🧠 Psychology, Made Simple · Understand Yourself & Others

What Are Cognitive Biases? 3 Mental Shortcuts That Fool You

Confirmation bias, the anchoring effect, and survivorship bias

一句话先懂 · TL;DR

Meet three cognitive biases that shape your decisions — confirmation bias, the anchoring effect and survivorship bias — and simple questions to catch them.

You Only See What You Want to See

The moment you decide to lose weight, suddenly your whole feed is full of workout check-ins, and your coworkers all seem to be ordering salads. Nothing really changed—your attention just started leaning that way.

We're also especially fond of collecting information that backs up what we already think: if you believe a celebrity is a good person, you only remember their good deeds, and the bad news slides right past.

🔆It's like wearing glasses that only let supporting evidence through—this is called confirmation bias: a tendency to gather information that supports your existing view while ignoring evidence to the contrary.
💡Next time you're about to reach a conclusion, deliberately ask yourself: Is there contrary evidence I haven't looked at?

The First Number Drags You Along

You're shopping and see a piece of clothing tagged at 999, with "now 399" next to it, and you instantly feel like it's a great deal. But what if it was only ever worth 200? That 999 is just bait.

The number you see first becomes a reference point in your mind, and every judgment afterward unconsciously revolves around it. When haggling, who names a price first—and how high—often decides what range you end up settling in.

🔆It's like dropping an anchor into the water: the boat can only drift near it—this is the anchoring effect: the first number or piece of information you encounter pulls your judgment toward it.

You Only Heard from the Ones Who Survived

"My neighbor smoked every day and lived to 90, so smoking is fine."—the problem is that the people who died early from smoking can no longer speak up to disagree.

It's the same with startup stories: bookstores are full of memoirs by the successful, while the tens of thousands who failed so completely that no one interviews them simply aren't in front of you. Look only at the survivors, and your conclusions naturally come out wildly optimistic.

🔆It's like counting only the lottery winners and forgetting to count everyone who lost—this is called survivorship bias: you see only the samples that "stayed/succeeded" and ignore the huge group that "disappeared/failed."
💡When you hear a conclusion, ask one more question: Where did all the people or cases that aren't in front of me go?

自测 · 学完检查一下

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In an interview, the HR rep opens with "our budget for this role is around 8K," and your salary expectation immediately drifts toward 8K. Which bias should you most beware of?

答案:Anchoring: the 8K thrown out first became your reference point

8K is the number that appeared first and became a reference point pulling you toward it—anchoring. Confirmation bias is "only collecting evidence that supports a view you already hold," but here you had no view yet—you were led by a new number. "No bias involved" is a trap: once a first number influences you, anchoring has already happened.

"Astrology really works! I'm a Scorpio, and the Scorpios around me are all super vindictive—see?" What's the core problem with this statement?

答案:Confirmation bias: cherry-picking the cases that confirm astrology and ignoring the ones that don't

They actively collect cases that "confirm astrology" and ignore the counterexamples (non-vindictive Scorpios, vindictive people of other signs)—confirmation bias. The distinction: confirmation bias = picking supporting evidence; survivorship bias = not seeing the "vanished/failed" samples (none here); anchoring = being pulled by a number that appeared first (no number here).

There's a classic WWII case often told this way: tallying the bullet holes on planes that returned shows the most on the wings and the fewest on the engines. Recommending "reinforce the wings" on that basis is exactly backwards. Why?

答案:Planes hit in the engine mostly never made it back, so the spot to reinforce is the engine—the part that "looks barely hit" in the surviving sample

You only counted the planes that made it back alive. Those hit in the engine crashed and aren't in the sample, so "few holes on the engine" isn't because it's rarely hit—it's because a hit there means you don't return. The most-cited case of survivorship bias (the specifics are largely a later, popularized retelling). "Trust the data, reinforce the wings" is exactly the intuitive answer that falls into the trap.

True or false: "Every time I wait until the deadline to start, it turns out fine, so pressure makes me perform better."—since this is my own real experience, it's not survivorship bias.

答案:False

False. "Real experience" still gets polluted by bias: the times you procrastinated and blew it are easily forgotten and never counted (the vanished samples), and you only remember the few times waiting till the end turned out fine—survivorship bias plus confirmation bias working together.

Buying a used car, the seller opens at 150K. To avoid being anchored as much as possible, which move is most effective?

答案:Look up the fair market price for this car independently before you go in, then negotiate

The key to countering anchoring is walking in with your own independent reference point—with a market price in mind, 150K can't drag you. The other three (counter at 140K / ask them to drop first / cut 10%) all orbit the 150K anchor and are still being anchored.

"This fund has gone up every year for 3 years, the manager went on TV calling it a sure thing, and I dug up a pile of posts praising it—the more I look the more I want to buy." Which one is **not** directly present here?

答案:The anchoring effect

Confirmation bias (only seeing the praise) and survivorship bias (only seeing the funds that survived) are both here, but there's no specific number that appeared first dragging your judgment, so anchoring isn't directly present. This "which one is missing" format forces you to check all three biases one by one.

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