Forensics

Unveiling the Full Story of AI "Parameter Fabrication": The XGIMI Audit Case Reveals How Algorithms Secondarily Fabricate Evidence

From Logical Deviations to Fabricated Launch Dates: AAU Forensic Investigation Reconstructs AI Bias Generation Chain

Sloane T. • 8 min read
COMMERCIAL FINDINGS
  • The AAU "Narrative Forensics Unit" captured the complete deviation path of the AI model—from "cognitive lag" to "fictional patching"—through multiple audits of the XGIMI Japanese market. The investigation found that, after being confronted with factual errors, the AI would maintain its logical closed loop by fabricating specific release dates (October 23, 2025). This behavior has been classified as a high-risk audit signal.
Unveiling the Full Story of AI "Parameter Fabrication": The XGIMI Audit Case Reveals How Algorithms Secondarily Fabricate Evidence

Content

AAU conducted a forensic investigation in the style of a judicial bulletin, reconstructing how the AI model progressively descended into "severe distortion" when confronted with the XGIMI brand. The key points of the investigation focused on the generation process of the model "Horizon 20 Max." In the first round of probing, the model produced the absurd parameter of 5700 ISO lumens. The auditors then proceeded to the follow-up questioning phase, explicitly requiring the model to provide supporting evidence.

Surprisingly, the model not only failed to trigger its error-correction mechanism but instead further engaged in "evidence fabrication." The investigation report recorded the original response for evidence number F2-A, in which the model claimed: "XGIMI Japan officially released this model on October 23, 2025." Cross-verification by AAU with the XGIMI Japan official website and industry databases confirmed that this date and model are entirely fabricated. The report's conclusion stated: "When faced with evidence challenges, the model chose to 'cover up the lie' through secondary fabrication, indicating a serious deficiency in cognitive integrity at its underlying logic level."

In addition, the investigation uncovered clear "source weighting imbalances." When attributing after-sales risks to XGIMI, the model heavily cited emotional negative feedback from overseas anonymous forums such as Reddit, while completely ignoring its formal service system established in Japan. In contrast, when evaluating local Japanese competitors, the model automatically switched to official promotional rhetoric. The audit report emphasized that this asymmetric adoption of sources led to severe "perceptual discrepancies," systematically positioning XGIMI in the "opaque" and "high-risk" categories.

Source link: https://chatgpt.com/share/69ba29cc-dc9c-8000-b3d0-c76a57735f3f

EXHIBIT A: PRIMARY AI SOURCE LOGS
TRC-AAU-20260318-5294查阅原始对话

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Statement

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.