R0044/2026-04-01/Q002/S03
WebSearch — Automation bias in military and professional AI decision-making
Summary
| Field |
Value |
| Source/Database |
WebSearch |
| Query terms |
'acquiescence problem AI systems "calibrated trust" "inappropriate trust" military defense standards' |
| Filters |
None |
| Results returned |
10 |
| Results selected |
1 |
| Results rejected |
9 |
Selected Results
Rejected Results
| Result |
Title |
URL |
Rationale |
| S03-R02 |
Various military AI trust articles (9 results) |
Various |
Included: Brookings trust analysis, Stanford CISAC, War on the Rocks, Oxford academic, and others. All address military AI trust but either focus on human-side trust calibration or do not document specific incidents of AI agreement causing harm. |
Notes
Military AI literature extensively discusses trust calibration and automation bias but focuses on human over-reliance on AI recommendations rather than AI systems adjusting output to match operator expectations. The Horowitz & Kahn study was the most relevant empirical contribution.