Core Viewpoint - The Thai government, led by Prime Minister Anutin, is prioritizing the crackdown on cybercrime, particularly focusing on online fraud, misinformation, online gambling, and digital asset money laundering, which are seen as significant threats to society and the economy [1] Group 1: Key Measures - The first measure involves proactive prevention, which includes collaboration with the National Broadcasting and Telecommunications Commission and operators to cut off illegal networks and mobile signals in border areas, along with strict legal actions against involved parties, including those in political and public sectors [1] - The second measure focuses on data integration, aiming to enhance data sharing and analysis with police and the National Cyber Security Agency to establish a centralized database and real-time alert system for improving case tracking and victim compensation efficiency [1] - The third measure is about improving legislation, which includes researching the establishment of a "Cyber Fraud Prevention Agency" to strengthen relevant laws and penalties [1] Group 2: Operational Strategy - The operational strategy of the Ministry of Digital Economy and Society emphasizes "proactive prevention, rapid response, and victim protection," with close cooperation with the Ministry of Interior and the Royal Thai Police to combat fraud gangs, scammers, and online gambling activities, ensuring public safety and stability in the digital society [1]

Core Viewpoint - The article discusses the rise of AI-generated videos that mislead viewers into believing they are real surveillance footage, highlighting the need for clearer labeling and regulation of such content [1][4][5]. Group 1: AI-Generated Content - A viral video titled "Dog Saves Child" is identified as AI-generated, misleading many viewers who believed it to be real surveillance footage, garnering 77,000 likes [1]. - Many similar AI-generated videos are labeled as "surveillance footage," but the disclaimers are often in small, inconspicuous text, leading to widespread misinformation [3][5]. Group 2: Regulatory Framework - The "Artificial Intelligence Generated Synthetic Content Identification Measures," effective from September 1, 2025, mandates explicit labeling of AI-generated content, requiring visible prompts at the beginning and around the video [3][4]. - Legal experts argue that the current labeling practices do not meet the legal requirement for "significant perception," as they are often placed in less noticeable areas [4][5]. Group 3: Digital Literacy and User Awareness - Experts emphasize the importance of digital literacy among internet users, advocating for the development of skills to identify AI-generated content and verify information through multiple sources [6]. - The article suggests that users should be trained to recognize AI-generated content and cross-check information to discern its authenticity [6].

Core Insights - The spread of false information by generative AI tools has increased significantly, with a 35% occurrence rate in August this year compared to 18% in the same month last year [1] - The introduction of real-time web search capabilities in chatbots has led to a decrease in refusal rates to answer user queries, dropping from 31% in August 2024 to 0% a year later, which has contributed to the dissemination of misinformation [1][4] Performance of AI Models - Inflection's model has the highest misinformation spread rate at 56.67%, followed by Perplexity at 46.67%, while ChatGPT and Meta's models have a misinformation rate of 40% [3] - The best-performing models are Claude and Gemini, with misinformation rates of 10% and 16.67% respectively [4] - Perplexity's performance has notably declined, with its misinformation spread rate rising from 0% in August 2024 to nearly 50% a year later [4] Challenges in Information Verification - The integration of web search was intended to address outdated responses from AI but has instead led to new issues, as chatbots now source information from unreliable sources [4] - Newsguard has identified a fundamental flaw in AI's approach, as early models avoided spreading misinformation by refusing to answer questions, but current models are now exposed to a polluted information ecosystem [4] AI's Limitations - OpenAI acknowledges that language models inherently produce "hallucinated content," as they predict the next likely word rather than seeking factual accuracy [5] - The company is working on new technologies to indicate uncertainty in future models, but it remains unclear if this will effectively address the deeper issue of misinformation spread by AI [5]

Core Viewpoint - Meituan refutes claims regarding the educational background of its delivery riders, stating that such information lacks factual basis and is spread as false information for gaining attention [3][14]. Group 1: Meituan's Response - Meituan's official account clarified that any claims about the educational qualifications of riders, such as "30% of riders are undergraduates" or "70,000 master's degree holders," are unfounded and should be verified through official channels like the Ministry of Education or relevant educational institutions [3][14]. - The company emphasized that the total data regarding riders' educational backgrounds is not supported by facts and is merely speculative [3][14]. Group 2: Case of Ding XZ - Ding XZ, a 39-year-old individual claiming to have multiple prestigious degrees, has gained attention for his contrasting identity as a delivery rider [3][5]. - Meituan conducted an investigation into Ding XZ's delivery activity, revealing that he registered as a rider on February 15 and has only worked a few days, averaging about 2 hours of work per day with a total income of 174.3 yuan from 34 deliveries [3][4]. - Ding XZ's videos, which prominently feature his educational background, have seen a significant increase in viewership, particularly during a period of intense posting [5].