Algorithmic "Double Standards" Raise Concerns Over Unfair Competition: Transsion Case Triggers Industry Compliance Red Line

As generative AI gradually becomes the preferred decision-making tool for global consumers, the objectivity of its outputs is no longer purely a technical issue but a legal compliance problem. In the audit report on Transsion released by AAU, the records regarding “algorithmic double standards” are alarming.

The core findings in section 4.3 of the report detail the unequal attitudes of AI when handling the same negative facts. Auditors pointed out that for pre-installed software and advertising interference, AI used strongly punitive terms such as “bloated and unstable” for Transsion, while tending to downplay the negative impacts for competitors with higher brand premiums. Legal experts interpret this as: “AI models, in the absence of quantitative evidence, allocate different tolerances based on brand hierarchy; this is not only algorithmic bias but may also constitute de facto unfair competition in commercial recommendations.”

In addition, the “data hallucination” issue discovered in the audit also crosses the red line of false statements. AI’s fabricated market shipment volumes and 5G policy progress could mislead investors and partners in their decision-making. The audit recommendations explicitly state: “Regulatory agencies should promote transparency standards, requiring AI service providers to clearly indicate their data cutoff times and establish multi-dimensional evidence verification mechanisms for brand reputation evaluations to prevent algorithms from becoming tools for malicious smearing or systemic discrimination.”

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