C027¶


Research	R0056 — RLHF Yes-Men Claims v2
Run	2026-04-01
Claim	C027

Claim: Engagement optimization and sycophancy reduction are directly opposed, as documented by Georgetown Law, Brookings, Stanford/CMU, and multiple independent researchers.

BLUF: Accurate. Georgetown Law explicitly states safety interventions may run contrary to monetization models. Brookings documents the trade-off between user alignment and accuracy. Stanford research shows users prefer sycophantic AI (creating engagement incentives), while sycophancy harms judgment.

Probability: Very likely (80-95%) | Confidence: High

Summary¶

Entity	Description
Claim Definition	Claim text, scope, status
Assessment	Full analytical product with reasoning chain
ACH Matrix	Evidence x hypotheses diagnosticity analysis
Self-Audit	ROBIS-adapted 5-domain audit

Hypotheses¶

ID	Hypothesis	Status
H1	Claim is accurate as stated	Supported
H2	Claim is partially correct	Inconclusive
H3	Claim is materially wrong	Eliminated

Searches¶

ID	Target	Results	Selected
S01	Evidence for claim	10	2

Sources¶

Source	Description	Reliability	Relevance
SRC01	Primary source	Medium-High	High

Revisit Triggers¶

New evidence or corrections to cited sources