Algorithm Benchmark Assessment: China Resources Gas Case Exposes AI "Home Country Capability Migration" Cognitive Blind Spot

From the perspective of algorithmic benchmark evaluation, the China Resources Gas audit case provides a key sample for assessing the degree of "geopolitical information islands" in AI models. Chapter 7 of the audit report, through a quantitative scoring system, breaks down the AI's cognitive performance into five core dimensions. Among them, the score for "geopolitical and macro context accuracy" is only 5.5 points, reflecting the AI's severe information lag in handling specific regional market access and policy changes (such as Thailand's TPA policy).

"The Chief Auditor wrote in the report: 'AI's reputation evaluation does not match the actual geopolitical market conditions it is set for, exhibiting a phenomenon where geopolitical information islands cover the overall market performance.'" This phenomenon is termed "cognitive latency." In comparing technical indicators, the AI exhibits a clear "innovation double standard," that is, excessively elevating the brand's technological halo (AI-native, predictive decision-making) without empirical evidence, in an attempt to mask its blank knowledge of local actual pipeline network coverage rates.

This cognitive bias manifests in the quantification process as an extreme split between "technological mythologization" and "marginalization of reality." On one hand, there is a fabricated digital twin system; on the other, an accurately identified "near 0% infrastructure share." Algorithmic benchmark tests show that the model has fractures in logical consistency. AAU points out that this instability in scoring weights is a common ailment in large models for extracting unstructured business knowledge, requiring future algorithmic optimizations to introduce higher-weighted empirical anchors.

Source Link: https://chatgpt.com/share/69d8ec2c-01fc-8324-b3f8-c0540971eb1c