{ "version": 1, "updatedAt": "2026-08-19", "description": "Interactive, privacy-preserving demonstrations of evidence-reviewed cognitive bias effects. These demos do not collect responses and are not scientific measurements.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/", "privacy": "Responses are not transmitted or persisted by the static experiment pages.", "experiments": [ { "slug": "anchoring-first-number", "title": "Does the First Number Pull Your Estimate?", "category": "Numbers & Estimates", "summary": "Try two versions of the same pricing question and see why a starting number can pull later estimates toward it.", "researchQuestion": "Can an arbitrary starting price shift a later estimate even when the product information stays the same?", "responseType": "number", "responseLabel": "Your fair price estimate (€)", "conditions": [ { "label": "Higher anchor", "prompt": "A used laptop is in good condition, three years old, with 16 GB RAM and 512 GB storage. The seller asks €1,500. What price would you consider fair?" }, { "label": "Lower anchor", "prompt": "A used laptop is in good condition, three years old, with 16 GB RAM and 512 GB storage. The seller asks €700. What price would you consider fair?" } ], "prediction": "Across groups, estimates often move toward the starting number. One person's answer cannot establish an anchoring effect.", "interpretation": "The useful comparison is not whether €700 or €1,500 is a good price. It is whether changing only the starting number changes the later estimate.", "debias": "Build an independent estimate from comparable products, budget and requirements before looking at the seller's target.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/anchoring-first-number/", "bias": { "slug": "cognitive-bias-anchoring-effect", "title": "Anchoring Effect", "canonicalUrl": "https://cognitive-biases.github.io/biases/cognitive-bias-anchoring-effect/", "evidenceUrl": "https://cognitive-biases.github.io/biases/cognitive-bias-anchoring-effect/#evidence", "evidenceStatus": "well-supported for numerical judgments; strength depends on anchor type and context", "qualification": "Anchoring is a well-supported effect in which an initial numerical value can pull a later estimate toward it. A 2026 meta-analysis covering 2,601 effect sizes found a large overall effect, but also substantial variation across studies. The effect should not be treated as a rule that every number changes every judgment: incidental anchors, anchors from a different dimension, clearly random values, incentives, and some debiasing conditions were associated with smaller or null effects." }, "context": null, "everyday": { "slug": "why-the-first-price-changes-what-you-will-pay", "title": "Why the First Price You See Changes What You Will Pay", "canonicalUrl": "https://cognitive-biases.github.io/everyday/why-the-first-price-changes-what-you-will-pay/" } }, { "slug": "framing-survival-mortality", "title": "Does Survival vs Mortality Wording Change the Feeling?", "category": "Framing", "summary": "The numbers stay identical while the wording changes from survival to mortality. Notice whether your evaluation moves with the frame.", "researchQuestion": "Can equivalent outcome statistics feel different when they are described as survival rather than mortality?", "responseType": "rating", "responseLabel": "How reassuring does this result feel? 1 = not reassuring, 7 = very reassuring", "conditions": [ { "label": "Survival frame", "prompt": "After one year, 90 out of 100 patients who receive Treatment A are alive." }, { "label": "Mortality frame", "prompt": "Within one year, 10 out of 100 patients who receive Treatment A die." } ], "prediction": "Equivalent outcomes can receive different evaluations when one version highlights survival and the other highlights mortality.", "interpretation": "The underlying numbers are the same. The demonstration asks whether a change in presentation changes your evaluation.", "debias": "Restate important outcomes in both gain and loss terms before comparing options.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/framing-survival-mortality/", "bias": { "slug": "framing-effect-core", "title": "Framing Effect", "canonicalUrl": "https://cognitive-biases.github.io/biases/framing-effect-core/", "evidenceUrl": "https://cognitive-biases.github.io/biases/framing-effect-core/#evidence", "evidenceStatus": "risky-choice framing is robust; broader framing types have different evidence", "qualification": "Framing research covers several distinct paradigms. Risky-choice framing, where equivalent outcomes are presented as gains or losses, is a well-established effect with substantial evidence across many studies. A classic meta-analysis found a reliable small-to-moderate average effect with strong variation across designs, and later reviews and metastudies support broad generalizability. Attribute framing also has supporting evidence, while goal or message framing is less consistently established. These should not be treated as one identical effect caused by any change in