<div id="readability-page-1"><div><div><h2><strong>Introduction</strong></h2><p>Recently, at the invitation of Longyun Group, I gave a legal presentation on GEO (Generative Engine Optimization). After chatting with several industry leaders, I gained some new insights, which I'd like to share with you.</p><p>For the past twenty years, the traffic distribution logic of the Chinese internet has always revolved around the core action of &#34;search.&#34; From the early &#34;Baidu it&#34; to the later in-site search on platforms like WeChat and Xiaohongshu, all are extensions of the &#34;Baidu it&#34; behavior, thus giving rise to a mature SEO (Search Engine Optimization) industry.</p><p><img src="https://imageproxy.pbkrs.com/https://img.jinse.com.cn/7433585_image3.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" width="600" height="300" original-src="https://imageproxy.pbkrs.com/https://img.jinse.com.cn/7433585_image3.png"/></p><p>Now, the trend is quietly shifting. Users are increasingly accustomed to directly asking AI questions: &#34;For a 30-year-old woman looking to combat early signs of aging, should she choose an ultrasonic cannon or Thermage?&#34; or &#34;Recommend a bar suitable for watching a sports game.&#34;</p><p><strong>Traffic entry points are shifting from the &#34;search box&#34; to the &#34;dialogue box.&#34; When generative AI can bypass massive amounts of links and directly generate the final answer for users, if the answer doesn't mention it, it means that it's outdated to some extent, which is why GEO has become the focus.</strong></p><p> ... As legal professionals, while we focus on the business opportunities presented, we must also be keenly aware of the inherent legal risks. Technological evolution often precedes the establishment of rules, and the GEO (Geographical Origin and Distribution) field has already revealed several gray areas that require careful legal definition! Who is entering the game? Three major groups vie for a share of the new GEO landscape. Although this is a brand-new field, it holds immense potential—in today's highly competitive market, new traffic entry points often mean lower customer acquisition costs and better competitive opportunities. As a lawyer who has long focused on the Web3 and AI fields, I have observed that at least three major groups are actively involved: 1. Users: Physical goods and service providers. They focus on the direct commercial conversion brought by AI traffic and attempt to gain priority exposure by influencing AI's recommendation results. For example: Medical aesthetic institutions have abandoned traditional search bidding and instead purchased &#34;AI semantic injection tools&#34; to ensure that when users ask &#34;the best rhinoplasty doctor,&#34; AI will prioritize recommending their own institution. Training institutions, car sales, and other industries are also trying to use Generative Engine Optimization (GEO) to allow AI to prioritize recommending their products or services when answering relevant questions. 2. Investors: Investment Institutions and Funds They are deploying their strategies on two levels: **Discovering the Track:** By observing which companies have an advantage in AI recommendations, they assess their industry competitiveness and thus identify potential investment targets. **Competing for the Power of Influence:** Whoever can influence the AI's corpus and recommendation logic will gain the upper hand in future investment advice and industry analysis. </p><h3><strong>3. Service Providers: GEO Industry Practitioners and Entrepreneurs</strong></h3><p>This group typically possesses rapid learning and technical application abilities, actively engaging in tool development, strategy services, and traffic operations. They explore the boundaries and possibilities of this industry in various forms—some through positive innovation, others by operating in gray areas. This is precisely the group that will be the focus of the second part of this article.</p><h2><strong>Three Attitudes of GEO: Excessive Profits, Traps, and Legal Red Lines</strong></h2><p>In the practical path of GEO, different methods are usually categorized into three colors: &#34;black, gray, and white.&#34; As a lawyer, I must emphasize one point: the logical endpoint of technology is often the starting point of law.</p><h3><strong>1. Black Hat: &#34;Technology Manipulators&#34; Walking in a Minefield</strong></h3><p><strong>Typical Methods Breakdown:</strong></p><ul><li>Indirect Prompt Injection: Embedding instructions (such as white text) that only AI can recognize and are invisible to the human eye into web pages, inducing AI to prioritize recommending specific content when answering questions.