Impact Bias
Updated 2026-08-05
INTRODUCTION
English translation pending.
CORE DEFINITION
Studied by Daniel Gilbert and colleagues in affective forecasting research, impact bias is the systematic overestimation of the duration and intensity of emotional reactions to future events. People expect a lottery win to make them happy for years and a serious injury to make them miserable permanently, yet emotional states return toward baseline far faster than predicted. The error comes largely from focalism, which concentrates attention on the event and ignores the other circumstances that will occupy daily life.
SCAFFOLDING EFFECT
Reduce cognitive load
- Discount the peak: reduce the predicted intensity and duration of any emotional reaction. - Expect the baseline: assume you will adapt faster than you currently believe. - Use history: calibrate the forecast against how you felt after similar past events.
Anchor fast decisions
Forecasts are built by simulating the focal event in isolation, so the imagined state dominates attention and no competing concerns are represented. Because real life continues to supply other demands, the actual emotional impact is diluted and adaptation proceeds quickly. The gap between the isolated simulation and the crowded reality produces the systematic overestimate.
MINIMUM ACTION
In progress 0/1Practice this model in one real situation:
account_treeGenealogyexpand_more
menu_bookReferencesexpand_more
Source support: Explicit
- en.wikipedia.orghttps://en.wikipedia.org/wiki/Impact_biasverified
PRIVATE NOTES · Only visible to you
SAVED Q&A
ENTRY Q&A · Private saving available
Ask with a clear boundary
thinkingmodels answers from published entry context only.
Your question is sent to thinkingmodels. The answer uses public entry context only.
RELATED MODELS