🪞 Cognitive Biases
Learn the predictable ways your mind fools you — which of them the evidence actually supports, and the handful of procedures that beat simply knowing better.
What you’ll learn
- A Bias Is the Shadow of a ShortcutDefine a cognitive bias as the predictable failure mode of a heuristic that is usually useful, and explain why this framing — rather than 'the mind is broken' — is the accurate one.A heuristic is a mental shortcut that trades accuracy for speed and usually wins that trade; a bias is what the shortcut produces in the specific circumstances where the trade fails. Because biases are the price of a working system rather than defects bolted onto it, they cannot be removed by deciding to be smarter — a framing that determines everything else in this course. The popular 'System 1 and System 2' shorthand is a useful metaphor, not two places in the brain.
- Anchoring: The Bias That Survived EverythingDemonstrate the anchoring effect, explain why it is one of the best-replicated findings in judgement research, and identify where it operates in real life.Anchoring — the tendency for an arbitrary number to drag a subsequent estimate toward it — is unusual among biases in that it is large, easy to demonstrate, and replicates robustly, including across 36 samples and 6,344 participants in the Many Labs 1 project, where the Mount Everest item produced an effect of d = 2.23. It works even when the anchor is transparently random and even when people are warned about it. It is the mechanism underneath list prices, opening offers and salary negotiations.
- Availability: What Comes to Mind Is Not What Is CommonExplain the availability heuristic, show how memorability rather than frequency drives risk judgement, and connect it to how news coverage systematically distorts fear.The availability heuristic substitutes ease of recall for actual frequency, which works because common things are usually easy to recall — and fails whenever something is memorable for another reason, such as being vivid, recent, or newsworthy. The systematic consequence is that dramatic rare risks feel common and undramatic common risks feel rare. Because news is by definition a selection of the unusual, an accurate picture of the world cannot be assembled from it.
- Base Rates: The Error That Costs the MostExplain base-rate neglect using a worked medical-test example, show why the conjunction fallacy follows from representativeness, and present the frequency-framing critique honestly.Base-rate neglect — ignoring how common something is when judging how likely a case is — produces the largest practical errors of any bias in this course, as a worked example of a 99%-accurate test for a rare condition shows. The related conjunction fallacy (the Linda problem) shows resemblance overriding logic, though violations drop from a median of 87% to a median of 17% when the question is rephrased in frequencies, which is a real and instructive qualification rather than a refutation.
- Confirmation Bias: Looking Only Where the Answer Would Please YouExplain confirmation bias via Wason's 2-4-6 task and the selection task, and show why seeking disconfirmation is both the correct strategy and psychologically unnatural.Confirmation bias is the tendency to seek and weigh evidence that would confirm a hypothesis rather than evidence that could refute it — demonstrated cleanly by Wason's 2-4-6 task, where people test only sequences their rule permits and so never discover it is wrong. The selection task shows the same structure: two of 48 solved the abstract version in one study, against 74% on a logically identical problem about drinking age, which reveals that the failure is not a general inability to reason.
- Framing and Loss: The Same Fact, Two DecisionsDemonstrate the framing effect, explain prospect theory's account of losses looming larger than gains, and present the live scientific dispute over loss aversion honestly.Logically equivalent descriptions of the same outcome reliably produce different choices — 'saves 200 of 600' versus '400 die' flips risk preferences — and framing replicated robustly in Many Labs 1. The standard explanation is prospect theory's loss aversion, but the claim that losses loom roughly twice as large as gains is now genuinely contested, with critics arguing the evidence is weaker than its textbook status implies. The framing effect itself is not in dispute.
- Overconfidence and Hindsight: The Two That Hide the OthersExplain calibration and overconfidence, show how hindsight bias erases the memory of uncertainty, and connect them as the mechanism that prevents learning from error.Overconfidence is the systematic gap between how sure people are and how often they are right, measurable by calibration and largest where knowledge is thinnest: answers backed at odds of a million to one prove right about nine times in ten. Hindsight bias then rewrites memory so that known outcomes feel as though they were foreseeable, which destroys the feedback that would otherwise correct overconfidence. Together they form a closed loop that explains why experience alone often fails to improve judgement.
