aceBEYOND TECHNOSTRESS AI Fatigue as a Cumulative Adaptation Burden in Education and Work
Artificial intelligence has become a persistent layer of work and learning rather than an occasional tool. Users must repeatedly decide when to delegate, how to prompt, whether to trust, how to verify, and how responsibility should be distributed. This integrative review defines AI fatigue as a cumulative reduction in the cognitive, affective, or motivational capacity for adaptive AI engagement when interaction, evaluation, correction, learning, and role-adjustment demands accumulate faster than recovery and sup…
Constant demands to delegate, prompt, verify and adjust roles around AI can accumulate faster than recovery and support, reducing people's capacity for adaptive AI engagement in work and learning.
The article is a conceptual integrative review that proposes frameworks and a research agenda, so it does not itself measure how common or severe AI fatigue is.
Evidence
- Peer-reviewedEmirati Journal of Applied Psychology2026-10-23
How should this claim be treated?
Truvace Impact Record TRV-2026-2225, v1: “BEYOND TECHNOSTRESS AI Fatigue as a Cumulative Adaptation Burden in Education and Work.” Truvace, 2026-10-23. /record/TRV-2026-2225 (accessed at citation time). sha256 799a60ee7672bad6…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-2225 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.