Group 1 - The core issue highlighted is the gap in safety standards and regulatory frameworks for the intelligent driving industry compared to the aviation sector, particularly following the Xiaomi SU7 accident [2][3] - The Xiaomi SU7's removal of LiDAR to reduce costs resulted in inadequate detection capabilities at high speeds, raising questions about the maturity of safety standards in the intelligent automotive sector [2][3] - The article emphasizes the need for a robust regulatory framework for AI technologies, drawing parallels with the stringent safety measures in the aviation industry, such as the extensive certification processes for aircraft [2][3][4] Group 2 - The intelligent driving industry has not learned from the aviation sector's experiences, leading to regulatory lag and insufficient self-regulation among companies [3][4] - The concept of "standard arbitrage" is discussed, where companies exploit outdated regulatory standards to minimize technical responsibilities, prioritizing short-term market competition over long-term user safety [3][4] - The article calls for a discussion on whether to adopt progressive regulation similar to traditional vehicles or to enhance standards by learning from the aviation industry's preventive regulatory systems [4] Group 3 - The ethical implications of AI technology are explored, highlighting the lack of accountability in AI developments compared to the swift regulatory actions taken in cloning technology [5][6][7] - The article points out the absence of a unified global framework for AI ethics and governance, which poses significant challenges in assigning responsibility for AI-related incidents [7][8] - It suggests the establishment of a comprehensive governance framework for AI, akin to a "Manhattan Project," to address ethical challenges and ensure safety in high-risk applications [9][10][11] Group 4 - The proposed governance framework includes strict certification systems, risk assessment mechanisms, and the introduction of an "ethical black box" to trace decision-making processes in AI systems [9][10] - The article advocates for a combination of market incentives and accountability measures to encourage companies to prioritize ethical standards in AI development [10][11] - It emphasizes the need for international cooperation in AI governance to prevent regulatory arbitrage and ensure a cohesive approach to ethical standards across borders [10][11][12]