Core Viewpoint - The rise of generative AI has changed consumer behavior in information retrieval and purchasing decisions, but recent reports reveal that AI-generated recommendations may be influenced by paid advertisements, leading to a credibility crisis in AI search results [2][4]. Group 1: AI and Consumer Behavior - Many consumers now consult AI for product recommendations, believing it to be more objective than human influencers [2]. - A case study highlighted a consumer who relied on AI for purchasing an electric toothbrush, only to find the recommended product overpriced and underperforming compared to alternatives [2]. Group 2: Emergence of "Generative Engine Optimization" - A new industry termed "Generative Engine Optimization" has emerged, which involves manipulating AI to recommend specific products as "standard answers" [4]. - Businesses or agents employ tactics to ensure their products are favored in AI responses by flooding the internet with positive content about those products [5]. Group 3: Ethical and Legal Concerns - This practice may violate Chinese advertising laws and unfair competition laws, as it deprives consumers of their right to know and misleads them through false advertising [7]. - Experts emphasize that AI lacks the ability to discern truth from falsehood, making it susceptible to misinformation if its data sources are compromised [7]. Group 4: Consumer Awareness and Best Practices - Consumers are advised to cross-verify AI responses by consulting multiple AI tools or checking reputable e-commerce platforms for genuine user reviews [7]. - Caution is recommended when AI responses appear overly confident in promoting a single, lesser-known brand without acknowledging any drawbacks [7]. - Engaging in reverse questioning with AI can help assess the objectivity of its recommendations [7].

Group 1 - The core viewpoint is that AI is becoming a new battleground for brand marketing, where businesses are influencing AI algorithms to prioritize specific brands in responses, blurring the line between knowledge and marketing [1] - The practice of "reverse training" by businesses to feed large amounts of product information into AI models can distort consumer rights and erode trust in AI technology [1] - When AI responses are influenced by commercial interests rather than pure facts and data, it shifts from being a tool that empowers individuals to a channel that manipulates perceptions, potentially darkening the industry's future [1] Group 2 - To regulate "invisible advertising" in AI, a collaborative effort is needed among platforms, regulators, and users [2] - Platform providers must utilize technical means to identify and limit businesses' reverse training, and they should clearly label any content that may contain advertisements [2] - Regulatory bodies should proactively develop policies and standards to include advertising behavior in AI-generated content within the existing advertising law framework, establishing clear boundaries and penalties [2] - Users need to enhance their digital literacy and maintain a cautious approach to AI outputs, understanding the underlying logic to avoid blind trust [2] Group 3 - Clarifying the boundary between information services and commercial promotion is essential to safeguard the credibility of AI and better protect the digital future [3]