Fear of missing out on AI is linked to anxiety and depression

Artificial intelligence is reshaping the modern workplace, but it is also generating a new kind of anxiety about being left behind. A recent study published in Telematics and Informatics Reports found that an emerging condition called the fear of missing out on artificial intelligence is linked to higher levels of depression and anxiety. Enhancing a person’s practical understanding of these tools appears to buffer against this psychological burden.

As generative artificial intelligence systems become integrated into daily life, basic proficiency with the technology is increasingly tied to job security. This rapid transition has introduced new psychological pressures. Researchers refer to one specific anxiety as the fear of missing out on artificial intelligence. This concept describes the worry that a person’s technological skills or access are lagging behind their peers, potentially costing them future social or economic benefits.

Chi-Lin Yu, a psychology researcher at Oklahoma State University, led the investigation into this phenomenon. Previous research had established a scale to measure this specific fear in Chinese populations. Yu sought to validate an English version of the questionnaire and determine how widespread the anxiety is in the United States.

The research also explored whether practical knowledge of artificial intelligence or general feelings about the technology influenced these fears. Finally, the study examined whether this modern anxiety is tied to broader mental health consequences. Measuring these impacts provides insight into how rapid technological shifts create hidden burdens for the public.

To answer these questions, Yu surveyed 557 adults in the United States using an online research platform. The participant pool was selected to approximate national census benchmarks for age, gender, and race. Participants first completed a 26-item questionnaire designed to measure their fear of missing out on artificial intelligence.

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The survey asked participants to rate their agreement with various anxiety-related statements. For instance, questions asked if respondents were exhausted by the energy required to keep up with the field, or if they felt anxious seeing others use the tools skillfully.

The original Chinese survey grouped these fears into three distinct categories: worries about falling behind, concerns about lacking access, and anxiety about missing out on economic rewards. Yu found that for the English-speaking sample, these specific concerns merged into one dominant, generalized fear.

The results showed that most people are not currently experiencing high levels of this generalized fear. A meaningful minority, however, reported elevated anxiety. More than one in nine participants scored high on the overall scale.

When looking at specific questions, the distress was even more common. Nearly forty percent of the respondents agreed that they were concerned the technology was developing faster than they expected. Demographic analysis revealed that younger adults and women were more likely to report these fears. Income and educational background did not alter the results, suggesting the anxiety spans various socioeconomic classes.

Next, the study measured the participants’ objective knowledge and their subjective attitudes toward the technology. To assess literacy, participants took a 20-item multiple-choice test evaluating their practical competence. The test covered topics like how large language models work, data privacy, and algorithmic bias. A large language model is the underlying architecture that powers popular chatbots by predicting and generating human-like text.

To measure attitudes, participants rated their excitement or concern regarding the potential benefits and risks of the technology. The survey captured both positive feelings about utility and negative feelings about issues like loss of control. Yu then analyzed how these two factors interacted with the fear of missing out.

The analysis revealed that actual literacy was the central factor in shaping a person’s fear. Participants who scored higher on the practical knowledge test reported lower levels of anxiety about falling behind. General attitudes about whether artificial intelligence is good or bad did not predict a person’s fear of missing out. Building competence with the tools served as a protective buffer, while a lack of understanding made individuals more vulnerable to feeling left behind.

These findings suggest a practical roadmap for addressing the anxiety in professional and educational settings. If a lack of literacy drives the fear of missing out, workplaces and schools could implement introductory training programs to build confidence. Learning simple tasks, such as generating meeting summaries or drafting emails, might be enough to ease the psychological burden. Shifting the public focus from the overwhelming speed of technological progress to accessible, everyday learning could help protect mental health.

The final portion of the study investigated how this specific technological anxiety relates to overall well-being. Participants completed standard clinical questionnaires measuring how often they experienced symptoms of depression and generalized anxiety over the previous two weeks. They also answered a survey assessing their general life satisfaction.

The data revealed a direct link between the fear of missing out on artificial intelligence and broader mental health struggles. Higher scores on the technological anxiety scale predicted greater symptoms of both anxiety and depression. The increase in depressive symptoms, in turn, predicted a drop in the participants’ overall life satisfaction. Experiencing this specialized fear acts as a psychological weight associated with poorer mental health.

While the findings highlight a new digital stressor, the research relies on data collected at a single point in time. This approach means the study can identify strong patterns but cannot definitively prove that the technological fear causes the depression or anxiety symptoms. It is possible that individuals who already experience higher levels of depression are simply more prone to worrying about falling behind. Future research will need to track participants over time or test whether educational interventions directly reduce these anxieties.

Additionally, the survey focused exclusively on adults in the United States using an online platform. Because these participants might be more comfortable with technology than the general public, the prevalence of these fears might look different in other populations. Different cultures might also frame technological advancement as either an opportunity or a threat, which could alter how people experience this psychological burden. Tracking these differences globally will help determine how the rapid evolution of digital tools impacts public health.

The study, “Fear of missing out on AI: A psychological cost of technological revolution,” was authored by Chi-Lin Yu.