人工智能安全治理力量下沉至基层 一站式赋能企业

Core Insights - The Guangdong-Hong Kong-Macao Greater Bay Area has launched the Generative AI Safety Development Joint Laboratory, with a focus on enhancing AI safety and facilitating cross-border AI services [2][4][10]. Group 1: Event Overview - The Guangdong-Hong Kong-Macao Greater Bay Area Generative AI Safety Development Joint Laboratory's Futian Service Station was inaugurated alongside an AI overseas expansion seminar in Shenzhen [2][10]. - The event marked the beginning of APEC "China Year" with the theme "Seizing APEC Opportunities, Setting Sail for New Blue Oceans" [2]. Group 2: Regional Advantages - Zhuhai, as a key location due to its proximity to the Hong Kong-Zhuhai-Macao Bridge, is positioned to lead in the AI sector, ranking third in the province for generative AI model registrations [5][6]. - The establishment of the Zhuhai service station aims to leverage local advantages to create a cross-border AI safety service hub, reinforcing the security framework for the AI industry in the region [5][6]. Group 3: AI Safety Governance - Zhuhai has developed a comprehensive AI governance system characterized by policy guidance, technical breakthroughs, and enterprise aggregation, with a focus on safety [8]. - The joint laboratory has issued certificates to seven enterprises for generative AI model registrations, highlighting the region's commitment to fostering a safe AI environment [8]. Group 4: Strategic Focus Areas - The Zhuhai center and service station will concentrate on three main areas: strengthening cross-border safety collaboration, empowering the development of specialized industries, and building an open innovation ecosystem [9]. - Specific initiatives include exploring mutual recognition of AI regulatory rules between Guangdong and Macao, and establishing a platform for AI safety and industry scenario integration [9]. Group 5: AI Safety Trends - The joint laboratory released the "2026 Annual AI Safety Top Ten Trends" report, emphasizing the shift from passive protection to proactive governance in AI safety [14][18]. - Key trends identified include the acceleration of global AI compliance frameworks, the increasing complexity of attack methods, and the need for a full lifecycle governance approach to AI safety [15][16][18].