C001 — Self-Audit¶

ROBIS 4-Domain Audit¶

Rating: Low risk

Criterion	Assessment
Criteria defined before searching	Yes — looked for empirical studies measuring user preference for agreeable AI
Criteria stable throughout	Yes — no shift in what counted as relevant

Notes: Clear, testable claim with well-defined evidence criteria.

Rating: Some concerns

Criterion	Assessment
Multiple search strategies used	One primary search strategy
Searches designed to test each hypothesis	Yes — searched for both supporting and contradicting evidence
All results dispositioned	Yes
Source diversity achieved	Limited — primary source is one study

Notes: The evidence base centers on a single major study. Broader search for contradicting studies would strengthen the assessment.

Rating: Low risk

Criterion	Assessment
All sources scored using same framework	Yes
Evidence typed consistently	Yes
ACH matrix applied	Yes
Diagnosticity analysis performed	Yes

Notes: Consistent framework applied across all sources.

Rating: Low risk

Criterion	Assessment
All hypotheses given fair hearing	Yes — H2 distinguished from H1 based on metric precision
Contradictory evidence surfaced	Yes — the 13% vs 49% distinction noted
Confidence calibrated to evidence	Yes
Gaps acknowledged	Yes

Notes: Fair treatment of the nuance between AI behavior frequency and user preference.

Rating: Low risk

Source	Claim in Assessment	Source Actually Says	Match?
SRC01	AI affirms 49% more than humans	Study finds AI endorsed users 49% more than human respondents	Yes
SRC02	Models sided with wrong users 51% of time	Fortune reports "models still said the poster was right 51% of the time"	Yes

Discrepancies found: 0

Corrections applied: None needed

Unresolved flags: None

Notes: Source representations are accurate.

Overall risk of bias: Low risk

The main limitation is reliance on a single major study. The nuanced distinction between H1 and H2 is well-supported by the evidence.

Confirmation bias risk: The researcher's anti-sycophancy stance could lead to accepting the "50%" at face value without questioning the metric. Mitigated by explicitly distinguishing the endorsement frequency from user preference magnitude.
Anchoring bias: The round "50%" figure is memorable and may be preferred for narrative purposes over the more precise finding. Flagged in the assessment.