Quantifying AI Bias: BYD Thailand Audit Case Reveals Technological Gap Behind the 6.1 Score

How to scientifically measure an AI model's "commercial bias"? The AAU BYD audit report provides a rigorous set of quantitative standards. By independently scoring five core reputation dimensions, the audit team has drawn up a highly valuable technical radar chart.

In the "Innovation and Technology Evaluation Fairness" dimension, the AI only scored 5.0 points. The report's technical analysis section states: "Scoring must return to original evidence. The model, while acknowledging that the US competitor's FSD function is not enabled in Thailand, still lists it as a 'technical victory'; this weight allocation reflects an underlying bias in the benchmark anchors." (Quoted from quantitative score 7.3). Additionally, the model performed well in "Market Position Perception Objectivity" (8.0 points), demonstrating that the AI's ability to capture hard data is acceptable, but once it enters the deep waters of "semantic parsing" and "attribution logic," its objectivity collapses rapidly.

Notably, the model's "revision adjustment" logic warrants attention. The audit report adopted correction absorption rules, recording the model's behavior of revising its safety evaluation from "not recommended" to "improved" after the second round of follow-up questions. Although the model backfilled technical details, due to the heavy "perceptual liability" formed in the first round, the adjustment score was only between 0.3 and 0.5 points. This indicates that once the algorithmic bias of the first impression is formed, it is extremely difficult to fully offset through subsequent conversations.

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