我国拟修改网安法 智能驾驶如何系好网络“安全带”

Core Viewpoint - The increasing development of artificial intelligence (AI) has led to heightened attention on cybersecurity, particularly in the context of data collection and personal information protection in smart driving technologies [1][2]. Group 1: Legislative Developments - The draft amendment to the Cybersecurity Law was presented for review, focusing on strengthening legal responsibilities related to cybersecurity and ensuring systematic connections with other relevant laws [1]. - The amendment emphasizes a problem-oriented approach, categorizing legal responsibilities for different types of violations in network operation and information security [1]. Group 2: Data Collection in Smart Driving - Smart driving technologies inherently require extensive data collection, including personal information, due to their reliance on high-precision, multidimensional data for functionality [2]. - Advanced Driver Assistance Systems (ADAS) utilize various sensors to monitor both the vehicle's environment and the driver's state, necessitating the collection of sensitive data such as facial images and voice recordings [2]. Group 3: Risks and Legal Responsibilities - The transmission of collected data to cloud servers for model training poses risks of information leakage and misuse, with potential legal consequences for companies failing to comply with the Personal Information Protection Law [3]. - The necessity of processing personal information for safety features, such as e-Call services, highlights the balance between privacy and life safety [3]. Group 4: Privacy Protection Measures - Companies are implementing various measures to protect personal information, including user consent for data collection and local data processing to minimize external transmission [6]. - For instance, XPeng Motors has introduced features allowing users to disable monitoring systems and process data locally, enhancing user privacy [6]. Group 5: Comprehensive Risk Mitigation Strategies - To mitigate privacy risks in the AI era, a multi-faceted approach is recommended, encompassing legal compliance, technical governance, internal controls, and public awareness [7]. - Companies should adopt techniques such as data anonymization, encryption, and access control, while establishing dedicated data protection roles to oversee compliance efforts [7].