Core Viewpoint - The rise of AI technology brings convenience but also poses challenges, particularly in the realm of black and gray market activities, as AI makes it difficult for apps to determine whether the user is the legitimate owner of the device [1] Group 1: AI and Black Market Operations - AI technology is being exploited by black market entities to enhance efficiency in operations such as account farming and mimicking user behavior, making it harder for traditional risk control measures to be effective [3] - The use of large models by black market actors allows for the automatic generation of realistic responses, significantly reducing the cost of account farming and increasing profit potential [3] - Traditional methods of automated scripts are being replaced by intelligent agents that can execute complex operations with human-like behavior, making detection more challenging [3] Group 2: Risk Control Strategies - The identification of good versus bad users is becoming increasingly complex as the majority of online operations shift from human to intelligent agent interactions [2] - A new paradigm for risk control, termed "AI risk control new paradigm," has been proposed, focusing on distinguishing between normal user behavior and black market operations through behavioral analysis [2] - The approach includes the "three laws of anti-fraud," which involve diversity, consistency, and correlation to effectively identify black market activities [2] Group 3: Future Implications - In the next 5-10 years, it is anticipated that over 50% of information encountered by humans will be generated by AI, necessitating an evolution in content risk control from merely identifying objects to understanding intent [5] - The introduction of AI-based review agents is suggested as a potential solution to address the new challenges posed by the increasing sophistication of black market operations [5]