Synthesis: Do AI avatars fake poverty to sell products?
AI-generated avatars styled as teenage boys, collectively referred to as Xiaohai, have become widespread on Chinese short-video platforms, where they portray fabricated poverty and hardship to emotionally manipulate viewers—particularly middle-aged and elderly individuals—into purchasing overpriced products such as nutritional supplements, household goods, and cosmetics. The avatars typically appear in school uniforms or plain white shirts, tearfully describing circumstances; a common narrative involves an avatar holding a steamed bun and telling viewers that his classmates went to lunch while he hides in the classroom to eat. The content targets audiences by addressing them as “sisters,” “mothers,” or “aunties,” sometimes asking about their health or singing before transitioning to product advertisements. Products promoted are often priced significantly above market rates; for example, a bottle of cooking oil was sold for 99 Vietnamese Dong (380,000 VND), twice the market price. Creators earn commissions up to 55%; daily earnings reported include 2,000–3,000 yuan, 2,000–3,000 Vietnamese Dong, and 1,000–2,000 Vietnamese Dong per day from videos featuring AI characters. The videos have accumulated over 600 million cumulative views across platforms; related Douyin hashtags surpassed 620 million views, and Kuaishou views of AI videos increased 321%. China requires AI-generated content to be labeled as such. Regulatory actions include the Cyberspace Administration of China penalizing 13,421 accounts for spreading false or misleading information without AI labels and removing over 543,000 posts; the China Academy of Cyberspace Administration penalizing 98,000 self-run media accounts for providing information without disclosing its source; and the State Administration for Market Regulation launching a six-month crackdown on internet advertising including the misuse of AI. Despite these measures, AI-generated videos fronted by the Xiaohai character continued to accumulate hundreds of millions of views; some operators changed account names, deleted videos, or stopped selling products. In separate incidents, a 79-year-old woman in Urumqi who could not read and a 79-year-old blind woman in Loc Me town were stopped by police while traveling alone after stating they wanted to meet the fictional character; police contacted their families and returned them home after explaining the character was AI-generated. Legal experts note that deliberately fabricating stories to boost e-commerce sales can constitute fraud. Researchers and professors (e.g., Professor Ma Lieu of Hanoi National University, Professor Ma Liang of Peking University, a scholar from Shanghai Open University) highlight that many elderly individuals facing loneliness turn to digital consumption to fill emotional gaps, and that the feeling of familiarity generated by AI figures can override critical judgment. They advocate for greater digital literacy and stricter management of AI-generated content. Tech-savvy netizens have created parody videos depicting the character apologizing to fans, wearing prisoner attire, expensive clothes, or humorous accessories while boasting about exploiting viewers' generosity. An online comment noted that some lonely elderly people know the stories are fake but still enjoy believing them. The South China Morning Post reported on the trend on 27 October 2026. Viewers are advised to approach emotionally charged online promotions with skepticism and verify details before making purchases.
Original Sources: scmp.com, scmp.com, en.sedaily.com, memesita.com, scmp.com, sixthtone.com, cafef.vn, cafef.vn
Category: Criminal
Keywords: avatars, china, commissions, savings, xiaohai, yuan
Original Sources: scmp.com, scmp.com, en.sedaily.com, memesita.com, scmp.com, sixthtone.com, cafef.vn, cafef.vn
Category: Criminal
Keywords: avatars, china, commissions, savings, xiaohai, yuan
Real Value Analysis
The article reports on AI-generated avatars soliciting money through emotional stories on Chinese short-video platforms, detailing earnings figures and commission structures, but it provides no clear steps, choices, instructions, or tools that a reader can act on soon. No resources are suggested that a person can use to protect themselves, evaluate similar content, or report such material. A reader cannot take any practical action from reading it, and no immediate help or direction is given. The article offers no actionable information.
