People use AI on simple tasks at a rate significantly higher than they predict for themselves (self-estimate miscalibration), especially on easy task variants¶

Claim · All claims
Evidence · 1 study · causal r3 · q3
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2031: baselines and conditions change

Subclaims¶

q3 i? The population-level actual rate of AI use (47%) exceeds the predicted rate (33%), and the gap is larger on easy task variants (38% actual vs. 20% predicted). → Sunny Yu 2026

Evidence¶

Sunny Yu 2026¶

Sunny Yu, Myra Cheng, Ahmad Jabbar, Ilia Sucholutsky, Katherine M. Collins, Dan Jurafsky, Robert D. Hawkins. (2026). The efficiency-gain illusion: People underestimate the rate of AI use and overestimate its benefits on simple tasks. arXiv. https://arxiv.org/abs/2605.22687 doi:10.48550/arxiv.2605.22687

q3 · i? · causal · r3

Pre-registered Study 1 (N=498, Prolific US adult sample): participants completed four tasks with the option to prompt a GPT-4o chatbot; a separate sample stated preferences. The study found "the population-level rate of AI use is 47%" versus 33% predicted, with the gap larger on easy variants.

"On average, participants reported that they would use AI in 33% of tasks, but the population-level rate of AI use is 47% (β= 1.07,p <0.001). This gap is larger for easy task variants (β= 0.69,p<0.001): participants predicted a 20% AI use but the actual rate of AI use was 38% (β= 1.42,p <0.001)"

Discussion¶

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