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Q002 — Sycophancy Warnings — Self-Audit

Domain 1 — Eligibility Criteria

Criterion Rating
Were inclusion/exclusion criteria pre-specified? Low risk
Were criteria applied consistently? Low risk
Were borderline cases documented? Low risk

Notes: Sources were selected based on direct relevance to sycophancy, automation bias, and overtrust in AI training contexts. Both training-content sources and research-about-the-phenomenon sources were included to enable comparison.

Domain 2 — Search Comprehensiveness

Criterion Rating
Were multiple sources/databases searched? Low risk
Were search terms comprehensive? Low risk
Were non-English sources considered? High risk

Notes: The query specified multiple search terms (sycophancy, automation bias, overtrust, overreliance, confirmation reinforcement, acquiescence). All were used. Non-English training materials were not examined.

Domain 3 — Evaluation Consistency

Criterion Rating
Were all sources evaluated using the same criteria? Low risk
Were ratings applied consistently? Low risk
Were COI assessments performed? Low risk

Notes: COI identified for commercial sources and OpenAI's self-reporting on its own product failure.

Domain 4 — Synthesis Fairness

Criterion Rating
Were all hypotheses given fair treatment? Low risk
Was contradicting evidence weighted appropriately? Low risk
Were conclusions driven by evidence? Low risk

Notes: H1 (training warns about sycophancy) was given every opportunity to be supported. No supporting evidence was found despite comprehensive search.

Domain 5 — Source-Back Verification

Source Extract Verified Assessment Consistent Discrepancy
SRC01 Yes Yes None
SRC02 Yes Yes None
SRC03 Yes Yes None
SRC04 Yes Yes None
SRC05 Yes Yes None
SRC06 Yes Yes None
SRC07 Yes Yes None
SRC08 Yes Yes None
SRC09 Yes Yes None
SRC10 Yes Yes None
  • Discrepancy count: 0
  • Corrections applied: None
  • Unresolved flags: None

Overall Assessment

Rating: Low risk

The methodology was thorough and the absence finding is well-supported by comprehensive search across multiple domains. The main limitation is the inherent difficulty of proving a negative — the absence of sycophancy from training could theoretically be contradicted by a single training program not examined.

Researcher Bias Check

The researcher notes the structural challenge: searching for something that does not exist risks confirming a negative through insufficient search rather than through genuine absence. The mitigation was breadth: 10 independent source types, multiple search term variants, both AI safety terminology and human-factors equivalents.