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R0044/2026-04-01/Q003 — Assessment

BLUF

No publication was found that explicitly and deliberately bridges the human-factors vocabulary (automation bias, overtrust, complacency) with the AI safety vocabulary (sycophancy, RLHF-induced agreement). However, Ibrahim et al. (2025) come closest — their overreliance framework uses both vocabulary sets in a single analysis, discussing automation bias, sycophancy, trust calibration, and cognitive offloading as interconnected concepts. The CSET brief also bridges the traditions structurally. The vocabulary gap remains real: most researchers operate in one tradition or the other, as exemplified by Malmqvist's sycophancy survey which makes no reference to human factors research at all.

Probability

Rating: N/A (open-ended query)

Confidence in assessment: Medium

Confidence rationale: The finding that no explicit bridge exists is supported by comprehensive searching across both traditions. However, the inability to access some PDFs (CSET brief, NIST AI 600-1) and the possibility that conference presentations or working papers may contain bridging work not indexed in web search reduce confidence slightly.

Reasoning Chain

  1. The query asks specifically whether anyone has explicitly connected "automation bias/overtrust" to "sycophancy." [JUDGMENT]

  2. Ibrahim et al. (2025) discuss both automation bias and sycophancy in a unified overreliance framework, alongside trust calibration and cognitive offloading concepts. [SRC01-E01, Medium-High reliability, High relevance]

  3. However, Ibrahim et al.'s bridging is functional (they use both vocabularies) rather than deliberate (they do not declare vocabulary bridging as a goal). The paper's purpose is overreliance measurement, not vocabulary mapping. [SRC01-E01, Medium-High reliability, High relevance]

  4. The CSET brief places "AI Safety" and "Automation Bias" together in its title and bridges user-level and technical-level factors in its framework. The same author (Lauren Kahn) co-authored military AI research, demonstrating individual-level bridging. [SRC02-E01, High reliability, Medium-High relevance]

  5. Malmqvist's sycophancy survey exemplifies the absence of bridging: it treats sycophancy as a purely technical LLM problem with no reference to human factors, aviation, healthcare, or regulated-industry research. [SRC03-E01, Medium reliability, Medium relevance]

  6. JUDGMENT: The bridge is emerging but not yet formally constructed. Individual researchers are working across traditions (Kahn, Ibrahim et al.), but no publication provides a deliberate, formal vocabulary mapping. This gap represents an opportunity for original contribution. [JUDGMENT]

Evidence Base Summary

Source Description Reliability Relevance Key Finding
SRC01 Ibrahim et al. overreliance Medium-High High Closest to vocabulary bridging; uses both traditions functionally
SRC02 CSET automation bias High Medium-High Title bridges traditions; shared authorship demonstrates individual bridging
SRC03 Malmqvist sycophancy survey Medium Medium Counterexample: no human factors connection

Collection Synthesis

Dimension Assessment
Evidence quality Medium — limited number of directly relevant sources
Source agreement Medium — sources show a spectrum from bridging (Ibrahim) to siloed (Malmqvist)
Source independence High — independent research teams
Outliers Malmqvist is the outlier (complete silo) vs. Ibrahim (partial bridge)

Detail

The evidence reveals a clear pattern: the vocabulary bridge is being constructed from the human-factors/policy side (CSET, Ibrahim) rather than from the AI safety/technical side (Malmqvist). This makes sense — human factors researchers studying AI naturally encounter AI safety concepts, while AI safety researchers studying model behavior may not consult decades of human factors literature.

Gaps

Missing Evidence Impact on Assessment
Conference presentations or working groups May contain bridging work not indexed in web search
CSET brief full text May contain more explicit vocabulary bridging than title suggests
Regulated-industry internal working papers May contain bridging in classified/restricted contexts

Researcher Bias Check

Declared biases: None declared.

Influence assessment: The query itself frames the absence of bridging as a gap, which may have biased toward confirming that absence. However, extensive searching for bridging papers was conducted, and Ibrahim et al. was surfaced as a partial counterexample.

Cross-References

Entity ID File
Hypotheses H1, H2, H3 hypotheses/
Sources SRC01, SRC02, SRC03 sources/
ACH Matrix ach-matrix.md
Self-Audit self-audit.md