借道“无障碍”，AI助手可能在盯着你

Core Viewpoint - The article emphasizes that 2025 will be a pivotal year for AI Agents, highlighting the shift from traditional language models to more versatile AI Agents capable of performing complex tasks through simple natural language commands [4][6]. Group 1: AI Agent Development - The rise of AI Agents is driven by the increasing capabilities of mobile devices, with predictions indicating that by 2027, global AI mobile penetration will reach approximately 40%, with an expected shipment of 522 million units [9]. - Major tech companies, including Apple, are launching their own AI models, such as Apple Intelligence, while domestic manufacturers like Xiaomi and OPPO are also entering the market with their versions [9]. - The challenge lies in overcoming app isolation, as different applications typically prevent data sharing, necessitating either API agreements or the use of accessibility permissions to enable AI operations [11]. Group 2: Security and Privacy Concerns - The use of accessibility permissions raises significant privacy risks, as AI applications can potentially access sensitive information, including payment passwords and chat records [6][12]. - There are two main technical paths for AI Agent development: an interface model that requires cooperation between app developers and a non-interface visual solution that utilizes system-level permissions [11]. - The article notes that while the interface model is safer, it is also more complex and costly due to the need for adaptation across different devices [12]. Group 3: Market Potential and Growth - The AI Agent market is projected to grow from $5.1 billion in 2024 to $47.1 billion by 2030, with a compound annual growth rate of 44.8% [17]. - A survey indicated that over half of respondents have encountered data privacy and security issues, with 60.09% believing that AI could uncontrollably collect and process personal information [17]. Group 4: Regulatory and Industry Response - The article suggests that proactive measures are essential for managing AI risks, with companies needing to enhance their awareness of privacy issues [19]. - Recommendations include defining the minimum data required for specific functions and establishing data quality management standards to ensure data integrity and security [19][21]. - Regulatory bodies are encouraged to adopt agile governance strategies to address the rapid evolution of technology and its associated risks, ensuring a balance between user protection and innovation [21].