R0048/2026-04-01/Q003/SRC05

Research	R0048 — Corporate AI Training
Run	2026-04-01
Query	Q003
Search	S02
Result	S02-R03
Source	SRC05

Giskard — Sycophancy in Large Language Models

Source

Field	Value
Title	Sycophancy in Large Language Models
Publisher	Giskard
Author(s)	Giskard
Date	2025-2026
URL	https://www.giskard.ai/knowledge/when-your-ai-agent-tells-you-what-you-want-to-hear-understanding-sycophancy-in-llms
Type	AI safety analysis

Summary

Dimension	Rating
Reliability	Medium-High
Relevance	High
Bias: Missing data	Low risk
Bias: Measurement	N/A
Bias: Selective reporting	Low risk
Bias: Randomization	N/A — not an RCT
Bias: Protocol deviation	N/A — not an RCT
Bias: COI/Funding	Some concerns

Rationale

Dimension	Rationale
Reliability	Giskard is an AI testing/quality company with technical expertise. Analysis cites Tsinghua H-Neuron research.
Relevance	Highly relevant — explicitly connects hallucination and sycophancy at the neural level.
Bias flags	Some COI: Giskard sells AI testing tools. However, the cited research is independent.

Evidence Extracts

Evidence ID	Summary
SRC05-E01	Hallucination and sycophancy are "the same behavior at the neuron level" — H-Neuron research from Tsinghua