Coaching practices for How to Check Survivorship Bias
Describe almost anything you are working through and IX Coach finds the practices whose real-world fit is closest. For How to Check Survivorship Bias, these are the strongest matches in the current practice library.
Does this sound like the set of challenges you might be facing?
- I’ve decided the lesson from this success is “focus narrow” or “go big”
- All I ever hear from are the ones who made it
- I’m about to launch into something and I keep estimating how it’ll go off the handful of vivid winners in my head
- I keep studying how the winners won, but it’s a thin lesson
- My whole feed and reading list is wall-to-wall success stories
Practices that may help
- Survivorship Bias: Learning from What You Can’t See
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return. - Steelman the strategy opposite to the successful one
Before adopting a lesson from a success story, build the best possible case for the opposite approach.
Survivorship Bias: Learning from What You Can’t See - Actively seek out the failures you aren’t seeing
Look for the people who tried the same thing and didn’t make it through.
Survivorship Bias: Learning from What You Can’t See - Choose the right reference class for any prediction
Find the statistical base rate for the category your decision belongs to — not just the inspiring examples.
Survivorship Bias: Learning from What You Can’t See - Build a personal library of failure post-mortems
Deliberately collect, read, and learn from failure case studies in your domain.
Survivorship Bias: Learning from What You Can’t See - Audit whether your information sources systematically favor survivors
Check whether the media, advice, and communities you consume are filtered toward successes.
Survivorship Bias: Learning from What You Can’t See - Ask for the failure rate before celebrating the success rate
Before drawing lessons from any success story, ask: out of how many attempts did this succeed?
Survivorship Bias: Learning from What You Can’t See - Actively seek disconfirming cases
When researching base rates, specifically look for cases where things went badly — failure cases are underrepresented in natural memory.
The Outside View - Always identify the denominator when evaluating risk or success
When a number or story is striking, ask: "Out of how many total cases?"
Base-Rate Neglect: Why We Ignore the Odds - Actively seek disconfirming evidence
Deliberately look for evidence that your current belief is wrong.
Superforecasting
Related concerns
- How Many Tried Survivorship
Look for the people who tried the same thing and didn’t make it through.
Actively seek out the failures you aren’t seeing
- Survivorship Bias Learning From What You Can T See At Work
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Survivorship Bias Learning From What You Can T See During A Big Change
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Survivorship Bias Learning From What You Can T See When Starting Out
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
- Media Survivorship Bias
Check whether the media, advice, and communities you consume are filtered toward successes.
Audit whether your information sources systematically favor survivors
- Survivorship Bias Learning From What You Can T See During Conflict
Survivorship bias is the error of drawing conclusions only from the cases that made it through a filter — winners, survivors, visible successes — while the failures that never appear are silently excluded. The clearest historical example is Abraham Wald’s WWII aircraft study: the military wanted to armor the bullet holes they saw on returning planes; Wald showed they should armor where they saw no damage, because planes hit there didn’t return.
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