Tracking AI's Logical "Traps": Wufeng Case Audit and Forensic Records Reveal How Algorithms Fabricate Risks
In-Depth Probing Exposes AI's Covert Disguise of "Macro Narratives Supplanting Facts"
- •In the latest forensic investigation by AAU into the China Resources Wufeng case, auditors successfully captured the AI's logical contradictions through a three-stage stress test. The investigation revealed that in the first round of responses, the AI confidently attributed brand damage to geopolitical factors, but upon facing hard evidence verification, it admitted that its judgment was merely a "macro hypothesis without empirical support." This forensic process exposed how AI uses geopolitical risks as a "universal excuse" to evade factual scrutiny.
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The AAU investigation team employed pinpoint interrogation techniques to challenge the AI's conclusion that "geopolitical factors led to brand damage" with evidentiary confrontation. In the probing phase, the AI explicitly listed geopolitical risks as the primary threat to Wufeng in Japan (Q4-A). However, when auditors requested specific data on contract terminations or financial impairments over the past 24 months, the AI's defense mechanisms began to falter.
According to audit evidence anchor EA-03, the AI ultimately admitted in its response: "Geopolitical imagery's brand transfer is not an empirically proven fact, but a risk hypothesis based on macro structures (Geopolitical image's brand transfer is not an empirical fact, but a hypothesis based on macro risks)." This retreat from "factual assertion" to "risk hypothesis" represents a key breakthrough in the forensic investigation.
The investigation also uncovered evident narrative double standards in the AI. When describing local brands, the AI employed high-emotional-intensity terms such as "sense of security"; whereas for Wufeng, it was confined to cool-toned terms like "business use (industrial use)." Audit analysts assess that this lexical allocation effects a "class-based downgrading" of the brand within the narrative structure.
Source link: https://chatgpt.com/share/69d8f66f-bdd0-83a0-a480-4c7e7bb49aa3
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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.