Researcher Chi-Lin Yu from Oklahoma State University published a paper in the journal Telematics and Informatics Reports titled “Fear of missing out on AI: A psychological cost of technological revolution”: the fear of missing out on AI (FOMO-AI) is statistically linked to higher anxiety and depression symptoms. The survey included 557 American adults.
What happened
According to the survey data, more than one in nine respondents scored high on the overall fear scale, and about 40% agreed that technology is developing faster than they expected. Younger adults and women are more affected, while income and education do not play a role. Depression symptoms were linked to lower life satisfaction. It was also found that a 20-item test on knowledge of how large language models work, data privacy, and algorithmic bias is linked to lower levels of fear, while general attitudes toward AI are not linked to it.
Context
The work belongs to the field of human-AI interaction and psychometrics: this is the first quantitative measurement of the FOMO-AI construct, not an evaluation of any model, so architecture, benchmarks, and training methods are not addressed here. Methodologically, this is a cross-sectional survey: data were collected once on an online sample selected by age, gender, and race to match census data, using a 26-item English version of the FOMO-AI scale, validated on the Chinese original. The novelty of the study lies in the construct itself and its measurement, that is, in the emergence of an open, measurable marker.
Why this matters for the industry
The psychological cost of the pace of AI adoption has become a measurable phenomenon: the FOMO-AI scale is the first public marker of stress in teams linked to technological shifts. For providers of corporate and academic AI training, this changes the argumentation: the buyer shifts from productivity to HR and corporate wellness, and basic practical skills like generating email drafts and summarizing meetings are linked to reduced employee anxiety, and HR gets a named metric for assessing team vulnerability. For production infrastructure, the news is neutral: there are no new models, APIs, prices, or latency requirements in the sources.
Why this matters for users
The main practical takeaway — protection against the anxiety “I’m falling behind on AI” — is real skills, not the attitude “AI is bad/good”: the better a person understands how LLMs work and what specific tools can do, the less they fear. If you notice obsessive anxiety due to AI news, it’s not paranoia: such fear has measurable psychological consequences, and it can be reduced through applied learning.
What is still unknown / limitations
The direction of causality in the discovered links is not established: the link “knowledge about LLMs is linked to less fear” is a correlation, not a proven mechanism, and it is possible that people with lower anxiety simply learn tools more often. The sample is limited to 557 American adults from a single online survey, so the transfer of conclusions to other countries, cultures, and age groups is not yet confirmed. Replications on other samples and experimental or longitudinal checks of the link between learning and reducing FOMO-AI are still ahead.
Sources
- PsyPost — Fear of missing out on AI is linked to anxiety and depression
- Chi-Lin Yu, Telematics and Informatics Reports — article on ScienceDirect
Author
Look at AI, editorial team