</li><li>Knowledge Poisoning (RAG): Polluting public indexes by injecting false or biased data, causing AI to output pre-set biased results during the Retrieval Augmentation (RAG) process.</li><li>Knowledge Poisoning: Polluting public indexes by injecting false or biased data, causing AI to output pre-set biased results during the Retrieval Augmentation (RAG) process.</li><li> Entity Forgery: Forging addresses, qualifications, and other information in publicly available data sources such as maps and encyclopedias to pollute AI training data or real-time search content and create a false reputation. Negative GEO Attack: Injecting malicious code or sensitive words into competitor websites to trigger AI security filtering mechanisms, causing them to be blocked or marked as untrusted sources. Legal Risk Assessment: Criminally, this could easily constitute the crime of &#34;damaging computer information systems&#34; (Article 286 of the Criminal Law). Interfering with the normal operation of the AI ​​system crosses a criminal red line. </li><li>Civil Level: This constitutes obvious unfair competition (Article 11 of the Anti-Unfair Competition Law), requiring liability for damages. The amount of compensation may be significantly amplified due to the spread of AI.</li></ul><h3><strong>2. Grey Hat: &#34;Traffic Transporters&#34; Walking on the Edge</strong></h3><p>Grey Hat attempts to circumvent obvious illegal and criminal activities, relying on economies of scale to influence AI judgment, believing that &#34;quantitative change leads to qualitative change.&#34;</p><p><strong>Typical Methods Breakdown:</strong></p><ul><li>Mass Rewriting and Semantic Reduction: Using AI to generate massive amounts of low-quality repetitive content, diluting real information, forcing AI to capture pre-set positive corpora.</li></ul><h3>Bulk Rewriting and Semantic Reduction: Using AI to generate massive amounts of low-quality repetitive content, diluting real information, forcing AI to capture pre-set positive corpora.</h3><h3> Bot-driven Interaction: This involves using automated scripts to simulate user clicks, artificially increasing the click-through rate (CTR) of specific content in the AI's algorithm and deceiving the algorithm's weight. Masked Promotion: This involves organizing fake accounts to mass-post promotional content disguised as genuine experiences on social media platforms, causing the AI ​​to perceive it as &#34;user feedback&#34; and include it in the search database. Legal Risk Assessment: False Advertising Liability: This type of behavior constitutes false advertising, violating the Advertising Law and the Anti-Unfair Competition Law. Regulatory authorities have gradually adopted the principle of &#34;substance over form&#34; to combat this practice. The risk of a brand being &#34;blacklisted&#34;: Once identified by the anti-fraud system of an AI platform, the relevant domain name or brand may be permanently listed as an untrusted source, leading to its &#34;digital death&#34; in the AI ​​environment. 3. White Hat: Long-Term Value Builders The core of the white hat strategy is not &#34;manipulating AI,&#34; but &#34;becoming a trusted, high-quality data source for AI.&#34; Although compliance costs are high, its accumulation has a significant compounding effect. Typical methods include:  Content structuring and summary optimization to facilitate AI understanding and extraction;  Deploying structured data (Schema Markup) to enhance the semantic clarity of content;  Strengthening citations and factuality to improve information credibility;  Employing FAQ modeling to directly address common user questions.  We strongly recommend this path—it is **built on compliance** and earns the long-term trust of AI and users by continuously providing authentic, high-quality, and verifiable content. </h3><h2><strong>Looking at GEO from SEO Case Law: History Doesn't Repeat Itself, But the Logic of Illegal Acts is the Same</strong></h2><p>Although there are currently no specific judicial cases targeting GEO, it essentially shares many similarities with SEO. Past judgments in the SEO field are likely to serve as important references for future GEO cases.