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R0048/2026-04-01/Q002/SRC01/E01

Research R0048 — Corporate AI Training
Run 2026-04-01
Query Q002
Source SRC01
Evidence SRC01-E01
Type Analytical

Georgetown policy analysis — sycophancy as unaddressed policy risk

URL: https://www.law.georgetown.edu/tech-institute/insights/reduce-ai-sycophancy-risks/

Extract

Georgetown Tech Institute analysis identifies four categories of intervention needed:

  1. Product-level changes: Product recalls and design modifications
  2. Accountability & governance: Internal oversight structures
  3. Audits & independent evaluation: Third-party assessments
  4. Public disclosures: "Real-time disclosure of safety data, clear and consistent criteria, and longitudinal measures"

Key findings: - OpenAI acknowledges sycophancy exists but lacks sufficient transparency - Mental health professionals are involved in post-hoc evaluation only, not model training - 44 state attorneys general are demanding accountability, signaling self-regulation is insufficient - No mention of employee training as a current or recommended mitigation strategy

The framing as a product-safety and regulation problem (rather than a training problem) implicitly confirms that sycophancy is not being addressed through user education.

Relevance to Hypotheses

Hypothesis Relationship Strength
H1 Contradicts If training addressed sycophancy, the paper would not need to propose these interventions
H2 Supports The paper's silence on training as a current mitigation supports the finding that adjacent concepts exist but direct coverage does not
H3 Supports Framing as entirely a product/regulation problem implies training does not address it at all

Context

Georgetown's analysis positions sycophancy as a product safety problem requiring regulatory intervention, not as a user education gap. This framing is itself evidence that sycophancy awareness is not considered a training topic by policy experts.