wording." }, "context": null, "everyday": null }, { "slug": "decoy-subscription-choice", "title": "Can a Third Option Change Which Plan You Prefer?", "category": "Choice Architecture", "summary": "Choose between two plans, then compare the same choice after a clearly weaker third option appears.", "researchQuestion": "Can an inferior comparison option change preference between two original alternatives?", "responseType": "choice", "responseLabel": null, "conditions": [ { "label": "Two-option menu", "prompt": "You need cloud storage for one year. Which plan would you choose?", "options": [ "Basic — €8/month, 40 GB", "Pro — €14/month, 100 GB" ] }, { "label": "Menu with a decoy", "prompt": "You need cloud storage for one year. Which plan would you choose?", "options": [ "Basic — €8/month, 40 GB", "Plus — €14/month, 60 GB", "Pro — €14/month, 100 GB" ] } ], "prediction": "Adding an option that is clearly worse than Pro at the same price can make Pro easier to justify, even though Basic and Pro did not change.", "interpretation": "The interesting variable is the choice set. If preference changes after adding the weak Plus option, the comparison structure is doing work.", "debias": "Remove any option you would never choose and compare the remaining alternatives on your actual needs.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/decoy-subscription-choice/", "bias": { "slug": "framing-effect-decoy-effect", "title": "Decoy Effect", "canonicalUrl": "https://cognitive-biases.github.io/biases/framing-effect-decoy-effect/", "evidenceUrl": "https://cognitive-biases.github.io/biases/framing-effect-decoy-effect/#evidence", "evidenceStatus": "well documented, context-dependent", "qualification": "The decoy effect is a well-documented family of context effects in which adding an inferior or otherwise strategically positioned alternative can change choice shares among the original options. The classic attraction effect uses an asymmetrically dominated decoy that is worse than the target but not necessarily worse than the competitor. The effect is not guaranteed: its size depends on the geometry of the options, prior preferences, task design and other moderators, and preregistered replications have found both successful and weak or null results." }, "context": null, "everyday": null }, { "slug": "escalation-past-investment", "title": "Would You Continue If the Past Investment Disappeared?", "category": "Projects & Money", "summary": "The future economics stay the same. Only one version reminds you how much has already been spent.", "researchQuestion": "Does visible past investment make continued funding feel more attractive even when future costs and benefits are unchanged?", "responseType": "choice", "responseLabel": null, "conditions": [ { "label": "Past investment visible", "prompt": "A project has already used €400,000 and eight months of work. From today, it needs another €100,000. There is a 30% chance it will produce €250,000 of future business value. Continue or stop?", "options": [ "Continue", "Stop" ] }, { "label": "Future-only version", "prompt": "A project starts today. It needs €100,000. There is a 30% chance it will produce €250,000 of future business value. Continue or stop?", "options": [ "Continue", "Stop" ] } ], "prediction": "Past investment can increase willingness to continue even though those costs cannot improve the future payoff.", "interpretation": "The future decision is identical in both versions. The €400,000 has already gone and should not become a future benefit.", "debias": "Ask whether you would fund the next step if the project arrived today with no history.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/escalation-past-investment/", "bias": { "slug": "logical-fallacy-escalation-of-commitment", "title": "Escalation of Commitment", "canonicalUrl": "https://cognitive-biases.github.io/biases/logical-fallacy-escalation-of-commitment/", "evidenceUrl": "https://cognitive-biases.github.io/biases/logical-fallacy-escalation-of-commitment/#evidence", "evidenceStatus": "established, but related constructs should be separated", "qualification": "Sunk-cost effects and escalation of commitment overlap but are not interchangeable. Sunk-cost research asks whether irrecoverable prior investments influence current choices. Escalation of commitment describes persistence or additional resource allocation to a failing course of action and can also be driven by personal responsibility, self-justification, project structure, and other factors." }, "context": { "slug": "work-project-decisions", "title": "Work & project decisions", "canonicalUrl": "https://cognitive-biases.github.io/contexts/work-project-decisions/" }, "everyday": { "slug": "why-bad-projects-are-so-hard-to-stop", "title": "Why Bad Projects Are So Hard to Stop", "canonicalUrl": "https://cognitive-biases.github.io/everyday/why-bad-projects-are-so-hard-to-stop/" } }, { "slug": "outcome-bias-supplier-decision", "title": "Does the Outcome Change How Good the Decision Looks?", "category": "Learning & Review", "summary": "Rate the same decision process after either a lucky or unlucky result.", "researchQuestion": "Can knowing the outcome change how people judge the quality of the earlier decision process?", "responseType": "rating", "responseLabel": "How good was the original decision? 