C029 — Claim Definition¶


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

Claim as Received¶

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

Claim as Clarified¶

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.

Scope¶

Domain: AI sycophancy research
Timeframe: Current (2024-2026)
Testability: Verifiable against published research and public records

Assessment Summary¶

Probability: Very likely (80-95%)

Confidence: High

Hypothesis outcome: H1 is supported based on available evidence.

[Full assessment in assessment.md.]

Status¶

Field	Value
Date created	2026-04-01
Date completed	2026-04-01
Researcher profile	Phillip Moore
Prompt version	Unified Research Methodology v1
Revisit by	2027-04-01
Revisit trigger	If AI vendors demonstrate that engagement and sycophancy reduction can be aligned