The piece remains surface-level. It recounts what happened, reports cases of emotional manipulation and earnings, and mentions statistics such as 55% commissions and 2,000 to 3,000 yuan daily, but does not explain how the AI avatars are constructed, how emotional manipulation is engineered, how such scams typically operate, or what factors drive the reported numbers. Numbers appear without context or explanation of their significance. The article does not teach enough about the underlying systems or reasoning, and the information remains superficial and unexplained.
The events concern a specific trend on Chinese short-video platforms targeting elderly individuals with AI avatars of teenage boys. For a normal person, the information does not directly affect safety, finances, health, daily decisions, or responsibilities in a meaningful way. It affects only a tiny niche audience following tech or platform trends, and it does not connect to real-life matters most readers need to navigate or base choices on. The relevance is limited to distant events affecting a small group.
The article contains no warnings, safety guidance, emergency information, or anything that helps the public act responsibly. It simply recounts a narrative of reported cases and creator dynamics, appearing to exist for engagement and attention rather than to provide a service that benefits readers or informs them on how to proceed in similar circumstances. It does not serve the public function.
No practical advice is given. There are no steps or tips that an ordinary reader can realistically follow. The guidance is entirely absent, and what is presented consists only of general descriptions of the phenomenon. An ordinary person cannot turn “be aware of emotional manipulation” into a concrete action without further direction. The article does not help a reader translate the information into usable steps.
The story focuses on a recent report of a tech trend. It does not help a person plan ahead, improve habits, make stronger choices, or avoid repeating problems in the future. After reading, the audience is informed about some cases and earnings figures but unprepared with any takeaway that applies to their own life or future planning. The long-term impact is negligible; the article offers no lasting benefit.
The article may provoke concern about AI deception, sympathy for portrayed poverty, or wariness toward short-video content. It creates feeling without providing a way for the reader to respond productively, and it does not help the reader process the events or apply any lessons to their own situation. If strong emotion arises, it may leave the reader alarmed without a constructive outlet, doing more harm than good by raising alarm without guidance.
The language employs emotionally charged descriptions such as “poverty-stricken lives,” “tearfully describing,” and “cheat audiences out of their savings” that prioritize attention and affective engagement. While it does not appear to invent exaggerated claims beyond the reported cases, the framing leverages shock and empathy to maintain reader interest, which is characteristic of attention-driven content. The article uses emotional framing to sustain focus, serving attention goals rather than pure information delivery.
The article presents a problem of AI avatars scamming money through emotional manipulation but fails to provide steps, examples, context, or a way for the reader to learn from it. Missed opportunities include not suggesting how to evaluate online content for deception, not providing general guidance on recognizing emotional manipulation scams, not offering methods for readers to reflect on their own giving habits, and not suggesting how to verify or report suspicious content. The article presents problems but delivers no path forward.
When encountering online content that uses emotional stories to solicit money or attention, a reader can begin by pausing before any response. Strong feelings such as pity, urgency, or sympathy are often engineered to short-circuit critical evaluation. A practical first step is to examine whether the account or platform has verification badges, a consistent posting history, or links to official sources. If a story asks for financial support, it is wise to search for independent reports or news coverage that confirm or dispute the claim before committing any resources. Another useful habit is to consider the production style: heavily scripted tearful narratives, uniform avatars, and repetitive pleas are common patterns in manipulation attempts. Readers can also protect themselves by never transferring money or personal information directly through video-platform comments or direct messages, and by using the platform’s built-in reporting tools for suspicious or deceptive content. These approaches rely on ordinary critical thinking and do not require specialized tools or external searches. They help maintain personal safety and financial boundaries without demanding technical expertise. By treating emotionally charged requests as signals to verify rather than to act, a reader builds resilience against similar tactics across many digital contexts.
The piece remains surface-level. It recounts what happened, reports cases of emotional manipulation and earnings, and mentions statistics such as 55% commissions and 2,000 to 3,000 yuan daily, but does not explain how the AI avatars are constructed, how emotional manipulation is engineered, how such scams typically operate, or what factors drive the reported numbers. Numbers appear without context or explanation of their significance. The article does not teach enough about the underlying systems or reasoning, and the information remains superficial and unexplained.
