeper into the meaning of psychology-related terms. This week’s term is heuristic.

A heuristic (from the Greek “to discover”) is a mental rule of thumb or shortcut that allows our brains to process information and arrive at conclusions more quickly. I recently wrote about philosophical razors, which are a type of logical heuristic. This post will cover psychological heuristics, which you probably use regularly without even realizing it.

Heuristics aren’t necessarily a bad thing. They’re efficient, they don’t require conscious thought, and they handle unimportant stuff pretty well. The problem comes when we get too attached to our conclusions and believe that we arrived at them logically. Despite the logical appearance, our mind just made a flying leap and that’s where it happened to land.

Heuristics were first described by psychologists Amos Tversky and Daniel Kahneman in a 1974 paper. They identified three of them: representativeness, availability, and anchoring and adjustment. Several more have since been identified.

Anchoring and adjustment

People will evaluate pricing based on the initial anchor point they’re given. A used car might be worth $6000, but if the dealer’s asking price is $10,000, that’s what your brain wants to use a reference point. You end up adjusting your evaluation and thinking you got an awesome deal by only paying $7500. The dealer, on the other hand, is happy you fell for their trick and paid too much.

When you go to a clothing store, either in-person or online, sale items will always be clearly marked with the original price. That serves as the anchor, making you think you’re getting a great deal, even if the original price was way higher than it deserved to be in the first place. I can get sucked into this one; I am cheap, and feeling like I got a great deal is very satisfying.

Availability heuristic

We judge the frequency of events based on the example that comes to mind most easily; this is known as the availability heuristic. Car crashes are waaaaaay more common than plane crashes; however, because plane crashes are big news and car crashes are not, the way we estimate likelihood is skewed by plane crashes being more front of mind. Car crashes become background risk, while some people are terrified of flying.

We also overestimate violent crime rates and misjudge trends in those rates because those types of crimes get a lot of media attention.

Familiarity heuristic

The familiarity heuristic is a variation of the availability heuristic, and it means that if something comes to mind quickly, we’re likely to think it’s the right/safe choice. We’re also likely to overestimate the safety of familiar environments, to the point that we may miss seeing major hazards. This may be part of why you’re most likely to have a car accident when you’re close to home.

Representativeness heuristic

Our brains like to create social categories and come up with representative examples of those categories. When someone comes along who reminds of one of those representative examples, we slot them into that category and apply all the beliefs and judgments we have around the category to the person we’ve just shoved in there. That’s the representativeness heuristic—hello, stereotypes.

This is also why we’re bad at identifying what’s random and what’s not. We expect a random set of data to look a certain way… but we’re totally out to lunch. If you flip a coin ten times and it comes up heads each time, you might think that it’s a trick coin or, at the very least, that there’s a higher likelihood of flip #11 coming up tails, because getting 11 heads in a row just doesn’t happen randomly. Except it does, and you’d be wrong, because the odds of every flip are 50:50, and the coin has no memory of what’s already happened. Even if it did, it probably wouldn’t care.

Scarcity heuristic

The scarcity heuristic means that the rarer something is, the more valuable it’s believed to be. When toilet paper started flying off shelves because of panic buying in spring 2020, the scarcity heuristic kicked in and people start hoarding enough toilet paper to last for the next decade.

Think of diamonds and cubic zirconia. Diamonds cost more because they’re rare, so people are willing to shell out the big bucks for them even though they look pretty much the same to the average person.

Social proof

We are sheeple, and if other people are doing it, we think we probably should be too. Add this to the scarcity heuristic, and it’s not just a few nutters hoarding toilet paper; the social proof of seeing others walking out of the store with a cart full of toilet paper everyone makes everyone want to get in on the action.

Similarly to the social proof heuristic, we make some moral evaluations based on how commonly we observe a behaviour. The more common that a behaviour is, the more likely we are to deem it a moral action, even if the behaviour itself is actually selfish. Baaaaaa!

Being aware of our thinking patterns

I find it fascinating that our brains try so hard to be helpful, but can totally miss the boat. Perhaps the takeaway is that thoughts just aren’t reliably accurate. Someone (although I don’t know who) has said “don’t believe everything you think”, and that’s very good advice. There’s some good stuff that our minds come up with, but there’s also a lot of nonsense floating around in there. Deciding which is which isn’t necessarily easy.

Do these heuristics sounds familiar to you (not necessarily the name of the heuristic, but the shortcuts they refer to)? How do you think we can get around our natural tendency to believe in nonsense thoughts?

You may also be interested in the post What Is… a Cognitive Bias.

References

• American Psychological Association. (2017). Heuristics.
• Herbert, W. (2010). Heuristics Revealed. Association for Psychological Science.
• The Decision Lab: Why Do We Take Mental Shortcuts?
• Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131.
• Walters, S. (n.d.). Heuristics and Algorithms. In Psychology – 1st Canadian Edition.
• Wikipedia