AIGC全生命周期业务风控白皮书，从备案到运营的合规与安全实践

Core Viewpoint - The release of the 2.0 version of the "Artificial Intelligence Security Governance Framework" highlights the urgent need for security measures in the rapidly growing generative AI sector, addressing risks such as content compliance, data security, and algorithmic bias [1][2]. Industry Growth and Risks - Generative AI technology is accelerating, with IDC predicting a global market size of $284.2 billion by 2028, and China's market expected to exceed $30 billion, accounting for 30.6% of total AI investment [2]. - The rapid market expansion is accompanied by significant risks, including compliance gaps and data security issues, which pose challenges to healthy industry development [2]. AI Risk Governance - The Chinese government has been progressively enhancing its AI risk governance framework, with the recent release of the updated governance document reinforcing the importance of security in AI applications [2]. - The "AIGC Full Lifecycle Business Risk Control White Paper" by a leading AI risk management company outlines a comprehensive risk control system that spans from pre-launch safety assessments to ongoing operational safeguards [3]. Compliance Challenges - The dual filing system for algorithms and large models presents compliance challenges for many companies, leading to issues such as incomplete materials and unclear processes [5]. - The white paper provides detailed solutions to these compliance challenges, including specific requirements for safety assessments and the submission of necessary documentation [5]. Security Assessment for Large Models - Large model security assessments are crucial for compliance and risk mitigation, with the white paper identifying four foundational capabilities required for effective assessments [6][7]. - The assessment process involves a structured approach that includes designing attack instructions, building test question sets, and conducting automated and manual testing [7]. Comprehensive Risk Control Framework - The white paper proposes a dual-wheel risk control system focusing on "account security" and "content compliance," addressing user interaction risks throughout the entire process [8]. - The account risk control system aims to prevent issues such as resource exploitation and unauthorized account registrations through multi-dimensional defenses [8]. Innovative Content Risk Management - A new paradigm for content risk management is introduced, combining AI machine review, large model review agents, and human review to enhance content governance [10]. - This approach includes a four-level risk labeling system to categorize and analyze content risks effectively [10]. Operational Safeguards and Dynamic Response - The white paper outlines a comprehensive solution for managing public sentiment, emphasizing rapid response and monitoring to mitigate potential crises [11]. - A data-driven iterative system is established to adapt risk control strategies in real-time, ensuring alignment with evolving risks [14]. Practical Case Studies - The white paper includes case studies from various sectors, illustrating effective risk control implementations and providing actionable insights for companies [15]. - It serves as a guide for organizations navigating AI compliance and risk management, particularly in AI social, office, and marketing applications [15]. Conclusion - As the AIGC market approaches a trillion-dollar valuation, robust risk control capabilities will become a critical competitive advantage for companies [16].