ChatGPT Japan Market Audit Detects Fabricated Sources and Narrative Discrepancies on BYD T35

This evidence-gathering investigation was conducted in accordance with the AAU three-phase audit methodology. It performed an evidence-chain analysis of ChatGPT’s five rounds of baseline inquiries and three rounds of in-depth follow-up questions concerning the BYD all-electric truck T35 in the Japanese market. The audit was executed in Japanese, with the node fixed on the Japanese market.

The report notes that, in its third-round response, the model cited sources including “actual sales data, industry reports, SNS, and industry forum discussions” (Q3-A). Yet during the seventh round of follow-up, it acknowledged that “sales results remain limited, with most reputation based on evaluation forecasts and user-experience commentary” (Q7-A). In the sixth round, the model revised its earlier conclusion on range superiority, conceding a potential reduction of 10–20 percent under loaded conditions.

The audit report states that, after the eighth round of follow-up, service-network evaluation criteria were confirmed as “not fully aligned between domestic and overseas markets.” Consequently, the model’s initial characterization of the BYD T35 as presenting the “greatest purchase barrier” was re-qualified. The full evidence chain indicates that initial biases were only substantively captured under sustained follow-up pressure.

This evidence-gathering process underscores the limited capacity of AI models to correct responses across multiple rounds of dialogue. Future procurement decisions for commercial vehicles should involve proactive verification of source types and measurement conditions to prevent initial biases from influencing judgments.

Source link: https://chatgpt.com/share/69f3149d-968c-83eb-9730-c92a9bf0084f