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Q001-H3 — Training Covers Limitations Superficially

Statement

Standard corporate AI training mentions AI limitations but treats them superficially — typically as brief warnings to "verify outputs" without explaining the mechanisms, spectrum, or behavioral dimensions of AI failure, leaving employees with a false sense of preparedness.

Status

Supported. The strongest evidence supports this hypothesis. Training programs widely exist and include limitation warnings, but coverage is generic, brief, principle-level, and disconnected from the practical skills needed to detect and manage AI failures.

Supporting Evidence

Evidence Summary
SRC01-E01 High-level overview; hallucination mentioned as risk category without depth
SRC02-E01 Awareness-level training; depth of limitation coverage unclear
SRC05-E01 Only 5 of 12 agencies acknowledge hallucinations despite 9x growth in AI use
SRC06-E01 82% train, 59% gap; generic, one-time, disconnected from practice
SRC07-E01 "Verify outputs" advice without explaining verification challenges
SRC08-E01 Legal mandate is flexible — "sufficient" undefined, no specific topics prescribed
SRC09-E01 Single-sentence hallucination warning; no explanation of failure mechanisms
SRC10-E01 >50% of workers find training inadequate

Contradicting Evidence

Evidence Summary
SRC03-E01 Deloitte academy is more comprehensive than typical training
SRC04-E01 UK playbook uses stronger language about limitations than most

Reasoning

Every source examined follows a similar pattern: limitations are acknowledged but not explained in depth. The universal advice is "verify AI outputs" but no training material found explains why verification is difficult — specifically, that AI may generate outputs that match user expectations, making them harder to detect as errors. The gap between awareness (training exists) and capability (skills gap persists) is the defining feature.

Relationship to Other Hypotheses

H3 synthesizes the valid elements of H1 (training exists) and H2 (training is inadequate) into a coherent explanation. The evidence strongly favors this nuanced position over either extreme.