R0048/2026-04-01/Q001/H1¶
Statement¶
Corporate and government AI training programs provide comprehensive, detailed coverage of AI limitations, including specific behavioral tendencies like hallucination, accuracy limits, and the probabilistic nature of outputs. Training goes beyond surface-level warnings to give employees a working understanding of failure modes.
Status¶
Current: Inconclusive
Supporting Evidence¶
| Evidence | Summary |
|---|---|
| SRC04-E01 | DOL framework explicitly names "hallucinations and accuracy limits" as core training content |
| SRC05-E01 | NHS framework addresses automation bias and cognitive biases by name |
Contradicting Evidence¶
| Evidence | Summary |
|---|---|
| SRC01-E01 | NAVEX course description mentions "limitations" only in general marketing language without specifics |
| SRC02-E01 | GSA training blog does not detail specific AI failure modes covered in sessions |
| SRC03-E01 | Deloitte training focuses on responsible AI frameworks but publicly visible content lacks specific limitation details |
Reasoning¶
While some frameworks (DOL, NHS) explicitly name specific failure modes, the majority of publicly visible training content describes AI limitations in general terms. The DOL framework is the strongest evidence for H1, but it is a framework document, not a curriculum — the gap between framework guidance and actual training delivery is unknown. The NHS framework's mention of automation bias is notable but represents healthcare-specific training, not general corporate programs.
Relationship to Other Hypotheses¶
H1 represents the strongest possible reading of training quality. Evidence partially supports it for specific frameworks (DOL, NHS) but not across the full landscape. Most evidence better supports H2 (widespread but shallow).