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R0055/2026-04-01/C014 — Claim Definition

Claim as Received

A search of 29 sources across corporate training providers, consulting firms, government agencies, regulatory frameworks, law firm policy templates, and UX research organizations found zero warnings about sycophancy under any terminology

Claim as Clarified

A search of 29 sources across corporate training providers, consulting firms, government agencies, regulatory frameworks, law firm policy templates, and UX research organizations found zero warnings about sycophancy under any terminology

BLUF

Cannot independently verify. This claim describes the author's own research methodology and findings. The claim is about the absence of sycophancy warnings in specific sources the author searched. Independent verification would require replicating the same 29-source search, which was not feasible in this research run. The claim is plausible given that sycophancy awareness is recent and corporate training typically lags research.

Scope

  • Domain: AI alignment, sycophancy, enterprise AI
  • Timeframe: 2022-2026
  • Testability: Verifiable against published research and documentation

Assessment Summary

Probability: Likely (55-80%)

Confidence: Low

Hypothesis outcome: H2 prevails — see assessment for details.

[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 2026-10-01
Revisit trigger Any corporate training provider adding sycophancy/automation bias warnings to AI curricula