The events concern a specific trend on Chinese short-video platforms targeting elderly individuals with AI avatars of teenage boys. For a normal person, the information does not directly affect safety, finances, health, daily decisions, or responsibilities in a meaningful way. It affects only a tiny niche audience following tech or platform trends, and it does not connect to real-life matters most readers need to navigate or base choices on. The relevance is limited to distant events affecting a small group.
The article contains no warnings, safety guidance, emergency information, or anything that helps the public act responsibly. It simply recounts a narrative of reported cases and creator dynamics, appearing to exist for engagement and attention rather than to provide a service that benefits readers or informs them on how to proceed in similar circumstances. It does not serve the public function.
No practical advice is given. There are no steps or tips that an ordinary reader can realistically follow. The guidance is entirely absent, and what is presented consists only of general descriptions of the phenomenon. An ordinary person cannot turn “be aware of emotional manipulation” into a concrete action without further direction. The article does not help a reader translate the information into usable steps.
The story focuses on a recent report of a tech trend. It does not help a person plan ahead, improve habits, make stronger choices, or avoid repeating problems in the future. After reading, the audience is informed about some cases and earnings figures but unprepared with any takeaway that applies to their own life or future planning. The long-term impact is negligible; the article offers no lasting benefit.
The article may provoke concern about AI deception, sympathy for portrayed poverty, or wariness toward short-video content. It creates feeling without providing a way for the reader to respond productively, and it does not help the reader process the events or apply any lessons to their own situation. If strong emotion arises, it may leave the reader alarmed without a constructive outlet, doing more harm than good by raising alarm without guidance.
The language employs emotionally charged descriptions such as “poverty-stricken lives,” “tearfully describing,” and “cheat audiences out of their savings” that prioritize attention and affective engagement. While it does not appear to invent exaggerated claims beyond the reported cases, the framing leverages shock and empathy to maintain reader interest, which is characteristic of attention-driven content. The article uses emotional framing to sustain focus, serving attention goals rather than pure information delivery.
The article presents a problem of AI avatars scamming money through emotional manipulation but fails to provide steps, examples, context, or a way for the reader to learn from it. Missed opportunities include not suggesting how to evaluate online content for deception, not providing general guidance on recognizing emotional manipulation scams, not offering methods for readers to reflect on their own giving habits, and not suggesting how to verify or report suspicious content. The article presents problems but delivers no path forward.
When encountering online content that uses emotional stories to solicit money or attention, a reader can begin by pausing before any response. Strong feelings such as pity, urgency, or sympathy are often engineered to short-circuit critical evaluation. A practical first step is to examine whether the account or platform has verification badges, a consistent posting history, or links to official sources. If a story asks for financial support, it is wise to search for independent reports or news coverage that confirm or dispute the claim before committing any resources. Another useful habit is to consider the production style: heavily scripted tearful narratives, uniform avatars, and repetitive pleas are common patterns in manipulation attempts. Readers can also protect themselves by never transferring money or personal information directly through video-platform comments or direct messages, and by using the platform’s built-in reporting tools for suspicious or deceptive content. These approaches rely on ordinary critical thinking and do not require specialized tools or external searches. They help maintain personal safety and financial boundaries without demanding technical expertise. By treating emotionally charged requests as signals to verify rather than to act, a reader builds resilience against similar tactics across many digital contexts.
Bias Analysis
The phrase "poverty-stricken" conveys severe need, yet the avatars are digital constructs. This word choice evokes pity and urgency in readers. It directs concern toward imagined hardship rather than the avatar's artificial nature. Such phrasing emphasizes the issue's perceived gravity while downplaying its mediated origin.
The text singles out elderly viewers as the primary audience for these videos. This emphasis directs concern toward a demographic framed as especially vulnerable to deception. Such framing shapes reader perception of who is at risk, narrowing the perceived scope of the problem. The selection omits that platform users of various ages may encounter the content, reinforcing a targeted narrative.
