Imagine a team deciding whether future meetings should remain online or return to the office. People who choose online meetings tend to estimate that more colleagues would choose the same, while those who prefer attending in person assign greater support to that option. This tendency for our own choice to raise our estimate of how common it is is called the false-consensus effect.
It is not simply a narcissistic belief that “everyone is like me”. Our own reasons are easiest to retrieve, and the people around us are often similar to us, so a narrow sample can stand in for a wider society. We may also interpret our choice as a reasonable response to the circumstances and expect others facing those conditions to respond likewise. A 1985 meta-analysis combining 115 tests found a statistically reliable, moderate overall effect, alongside substantial variation between studies. The number of judgements and whether participants chose before or after estimating consensus affected the result. The effect is dependable, but not a fixed psychological constant.
One boundary is often missed. The classic definition compares how people making different choices estimate the prevalence of the same option; it does not guarantee that everyone literally overestimates the true percentage. Someone may still underestimate the size of their own side, but estimate it as larger than a person on the other side does. Correcting the bias therefore does not mean assuming “I must be wrong”. It means treating personal experience as one sample, seeking data from different groups, and specifying exactly which population an estimate concerns.
https://doi.org/10.1016/0022-1031(77)90049-X
https://doi.org/10.1016/0022-1031(85)90020-4
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