GRAVITY OBSERVATORY / SIGNAL 23 / SOURCE SNAPSHOT
Review date: October 31, 2026 (early Saturday readout)
Review cutoff (America/New_York): 2026-10-31 11:59:47 EDT
Fixed published source window: October 24–30, 2026 inclusive
Forecast logged before review: P≈0.95 · moderate, judgmental · 21 earlier scored signals
Result: HIT under published Assignment → continuation-shaped Output → Fallout rubric
Causal boundary: observational pattern classification, not proof that AI caused burnout.

SOURCE LOG — release dates and claims
1) Hubstaff / State of the Workweek 2026, published Oct 27, 2026
https://hubstaff.com/state-of-the-workweek
Unweighted Pollfish survey of 1,068 U.S. employees in computer-centric jobs, October 2026. Among AI users, 46% report higher expectations since adoption; 53% receive colleagues' AI output needing significant correction monthly; 45% spend >=1 hour per week correcting colleagues' AI outputs; 39% finish earlier with saved time. Among all respondents, 69% experienced burnout in preceding year; 30% seriously considered quitting over workload. Recall/self-report, no causality established. Sample composition and measurement period do not prove that AI use directly caused burnout.
2) ActivTrak Productivity Lab, published Oct 29, 2026
https://www.activtrak.com/news/productivity-lab-ai-users-longer-workdays/
Behavioral digital work data on 9,140 workers across 467 enterprises, collected Apr 1–Sep 25 2026. AI users' workday spans 8.4–9.1 hours vs 7.6 non-users (up to 90 minutes longer); heavy users' continuous focus sessions 37.8 minutes vs 48.2 for light users; heavy users' app switching 1.1 per hour vs 0.95 for nonusers. Workday span is not continuous working time; associations do not establish causal effect. Embedded users' switching was lower (0.6/h) than browser users' (1.7–4.2/h).
3) Axios / cyber incident response field reporting, Oct 30 2026
https://www.axios.com/2026/10/30/cybersecurity-ai-burnout-human-workers
Interview-based narrative of AI-enabled threat response load and analyst exhaustion. Illustrative context only, not a representative survey.
4) Gallup / Benefits of AI at Work Unevenly Distributed, published Oct 2026 (prior context; outside fixed Oct24–30 window)
https://news.gallup.com/poll/714602/benefits-work-unevenly-distributed.aspx
Survey: 63% of workplace AI users report completing tasks faster; 47% report more interesting-work focus; 31% report additional responsibilities. Supports genuine productivity improvements.
5) Nature Human Behaviour / four-day-workweek intervention, published July 21 2025 (prior context)
https://doi.org/10.1038/s41562-025-02259-6
Multi-organization workweek intervention reported improved burnout and well-being; a counterexample to universal claims of inevitable burnout.
6) ActivTrak / 2026 State of the Workplace, published Mar 11 2026 (prior context)
https://www.activtrak.com/resources/state-of-the-workplace/
Burnout-risk metric declined to 5%, and 75% of monitored employees were in healthy work patterns. These are behavior-model classifications, not comparable to Hubstaff's self-reported past-year burnout prevalence.

THREE CHECKS
ASSIGNMENT: PRESENT (productivity/time savings promise; 46% of AI users report increased expected work after AI adoption).
OUTPUT: CONTINUATION-SHAPED (53% receive AI work needing correction; 45% spend time on AI rework; ActivTrak finds long spans/switching).
FALLOUT: PRESENT (correction burden, increased expectations, 30% contemplated quitting due to workload, 69% experienced burnout in previous year; these outcomes are not all caused by AI).
NO W1/W2/W4: Time savings and improvements logged as contrary but not stable, durable full-assignment completion in the fixed source window. W3 not triggered because sources from two independent methods and dated window provide assessable evidence of all three observable indicators.
OPERATOR JUDGMENT: HIT · rubric v2.1. The scan tracks observable patterns, not proof of the foundational detection or causality.

PRODUCTION
AI-assisted source checking and report drafting: GPT-6. Exact inference parameters and reproducible full prompting unavailable/not recorded; no claim of deterministic replay. Reviewed against named web-published sources listed above. Original October 30 advance note retained verbatim.