Selection Bias
Your sample isn't random.
"Surveys of your best customers are not surveys of your customers."
What is Selection Bias? Your sample isn't random. Strategy decisions distorted by non-random data.
Customer feedback dominated by power users.
Strategy decisions distorted by non-random data.
Always ask: 'Who's not in this data?'
Use the model. Pick the move.
Your sample isn't random. You've just seen this: Customer feedback dominated by power users. Which lever does the model recommend?
Pick a lever. There are no neutral ones — every incentive funds a behavior somewhere.
Pick a reaction to Selection Bias
One tap. We'll point you at the most useful next surface based on how this hits.
The full taxonomy entry
Every concept in the Atlas uses the same structure — so Selection Bias can be compared, recombined, and cited like an element on a periodic table.
- Business
- Leadership
- Government
- Healthcare
- Education
- Sales
- Marketing
- AI
- Negotiation
- Media
- Public Policy
- Relationships
- Where in our org would Selection Bias most often show up unnoticed?
- Which metric, ritual, or contract clause quietly rewards Selection Bias?
- If we removed every payoff for Selection Bias, what behavior would replace it?
- Who benefits when Selection Bias persists — and who pays the cost?
- People defend the status quo using the language of selection bias.
- Decisions cluster around the easiest narrative rather than the strongest evidence.
- New data changes the slide deck but not the decision.
- Anyone naming the pattern is treated as the problem.
Every Atlas entry is a node in a knowledge graph. See the related rail below to follow the connections.
See Selection Bias through 2 lenses
Each layer of the Incentives OS reframes this concept with its own thinkers, vocabulary, and diagnostic question.
Do you actually know Selection Bias?
Three quick questions. Result is saved into your review streak — come back when the term is due to lock it in.
Which best describes Selection Bias?
Worked example, counter-example & concept map
On-demand AI analysis grounded in the Lab's research. Cached on your device after first run.
When you encounter Selection Bias, your prefrontal cortex has to do extra work to override the automatic response — and that override budget is finite.
Executive control, planning, impulse override, working memory, System 2. First thing to go offline under stress, fatigue, or low blood sugar. Why your 4pm decisions are worse than your 9am ones.
See Prefrontal in the Brain Atlas →Picked for you, from the Atlas
Ranked by shared learning paths, overlapping chips, and what you've saved.
Ignoring general statistics in favor of specific, vivid information.
Posterior = (likelihood × prior) / evidence.
Update beliefs in proportion to the strength of new evidence.
Start with a prior; update with new evidence.
Novices experiencing early success, often due to variance and small samples.
High-impact, hard-to-predict, retrospectively explainable events.
Send the card, not just the link
A pre-rendered social card with the title, eyebrow, and URL. Copy the link, post it anywhere, or download the SVG for slides.
More definitions to follow
Every term in the Atlas connects to a dozen others. Pick any of these and see where it takes you.
AI bolted onto existing workflows to look forward-leaning.
Cryptographic tracking of content origin.
Insights from one domain don't automatically transfer to another.
Presenting two options as the only possibilities when more exist.
People change behavior when they know they are being observed.
Bet size optimized to maximize long-run growth without ruin.
Spreading limited resources evenly across options regardless of merit.
An ordering of options by expected satisfaction — often constructed in the moment rather than retrieved.
Federal focus on technical milestones over commercial outcomes creates 'professional applicants.'
Higher-level properties depend on, but aren't reducible to, lower-level ones. Identical bases → identical higher properties.
Buddhist-derived principle: applying the right amount of effort, neither forcing nor slacking — taught by Shauna Shapiro and Rick Hanson.
Claiming something is true or better because most people believe it.