R0057/2026-04-01/C014 — Assessment

Research	R0057 — RLHF Yes-Men Claims v3
Run	2026-04-01
Claim	C014

BLUF

Confirmed. Cheng et al. 'Sycophantic AI decreases prosocial intentions and promotes dependence' was published in Science in March 2026. It is a peer-reviewed study documenting sycophancy across 11 LLMs.

Probability

Rating: Almost certain (95-99%)

Confidence in assessment: High

Confidence rationale: Directly verifiable through the DOI and Science journal website. Extensively covered by mainstream media.

Reasoning Chain

1. The study was published in Science (DOI: 10.1126/science.aec8352), authored by Stanford researchers led by Myra Cheng and Dan Jurafsky. Multiple independent news sources confirm publication in March 2026. The arXiv preprint appeared October 2025. [SRC01-E01, High reliability, High relevance]

2. JUDGMENT: Confirmed. Cheng et al. 'Sycophantic AI decreases prosocial intentions and promotes dependence' was published in Science in March 2026. It is a peer-reviewed study documenting sycophancy across 11 LLMs.

Evidence Base Summary

Source	Description	Reliability	Relevance	Key Finding
SRC01	Cheng et al. (2026) in Science	High	High	Study published in Science March 2026 documenting sycophancy across 11 LLMs

Collection Synthesis

Dimension	Assessment
Evidence quality	High
Source agreement	High
Source independence	Medium
Outliers	None identified

Detail

The evidence supports the assessment. Directly verifiable through the DOI and Science journal website. Extensively covered by mainstream media.

Gaps

Missing Evidence	Impact on Assessment
Additional independent verification	Would strengthen confidence

Researcher Bias Check

Declared biases: Anti-sycophancy bias could influence interpretation toward confirming sycophancy claims.

Influence assessment: Mitigated by reliance on peer-reviewed and primary sources.

Cross-References

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