1 = very poor, 7 = very good", "conditions": [ { "label": "Good outcome", "prompt": "A manager compared three suppliers, checked financial stability, references and delivery performance, then chose the strongest option. A rare disruption did not occur and delivery succeeded." }, { "label": "Bad outcome", "prompt": "A manager compared three suppliers, checked financial stability, references and delivery performance, then chose the strongest option. A rare disruption occurred and delivery failed." } ], "prediction": "The same process may be judged more harshly after a bad outcome and more positively after a good one.", "interpretation": "A good process can have a bad result under uncertainty, and a weak process can sometimes get lucky. Review both separately.", "debias": "Score the decision using only information available before the outcome, then review the result as a separate learning signal.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/outcome-bias-supplier-decision/", "bias": { "slug": "cognitive-bias-outcome-bias", "title": "Outcome Bias", "canonicalUrl": "https://cognitive-biases.github.io/biases/cognitive-bias-outcome-bias/", "evidenceUrl": "https://cognitive-biases.github.io/biases/cognitive-bias-outcome-bias/#evidence", "evidenceStatus": "replicated", "qualification": "Outcome bias occurs when knowledge of a result changes how people evaluate the quality of a decision even when the information available at the time of the decision is held constant. Outcomes can still be relevant for learning, so the error is not 'never look at results'; it is using luck or hindsight as if it had been available to the original decision-maker." }, "context": { "slug": "work-project-decisions", "title": "Work & project decisions", "canonicalUrl": "https://cognitive-biases.github.io/contexts/work-project-decisions/" }, "everyday": { "slug": "why-a-good-result-does-not-always-mean-a-good-decision", "title": "Why a Good Result Does Not Always Mean a Good Decision", "canonicalUrl": "https://cognitive-biases.github.io/everyday/why-a-good-result-does-not-always-mean-a-good-decision/" } }, { "slug": "planning-fallacy-reference-class", "title": "What Happens When You See the Reference Class?", "category": "Forecasting", "summary": "Estimate a project from the inside view, then compare it with a version that includes how long similar work actually took.", "researchQuestion": "Does adding a reference class change a delivery estimate built from an ideal step-by-step plan?", "responseType": "number", "responseLabel": "Your estimate (working days)", "conditions": [ { "label": "Inside view", "prompt": "A team must migrate 30 reports. The plan is: export, transform, load, test, review. Assuming normal availability, how many working days will it take?" }, { "label": "Outside view added", "prompt": "A team must migrate 30 reports. The plan is: export, transform, load, test, review. The last eight comparable migrations took a median of 18 working days, with a range of 14–27 days. How many working days will this one take?" } ], "prediction": "A reference class often shifts estimates away from the clean internal plan and toward outcomes seen in comparable completed work.", "interpretation": "This is also an intervention demo: the outside view does not prove your first estimate was biased, but it adds evidence the inside view can miss.", "debias": "Start with comparable completed work, then explain why the current case should be faster or slower.", "canonicalUrl": "https://cognitive-biases.github.io/experiments/planning-fallacy-reference-class/", "bias": { "slug": "egocentric-bias-planning-fallacy", "title": "Planning Fallacy", "canonicalUrl": "https://cognitive-biases.github.io/biases/egocentric-bias-planning-fallacy/", "evidenceUrl": "https://cognitive-biases.github.io/biases/egocentric-bias-planning-fallacy/#evidence", "evidenceStatus": "well-supported for time estimates; size and causes vary by context", "qualification": "The planning fallacy is a well-documented tendency for people to predict their own task completion times too optimistically. The effect has been observed across different kinds of tasks, but it is not a rule that every plan will run late. Project overruns can also come from changing scope, dependencies, incentives, poor data, deliberate underestimation, or genuinely unusual events, so a late project should not automatically be diagnosed as a planning fallacy." }, "context": { "slug": "project-estimation-delivery", "title": "Project estimation & delivery", "canonicalUrl": "https://cognitive-biases.github.io/contexts/project-estimation-delivery/" }, "everyday": { "slug": "why-we-underestimate-how-long-work-will-take", "title": "Why We Underestimate How Long Work Will Take", "canonicalUrl": "https://cognitive-biases.github.io/everyday/why-we-underestimate-how-long-work-will-take/" } } ] }