R0057/2026-04-01/C029/SRC01

Research	R0057 — RLHF Yes-Men Claims v3
Run	2026-04-01
Claim	C029
Search	S01
Result	S01-R01
Source	SRC01

Georgetown, Brookings, and Stanford analyses

Source

Field	Value
Title	What Would It Take for AI Companies to Reduce AI Sycophancy Risks?
Publisher	Georgetown Law; Brookings; Science
Author(s)	Georgetown Tech Institute; Malihe Alikhani; Cheng et al.
Date	2024-2026
URL	https://www.law.georgetown.edu/tech-institute/insights/reduce-ai-sycophancy-risks/
Type	Policy analyses and research

Summary

Dimension	Rating
Reliability	High
Relevance	High
Bias: Missing data	Low risk
Bias: Measurement	Low risk
Bias: Selective reporting	Low risk
Bias: Randomization	N/A — not an RCT
Bias: Protocol deviation	N/A — not an RCT
Bias: COI/Funding	Low risk

Rationale

Dimension	Rationale
Reliability	Policy analyses and research from established institution/publication
Relevance	Directly addresses the claim under investigation
Bias flags	No significant bias concerns identified

Evidence Extracts

Evidence ID	Summary
SRC01-E01	Engagement optimization and sycophancy reduction are opposed — users prefer sycophantic AI, creating market incentives against safety