C029¶


Research	R0057 — RLHF Yes-Men Claims v3
Run	2026-04-01
Claim	C029

Claim: Consumer AI engagement optimization and sycophancy reduction are directly opposed — documented by Georgetown Law, Brookings, Stanford/CMU, and multiple independent researchers.

BLUF: Confirmed. Georgetown Law documents that firms may resist sycophancy safeguards that run contrary to monetization models. Brookings (Alikhani) identifies positive feedback loops from sycophancy. Stanford (Cheng et al.) shows users prefer sycophantic AI, creating perverse incentives for developers.

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	Engagement and sycophancy reduction are directly opposed	Supported
H2	There is tension but not absolute opposition	Not supported
H3	Engagement and sycophancy reduction can coexist	Eliminated

Searches¶

ID	Target	Results	Selected
S01	Consumer AI engagement optimization sycophancy reduction opposed Georgetown Brookings Stanford	10	1

Sources¶

Source	Description	Reliability	Relevance
SRC01	Georgetown, Brookings, and Stanford analyses	High	High

Revisit Triggers¶

If AI vendors demonstrate that engagement and sycophancy reduction can be aligned