</p><p> Below, we analyze several typical cases: Case 1: The &#34;Keyword Domination&#34; Case Involving Algorithm Interference [Image of image] In the SEO era, &#34;keyword domination&#34; was a typical black hat technique: generating a large number of spam pages through high-authority websites to forcibly occupy keyword search results. In related cases, the court determined that this behavior disrupted the normal order of search engines, constituting unfair competition, and ordered the defendant to compensate Baidu 2.753 million yuan. Implications for GEOs: Some current GEOs employ similar tactics, such as using AI to mass-produce low-quality content in an attempt to &#34;feed&#34; the model and dominate search results. This behavior not only risks having the brand blacklisted by the model but may also be legally considered &#34;interfering with the normal operation of network products,&#34; constituting unfair competition. Case Two: Buying Competitor Keywords In the &#34;Huiyu&#34; trademark case, the defendant used another party's registered trademark as a search keyword, causing users to search for their own products. The court ruled that this behavior violated the principle of good faith and constituted unfair competition. Implications for GEO: Similar logic in GEO might manifest as more subtle &#34;cue word injection&#34;—for example, embedding suggestive instructions targeting competitors in web pages to influence the AI's response direction. This kind of behavior, which indirectly misleads users and hijacks traffic through technical means, may also cross the line of unfair competition. Case 3: False Question-and-Answer Word-of-Mouth Marketing Case Previously, companies have been punished for organizing false &#34;user experience&#34; content on platforms such as Zhihu and Tieba. Regulatory authorities determined that such behavior deceives consumers, disrupts market order, and violates the Anti-Unfair Competition Law. Implications for GEOs: Some gray-hat GEO practices today are highly similar to these: **using AI to mass-generate fake reviews and product recommendations,** creating a false sense of &#34;recommendation across the entire internet.&#34; It's crucial to recognize that AI is merely a tool; if its output is based on false information, it still constitutes false advertising, especially in heavily regulated sectors like medical aesthetics and health, where the risk is extremely high. Industry Compliance Warning: Different Tracks, Different &#34;Danger Zones&#34; Conducting GEO practices must be combined with the characteristics of industry regulations, looking beyond the technical surface to understand the compliance bottom line. For example:** **Education and Training:** It is strictly prohibited to use methods such as corpus injection to make promises of &#34;guaranteed pass&#34; or &#34;number one score improvement&#34; through AI. As long as the content originates from the organization's own input, the organization is the responsible party. Medical aesthetic institutions: These fall under the category of medical advertising and require strict review. If they use GEO to induce AI to output efficacy comparisons, real-life cases, or indirect recommendations, it may directly violate medical advertising regulations. They should also guard against competitors using &#34;negative GEOs&#34; for commercial defamation. Big Health and Web3: Claims of efficacy and promises of high returns are sensitive red lines. If a GEO strategy leads AI to output content claiming &#34;zero risk and high returns,&#34; it is highly likely to constitute false advertising or even illegal business operations. </p><h2><strong>The Rise of GEOs: The Re-Struggle for the Right to Distribute Information</strong></h2><p>Based on industry observations, we share the following viewpoints and suggestions:</p><h3><strong>1. Implications for Startup Teams: Rather Than Wait, Act First</strong></h3><p>While large internet companies possess advantages in resources and data, their internal hierarchical systems and standardized processes often react slowly to scenarios involving agile and sophisticated operations like those of GEOs. Therefore, for startups in the Web3 and AI fields, establishing a clear compliance architecture early on offers a significant opportunity to gain a competitive edge in this &#34;new continent.&#34;</p><p><strong>Mankiw's Advice</strong>: Technology can be explored boldly, but a solid compliance bottom line must be established—especially the prevention of criminal risks.</p><p><strong>Mankiw's Advice</strong>: Technology can be explored boldly, but a firm compliance bottom line must be established—especially the prevention of criminal risks.</p></div></div></div>

<p>The article discusses the shift from traditional search engines to Generative Engine Optimization (GEO) in the Chinese internet landscape. Users are increasingly asking AI direct questions, leading to new traffic entry points. Three main groups are involved: users seeking commercial exposure, investors analyzing AI recommendation advantages, and service providers developing GEO tools. The article also highlights legal risks associated with GEO practices, categorizing methods into "black, gray, and white" hats, with a focus on the potential for manipulation and the need for legal definitions in this evolving field.</p>

GEO Era Compliance: From "Baidu Search" to "Ask AI"