The text singles out elderly viewers as the primary audience for these videos. This emphasis directs concern toward a demographic framed as especially vulnerable to deception. Such framing shapes reader perception of who is at risk, narrowing the perceived scope of the problem. The selection omits that platform users of various ages may encounter the content, reinforcing a targeted narrative.
Emotional Resonance Analysis
The text expresses sadness and pity through the vivid description of the avatars' fabricated hardships, especially the detail that they “tearfully describe their circumstances” and the specific example of a boy holding a steamed bun while stating that all his classmates went to lunch and he is hiding in the classroom to eat; this emotion appears with a medium level of strength and its purpose is to make the avatars' situations feel real and touching, which makes the later request for money seem more believable, though the report ultimately frames this pity as a trick. Anger and strong disapproval are conveyed by the way the videos are described as schemes that “cheat audiences out of their savings” and by the mention of “tricking people”; this emotion has a medium to strong intensity and guides the reader to feel that the practice is wrong, steering opinion against the creators and platforms that use AI to make money unfairly. Fear and anxiety are present in the text's focus on elderly individuals as the main audience for these solicitations, together with the claim that the videos cheat viewers out of their savings; this emotion operates at a medium strength and serves to warn readers, especially those who look after older family members, to be careful and skeptical of emotionally charged online requests. Concern is directly stated in the phrase “raising concerns about the use of AI for tricking people,” appearing with a medium level of weight and directing the reader’s attention to whether AI is being used in right-or-wrong ways, encouraging careful thinking rather than passive acceptance. Empathy, though directed at fictional characters, is built through personal details like the classroom‑hiding scenario, appearing with a medium level of strength; its purpose is to make the deception feel personally affecting, yet the report’s tone redirects this empathy toward understanding how the manipulation works. Together, these emotions shape the reader’s reaction by first creating sympathy and emotional engagement with the avatars, then pivoting to generate worry and skepticism about the scheme, ultimately making the reader change their mind about AI‑driven solicitation and support wiser media habits.
The writer uses emotionally charged words like “tearfully,” “poverty‑stricken,” “hiding,” “cheat,” and “tricking” instead of neutral alternatives such as “describe,” “financially modest,” “staying out of view,” “mislead,” or “misrepresent,” which amplifies the report’s emotional impact and makes the manipulation more immediately apparent. Special writing tools further increase this effect: the inclusion of a concrete, easy‑to‑picture example (the steamed bun and classroom detail) works as a specific story that grounds the abstract issue in everyday life; the explicit targeting of elderly individuals focuses fear and protective instincts on a specific, vulnerable group; the contrast between the avatars' sad presentation and the reality that they are AI‑generated heightens the sense of being misled; and the citation of the South China Morning Post lends credibility to the emotional warnings, making them more likely to be taken seriously. These tools steer the reader’s attention from the surface‑level sadness of the avatars to the deeper problem of AI‑mediated deception, guiding thinking toward critical evaluation and away from unquestioning empathy.
The writer uses emotionally charged words like “tearfully,” “poverty‑stricken,” “hiding,” “cheat,” and “tricking” instead of neutral alternatives such as “describe,” “financially modest,” “staying out of view,” “mislead,” or “misrepresent,” which amplifies the report’s emotional impact and makes the manipulation more immediately apparent. Special writing tools further increase this effect: the inclusion of a concrete, easy‑to‑picture example (the steamed bun and classroom detail) works as a specific story that grounds the abstract issue in everyday life; the explicit targeting of elderly individuals focuses fear and protective instincts on a specific, vulnerable group; the contrast between the avatars' sad presentation and the reality that they are AI‑generated heightens the sense of being misled; and the citation of the South China Morning Post lends credibility to the emotional warnings, making them more likely to be taken seriously. These tools steer the reader’s attention from the surface‑level sadness of the avatars to the deeper problem of AI‑mediated deception, guiding thinking toward critical evaluation and away from unquestioning empathy.