Survivorship Bias

Survivorship bias is a common cognitive bias that occurs when people evaluate situations based only on the individuals or data that have "survived" a selection process—such as successful, visible, or existing cases—while overlooking those that were eliminated, failed, or are no longer visible. This leads to incorrect conclusions about overall trends. As a result, people tend to overestimate the likelihood of success, underestimate the risks of failure, and draw overly generalized lessons from a limited number of success stories. At its core, survivorship bias arises from incomplete or non-random sampling: we only see the "tip of the iceberg"—the visible survivors—while missing the vast submerged portion of failures.