- The Honest Ledger: Which of These Actually ReplicateSort the biases in this course by evidentiary strength, and explain why an accurate account of a field must include what it got wrong.Judgement and decision research came through psychology's replication crisis in better shape than social psychology, but not untouched: anchoring, framing, the conjunction fallacy, base-rate neglect and hindsight bias all hold up, while priming-based effects failed and loss aversion's general form is contested. Presenting a curated list of biases as uniformly settled would repeat the exact error that caused the crisis, which is why the ledger belongs in the course rather than in a footnote.
- The Bias Blind Spot, and What Actually WorksState the bias blind spot finding, explain why awareness is a poor defence, and assemble the procedural fixes — outside view, premortem, written predictions, frame-flipping — that do work.Asked across fourteen biases, 85% of 661 people come out reliably less biased than the average American and exactly one comes out reliably more so (Scopelliti et al. 2015), while the original and much smaller Pronin study shows the asymmetry disappearing for shortcomings people can feel operating — a finding that applies to the reader of this course with particular force. Because biases operate below introspective access, awareness is a weak defence and can backfire by supplying a vocabulary for diagnosing others. What works is procedural: taking the outside view, running premortems, writing predictions down, and flipping frames before deciding.
Questions this course answers
Why can't cognitive biases simply be trained away by learning to think more carefully?
The shortcut and the bias are the same mechanism seen in different circumstances. A mind with no availability heuristic wouldn't be an unbiased mind; it would be a mind that couldn't estimate anything quickly. This is why the fixes in this course are procedures, not effort.
Participants watched a wheel of fortune land on a random number and still let it move their estimate by twenty points. Why is this so damaging to the 'just be aware of it' defence?
Anchoring survives full knowledge of its own arbitrariness. This is the recurring lesson of the whole course: knowing about a bias, in the moment, buys you far less than it feels like it should. Procedures beat awareness.
What makes anchoring one of the strongest findings in this course?
Big effect, tight measurement, no dependence on scenario interpretation, and it survived a high-powered preregistered multi-site test. That's the profile of a finding you can build on.
Why does consuming more news tend to make your sense of risk worse rather than better?
Each individual report can be perfectly accurate and the aggregate picture still inverted. The distortion is in the selection, not the reporting — and your recall has no way to correct for a sample it didn't choose.
A disease affects 1 in 1,000. A test never misses a case but falsely flags 5% of healthy people. You test positive. Roughly what are the odds you're ill?
Of 1,000 people: 1 true positive, and 5% of the 999 healthy — about 50 — false positives. So 1 in 51, about 2%. The test's accuracy was never the issue; the base rate was, and it's the number nobody mentions.
Violation rates on the Linda problem fall from a median of 87% to a median of 17% when it is rephrased in frequencies. What's the right conclusion?
Both extremes are wrong. The effect doesn't vanish, but it drops by seventy percentage points with a better interface — which tells you something useful about your own mind: give it whole numbers of people and it reasons far better than it does with percentages.
Grounded in trusted sources
- Tversky & Kahneman, 'Judgment under Uncertainty: Heuristics and Biases', Science 185 (1974)
- Tversky & Kahneman, 'The framing of decisions and the psychology of choice', Science 211 (1981)
- Tversky & Kahneman, 'Extensional versus intuitive reasoning: The conjunction fallacy in probability judgment', Psychological Review (1983)
- Klein et al., 'Investigating Variation in Replicability: A Many Labs Replication Project', Social Psychology 45 (2014)
- Pronin, Lin & Ross, 'The Bias Blind Spot', Personality and Social Psychology Bulletin (2002)
- Wason, 'On the failure to eliminate hypotheses in a conceptual task', Quarterly Journal of Experimental Psychology (1960)
- Griggs & Cox, 'The elusive thematic-materials effect in Wason's selection task', British Journal of Psychology 73 (1982)
- Fischhoff, 'Hindsight ≠ Foresight', Journal of Experimental Psychology: Human Perception and Performance (1975)
Every Wunder lesson is built from real, reputable sources — never invented.
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