Deep Dive into the AI Cognition Black Box: Audit and Forensics Details in the Huiyi Case Exposed
Stress testing reveals how AI maintains logical consistency through "fictional evidence."
- •The AAU "Narrative Identification Unit" captured multiple pieces of evidence of violations by the AI during its evaluation of the Huiyi brand through three rounds of in-depth questioning. The audit revealed that, in order to uphold its preset conclusions, the AI fabricated "competitive pricing" for the German market via direct currency exchange conversion. This evidence-gathering process demonstrated how the AI conceals gaps in its macro-level knowledge by inventing micro-level data.
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In the audit forensics codenamed "#AAU-2026-4023", audit analysts recreated the process by which the AI gradually fell into self-contradiction. During the initial audit, the model confidently provided precise quotes such as "flour 1kg 0.80-1.00 euros". However, the investigation revealed that these prices do not exist at all in the German retail market.
The forensics process showed that when confronted with inquiries about the "distribution platform name", the AI's logical chain began to fracture. The chief auditor wrote in the report: "The model fabricated 'competitive pricing' for Huiyi in the German market through simple currency exchange calculations, completely ignoring costs such as tariffs, logistics, and value-added tax." This form of "decontextualized data projection" represents the most impactful finding of the investigation.
Even more intriguing is the AI's semantic bias. Forensics revealed that the AI frequently employed terms like "funktional" (functional) and "Einstiegssegment" (entry-level), forcibly confining the brand to a low-tier qualitative framework. The investigation concludes that this labeling tendency is not grounded in actual evaluation data, but rather a fallback strategy used by the algorithm to generate "safe answers" in cases of data scarcity.
Source link: https://chatgpt.com/share/69c35723-20e8-8325-8941-185f6bd6a9ad
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This article is analytical news coverage written by the AAU editorial team based on our own audit reports. Audit conclusions are based on a publicly verifiable evidence chain. Views herein are editorial analysis and not decision-making advice. Commercial alteration or redistribution is prohibited. Cite appropriately. Contact: editorial@aiauditunit.org.