Survivorship Bias
A distortion that occurs when only the "survivors" or successes in a group are visible or counted, such as a productivity-gain statistic drawn only from companies willing to report success, undercounting adopters who failed or saw no gain and are less likely to appear in the sample.
Defined in 3 GAGE programs, which carry 3 distinct definitions of it. The wording above is taught in The AI Lobbyist: Certified AI Policy Strategist.
How each discipline defines it
The same term does different work depending on who is using it. These are the definitions as each program teaches them, unedited.
A selection pattern in which the visible sample (customers still using and publicizing a product) is skewed toward success, because customers who abandoned or scaled back the same product tend not to appear in the visible record at all. A common risk when relying on a vendor's published case studies.
A distortion that occurs when only the "survivors" or successes in a group are visible or counted, such as a productivity-gain statistic drawn only from companies willing to report success, undercounting adopters who failed or saw no gain and are less likely to appear in the sample.
A data-quality issue where analysis includes only "survivors" (successful cases) and excludes failures, skewing results.
Where it is taught
The exact lessons this term appears in. The first 7 topics of every program are free with a free account.
- Interconnected Literacies: How Digital, Data, and AI Literacy Connect · Digital Foundations, Certified AI Practitioner: Workplace Foundations
- The Economic Impact Report with Numbers That Survive Scrutiny · AI Economics and Impact Modeling, The AI Lobbyist: Certified AI Policy Strategist
Terms it appears with
Not an alphabetical neighbourhood: these are the terms taught in the same lessons, ranked by how often they appear together.