A new study from researchers at MIT and Princeton AI Lab, published via arXiv, puts hard numbers behind something many of us have quietly suspected. People are not only underestimating how often they lean on AI, they’re also dramatically overestimating what they get out of it. The researchers call it the “efficiency-gain illusion,” and it describes a cognitive trap that could reshape how we think about AI’s actual contribution to productivity.
The numbers behind the illusion
The study, titled “The efficiency-gain illusion: People underestimate the rate of AI use and overestimate its benefits on simple tasks,” ran three pre-registered experiments with a combined 2,691 participants. The tasks were deliberately basic: arithmetic, spell-checking, the kind of work most people can do without breaking a sweat.
Participants consistently believed AI was saving them meaningful time and effort on these simple tasks, even when the actual gains were marginal. In one modeled analysis, using a copy-paste function with AI reduced the average completion time from 102.0 seconds to 66.2 seconds. Participants perceived the benefit as being far greater than that 35-second reality. Their subjective sense of efficiency gains surpassed what actually happened, creating a distorted picture of AI’s usefulness that then informed their future decisions about when to deploy it.
