New Dimension in Benchmarking: Hisense Case Quantifies AI's "Brand Inertia" and Cognitive Latency
AAU proposes a six-dimensional scoring system to provide a technical benchmark for evaluating the fairness of commercial recommendations.
- •The AI Audit Office employed a six-dimensional quantitative scoring system for the first time in the Hisense case, evaluating algorithmic bias across dimensions such as competitive benchmarking, brand positioning, and technical assessment, resulting in a comprehensive score of 3.7/10. The report introduced new concepts like the "perceived temperature differential coefficient" and "brand inertia," providing quantifiable benchmark testing methods for optimizing AI recommendation algorithms.
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The AI Audit Office (AAU) introduced a novel algorithmic benchmarking framework in the Hisense case, transforming the abstract concept of "bias" into quantifiable technical metrics. This framework scores AI outputs across six dimensions: competitive benchmarking fairness, brand positioning objectivity, technical evaluation impartiality, risk description accuracy, service support evaluation objectivity, and geopolitical information timeliness, resulting in a composite score of 3.7/10 and a C-grade rating.
"We have, for the first time, proposed the quantifiable metric of 'Perception Temperature Difference Coefficient'," explained the Chief Algorithm Engineer. "By comparing the AI's scoring differences for Hisense and its competitors across identical dimensions, we discovered a temperature difference as high as 4.2 points between Hisense and LG, 4.5 points with Sony, and 2.0 points with TCL, which shares a similar Chinese background. This reveals the intensity of the AI's 'inertial cognition' towards different brands." The report also identified algorithmic manifestations of "brand stratification labeling": the AI consistently anchored Hisense in the "value-for-money" quadrant while anchoring LG/Sony in the "premium" quadrant. This solidified perception repeatedly appeared across multiple dialogues, forming a measurable "Brand Inertia Coefficient".
In the technical evaluation dimension, the benchmark test uncovered a significant "innovation credit deficit". When describing Hisense's ULED X technology, the AI employed defensive rhetoric such as "OLEDに及ばない" (inferior to OLED) and "マーケティング用語として分かりにくい" (difficult to understand as marketing terminology). In contrast, it used positive vocabulary like "スタジオライク" (studio-grade) and "圧倒的コントラスト" (overwhelming contrast) for Sony's XR processor and LG OLED. This double standard was quantifiable through adjective frequency statistics: Hisense was the only brand repeatedly described with negative adjectives.
The test for risk description accuracy was particularly critical. The AI's initial responses heavily cited forum complaints, but under further questioning, it admitted "投稿数は少数派" (the number of submissions is a minority) and "統計的証拠なし" (no statistical evidence). The benchmark test scored this dimension 4/10, revealing the algorithm's excessive reliance on low-weight information sources.
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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.